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Apple, Amazon, and… your business? Join the ranks of the planet’s biggest brands, and find out how CRM is the secret to their success

How did a handful of ambitious thinkers take simple ideas and grow them into instantly recognisable brands, and… into companies worth hundreds of billions of pounds?

Well, they did it by retaining a firm focus on the customer. And they did that through the use of CRM (Customer Relationship Management) .

• A type of software (such as Maximizer or Salesforce ) that helps businesses manage leads, deals, and clients, and craft targeted marketing campaigns.
• The specific strategies via which a business engages and retains its existing customers.

With CRM , the Tescos and Amazons of this world were not only able to win new customers, clients, and users – they got lifetime value out of them. With targeted marketing campaigns , these brands hit the right people with the right offers, at exactly the right time.

So, what kind of lessons can you take from the best in the business? Is CRM the key with which you can unlock your own company’s potential, and fuel commercial growth on a scale that rivals the big guns? Let’s take a look at our top 11 CRM case studies from the world’s leading brands .   Or, if you’re just ready to get started with a CRM system yourself, check out our recommended partners below.

1. Tesco CRM

Tesco is a truly global business. It’s one of the world’s top 10 retailers , with supermarkets across Asia, Europe, and North America. With more than 3,400 stores in the UK alone, you’ll probably know it as your first port of call for a spontaneous pint of milk, or for an indulgent £3 meal deal during your lunch hour. So, what’s the secret to Tesco’s success? Well, it boils down to one main factor: The Tesco Clubcard .

Tesco CRM: Case Study

The Tesco Clubcard is Tesco’s way of rewarding its most loyal customers. For every pound you spend online or in-store, you’ll get a point. These points, when accumulated, can be traded in for Tesco Clubcard ‘vouchers’ (for instance, 150 points gets you a £1.50 voucher).

A voucher can then be traded in for rewards, such as an afternoon at Cineworld with the kids (a timeless experience), or an evening at Pizza Express (enjoy it while you can). Clubcard holders can also collect points at Tesco fuel stations, and by filling out feedback surveys online.

What’s in it for Tesco? Returning customers that are invested in the brand, and whose opinion Tesco can leverage to continue improving its growing basket of offerings.

2. Apple CRM

This one needs no introduction. Founded by visionary Steve Jobs in 1976, this instantly recognisable brand is the apple of many a tech-lover’s eye. Apple has given us the iPad, iPhone, iMac, and Apple TV. But anyone who’s ever used one of its slick, stylish products knows that Apple’s appeal goes far beyond its niftiest handheld devices…

… because it’s how it treats its customers that’s the key to Apple’s success. 

Apple CRM: Case Study

Let’s take Apple ID as an example. If you’ve ever used iTunes (Apple’s online music streaming service), you’ll have an Apple ID – and if you’ve ever used an Apple device, you’ll have had to register it using an Apple ID, too. 

These unique IDs synchronise across devices, remember music and film selections, and provide personalised recommendations based on what’s you’ve been watching or listening to. For the user, it offers convenience. And for Apple, it’s a constantly updating data set, telling the company exactly what its customers like and allowing for effortless, targeted marketing.

It’s…. CRM, done well.

3. Uber CRM

Uber arrived in 2009 to spearhead the ride-sharing revolution, and has quickly become a household name. But, with a huge host of new competitors driving costs down (not to mention a few other issues ), Uber’s monopoly over its 95 million worldwide monthly users could be under threat. Can Uber hold on? And what can help us understand how successful Uber has been thus far in retaining its enormous customer base?

Uber CRM: Case Study

Well, CRM is a good place to start – and for Uber, it’s industry-leading CRM software provider Salesforce that’s powering the ride-sharing giant’s strategy. Salesforce helps Uber extract data from people engaging with its brand on social media. With this system in place, Uber can reply with haste to customer complaints, and track all its interactions with the public from an intuitive dashboard.

And, of course, it runs its own loyalty program. Uber Rewards lets you earn points every time you ride or eat with Uber, and redeem them across its increasing range of services. It’s a textbook example of how Uber is incentivising customers to keep relying on its brand, as it continues to branch out .

4. British Airways CRM

In the hotly contested, heavily consumer-oriented aviation space, you’ve got to get your CRM strategy right. And, clearly, British Airways (BA) does – flying 145,000 people to more than 200 destinations every day . So, why do its customers keep coming back? The answer can be summed up in two words… Executive. Club.

British Airways CRM: Case Study

The British Airways Executive Club is an example of CRM loyalty schemes done right. Free to join and with no ongoing charges, the club allows customers to earn ‘Avios’ points through purchasing flights, hotel stays, holidays, or car rental through BA or its partners. Avios points can then be redeemed for discounts on travel or accommodation with (you guessed it!) BA. 

Customers can save their meal and seat preferences, making for a smoother, more seamless re-booking experience. And, as they continue to fly with BA, they’ll be able to progress through the levels of Executive Club membership – from blue to bronze, silver to gold, then (maybe one day) the elusive ‘Premier’ tier.

To keep track of all this, BA has been been using a CRM solution called Teradata since 2002. It allows the airline to keep track of all the customers on its books, and re-engage them with offers and deals targeted to their level of membership and favourite destinations.

5. Nokia CRM

Nokia has been around the block a few times. We’ve all owned one of its basic, ‘brick’ design mobiles at some point, and while these phones may seem a bit antiquated now, they’re still virtually indestructible – and perfect for a quick game of Snake while waiting for the bus. Despite iPhones and Galaxys hogging the plaudits more recently, Nokia’s brand is still ticking away. It’s currently valued in the region of a whopping 10 billion USD – and Nokia stock is poised to make an unexpected comeback in 2021 . So, what’s its secret? CRM, of course!

Nokia CRM: Case Study

Nokia implemented Salesforce (that name again) to help manage the size and diversity of its client base. Salesforce allows Nokia to customise its product range and marketing to suit geo-specific locations.

Nokia’s collaboration with CRM brought order to chaos, empowering marketing departments across countries and languages to organise customer data. Through the selecting and segmenting of data into specific target groups, Nokia’s team saw more effective lead generation – which probably helps explain why its brand is still thriving.

6. McDonald’s

Every day, McDonald’s serves almost four million customers in the UK alone – about the population of New Zealand. Worldwide, that figure’s more like 69 million – roughly the size of Great Britain’s own populace. So, with such a vast empire and super-sized customer database, how does this fast food giant ensure their customers keep lovin’ it? With an industry-leading CRM strategy, that’s how.

McDonald’s CRM: Case Study

McDonald’s partners with Astute Solutions , allowing the restaurant chain greater insights into consumer feedback and satisfaction levels. Being able to assess restaurants by region, or even individually, means that McDonald’s can quickly spot potential customer relationship issues, and resolve them before they become a serious problem.

And, with Astute Solutions, McDonald’s can also:

• Provide both its franchisees and corporate managers with live access to customer information
• Integrate data from its dynamic network of restaurants into an effective CRM tool
• Increase the accuracy of its reporting, and inform more intelligent decision-making

As Christopher Garrity, McDonald’s’ own Senior Director of Customer Satisfaction, espouses:

“CRM [is a] critically important function for any large company. It’s clear that Astute understands the important role it plays, and meets the ever-changing needs of our prime customers through continued innovation.”

Prime customers… was the pun intended? We don’t know.

What we can tell you, though, is that one too many Big Macs may leave you feeling bloated and unmanageable… but your SME’s customer database doesn’t have to be. Browse our guide to the best CRM systems for restaurants to learn more, or click below to start comparing CRM software quotes for your business.

7. Coca Cola CRM

While Coca-Cola’s iconic recipe has remained a secret since 1886, this global beverage giant has been less coy about the other secret of its success – a dedication to the customer. It came as no surprise when Coca-Cola’s German branch adopted Salesforce – but what role did CRM software play in engineering the soft drink goliath’s continued growth?

Coca-Cola CRM: Case Study

“We needed to get much faster, to work on collaboration, connectivity, and scalability — and all that in a mobile context. Salesforce has been a fantastic partner, and a great help for us.”

That’s Coca-Cola Germany’s CEO, Ulrik Nehammer. He’s happy, because his customer service team is happy. And they’re happy because CRM software allows them instant access to customer history – which, in turn, allows them to hit their targets, and deal more efficiently with complaints.

With Salesforce, Coca-Cola Germany’s team can easily log issues with customers or suppliers, and then respond by dispatching field service technicians in real time. The result? A sweet 30% increase in productivity . Refreshing!

8. Unilever CRM

Also known as Europe’s seventh most valuable company, Unilever’s products are available in almost 200 countries around the world. With brands like Lipton, Magnum, and Hellmann’s under its considerable belt, Unilever has its fingers in a lot of pies. But does it have its finger on the pulse when it comes to managing its customer relationships?

Unilever CRM: Case Study

If you guessed yes, then you’re absolutely right. With the help of SAP CRM , Unilever improved its call centre capabilities, and boosted the productivity of its consumer advisory representatives. Just ask one of its head honchos:

“[CRM] enables faster response time to queries and needs raised by consumers. It provides for effective maintenance of our customer database, and allows for easy access to customer information for analysis and strategy development.”

• Efren Samonte, Commercial Director – Unilever Philippines

And let’s face it, the proof of Unilever CRM’s effectiveness is, quite literally, in the pudding. Because if you’ve ever scoffed down a Magnum on a hot summer’s day, then you’ve witnessed first-hand the effectiveness of Unilever’s ability to keep customers coming back. Can you emulate them?

Hopefully! But to do so, you’ll need your own CRM first. While there are some free options you can go with, these are limited, not scalable, and certainly not fit for ambitious businesses. 

Nope – your best bet is to complete our quick, free quote finding form , to browse CRM options for your SME. We’ll just ask a couple of quick questions, including how many people you need the software for, and what features you’ll need. It takes half a minute at most, and when you’re done, you’ll receive quotes tailored to your business’ specific needs . 

9. Zara CRM

Leading European clothing brand Zara specialises in fast fashion at low(ish) prices, and the profits are also moving quickly – it made almost 19 billion USD last year. But is it the price point that keeps Zara’s customers coming back, or its relentless, CRM strategy-powered focus on the customer? We think the latter.

Zara CRM: Case Study

Zara was one of the first to pioneer the use of personal digital assistants (PDAs) to capture customer data in real time – not just on transactions, but on their customer’s preferences and habits. CRM software comes in when it’s time to use this data to sell, sell, sell, re-engaging existing buyers with fresh discounts and campaigns.

10. BMW CRM

Unless you’ve been living in a cave for the last hundred years, you’ll instantly recognise BMW’s iconic logo. Producing well over two million vehicles per year, and with its status as a film icon firmly cemented, BMW’s success shows no signs of slowing down. And though the cars may have changed a bit since the company was founded in 1916, its customer focus has remained just the same.

BMW CRM: Case Study

And again, a successful CRM strategy underpins it all. To execute it, BMW teamed up with Legacy Lifestyle to create a luxury loyalty scheme called – wait for it – ‘The Owner’s Circle’.

The Owner’s Circle lets BMW owners track their car’s financing and maintenance. Owners of new or old BMWs can also register their vehicles online. From here, they can check the status of a new car order, view the maintenance history of a used car, or get reminders about upcoming service milestones. There’s also an owner-to-owner chat box thrown in, for ultimate convenience. 

All this serves to strengthen the post-purchase relationship between BMW and its customers, ensuring an enduring connection long after they’ve rolled their car out of the garage. 

And, because any points earned through the Owner’s Circle can be used on a variety of luxury items, it strengthens BMW’s status as a luxury brand – and ensures it’ll be continuing to attract a lucrative clientele for many more years to come. 

11. Amazon CRM

We could spend all day throwing statistics demonstrating Amazon’s popularity around, but let’s face it – we’re all familiar with Amazon. As the world’s leading online retailer, Amazon continues to go from strength to strength, led by its enigmatic founder and CEO Jeff Bezos. But how have Bezos and the gang been so good at winning, retaining, and consolidating users of their wildly popular online platform?

Amazon CRM: Case Study

By using CRM, that’s how. And if you’ve ever used Amazon (and the data says you probably have), you’ll know how hard its tailored offers, recommendations, and promotions – all based on your past purchases – can be to resist. 

Plus, by asking its customers to register for an account, Amazon makes it extremely easy for customers to re-order. Cash-rich, time-poor consumers can pay with a click, and have their goods gracing their doorstep within 24 hours. 

Want to know more? Check out our full Amazon CRM case study to read more about how this ecommerce behemoth is crushing the competition.

We’ve said it before, and we’ll say it again – customers are the most important part of your business. Without them, you wouldn’t have one!

With that in mind, then, ensuring you have at least some kind of CRM strategy is crucial. How will you draw in new leads, juggle unfolding deals, and manage prospects and client relationships? How will you keep your customers engaged, ensuring they continue to use your services while identifying with your brand and values?

If these big brand CRM case studies have shown us anything, it’s that CRM software is just as important as the strategic side – all of the big companies are using it to manage customer data, and extract key insights which can help improve customer experience. Here are some CRM systems that we can highly recommend for all types of businesses:

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Not sure which CRM software is right for your business? To find out, simply fill in our 30-second form . We’ll ask a couple of questions about your software needs, and you’ll receive tailored CRM quotes from leading UK providers . And who knows… give it a few years, and your business could be on this list!

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Apple and Salesforce bring together the best devices for business and the world’s #1 CRM

Enabling Powerful Apps and Customer Experiences Exclusive to iPhone and iPad

• Native Salesforce iOS apps for business: Salesforce, working with Apple, will redesign the Salesforce Mobile App to give customers rich experiences exclusively on iOS, with unique Apple capabilities such as Siri Shortcuts, Face ID, Business Chat and more. Salesforce will also introduce the first ever Trailhead Mobile App, first on iOS. The partners will also deliver powerful iOS apps for industries and small business that will serve their specific customer needs.
• Empowering Salesforce developers on iOS: Apple and Salesforce are developing the first Salesforce Mobile SDK that is optimized for Swift, Apple’s powerful and intuitive modern programming language. The native SDK will enable businesses and developers to build and deploy apps for iPhone and iPad on the Salesforce Lightning Platform, adding to the hundreds of thousands of iOS apps for business in the App Store today.
• Accelerating developer learning and career growth: Apple and Salesforce believe strongly in the democratization of technology and empowering developers — with any education level or background — to learn skills for the jobs of today and tomorrow. To support developer learning and career growth, Apple is launching a new Get Started with iOS App Development Trail that will teach anyone how to build native iOS apps in Xcode with Swift.
• The Get Started with iOS App Development Trail is available today at trailhead.com/apple .
• The new Salesforce Mobile SDK for iOS will be available by the end of 2018.
• The rebuilt Salesforce Mobile App will be available in early 2019; the first ever Trailhead Mobile App will launch later next year.

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Apple Inc. in 2020

• Format: Print
• | Language: English
• | Pages: 31

About The Author

David B. Yoffie

Related work.

• December 2020
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• January 2022

Apple Inc. in 2020 – Select Market Data

• Apple Inc. in 2020  By: David B. Yoffie
• Apple Inc. in 2020 – Select Market Data  By: David B. Yoffie

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10 CRM Case Studies From the World’s Biggest Brands 2024

• Category : Case Studies , CRM , Marketing
• Last updated on August 2, 2023
• By Viktor. A
• No Comments

It is no news that customers are constantly demanding deeper and more meaningful relationships with their chosen brands. That’s why organizations are currently leveraging CRM software to serve their customers better.

Today, we’ve put together useful CRM case studies from some of the world’s biggest brands. This article highlights CRM case studies uses and vital lessons you can replicate in your business.

Before we proceed, let’s look at the meaning of customer relationship management (CRM)

There are two main definitions of a CRM:

• It refers to a business’s principles and strategies to engage better and retain its customers.
• It refers to a software system that helps businesses to manage client relationships, leads, contacts and campaigns. Also, it allows companies to automate their processes and increases productivity.

Examples of CRM Software for lead generation, contact management, and automation are:

Table of Contents

The Best Overall

A sales-focused CRM that leverages AI to automate sales, lead & demand generation. 

Best Budget Choice

Freshsales automates your sales process, and helps drives sustainable business growth.

Best for Workflows

Customize your workflows to track all aspects of the sales cycle, from lead gen to post-sale support.

Best CRM Case Studies

If you’ve ever looked at brands like Apple, McDonald’s, Amazon or even Zara and are wondering how they’re run such conglomerates and still efficient in customer service. Keep reading then; you’re about to find out.

Scott Cook said, Instead of focusing on the competition, focus on the customer. Most of these brands have no superpower. They’ve only learned to focus on only one thing – the customer.

When you’re obsessed with delighting your customers, you will devise creative ways of satisfying them. Let’s go right in.

1. Coca-Cola CRM

The Coca-Cola Company is one of the world’s oldest and most influential brands. With a presence in over 200 countries, Coca-cola started as a carbonated soft drink business. But today, they are a conglomerate with over 200 product lines servicing billions of customers globally.

Logically speaking, for them to exist across several decades and remain relevant and competitive says a lot about their customer service. That said, let’s examine their customer relationship management (CRM).

Coca-Cola CRM Case Study:

Coca-cola’s mission is “ to refresh the world in mind, body, and spirit, to inspire moments of optimism and happiness through our brands and actions, and to create value and make a difference .”

Inspiring optimism and happiness are at the core of Coca-Cola’s CRM strategy. This is evident in their  marketing campaigns , billboards, brochures, commercials, store locations, and products.

We have billions of transactions a day on Salesforce. And everything is connected collaborative, and mobile.

– Ulrik Nehammer, Coca-Cola Germany, CEO.

Coca-Cola uses several enterprise CRM platforms to manage its clients’ relationships and stores globally. They use Salesforce and SAP primarily for contact management. System Applications and Products (SAP) is a strategic enterprise management platform. It’s quite robust and feature-rich.

While they use SAP globally, they use Salesforce on some of their country divisions to manage their business flow, connectivity, and contact management.

Read our complete Coca-Cola case study here.

2. Zara CRM

When you hear the word “Zara”, what comes to mind is clothing, luxury, and lifestyle. Established in 1975, Zara is a Spanish multi-national retail clothing chain.

They specialize in clothing accessories, beauty, shoes, and other lifestyle products. Zara’s phenomenal success in fashion and beauty is a testament to its solid CRM strategy. They effortlessly delight their customers in a way that leaves them returning for more.

Zara CRM Case Study:

Zara’s mission is to “ give customers what they want, and get it to them faster than anyone else .” Deducting from their mission statement, you can see a wordplay that puts royalty and kingship on their customers.

Zara’s CRM case study aims at elevating their customer’s needs above the company objectives. Zara leverages transparency, incentives and perks, support, personalization, swift check-out, and social media to achieve this.

The success of your business is based in principle on the idea of offering the latest fashions at low prices, in turn creating a formula for cutting costs: an integrated company in which it is manufactured, distributed and sold.

– Amancio Ortega – Founder, Zara Fashion Chain

Zara CRM starts with their website, which has a simple UI and is highly personalized to suit the user’s needs. Then, they’re massively present on social media and contribute to social issues affecting their clientele.

Lastly, Zara’s CRM is not complete without transparency and incentives. They’re transparent in all their dealings and usually deploy incentive programs to delight customers.

3. Unilever CRM

Unilever is a British multi-billion dollar conglomerate that deals primarily in consumer goods and consumables. They are arguably the largest producers of soap globally.

Brands like Unilever that have stood the test of time in quality, customer service, transparency, and consistency are worth emulating. With over 400 brands in about 190 countries, Unilever’s CRM strategy is paying off.

Unilever CRM Case Study:

Unilever’s mission statement is “ to add vitality to life. We meet everyday needs for nutrition, hygiene and personal care with brands that help people feel good, look good and get more out of life .”

Unilever’s CRM strategy focuses on elevating people’s well-being and helping them enjoy life to its fullest. This singular aim is the driving force behind their great customer experience initiatives, marketing campaigns, products, and positioning.

It’s about digitizing all the aspects of Unilever’s business to leverage the world of data and increase our digital capability in everything we do.

– Alan Jope, CEO at Unilever.

Another main Unilever’s CRM strategy is centred around Value-Based Procurement. They are keen on supporting their suppliers with upfront value. And they achieve this by empowering their suppliers and distributors with the tools to better relate with them.

They use Salesforce to support their business community and build solid relationships with their partners.

Bayerische Motoren Werke AG, known as BMW, is Germany’s leading automobile brand. They’re a luxury car brand and the  fourteenth largest producer of motor vehicles . BMW cars are known for their standard, uniqueness, and luxury. Let’s examine BMW’s CRM strategy.

BMW CRM Case Study:

BMW’s mission is to “ become the world’s leading provider of premium products and services for individual mobility.”  You’ll agree that BMW has become the world’s leading provider of premium automobile products. But the big question is, how did they get there?

BMW CRM case study is not too distant from the others. Firstly, the focus is on treating customers fairly, which is clearly stated in their  Supplier Programme . Their suppliers and end-users are at the core of their CRM strategy, which has kept them going.

I promise our customers will never have to compromise between driving pleasure and sustainable mobility.

– Oliver Zipse, CEO BMW AG.

Secondly, BMW CRM is focused on producing premium cars to attract new customers and retain the existing ones. And fortunately, it works for them. I’ve seen a couple of folks switch car brands to BMW because their cars are more reliable and have the highest quality

5. Tesco CRM

Tesco PLC is one of the world’s leading grocery and general merchandise retailers. With operations in over 11 countries, Tesco is a hyper-growth company swiftly expanding across territories.

Although it started as a grocery store, it is now morphed into several industries such as banking, technology accessories, and a few others. Not just that, they’ve been named among the top customer-friendly organizations.

Tesco CRM Case Study:

Tesco’s mission statement is  “What we make matters better, together. This statement encapsulates Tesco’s aim to serve customers across cultures and backgrounds.

Tesco is among the first multi-national brand to adopt CRM software. In 2009, Tesco announced that they were adopting the RightNow CRM (now acquired by Oracle).

The key to Tesco’s success is the customer-focused culture that has permeated the company.

– Jeremy Garlick, Partner, Insight Traction.

Tesco’s CRM was primarily used in their call centres to support their electronics division. Aside from that, they used it to amplify their omnichannel communication strategy by managing customer data and interactions across phone, chat and email.

Adopting a CRM helped Tesco be present at all times for their customer when needed across channels. Most importantly, they were able to win the hearts of their customers.

6. Uber CRM

With a presence in 72 countries, Uber redefines how we move and eat. Uber is an American mobility provider allowing people to move conveniently from one location to another. One of the things that makes Uber special is that they’re a mobility startup with no cars. That means they’re servicing two main customer bases: drivers and passengers.

As of the time of writing, Uber has a 72% market share for ride-sharing in the United States, with about 122 million monthly active users

Uber CRM Case Study:

Uber’s mission is “ Transportation as reliable as running water, everywhere for everyone .” In other words, they aim to make transportation accessible at any time.

The big question is, what CRM does Uber use? Uber uses LiveRamp as their CRM anonymizer. Essentially, they LiveRamp CRM to segment users into specific life-cycle stages. It allows them to craft personalized and targeted campaigns that resonate with the customers.

There is a high cost to a bad reputation… it really matters what people think of us, especially in a global business like ours, where actions in one part of the world can have serious consequences in another.”  

– Dan Khosroshahi.

Furthermore, Uber uses CRM to gain deeper insights into how customers use their apps, the frequency, and overall interaction, and even sample their IDs. With these insights, Uber can better serve and delight its customers. More on Uber’s case study here.

7. McDonald’s CRM

As the name implies, McDonald’s is a fast-food conglomerate. They’re currently the leading food service organization operating over 30,000 restaurants in more than 100 countries. McDonald’s expansion strategy is bent on franchises and joint ventures. They also have some sister brands in the fast-fast industry doing incredibly well.

Mcdonald’s CRM Case Study:

McDonald’s mission statement is  to be our customers’ favourite place and way to eat and drink.  Their mission statements depict McDonald’s passion for differentiation, uniqueness, and class.

McDonald’s CRM case study is hinged on their passion for differentiation, which is evident in the architectural designs of their restaurants, food recipe and taste, service delivery, and mode of operation.

Our sustained performance gives us confidence that our strategy is working, as more customers are experiencing a better McDonald’s daily.

– Steve Easterbrook, CEO, McDonald’s.

McDonald’s uses PowerCenter CRM, which is powered by Astute Solutions. This CRM helps McDonald’s efficiently manage their huge volume of customer contacts, analyze data, and manage their store location.

The benefits of CRM software to a business are enormous, and McDonald’s is not left out. They’re equally using it to enhance their marketing efforts and close more deals.

8. British Airways CRM

British Airways is a UK-based carrier and one of the biggest airline groups in the world. They’ve built a reputable brand over the years, which has also given birth to several sister brands.

BA Group is the founding member of the Oneworld alliance. They have over 45,000 employees in 100 countries and assist about 40 million passengers annually. So how are they able to still maintain awesome customer service?

British Airways CRM Case Study:

British Airways’ mission statement is “ To ensure our customers fly confidently that together, we are acting responsibly to take care of the world we live in “. British Airways’ CRM case study is centred around “making their passengers feel confident.”

As we prepare for a safe return to travel, we remain focused on offering our customers the most convenient and affordable testing options to support and facilitate a seamless travel experience.

– Sean Doyle, CEO, British Airways

British Airways uses TCRM BA as its enterprise management solution. The company adopted it in 2002, and since then, they’ve been using it to do the following:

• Campaign management
• Management of loyalty programs
• Leisure database
• External requirements
• Cost savings

Best of all, they use this platform to efficiently manage and schedule all their marketing campaigns internally and externally. They also use for customer service across channels.

9. Amazon CRM

Amazon is an American conglomerate focusing on e-commerce, cloud computing, digital streaming, and artificial intelligence. They’re among the top 5 most valuable companies worldwide and one of America’s biggest employers.

Amazon, which started as an online book store, is currently dominating up to 7 industries. Not just that, they’re a customer-centric company famously known for their outstanding customer service.

Amazon CRM Case Study:

Amazon’s mission statement is “ to offer our customers the lowest possible prices, the best available selection, and the utmost convenience .” Amazon’s focus on the customer is truly remarkable.

Primarily, Amazon’s CRM case study follows these four guiding principles:

• Customer obsession rather than competitor focus
• Passion for invention
• Commitment to operational excellence
• Long-term thinking

We see our customers as guests at a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.

– Jeff Bezos, CEO of Amazon

In fact, they aim to become Earth’s most customer-centric company, Earth’s best employer, and Earth’s safest place to work. That drive to become the best led them to create innovative products like I-Click shopping, personalized recommendations, Amazon Echo, and Fire TV, to mention a few.

So, what CRM does Amazon use? Amazon developed its CRM in-house, which they use to manage its customer data across divisions, countries, languages, and products.

10. Apple CRM

Famously known for their slogan, think differently. Apple is a technology company specializing in consumer electronics, software and online services. Apple is the world’s most valuable company and the first to hit a trillion in market capitalization.

Apple CRM Case Study:

Apple’s mission is “ to bring the best user experience to its customers through innovative hardware, software, and services .” Like Amazon, Apple is a customer-centric company that is truly obsessed with its customers.

Apple is also obsessed with its product quality. Their products are highly standardized and unique. And it’s the reason why they enjoy a high level of brand loyalty. Apple’s customers are one of the most loyal sets of customers globally.

Apple CRM case study is centred around four cardinal points: Apple customer-centric outlets, understanding customer needs, Apple ID, & irresistible branding that works. I explained them in detail  here .

Also, like Amazon, Apple uses an in-house CRM to manage its customer data, marketing campaigns, and customer relationships. Apple loves owning their processes, so most of its operations are usually in-house.

Wrapping Up!

These case studies show us the efficacy and formidability of a CRM software. When out to efficient use, it can be a very powerful tool. And it doesn’t matter the size of your business, whether big or small. All you need to do is to pick a CRM that aligns with your business goals and run with it.

Looking for a CRM to start with? Here are our recommendations:  Zendesk ,  Pipedrive ,  Hubspot ,  Zoho  and  Freshsales . Click on any one of them to claim your free trial.

Frequently Asked Questions

Customer relationship management use cases are real-life examples and applications of CRM software and strategies. Like the 10 use cases from big brands listed in this article.

There are tons of use cases for CRM systems, but here are three profound ones: CRM systems can serve as a contact management system, a pipeline system for attracting and converting them paying customers, and a workflow automation station.

Essentially, the main components of CRM are contact and database management, workflow automation, omnichannel marketing capability, and integration options.

Viktor. A is a writer and researcher with experience writing about various topics, including CRM software, SaaS, finance, and technology. When he's not writing, he's swimming and travelling

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• A Chatbots in Customer Relations Management (CRM)

I CRM: An Introduction

The birth of the customer relationship management (CRM) system is inextricably linked to the emergence of marketing philosophy. It all started in the 1960s, when firms’ interest shifted from recurring sales to the substantial satisfaction of consumer needs. Their goal was thus to identify, through marketing research, the needs of consumers and not to sell a large number of products that did not really meet their needs. 1 x K. Tzortzakis & A. Tzortzaki, Marketing Principles: The Greek Approach (in Greek), 2nd ed., Gerakas, Rosili, 2002, pp. 38-39. This new marketing philosophy contributed to the ‘birth’ of CRM systems. In the early 1990s, with the invention of the World Wide Web (www), which allowed Internet users to search for information by moving from one document to another, companies faced many difficulties in organizing the vast amount of data created by customers. In response, specialists developed hardware and software solutions to better handle this huge volume of customers’ information. Sales Force Automation (SFA) and customer service support were parts of these new technologies. With their help, firms could analyse consumers’ behavioural patterns more effectively and build trustworthy relationships with them. As time passed, marketing specialists started to use the term ‘CRM’ to refer to the improvement between firms’ and customers’ relationships. 2 x H. Karjaluoto, H. Kuusela & H. Saarijärvi, ‘Customer Relationship Management: The Evolving Role of Customer Data’, Marketing Intelligence & Planning , Vol. 31, No. 6, 2013, pp. 1-4. The extended use of the CRM system led to various definitions as an attempt to describe its main characteristics. At the beginning, as Buttle and Maklan report, 3 x F. Buttle & S. Maklan, Customer Relationship Management: Concepts and Technologies , 4th ed., Routledge, 2019, pp. 3-4. Internet experts usually defined CRM as “an information industry term for methodologies, software and usually Internet capabilities that help an enterprise manage customer data in an organized way”. For them, CRM was considered a technological tool, which offered the possibility to manage customers’ data. Nowadays, companies present CRM not only as a software but also as a process, philosophy and intention to fulfil customers’ needs and desires. As they mention, CRM is the process of managing all aspects of interaction a company has with its customers, including prospecting, sales, and service. CRM applications attempt to improve the company/customer relationship by combining all these views of customer interaction into one picture. CRM’s primary goal is to improve long-term growth through a better understanding of customer needs and behavior.

This strategic approach emphasizes the whole journey, from gaining a customer to turning him/her into a loyal and profitable advocate. 4 x Buttle and Maklan, 2019, p. 4. There are also the supporters of the managerial approach, who link the CRM system with the customer experience (CX) movement. This movement attempts to improve the experience of customers as they interact with the company. When a company adopts effective CRM technologies, consumers and customers have the possibility to better interact with that company, by having a greater experience. 5 x Ibid ., p. 5.

CRM practices are extremely beneficial not only for the company itself but also for the customer. A host of benefits accrue at both the managerial and the CX levels. The organizational benefits can be considered to be the following:

Improving Customer Services: As Mohammadhossein and Zakaria explain, 6 x N. Mohammadhossein & H. Zakaria, ‘CRM Benefits for Customers: Literature Review (2005-2012)’, International Journal of Engineering Research and Applications , Vol. 2, No. 6, 2012, p. 1582. CRM services help firms to manage customers’ requests. For example, a call centre software connects customers with employees who can give a solution to their problem. High-quality services boost the company’s revenue and increase customer retention.

Customer Segmentation: Segmentation is defined as the classification of objects that have similar characteristics into the same groups. In CRM, customers are classified according to certain variables, for example demographics, into target groups. These segments help companies to find more easily and personalize customer needs. 7 x Ibid .

Improve Customization of Marketing: As CRM systems can capture customers’ needs, a company can possibly invest its resources properly and customize the right product for each customer. 8 x Ibid ., p. 1583.

Organization: CRM allows firms to organize and automate some of their components such as marketing processes, business analytics of customers’ data, business workflows and communication with suppliers. Thus, companies are organized more easily and efficiently. 9 x J. Kulpa, ‘Council Post: Why Is Customer Relationship Management So Important?’ [online], Forbes, 2017. Available at: www.forbes.com/sites/forbesagencycouncil/2017/10/24/why-is-customer-relationship-management-so-important/?sh=2e364abb7dac .

Proper implementation of CRM strategies can enhance the customer experience and loyalty. For example, with the right application of technologies, which consists partly of operational CRM, a company aims at recognizing better customers’ needs or communicating with them more accurately and reliably. Also, when analytical CRM works well, customers receive more personalized and on-time offers, because experts can detect their actual desires. 10 x F. Buttle, Customer Relationship Management Concepts and Technologies , 2nd ed., Elsevier, 2009, pp. 178-179. Therefore, they are more satisfied and willing to purchase products or services again from the same firm. Among the companies that first applied CRM techniques are Apple and Amazon. When consumers buy an Apple device, they are asked to create an Apple ID – a unique account that synchronizes their information across all Apple devices they may have. 11 x R. Binns, ‘Case Study: How Apple Have Mastered CRM’, Expert Market [online], 2020. Available at: www.expertmarket.co.uk/crm-systems/apple-crm-case-study . These accounts save their preferences and allow Apple to provide more personalized recommendations on the basis of their interest and previous search history. For consumers this is a convenient and time-saving solution. These accounts constitute a part of Apple’s CRM strategy and therefore provide data that allow insights about costumers’ needs as well as building the potential for implementing targeted marketing techniques. 12 x P. Singh, ‘Top 5 Customer Relationship Management Examples’. [online] appvizer.com , 2020. Available at: www.appvizer.com/magazine/customer/client-relationship-mgt/customer-relationship-management-examples#1-apple-crm . Amazon is the most well-known platform for online purchases. One of the main reasons underlying its success is the ideal utilization of the CRM system. When customers purchase an item from Amazon, they need to create a private account. This gives Amazon the possibility to track their purchases and browse their purchasing history to effectively build more personalized marketing and email campaigns. Moreover, Amazon offers the ability to adjust their accounts to carry out purchases in one click. Consumers really appreciate the fast checkout processes and the targeted product proposals. The better experience they have, the more likely they are to become loyal customers. 13 x Ibid . In recent years the field of artificial intelligence (AI) has been growing rapidly. According to Frankenfield, 14 x J. Frankenfield, ‘How Artificial Intelligence Works’. [online] Investopedia, 2020. Available at: www.investopedia.com/terms/a/artificial-intelligence-ai.asp . AI is the simulation of human intelligence in machines that are programmed to act like humans and mimic their behaviours. AI methods and technologies are not used for scientific reasons alone. Nowadays, businesses leverage AI technology for administrative, managerial or marketing purposes. One example is the use of AI ‘bots’ or, more precisely, ‘chatbots’, by firms in order to optimize their CRM system. 15 x P. Gentsch, AI in Marketing, Sales and Service: How Marketers Without a Data Science Degree Can Use AI, Big Data and Bots , Cham, Springer, 2019, p. 3.

III The Rise of Chatbots

Botadra 16 x B. Botadra, ‘Web Robots or Most commonly known as Bots’, p. 2. Available at: www.academia.edu/37700458/Web_Robots_or_Most_commonly_known_as_Bots . points out that a bot is also referred to as Web Robot, Internet Bot, Spider or WWW Bot. The first bot in history (1964) was ELIZA, whose purpose was to mimic a psychotherapist by using Natural Language Processing programming. The user asked a question, and ELIZA would answer by following the program code. With time, various bots were introduced: Siri, by Apple in 2013; Alexa, by Amazon in 2014; or Cortana, by Microsoft in 2014. Bots are software applications that automate specific tasks pretty fast 17 x Ibid . and in a seamless way, 18 x HubSpot Research, p. 4. Available at: https://cdn2.hubspot.net/hubfs/53/assets/hubspot.com/research/reports/What_is_a_bot_HubSpot_Research.pdf?t=1492209311951 . assigned to them through coding. Bots can be 19 x Botadra, p. 3. chatbots, crawlers, transaction bots, informational or entertainment bots. On the other hand, they can perform harmful tasks and therefore can be hacking bots, spam bots, scrapers, impersonators or zombie bots (Figure 1 ).

‘Chatbots’ are a category of bots that act online in chat or messaging platforms like Facebook, Messenger and so on. Botadra 20 x Ibid ., p. 7. and Aberer et al . 21 x K. Aberer, K. Fawaz, H. Harkous & K. Shin, ‘PriBots: Conversational Privacy with Chatbots’, 2016. Available at: www.researchgate.net/publication/305567688_PriBots_Conversational_Privacy_with_Chatbotsact_com . ‘What Is CRM: A Definition of CRM and Its Meaning’, p. 1. Available at: www.act.com/what-is-crm . explain that these bots have the ability to carry out a conversation with humans. There is a small promise in word ‘chatbots’. These bots are designed to perform a conversation and interact with users via auditory and textual methods. Brandtzaeg and Følstad 22 x P. Brandtzaeg & A. Følstad, ‘Chatbots: Changing User Needs and Motivations’, Interactions , Vol. 25, No. 5, 2018, p. 40. define chatbots as machine agents that serve as natural language user interfaces to data and services through text or voice. Chatbots allow users to ask questions or make commands in their everyday language and get the needed content or service in a conversational style.

Chatbots have been around since 1964, but their real expansion was in 2016, when Facebook and Messenger allowed firms to place chatbots on their social networking platforms (Figure 2 ). 23 x Brandtzaeg and Følstad, 2018, p. 38.

IV Chatbots Classification

Chatbots’ classification is based on parameters (Figure 3 ) such as knowledge domain, service provided goal, and input processing and response generation method. 24 x K. Nimavat & T. Champaneria, ‘Chatbots: An Overview. Types, Architecture, Tools and Future Possibilities’, International Journal for Scientific Research & Development , Vol. 5, No. 7, 2017, p. 1019.

1 Knowledge Domain

This classification concerns the amount of data a chatbot can handle and the level of its knowledge. 25 x E. Adamopoulou & L. Moussiades, ‘An Overview of Chatbot Technology’, IFIP International Conference on Artificial Intelligence Applications and Innovations , 2020, pp. 377-378. Open Domain chatbots can talk about general topics and respond in an appropriate way. Siri and Alexa are well-known examples of this case. 26 x Nimavat and Champaneria, 2017. Closed Domain bots’ knowledge is specified in a particular topic. For example, a restaurant bot would be able to book a table or to take an order but would not be able to tell how the weather is.

2 Service Provided

This categorization concerns the bots’ sentimental proximity to the user, its level of interaction and the task that a bot performs. Interpersonal chatbots do not consist of a companion for the user but are designed in order to pass him information about a service such as restaurant booking or flight booking. They are not obliged to be friendly or to remember user’s information. Intrapersonal bots exist within the user’s personal domain such as apps like WhatsApp or Messenger. Their main purpose is to perform tasks related to the user’s personal account such as managing calendar, storing the user’s opinions or photos and so on. Inter-agent bots dominate in the AI area. They have the ability to communicate with other bots. As bots become omnipresent, the need for protocols to achieve such kind of communication is growing rapidly. While a chatbot cannot be completely inter-agent, it can be a service that handles other bots or services. Amazon’s bot Alexa is a great example. A user can purchase from Amazon a device that has inside it bot technology and several protocols. When it is time to go to bed, he or she can say, “Alexa, could you please switch off the lights?” 27 x Ibid ., 2017, p. 1020.

Bots can also be classified on the basis of what their goal is. Informative bots aim at providing users with information that is already stored or available from a fixed site. Most of the time they are based on an information retrieval algorithm. An example of such a bot is FAQ chatbots. Conversational chatbots’ purpose is to talk to the user like another human being. Siri, Alexa, and so on can carry out conversations by correctly answering questions in a sentence posed by a human. Eventually, task-based bots are capable of performing some specific tasks, such as booking a flight. Their intelligence lies in asking for information and understanding users’ input. 28 x Adamopoulou and Moussiades, 2020. , 29 x Nimavat and Champaneria, 2017, p. 1020.

4 Input Processing and Response Generation Method

This classification is based on the methods of generating responses and processing inputs. Intelligent systems create responses and use natural language systems to understand the question. They are used when ample data are available. Ruled-based bots are used when the possible scenarios and outcomes are fixed. Hybrid bots do not belong to one category alone. Some bots, for example, have conversational capabilities but can also store data. 30 x Ibid .

V Chatbots and CRM Systems

The rise of chatbots is inextricably linked with the expansion of social media. On average, people are spending most of their time on messaging platforms like Facebook or Messenger, and 2.5 billion users have at least one messaging app installed in their phones. 31 x Aberer et al ., 2016. In 2017, for example, Messenger had 1.2 billion active users. 32 x Brandtzaeg and Følstad, 2018. Another interesting fact is the phenomenon of ‘app fatigue’. App platforms, such as Apple’s Appstore, offer a tremendous number of apps, but users are unwilling to add new apps to their smartphones. A recent study in 2016 has shown that 80% of a person’s online time is dedicated only to apps such as Facebook, Messenger, Instagram or Google and that nine out of the top ten most used apps were created by Facebook and Google. 33 x HubSpot Research, pp. 5-6. These fundamental changes in the behaviour of online users led companies to adopt the chatbot technology. Nowadays, firms leave aside the creation of new apps and prioritize chatbots in order to reach their audience. Not only technology legends like Google and Amazon but also customer service companies like Starbucks tend to reach their customers using chatbots. By 2021, more than 50% of companies will have invested on chatbot or bot technology rather than on traditional app creation. 34 x Brandtzaeg and Følstad, 2018. The mechanism that led chatbots to be part of the firms’ CRM system is explained shortly. Companies consider that, in general, the main motivation for someone to use a chatbot is to obtain specific service or information. In response, they use chatbots mainly for customer support. With customer support a company helps or gives advice to its clients. 35 x A. Følstad, M. Skjuve & P.B. Brandtzaeg, ‘Different Chatbots for Different Purposes: Towards a Typology of Chatbots to Understand Interaction Design’, in S. Bodrunova et al . (Eds.), Internet Science , Cham, Springer, 2019, p. 6. These humanized interfaces (chatbots) provide a personalized, more automated 24/7 support. 36 x A. Bergner & C. Hildebrand, ‘AI-Driven Sales Automation: Using Chatbots to Boost Sales’, NIM Marketing Intelligence Review , Vol. 11, No. 2, 2019, p. 36. The chatbot learns a lot of things about customers’ needs. It acts like a friend who understands their wishes and fulfils them. They are also designed to be fully personalized and to optimize customer satisfaction and increase firms’ sales. These automated assistants help the CRM system to fulfil its primary goal, that is, to better understand customers’ needs and establish long-term relationships with them. 37 x P. Gentsch, AI in Marketing, Sales and Service: How Marketers Without a Data Science Degree Can Use AI, Big Data and Bots , Cham, Springer, 2019, p. 113. Here are some case studies. British Airways has a chatbot in Messenger app. This bot includes events that happen in London, provides hotel discounts and sells tickets. Moreover, a well-known example is the Kayak Facebook Messenger bot (Figure 4 ), which provides information about discounts on flight tickets and hotels and also keeps records of previous conversations and uses Kayak search history to personalize its content. The fact that this bot has an internal database with customers’ previous purchases and reviews makes the communication between the company and its customers more efficient. An extended personalization is achieved with chatbot ‘Alexa’, which is directly connected to Amazon’s CRM. Several of Amazon’s devices, such as Amazon Echo, are powered by Alexa, a voice personal assistant that accompanies the user all the time. Some of its main abilities are playing music, informing about the weather, ordering food or finding the nearest store. This bot consists of a digital entity, which acts on behalf of the customers and improves Amazon’s CRM by personalizing their profile or storing their data. Hence, Amazon can track their desires and create efficient marketing campaigns. 38 x Ibid ., p. 116.

Undeniably, chatbots can be considered ‘tiny’ treasures that help CRM to optimize company’s interactions with its clients. For this reason, a chatbot is designed to be a friendly automated personal assistant with the ability to engage with the customer in more natural dialogue for enhancing his or her trust and experience. A study has shown that many clients put too much trust in advice provided by an automated assistant and are more willing to accept an incorrect recommendation from a chatbot rather than from a traditional adviser. Additionally, a bot is created to personalize customers’ characteristics and store an incredible volume of their data. As a result, by interacting with it, people are not seeing a machine but rather another human who can understand their needs, provide them with a service and suggest solutions to their problems. Hence, consumers have a highly relative and intimate attitude towards a company and are willing to pay higher prices to purchase a product or service (brand loyalty). 39 x Bergner and Hildebrand, 2019, pp. 38-39.

VI Reshaping E-Commerce

Digitalization is the driving force behind the evolution of e-commerce. As shown in the following Figure 5 , in the first stage we had ‘one-channel’ commerce. Customers were buying their products directly from the store. What was new was that they had the possibility to pay using a point of sale (POS). Companies, from their side, were using simple marketing strategies like direct email and advertisement, especially on TV. This level can also be defined as e-commerce 1.0. 40 x Gentsch, 2019, p. 117. The extended use of Internet led companies to create online channels such as e-shops or accounts on social platforms.

This was when ‘multichannel’ commerce or e-commerce 2.0 was born. Firms were now able to sell products or services through different channels. 41 x N. Beck & D. Rygl, ‘Categorization of Multiple Channel Retailing in Multi-, Cross-, and Omni-Channel Retailing for Retailers and Retailing’, Journal of Retailing and Consumer Services , Vol. 27, 2015, p. 174. This type of commerce looks like a wheel. At its centre lies the product, and on the rim of the wheel are all the channels from which the customer can find the product, such as retail stores, online catalogues and websites. 42 x N. Winkler, ‘Omnichannel Vs Multichannel: What Is the Difference?’ [online] Shopify Plus, 2019. Available at: www.shopify.com/enterprise/omni-channel-vs-multi-channel . The problem, here, is that these channels are not connected. The customer has no interaction with the channels, and companies do not control channel integration. 43 x Beck and Rygl, 2015. Because each channel works separately from the other, customers need to navigate through different ones to find the appropriate information. 44 x Omnisend Blog, ‘Omnichannel Vs. Multichannel: How to Know the Difference’, 2020. Available at: www.omnisend.com/blog/omnichannel-vs-multichannel/ . In response to this problem, e-commerce 3.0 strode onto the stage. In omnichannel commerce customers can choose products through a rich variety of channels, with which they can interact. 45 x Beck and Rygl, 2015, p. 175. Now at the centre of the wheel is the customer, and on its rim are the various interconnected channels. 46 x Winkler, 2019. Customers’ experience is enhanced for two reasons: at first, they are not obliged to jump from channel to channel because each one provides the same information and, secondly, companies’ focus on their needs optimizes their experience. 47 x Omnisend Blog, 2020. The last stage is Conversational Commerce. Owing to the extensive use of messenger apps and the advances in AI, e-commerce 4.0 is the new trend. This stage features intelligent personal assistants (chatbots), who can interact with customers and fulfil their needs in an automated way. All the channels of a company are interconnected, but customers can also communicate through these channels with personal assistants to ask questions and purchase a product or service. For example, Uber collaborated with Facebook so that customers could book their rides in a seamless way via a messenger chatbot. In this new era, e-commerce is becoming increasingly automated, and customers are having an even stronger connection with the companies. 48 x T. Choudhury, P. Kumar & N. Piyush, ‘Conversational Commerce a New Era of E-Business’, International Conference System Modeling & Advancement in Research Trends (SMART), 2016, p. 323.

VII Privacy Issues

While users appreciate the guidance and support a chatbot can provide, they also have to share a huge volume of personal information with the chatbot to receive the correct recommendations. By doing this, a firm stores a lot of data about customers, who are sometimes unaware of this. Hence, privacy concerns have been engendered to a great extent. A recent study shows that consumers worry about privacy and security concerning the interaction with chatbots. This concern, according to another study, can limit consumers’ willingness to use a chatbot. 49 x C. Ischen, T. Araujo, H. Voorveld, G. van Noort & E. Smit, ‘Privacy Concerns in Chatbot Interactions’, in A. Følstad et al . (Eds.), Chatbot Research and Design , Cham, Springer, 2019, pp. 1, 3. Data protectionists criticize the way companies collect and use our data and emphasize that we need to be aware of the data we share. 50 x Gentsch, 2019, p. 116. People share a lot of information, such as their location, name and purchasing history, with a chatbot, and, interestingly, they are often unaware of this. Most of them look at the convenience of talking with a bot, ignoring the consequences. For example, new research from the Northeastern University provides support for the idea that Amazon’s Alexa records ‘accidentally’ everything we say. This personal assistant collects data even when a user does not interact with it. It has been proven that Alexa is self-activated and records as much as 40 seconds of audio information each time. 51 x S. Morrison, ‘Alexa Records You More Often Than You Think’. [online] Vox, 2020. Available at: www.vox.com/recode/2020/2/21/21032140/alexa-amazon-google-home-siri-apple-microsoft-cortana-recording . By tracking our location and creating a vast amount of metadata, either accidentally or not, Amazon knows everything about every customer. Although it is beneficial for marketing strategies, Amazon has the possibility to share our information with other organizations. 52 x S. Kojouharov, ‘Chatbots, AI & the Future of Privacy’ [online] Medium, 2018. Available at: https://chatbotslife.com/chatbots-ai-the-future-of-privacy-174edfc2eb98 . Another similar example is Google Assistant. This bot recommends nearby places to eat, provides weather updates and personalizes our needs. However, it has been argued that users are sometimes being recorded without saying the trigger phrase ‘hey Google’. There are witnesses that personal assistants like Siri, Cortana and Google are activated because they thought that someone said the ‘wake up’ word. Moreover, it has been argued that Google suggests a search term or an advertisement on the basis of a conversation they had with another person. 53 x Choudhury, Kumar and Piyush, 2016, p. 323; Ischen, Araujo, Voorveld, van Noort, Smit, 2020, pp. 1, 3. The increase in the number of bots on chat platforms is rapid. What is missing is that as these interfaces are evolving, we have a shift in data control from users to Messenger or Facebook. It is not only companies that upload their bots on these platforms that store users’ data but also Facebook and Messenger that have the right to do that, according to their policy. Both of them have the potential to become strong data brokers. All conversations or transactions within these platforms are also stored and filtered on the basis of personal users’ IDs and can be sold to governments or other organizations. 54 x H. Harkous, ‘How Chatbots Will Redefine the Future of App Privacy’. [online] Medium, 2016. Available at: https://chatbotsmagazine.com/how-chatbots-will-redefine-the-future-of-app-privacy-eb68a7b5a329 . A great example is the Cambridge Analytica scandal, in which, in 2015, a political marketing company collected 50 million Facebook users’ data by using a personal quiz that was initially approved by Facebook. Because of this scandal, developers could not upload temporally new chatbots on Facebook’s platform. 55 x G. Skandali, ‘Cambridge Analytica: How Will It Play Out for Chatbots?’ online] Medium, 2018. Available at: https://medium.com/yellow-hammock/cambridge-analytica-how-will-it-play-out-for-chatbots-5c1d44f4fe29 . For this reason, Digital Liberties organizations have already expressed their concern about this trends, and several technical ways to solve the problems arising from it have been proposed. One such idea for Facebook could be to introduce private channels with a high level of encryption between the user and the chatbots so that Facebook would know the bots with which a user interacts but not their conversation. 56 x Harkous, 2016. In the following paragraphs, a thorough investigation is attempted to view chatbots through the lens of law protecting users’ privacy, personal data and digital liberties.

• B Legal Framework

I Legal Regulation of Chatbots

While the use of chatbots is constantly increasing, the regulation of their legal framework is not quite clear. As tools that process, collect and store personal data, they endanger our online privacy. Among the most representative examples of the application of AI is the digital policy of the Union, around which our interest is centred, as it foregrounds the reasonable exploitation of AI. The point of reference and study is the adoption of the first legislative framework for AI by the Commission (Artificial Intelligence Act-section I). AI technology is part of an ongoing evolution and constantly poses new challenges, which the laws and the rules of each country cannot timely regulate. 57 x J. Isaak & M.J. Hanna, ‘User Data Privacy: Facebook, Cambridge Analytica, and Privacy Protection’, Computer Magazine , Vol. 51, 2018, pp. 56-59. Available at: www.computer.org/csdl/magazine/co/2018/08/mco2018080056/13rRUxbCbmn . Yet, as different functions of AI can affect the right to privacy in several ways, such as data collection without the knowledge and consent of subjects, locating people, extracting and generating sensitive information, producing automated decision-making, profiling, etc., finding an appropriate legal framework is crucial for the protection of personal autonomy and the exercise of other fundamental rights. 58 x K.M. Manheim & L. Kaplan, “Artificial Intelligence: Risks to Privacy and Democracy”, Yale Journal of Law & Technology, Vol. 21, 2019, p 106. In addition, as privacy has a broad content, including the processing of personal data and while the use of chatbots includes similar procedures, the GDPR is applicable (section  2 ).

II Regulatory Framework on Artificial Intelligence

On 21 April 2021, the European Commission (‘Commission’) adopted a proposal for a “Regulation laying down harmonized rules on Artificial Intelligence” (‘AI Regulation’), which sets out how AI systems and their outputs can be introduced to and used in the European Union. The draft AI Regulation is accompanied by a proposal for a new Regulation on Machinery Products, which focuses on the safe integration of the AI system into machinery, as well as a new Coordinated Plan on AI outlining the necessary policy changes and investment at the member state level to strengthen the EU’s leading position in trustworthy AI. 59 x At the time being the draft AI Regulation is being processed by the European Parliament and Council. AI receives a wide definition in the official European text. Following Article 3,

‘artificial intelligence system’ (AI system) means software that is developed with one or more of the techniques and approaches listed in Annex I (‘machine learning’, ‘logic- and knowledge-based’ and ‘statistical’ approaches) and can, for a given set of human-defined objectives, generate outputs such as content, predictions, recommendations or decisions influencing the environments they interact with;

According to the official press release published by the European Commission regarding the new rules for AI, 60 x The official press release is available at https://ec.europa.eu/commission/presscorner/detail/en/QANDA_21_1683 . risk categories are adopted on the basis of the intended purpose of the AI system, in line with the existing EU product safety legislation. The criteria for this classification include the extent of the use of the AI application and its intended purpose, the number of potentially affected persons, the dependency on the outcome and the irreversibility of harms, as well as the extent to which existing Union legislation provides for effective measures to prevent or substantially minimize those risks.

As explicitly predicted, the Commission proposes a risk-based approach, with four levels of risk:

Unacceptable Risk: A very limited set of particularly harmful uses of AI that contravene EU values because they violate fundamental rights (e.g. social scoring by governments, exploitation of vulnerabilities of children, use of subliminal techniques and – subject to narrow exceptions – live remote biometric identification systems in publicly accessible spaces used for law enforcement purposes) will be banned.

High-Risk : A limited number of AI systems defined in the proposal, creating an adverse impact on people’s safety or their fundamental rights (as protected by the EU Charter of Fundamental Rights) are considered to be high-risk. Annexed to the proposal is the list of high-risk AI systems, which can be reviewed to align with the evolution of AI use cases (future-proofing). These also include safety components of products covered by sectorial Union legislation. They will always be high-risk when subject to third-party conformity assessment under that sectorial legislation.

In order to ensure trust and a consistent and high level of protection of safety and fundamental rights, mandatory requirements for all high-risk AI systems are proposed. Those requirements cover the quality of data sets used; technical documentation and record keeping; transparency and the provision of information to users; human oversight; and robustness, accuracy and cybersecurity. In case of a breach, the requirements will allow national authorities to have access to the information needed to investigate whether the use of the AI system complied with the law. The proposed framework is consistent with the Charter of Fundamental Rights of the European Union and in line with the EU’s international trade commitments.

Limited Risk : For certain AI systems specific transparency requirements are imposed, for example where there is a clear risk of manipulation (e.g. via the use of chatbots). Users should be aware that they are interacting with a machine.

Minimal Risk : All other AI systems can be developed and used subject to the existing legislation without additional legal obligations. The vast majority of AI systems currently used in the EU fall into this category. Voluntarily, providers of those systems may choose to apply the requirements for trustworthy AI and adhere to voluntary codes of conduct.

Regarding the use of chatbots, the draft AI Regulation reserves a relevant provision, namely, “ for some specific AI systems, only minimum transparency obligations are proposed, in particular when chatbots or ‘deep fakes’ are used ”. The aforementioned transparency obligation is thoroughly exposed in Article 52 of the text, whose paragraphs  1 and   3 are quite relevant. In this vein , providers shall ensure that AI systems intended to interact with natural persons are designed and developed in such a way that natural persons are informed that they are interacting with an AI system, unless this is obvious from the circumstances and the context of use . It is easily extracted that the nature of such ‘information’ corresponds directly to ‘transparency’, which can be described as the opposite of opaqueness and secretiveness. In this context, according to Advocate General R.J. Colomer in the case C-110/03, 61 x C-110/03, Judgement of the Court (Third Chamber) of 14 April 2005, Kingdom of Belgium v. Commission of the European Communities . transparency is concerned with the quality of being clear, obvious and understandable without doubt or ambiguity . It should also be noticed that the provision of such quality constitutes the main responsibility of administrators of AI systems. More specifically, in order to achieve an adequate and sufficient level of information for users of AI systems, their administrators shall disclose to the user that “the content has been artificially generated or manipulated”. 62 x See para.  3 of the Art. 52 of the draft AI regulation. It is of primary value that the subject recognizes, without any doubt, the existence of ‘bots’ during any process or type of communication. Widely approaching the issue, we could claim that not revealing to the person that ‘deep fake’ content could result in legal damages to the administrator of AI systems. In that context, transparency could be given a legal binding status appearing as a general principle of law. 63 x See T. Tridimas, The General Principles of EU Law , 2nd ed., Oxford, Oxford University Press, 2006, p. 242. Furthermore, since chatbots are intensively used in e-commerce, it should be underlined that the transparency obligation is imposed by other European legal texts, such as the Regulation (EU) 2019/1150 of the European Parliament and of the Council of 20 June 2019 on promoting fairness and transparency for business users of online intermediation services. The Regulation imposes new rules on parties operating online trading platforms and similar services and taking on the role of an intermediary. According to EU officers, as regards transparency , platforms are required to use plain and intelligible terms and conditions for the provision of their online intermediation services. They should provide a statement of reasons each time they decide to restrict, suspend or terminate the use of their services by a business user. Furthermore, platforms should publicly disclose the main parameters determining the ranking of business users in search results, as well as any differentiated treatment that they grant to goods and/or services offered directly by them or through any business falling within their remit. They should also disclose the description of the main economic, commercial or legal considerations for restricting the ability of business users to offer different conditions to consumers outside the platform . 64 x Information available at www.consilium.europa.eu/en/press/press-releases/2019/02/20/increased-transparency-in-doing-business-through-online-platforms/ . Additionally, there is also the Digital Services Act, which establishes certain transparency standards. In general, EU digital strategy incorporates specific rules offering businesses a more transparent, fair and predictable online platform environment. Chatbots have a dominant role to play in the achievement of the EU digital strategy’s goals. The draft AI Regulation dedicates a specific provision to their legal use and can therefore be considered as the main legal source. Transparency is the key factor that penetrates the lawful use of chatbots. While it has been thoroughly analysed, it is equally worthy to mention GDPR relevant provisions that fulfil the regulatory framework.

III The Contribution of the General Data Protection Regulation

processed lawfully, fairly and in a transparent manner (‘Lawfulness, Fairness and Transparency’);

collected only for specified, explicit and legitimate purposes (‘Purpose Limitation’);

adequate, relevant and limited to what is necessary in relation to the purposes for which it is Processed (‘Data Minimization’);

accurate and where necessary kept up to date (‘Accuracy’);

not kept in a form that permits identification of data subjects for longer than is necessary for the purposes for which the data is processed (‘Storage Limitation’);

processed in a manner that ensures its security, using appropriate technical and organizational measures (6: ‘Security, Integrity and Confidentiality’).

shall not be transferred to another country without appropriate safeguards being in place (‘Transfer Limitation’); and

be made available to data subjects, for them to exercise certain rights in relation to their Personal Data (‘Data Subject’s Rights and Requests’).

One of the most crucial issues that comes into consideration when using chatbots is cookies 65 x For further details about the different types of cookies and their management from users, see the official page of European Union https://europa.eu/european-union/abouteuropa/cookies_en . as their administrators often choose to pair their conversational assistants with cookies, in order to ensure continuity of experience for the human on the receiving end of the conversation – even in cases where the user decides to refresh the web page or open a new tab, for instance. The EU’s legislation offers a solid basis for the lawful processing of cookies. 66 x See a brief analysis of the European regulatory framework regarding cookies at https://gdpr.eu/cookies/ . Firstly, the GDPR predicts in recital 30 that natural persons may be associated with online identifiers provided by their devices, applications, tools and protocols, such as internet protocol addresses, cookie identifiers or other identifiers such as radio frequency identification tags. This may leave traces which, in particular when combined with unique identifiers and other information received by the servers, may be used to create profiles of the natural persons and identify them.

In this vein, cookies – as well as chatbots as an inherent part of their function – are, in principle, legitimate. Moreover, companies do have a right to process their users’ data as long as they receive consent or if they have a legitimate interest, which can be interpreted according to the specific provisions of Article 6 of GDPR. 67 x For example, a legitimate interest can be declared when processing is necessary for the performance of a contract to which the data subject is party or in order to take steps at the request of the data subject prior to entering into a contract (case (c) of Art. 6 of GDPR). Apart from GDPR, the main regulatory binding text for cookies is the e-Privacy Directive, 68 x In 2002, the European Union launched the Directive on Privacy and Electronic Communications (e-Privacy Directive), a policy requiring end users’ consent for the placement of cookies, and similar technologies for storing and accessing information on users’ equipment. In 2009, the law was amended by Directive 2009/136/EC, which will be eventually replaced by the ePrivacy Regulation. widely known as the ‘cookie law’. The most important amendment to the prior Directive of 2002 is included in Article 5§3 of the text. Instead of allowing users to opt out of cookie storage, the revised Directive requires consent to be obtained for cookie storage. 69 x As it is explicitly predicted, “ Member States shall ensure that the storing of information, or the gaining of access to information already stored, in the terminal equipment of a subscriber or user is only allowed on condition that the subscriber or user concerned has given his or her consent, having been provided with clear and comprehensive information, in accordance with Directive 95/46/EC, inter alia, about the purposes of the processing. This shall not prevent any technical storage or access for the sole purpose of carrying out the transmission of a communication over an electronic communications network, or as strictly necessary in order for the provider of an information society service explicitly requested by the subscriber or user to provide the service .”. The aforementioned requirement means that any time that one device contains chatbots its administrator (who is the processor of personal data) has to receive users’ content, which must be unconditioned, clear and explicit as well as subject to potential withdrawal from the data subject. 70 x See Art. 7 of GDPR regarding the conditions for consent. At this point, we should underline the recent guidelines published by the French Data Protection Agency (CNIL – Commission Nationale Informatique & Libertés) as well as the Italian Data Protection Authority (Garante), which illustrate the principles provided for the lawful use of cookies. 71 x CNIL published its guidelines on 1 October 2020 and Garante on 10 July 2021. A thorough analysis of those guidelines is provided at www.cookielawinfo.com/new-cnil-cookie-guidelines/ and www.dataguidance.com/news/italy-garante-releases-new-guidelines-cookies-six-month , respectively. In particular, both the guidelines mandate that consent must be requested through a clearly distinguishable banner, through which users must also be offered the possibility to continue browsing without being tracked in any way. Furthermore, the guidelines clarify that simply scrolling down the web page does not constitute consent and that, in any case, the user should have the right to withdraw consent at any time. Moreover, the guidelines further specify that information provided to users must also indicate any other recipients of personal data and the period for which their data will be retained. In addition, the guidelines confirm that such information can be provided in different formats, such as through videos or pop-ups. The European Court of Justice has reaffirmed those principles through significant decisions in case law, such as at the case C-673/17 72 x Case C-673/17, Judgment of the Court (Grand Chamber) of 1 October 2019 (request for a preliminary ruling from the Bundesgerichtshof – Germany) – Bundesverband der Verbraucherzentralen und Verbraucherverbände – Verbraucherzentrale Bundesverband eV v. Planet49 GmbH and case C-210/16 , Judgement of the Court (Grand Chamber), Unabhängiges Landeszentrum für Datenschutz Schleswig-Holstein v. Wirtschaftsakademie Schleswig-Holstein GmbH . and case C-210/16, where the Court decided that the consent referred to in the provisions of E-Privacy Directive and GDPR is not validly constituted if, in the form of cookies, the storage of information or access to information already stored in a website user’s terminal equipment is permitted by way of a pre-checked checkbox that the user must deselect to refuse consent. Therefore, we can conclude that since administrators of chatbots incorporate cookies their use should obey, with all urgency, the principle of prior clear, distinguishable and unconditioned consent from the data subject. Another crucial issue at stake when using chatbots is the profiling of the data subject. The GDPR provides sufficient answers to the problem. More specifically, Article 22 of the European regulation prohibits automated individual decision-making, including profiling, unless some specific exceptions occur, such as the need for entering into a contract between the data subject and the data controller. 73 x See paras.  1 and 2 of Art. 22 of GDPR. It should also be noticed that, according to the last paragraph of the article, automated decision-making that involves special categories of personal data is allowed only under the following cumulative conditions (Art. 22(4)): there is an applicable Article 22(2) exemption; and point (a) or (g) of Article 9(2) applies. 74 x 9(2) (a) - the explicit consent of the data subject; or 9(2) (g) - processing necessary for reasons of substantial public interest, on the basis of Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and interests of the data subject. In both these cases, the controller must put in place suitable measures to safeguard the data subject’s rights and freedoms and legitimate interests. Therefore, we could allege that chatbots should never constitute the legal basis for producing a binding agreement between the contracting parties. However, since chatbots are widely used in e-commerce we could accept the exception of Article 22 of GDPR owing to their necessity for pre-contractual processing and, consequently, an automated decision-making falling within that scope. The example provided by Article 29 Data Protection Working Party through the guidelines published on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679 75 x Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679, adopted on 3 October 2017, as last revised and adopted on 6 February 2018. is strictly relevant to our previous allegation:

A business advertises an open position. As working for the business in question is popular, the business receives tens of thousands of applications. Due to the exceptionally high volume of applications, the business may find that it is not practically possible to identify fitting candidates without first using fully automated means to sift out irrelevant applications. In this case, automated decision-making may be necessary in order to make a short list of possible candidates, with the intention of entering into a contract with a data subject.

The ideal tool for producing that goal (meaning the short list of possible candidates) would be the chatbots.

• C Conclusion

The thorough foregoing analysis demonstrated the dynamic presence of chatbots in the European digital strategy. Being a typical example of AI, they are strictly connected with high goals such as promoting digital economy and technology and empowering business and infrastructure in a secure and sustainable digital environment. Certainly, since the processing of data is inevitable, serious social, ethical and legal concerns arise. Human privacy is at risk and must be protected. The existing European regulatory framework, mainly the General Data Protection Regulation and E-Privacy Directive, offers safe guarantees and may be considered as the ‘traditional’ legal background for the protection of our privacy. But it is the draft AI Regulation, the main legal text, that could lead (after being adopted) to binding effects and harmoniously regulate all the controversial issues being raised in the new digital era. The provision of all necessary information from the administrators and the respect of prior consent from the data subject, as have been thoroughly described by the provisions of the foregoing legal texts, represent the key principles of the lawful use of chatbots. Transparency reflects all the demanded requirements and seems to be of primary value. It is consequently urgent that any business that uses chatbots must form a concrete privacy policy, easily accessible and with respect to all rights of the data subject. Under those circumstances we could strike a successful balance between the empowerment of digital economy, productivity and economy and the safeguarding of online privacy.

1 K. Tzortzakis & A. Tzortzaki, Marketing Principles: The Greek Approach (in Greek), 2nd ed., Gerakas, Rosili, 2002, pp. 38-39.

2 H. Karjaluoto, H. Kuusela & H. Saarijärvi, ‘Customer Relationship Management: The Evolving Role of Customer Data’, Marketing Intelligence & Planning , Vol. 31, No. 6, 2013, pp. 1-4.

3 F. Buttle & S. Maklan, Customer Relationship Management: Concepts and Technologies , 4th ed., Routledge, 2019, pp. 3-4.

4 Buttle and Maklan, 2019, p. 4.

5 Ibid ., p. 5.

6 N. Mohammadhossein & H. Zakaria, ‘CRM Benefits for Customers: Literature Review (2005-2012)’, International Journal of Engineering Research and Applications , Vol. 2, No. 6, 2012, p. 1582.

8 Ibid ., p. 1583.

9 J. Kulpa, ‘Council Post: Why Is Customer Relationship Management So Important?’ [online], Forbes, 2017. Available at: www.forbes.com/sites/forbesagencycouncil/2017/10/24/why-is-customer-relationship-management-so-important/?sh=2e364abb7dac .

10 F. Buttle, Customer Relationship Management Concepts and Technologies , 2nd ed., Elsevier, 2009, pp. 178-179.

11 R. Binns, ‘Case Study: How Apple Have Mastered CRM’, Expert Market [online], 2020. Available at: www.expertmarket.co.uk/crm-systems/apple-crm-case-study .

12 P. Singh, ‘Top 5 Customer Relationship Management Examples’. [online] appvizer.com , 2020. Available at: www.appvizer.com/magazine/customer/client-relationship-mgt/customer-relationship-management-examples#1-apple-crm .

14 J. Frankenfield, ‘How Artificial Intelligence Works’. [online] Investopedia, 2020. Available at: www.investopedia.com/terms/a/artificial-intelligence-ai.asp .

15 P. Gentsch, AI in Marketing, Sales and Service: How Marketers Without a Data Science Degree Can Use AI, Big Data and Bots , Cham, Springer, 2019, p. 3.

16 B. Botadra, ‘Web Robots or Most commonly known as Bots’, p. 2. Available at: www.academia.edu/37700458/Web_Robots_or_Most_commonly_known_as_Bots .

18 HubSpot Research, p. 4. Available at: https://cdn2.hubspot.net/hubfs/53/assets/hubspot.com/research/reports/What_is_a_bot_HubSpot_Research.pdf?t=1492209311951 .

19 Botadra, p. 3.

20 Ibid ., p. 7.

21 K. Aberer, K. Fawaz, H. Harkous & K. Shin, ‘PriBots: Conversational Privacy with Chatbots’, 2016. Available at: www.researchgate.net/publication/305567688_PriBots_Conversational_Privacy_with_Chatbotsact_com . ‘What Is CRM: A Definition of CRM and Its Meaning’, p. 1. Available at: www.act.com/what-is-crm .

22 P. Brandtzaeg & A. Følstad, ‘Chatbots: Changing User Needs and Motivations’, Interactions , Vol. 25, No. 5, 2018, p. 40.

23 Brandtzaeg and Følstad, 2018, p. 38.

24 K. Nimavat & T. Champaneria, ‘Chatbots: An Overview. Types, Architecture, Tools and Future Possibilities’, International Journal for Scientific Research & Development , Vol. 5, No. 7, 2017, p. 1019.

25 E. Adamopoulou & L. Moussiades, ‘An Overview of Chatbot Technology’, IFIP International Conference on Artificial Intelligence Applications and Innovations , 2020, pp. 377-378.

26 Nimavat and Champaneria, 2017.

27 Ibid ., 2017, p. 1020.

28 Adamopoulou and Moussiades, 2020.

29 Nimavat and Champaneria, 2017, p. 1020.

31 Aberer et al ., 2016.

32 Brandtzaeg and Følstad, 2018.

33 HubSpot Research, pp. 5-6.

34 Brandtzaeg and Følstad, 2018.

35 A. Følstad, M. Skjuve & P.B. Brandtzaeg, ‘Different Chatbots for Different Purposes: Towards a Typology of Chatbots to Understand Interaction Design’, in S. Bodrunova et al . (Eds.), Internet Science , Cham, Springer, 2019, p. 6.

36 A. Bergner & C. Hildebrand, ‘AI-Driven Sales Automation: Using Chatbots to Boost Sales’, NIM Marketing Intelligence Review , Vol. 11, No. 2, 2019, p. 36.

37 P. Gentsch, AI in Marketing, Sales and Service: How Marketers Without a Data Science Degree Can Use AI, Big Data and Bots , Cham, Springer, 2019, p. 113.

38 Ibid ., p. 116.

39 Bergner and Hildebrand, 2019, pp. 38-39.

40 Gentsch, 2019, p. 117.

41 N. Beck & D. Rygl, ‘Categorization of Multiple Channel Retailing in Multi-, Cross-, and Omni-Channel Retailing for Retailers and Retailing’, Journal of Retailing and Consumer Services , Vol. 27, 2015, p. 174.

42 N. Winkler, ‘Omnichannel Vs Multichannel: What Is the Difference?’ [online] Shopify Plus, 2019. Available at: www.shopify.com/enterprise/omni-channel-vs-multi-channel .

43 Beck and Rygl, 2015.

44 Omnisend Blog, ‘Omnichannel Vs. Multichannel: How to Know the Difference’, 2020. Available at: www.omnisend.com/blog/omnichannel-vs-multichannel/ .

45 Beck and Rygl, 2015, p. 175.

46 Winkler, 2019.

47 Omnisend Blog, 2020.

48 T. Choudhury, P. Kumar & N. Piyush, ‘Conversational Commerce a New Era of E-Business’, International Conference System Modeling & Advancement in Research Trends (SMART), 2016, p. 323.

49 C. Ischen, T. Araujo, H. Voorveld, G. van Noort & E. Smit, ‘Privacy Concerns in Chatbot Interactions’, in A. Følstad et al . (Eds.), Chatbot Research and Design , Cham, Springer, 2019, pp. 1, 3.

50 Gentsch, 2019, p. 116.

51 S. Morrison, ‘Alexa Records You More Often Than You Think’. [online] Vox, 2020. Available at: www.vox.com/recode/2020/2/21/21032140/alexa-amazon-google-home-siri-apple-microsoft-cortana-recording .

52 S. Kojouharov, ‘Chatbots, AI & the Future of Privacy’ [online] Medium, 2018. Available at: https://chatbotslife.com/chatbots-ai-the-future-of-privacy-174edfc2eb98 .

53 Choudhury, Kumar and Piyush, 2016, p. 323; Ischen, Araujo, Voorveld, van Noort, Smit, 2020, pp. 1, 3.

54 H. Harkous, ‘How Chatbots Will Redefine the Future of App Privacy’. [online] Medium, 2016. Available at: https://chatbotsmagazine.com/how-chatbots-will-redefine-the-future-of-app-privacy-eb68a7b5a329 .

55 G. Skandali, ‘Cambridge Analytica: How Will It Play Out for Chatbots?’ online] Medium, 2018. Available at: https://medium.com/yellow-hammock/cambridge-analytica-how-will-it-play-out-for-chatbots-5c1d44f4fe29 .

56 Harkous, 2016.

57 J. Isaak & M.J. Hanna, ‘User Data Privacy: Facebook, Cambridge Analytica, and Privacy Protection’, Computer Magazine , Vol. 51, 2018, pp. 56-59. Available at: www.computer.org/csdl/magazine/co/2018/08/mco2018080056/13rRUxbCbmn .

58 K.M. Manheim & L. Kaplan, “Artificial Intelligence: Risks to Privacy and Democracy”, Yale Journal of Law & Technology, Vol. 21, 2019, p 106.

59 At the time being the draft AI Regulation is being processed by the European Parliament and Council.

60 The official press release is available at https://ec.europa.eu/commission/presscorner/detail/en/QANDA_21_1683 .

61 C-110/03, Judgement of the Court (Third Chamber) of 14 April 2005, Kingdom of Belgium v. Commission of the European Communities .

62 See para.  3 of the Art. 52 of the draft AI regulation.

63 See T. Tridimas, The General Principles of EU Law , 2nd ed., Oxford, Oxford University Press, 2006, p. 242.

64 Information available at www.consilium.europa.eu/en/press/press-releases/2019/02/20/increased-transparency-in-doing-business-through-online-platforms/ .

65 For further details about the different types of cookies and their management from users, see the official page of European Union https://europa.eu/european-union/abouteuropa/cookies_en .

66 See a brief analysis of the European regulatory framework regarding cookies at https://gdpr.eu/cookies/ .

67 For example, a legitimate interest can be declared when processing is necessary for the performance of a contract to which the data subject is party or in order to take steps at the request of the data subject prior to entering into a contract (case (c) of Art. 6 of GDPR).

68 In 2002, the European Union launched the Directive on Privacy and Electronic Communications (e-Privacy Directive), a policy requiring end users’ consent for the placement of cookies, and similar technologies for storing and accessing information on users’ equipment. In 2009, the law was amended by Directive 2009/136/EC, which will be eventually replaced by the ePrivacy Regulation.

69 As it is explicitly predicted, “ Member States shall ensure that the storing of information, or the gaining of access to information already stored, in the terminal equipment of a subscriber or user is only allowed on condition that the subscriber or user concerned has given his or her consent, having been provided with clear and comprehensive information, in accordance with Directive 95/46/EC, inter alia, about the purposes of the processing. This shall not prevent any technical storage or access for the sole purpose of carrying out the transmission of a communication over an electronic communications network, or as strictly necessary in order for the provider of an information society service explicitly requested by the subscriber or user to provide the service .”.

70 See Art. 7 of GDPR regarding the conditions for consent.

71 CNIL published its guidelines on 1 October 2020 and Garante on 10 July 2021. A thorough analysis of those guidelines is provided at www.cookielawinfo.com/new-cnil-cookie-guidelines/ and www.dataguidance.com/news/italy-garante-releases-new-guidelines-cookies-six-month , respectively.

72 Case C-673/17, Judgment of the Court (Grand Chamber) of 1 October 2019 (request for a preliminary ruling from the Bundesgerichtshof – Germany) – Bundesverband der Verbraucherzentralen und Verbraucherverbände – Verbraucherzentrale Bundesverband eV v. Planet49 GmbH and case C-210/16 , Judgement of the Court (Grand Chamber), Unabhängiges Landeszentrum für Datenschutz Schleswig-Holstein v. Wirtschaftsakademie Schleswig-Holstein GmbH .

73 See paras.  1 and 2 of Art. 22 of GDPR.

74 9(2) (a) - the explicit consent of the data subject; or 9(2) (g) - processing necessary for reasons of substantial public interest, on the basis of Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and interests of the data subject.

75 Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679, adopted on 3 October 2017, as last revised and adopted on 6 February 2018.

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The main difficulty lay in overseeing the progress of these numerous operations, ensuring no task was overlooked, and assessing the overall business’s well-being. To address this issue, they required a centralized platform that could centralize all operational aspects and foster improved team collaboration.

How Kylas Helped?

Kylas has proven to be a game-changer for Omega Financial, leading to a remarkable enhancement in its operational efficiency. By implementing this CRM, the company has successfully streamlined its processes, enabling teams to work more efficiently and collaborate seamlessly. As a result, productivity has seen a significant boost across the entire organization.

One tangible outcome of this improvement is a remarkable 45% growth in sales. To effectively track and quantify sales performance , the company has adopted a system of assigning weightage points to each deal closed by salespersons.

Prior to implementing Kylas, sales executives were struggling to reach the target of 1500 points, typically achieving only 500-600 points. However, with Kylas in place, the average executive now consistently surpasses the target, scoring higher than 1500 points.  

Customer Testimonial ⭐

“We have seen a 45% increase in our sales in the past year- all thanks to Kylas. My team’s overall performance and productivity have improved because of the automation in the system. Even though Kylas is a Sales CRM all my departments use it on a daily basis. Kylas has helped us transition from hard work to smart work and I would like to rate it 5/5.” – Yogendra. S, Director of Sales, Omega Financial

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VK Ventures holds a significant position in the e-commerce and fintech sectors. The company has created a portal that facilitates merchants all over India to offer a wide range of financial and utility services. These services include account opening, cash deposits, withdrawals, recharge, bill payments, money transfers, micro-FDs, insurance, and more.

Through this portal, merchants can efficiently cater to their customer’s needs while earning a commission on every transaction they facilitate.

VK Ventures is an active player in the e-commerce and fintech sectors. The company has consistently emphasized providing exceptional services to its customers while prioritizing their needs. To support its operations, VK Ventures had an 80-member sales team utilizing a custom-developed CRM.

However, this CRM, developed in Ahmedabad, proved to be outdated and lacked essential features. As a consequence, the company encountered numerous challenges, particularly in effectively managing the large sales team and tracking leads generated from various marketing campaigns.

Thanks to Kylas, VK Ventures achieved a comprehensive customer view consolidated in a single database. This encompassed essential details like customer names, addresses, financial information, and more, readily accessible to the management.

The implementation of Kylas significantly enhanced operational agility for the company. VK Ventures successfully integrated with various external applications and ensured meticulous recording of every process in the CRM, thereby improving transparency.

The positive outcomes of this transformation manifested in increased sales and overall business growth for the company. VK Ventures now enjoys improved client management and better control over ad campaigns while making judicious expenditures across different sources.

“With Kylas, we have been able to track a plethora of fintech-related customer data with ease. Our sales reps can now instantly respond to customer inquiries, which has led to better conversion rates. The industry will witness growth in the times to come, and we are sure that with Kylas by our side, we will meet customer expectations and scale our business positively.” – Vinay Kedia, Director, VK Ventures

Fitness Bell India is a leading Fitness & Nutrition Consultation firm dedicated to helping clients achieve a healthier lifestyle. The company offers expert health advice, personalized diet plans, and tailored workout routines, all delivered through the collaborative efforts of a team of professionals, including dieticians, trainers, and healthcare experts.

With their guidance, Fitness Bell India can help you start your transformative journey towards improved health and a better physique.

Prior to adopting Kylas, Fitness Bell depended on Excel sheets to store customer records. Unfortunately, this manual data entry method was prone to human errors and consumed a significant amount of time.

As a consequence, data often became fragmented across multiple sheets, making it cumbersome to access historical information and past communications with prospects or clients. This disjointed flow of communication resulted in decreased customer experience and satisfaction.

Furthermore, the inflexibility of Excel sheets meant they couldn’t be customized to suit the company’s specific business needs, further hindering their operations. The absence of customized reporting capabilities also made it challenging to make data-driven decisions, adding to their business challenges.

Fitness Bell found the perfect fit for their needs with Kylas CRM, designed specifically for fitness professionals to efficiently engage, follow up with, and sell to clients. This user-friendly CRM empowered Fitness Bell to manage its sales process seamlessly, including contract renewals.

With Kylas, the sales team streamlined day-to-day operations related to data management, securely organizing all customer data for efficient nurturing and personalized touchpoints. Sales representatives tracked interactions with customers, while Kylas’s adaptability accommodated various membership options.

The sales manager easily assigned leads and tasks to specific staff members, ensuring timely follow-ups. The customizable dashboard provided comprehensive oversight for management, and Data Export functionality simplified data transfer.

Fitness Bell gained valuable insights for decision-making through crucial sales metrics and customized reports. Kylas’s multiple integrations fostered better relationships and faster conversions while linking WhatsApp business accounts strengthened customer connections.

Kylas played a vital role in promoting CRM adoption within the sales team, contributing to improved efficiency and success.

“With Kylas, we could scale up sales and improve customer engagement in the past 3 months. Features like Smart Filters helped us to filter data, identify hot and warm leads, and prioritize our leads. We are very happy to say that Kylas not just helped in team collaboration, but improved customer engagement as well.

Kylas does a great job of listening to its customers and keeping up with their feature-related demands. It’s a trustworthy platform that has helped in our path to success.” – Himanshu Kumar, Co-Founder, Fitness Bell India

MoneyNotSleep stands out as India’s pioneering Financial Media House tailored exclusively for Part-Time Traders. Established on December 8th, 2020, MoneyNotSleep is dedicated to delivering essential financial news updates, highlighting investment and trading opportunities, and providing market predictions for the best-performing stocks, equities, bonds, and companies.

Amidst the Covid challenges, MoneyNotSleep ventured into creating a platform for potential investors to build wealth through trading channels. However, as the business grew, it faced several hurdles. One major challenge was handling fragmented data stored in Excel, making it difficult to track leads and deals, impacting sales performance and growth.

The lack of team collaboration in closing deals was apparent, with internal communications suffering, leading to missed information by sales reps. Transitioning to a remote workforce during the pandemic added complexity in monitoring the sales team’s activities.

Recognizing the need for a comprehensive solution, MoneyNotSleep sought to reevaluate its technology strategy. They needed a scalable, integrated, and efficient platform to cater to bespoke needs while enhancing customer experience. Flexibility and adaptability were vital factors in their search for the right solution.

When the pandemic forced MoneyNotSleep to transition to remote work, coordinating with their dispersed sales teams became a challenge. However, Kylas proved to be a savior, facilitating collaboration among remote sales reps and significantly improving team performance.

Kylas brought about a revolutionary change by providing a comprehensive view of customers through centralized data management. The sales team could now track every interaction with leads, customers, and deals, gaining insights into customer behavior to cater to their needs effectively. This transformation from fragmented processes to a fully-integrated system empowered managers with complete control and visibility.

The multi-metric & multi-dimensional Reporting feature in Kylas enabled the sales team to generate performance and sales forecasting reports efficiently, surpassing the previous manual methods of progress tracking. Even while working from home, the sales manager could closely monitor the team’s activities and productivity.

Kylas streamlined data importing, particularly from external sources like their Leads databases, saving time and reducing manual tasks. With routine tasks automated, the sales team’s productivity surged, resulting in a faster sales process pipeline.

Inter-team communications improved significantly with Kylas, enabling a clear visualization of the entire customer journey and facilitating necessary corrections. The Kylas mobile app made curating client information more convenient, leading to better customer support on the go and enhanced satisfaction.

Reflecting on their journey with Kylas, Nishant appreciated the improved flow of information within the organization, directly impacting the end user’s customer experience positively. Kylas played a crucial role in helping MoneyNotSleep navigate the challenges of remote work during the pandemic and elevating their sales operations to new heights.

“After implementing Kylas, the sales team started leveraging the full potential of Kylas’s automation capabilities to take over a number of activities currently executed manually. Kylas has made our sales team more efficient and effective by automating their daily activities, reducing manual efforts, and saving time. Now our sales team can focus more on selling.

I am excited to say that with Kylas, the sales activity has increased by a whopping 150% in the last 3 months. Not just that, the revenue also went up by 20%. Kylas has allowed us to support clients better in the selling process, in turn, leading to greater customer satisfaction.” – Nishant Mishra, Co-founder, MoneyNotSleep

Ajay Modi Travels , based in Ahmedabad, is a well-established travel service company renowned for its diverse range of travel-related offerings across India. With over two decades of experience, the company remains dedicated to delivering top-notch services and tailor-made holiday packages to its valued customers.

The Indian travel and tourism industry took a hit during the pandemic, causing a significant decline in both domestic and international travelers. Ajay Modi Travels also experienced the adverse effects of this situation, leading to an unexpected slowdown in their business.

As the pandemic situation gradually improved, the travel industry began to witness signs of recovery, and Ajay Modi Travels saw a surge in inquiries. Recognizing the opportunity to capitalize on this increased interest and fortify their position in the market, the team decided to take action.

The influx of inquiries brought a diverse range of requests for customization, highlighting the need for a robust system to manage customer data and streamline all processes. Additionally, handling bulk data through manual entry became inefficient, prompting the search for an automated solution that could efficiently manage appointments and booking deadlines, ensuring no opportunities were missed.

Thanks to Kylas CRM, Ajay Modi Travels achieved a comprehensive 360-degree view of their customer database, including crucial details like names, addresses, booking history, and more. This enabled travel agents to efficiently manage customer accounts and handle bookings, saving valuable time.

The streamlined tracking of miscellaneous travel-related data made responding to inquiries easier, improving conversion rates.

Mr. Alaap Modi expressed satisfaction with Kylas’s support and customizable features. The platform seamlessly integrated lead capture forms, prioritized inquiries, and assigned them to the right agents. Workflow automation empowered in-house tour managers to create custom rules based on customer preferences.

With Kylas’s automation, concerns about missed appointments or inquiries vanished, as custom rules ensured prompt communication through emails and reminders. Mr. Alaap Modi also praised Kylas’s receptiveness to new ideas, making the partnership even more valuable for Ajay Modi Travels.

“Currently, we have 20+ users using Kylas, and let us tell you that they have not missed a single lead or call from any prospective traveler. Kylas didn’t just help us boost our sales; it also helped us build strong relationships with our clients. In fact, in the last 6 months, our sales increased to 30% and our customer satisfaction improved by 20%. This CRM is beneficial for businesses looking forward to scaling new heights. I would recommend Kylas CRM to everyone in the travel & tourism industry.” – Aalap Modi, Co-Founder, AjayModi Travels

Learn Digital Academy is a specialized training institute committed to empowering students with university certifications and on-campus placements. Distinguished as India’s sole awarded agency-based digital education institute, they offer a comprehensive learning journey encompassing training, certification, internships, and placement opportunities.

With a dynamic team of professionals, their mission revolves around upskilling aspiring individuals in cutting-edge disciplines like digital marketing, data science, artificial intelligence, and graphic design. As they continue to grow, Learn Digital Academy remains dedicated to providing a transformative learning experience for all.

As Learn Digital Academy expanded as an Ed-Tech business, its counselors found themselves handling a substantial amount of information daily. Initially, they utilized LeadSquared as their CRM for the sales team. However, when the management made the decision to downsize the sales team, they had to transition to using Excel and Google Sheets for data management.

The counselors at Learn Digital Academy regularly reached out to prospective students to identify suitable candidates and boost enrolments. Managing call logs for each call on Excel became a challenging task, leading to difficulties in following up on inquiries promptly, which ultimately resulted in a decline in the enrolment rate.

Recognizing that Excel sheets were no longer sufficient to meet their needs, Nishant realized it was time to explore alternative solutions for their data and customer management requirements.

Kylas CRM proved to be a game-changer for LearnDigital Academy, streamlining student enrolments and admissions with its comprehensive view of every contact and inquiry. The team seamlessly synchronized inquiries from various sources, efficiently tracked incoming students and stored all their details in one centralized location.

The Bulk Update and Bulk Delete features offered by Kylas CRM significantly reduced manual efforts, enabling the team to manage a large volume of student inquiries effortlessly and save valuable time.

Nishant highlighted the transformative impact of Kylas CRM on their counselors, who can now make one-click calls to candidates through IVR directly from the platform, greatly enhancing their outbound efforts.

Moreover, Nishant commended the seamless onboarding and adoption process for this new platform. The availability and responsiveness of Kylas’s Customer Success team through various communication channels, including Telephony, Chat, WhatsApp, and Email, impressed Nishant.

He further praised the team’s promptness in responding to queries within an hour and resolving issues within 24 hours, always handling their requests with utmost priority.

“Kylas’ notes, task reminders, and meeting updates have helped our counselors organize their daily tasks better. Our productivity has improved with this CRM system and most importantly- now we do not miss out on a single lead.

The productivity dashboard, multi-dimensional reports, and Smart Lists in Kylas helped us track inquiries that needed follow-up by our counselors .

I am delighted to say that due to timely follow-ups through Kylas’s automated messages and emails, our overall enrolment rate has improved significantly by 30%.” ­ – Nishant Jhunjhunwala, Co-Founder, Learn Digital Academy

Established in 2011, Upanal CNC Solutions specializes in offering service and maintenance programs for all CNC machine services. As a prominent wholesaler and dealer, Upanal provides a wide range of products, including Milling Machines, Turning Machines, CNC Machine Spare Parts, and more.

Headquartered in Bengaluru, Upanal is known for its tailor-made service and maintenance programs, catering to various needs, from simple care maintenance of technically challenging CNC machines to handling exceptional masterpieces in the industry.

Upanal CNC Solutions, a thriving business, upholds the belief of delivering top-notch service at competitive rates, all while understanding and catering to the unique requirements of its clients. As its clientele base expanded rapidly, Upanal recognized the importance of having a cohesive system that could provide a clear overview of its sales pipeline.

To meet their evolving needs, Upanal sought a CRM solution that would efficiently organize their sales team’s workflow and minimize errors in data collection. They required software that would enable their sales team to consistently follow up with clients, thereby enhancing the likelihood of lead conversions.

Thanks to Kylas, Upanal gained invaluable transparency, allowing them to access a comprehensive view of each customer’s activity log in a single place. The need for centralized information concerning clients, leads, and deals, including contacts, calls, past meetings, and opportunities, was fulfilled, significantly enhancing the visibility of their sales pipeline .

When asked about the top three features appreciated by Poonam, she highlighted Kylas’s ability to create custom reports and provide insights into sales performance. The automated workflows were also a standout feature as they allowed for streamlined sales processes. Additionally, the in-app notifications kept the sales representatives updated, ensuring no important updates or tasks were missed.

“Not only that, Kylas’ robust customer service helped us with quick training that helped our team get adapted to new business processes easily. Transitioning from one software to another was effortless.

It has been going great with Kylas and I am glad we made the switch. As a sales CRM, I would rate it 4/5.” – Poonam Anvedkar, Internal Sales Team Leader, Upanal CNC Solutions

With the right CRM in place, you can serve your customers in the best manner possible. If the CRM implementation is done correctly, it doesn’t matter how much your customer expectations evolve. You will always be on top of your sales.

If you want to understand how Kylas can help your business grow, Schedule your Demo with us and we will tell you how.

Shagun Sharma

Shagun is a content marketer at Kylas, extremely well-versed in all things Marketing. She works closely with the sales team to create best-in-class content for our readers. Her experience combined with her thorough research skills makes all her blogs very in-depth and insightful. In her leisure time, Shagun enjoys hiking, gardening, and immersing herself in music.

• CRM case study
• CRM Implementation
• CRM implementation case studies

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