Balancing Personalisation with Privacy

In today’s data-driven marketplace, companies face a paradox: customers demand personalised experiences, yet they are increasingly concerned about their privacy. Nearly three-quarters of consumers expect brands to deliver tailored, relevant interactions – and 76% even express frustration when they don’t receive them. At the same time, only about one in three customers trusts businesses with their personal data. This dichotomy poses a critical challenge for modern organisations: how do you leverage personalisation to enhance customer experience while rigorously protecting privacy?

Time-pressed executives and managers in retail, marketing, and tech are under pressure to find this balance. Personalisation can boost engagement, loyalty, and sales – McKinsey research highlights that companies excelling at personalisation can increase revenues by 5–15%. On the flip side, privacy missteps can erode trust and invite regulatory penalties; in fact, nearly half of consumers have stopped doing business with a company due to privacy concerns. This article offers a deep dive into what personalisation and data privacy mean today, why both matter, and strategies for balancing the two effectively in an omnichannel, privacy-conscious world.

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What Is Personalisation and Why Does It Matter?

Personalisation in business refers to tailoring products, services, content, and experiences to individual customers’ preferences and behaviours. Rather than a one-size-fits-all approach, a personalised experience uses customer data – purchase history, browsing activity, demographics, and even real-time context – to present what’s most relevant to each person. In retail and marketing, personalisation might mean product recommendations (“You might also like…”), targeted promotions, customised emails using the customer’s name and past purchase info, or a loyalty app that remembers a shopper’s favourite store location. In physical retail settings, personalisation could involve sales associates using a mobile POS device to instantly recognise a returning customer and offer tailored suggestions based on their purchase history.

Personalisation matters because it directly impacts customer satisfaction and loyalty. Consumers have come to expect it: surveys indicate about 71% of customers expect personalised experiences from the brands they engage with. When done well, personalisation makes customers feel understood and valued as individuals rather than as faceless transactions. This improved experience translates into tangible benefits for companies:

• Higher conversion and sales: Recommending relevant items or content increases the likelihood of purchase. For example, suggesting accessories that complement a customer’s recent purchase can drive an upsell.
• Greater customer loyalty: Shoppers are more likely to return to brands that “get” them. One study found 62% of consumers say a brand can lose their loyalty if communications are not personalised. On the other hand, tailored engagement can foster a sense of relationship and trust, encouraging repeat business.
• Improved engagement: Personalised content (such as emails or app notifications) tends to get higher open and click-through rates than generic messaging. Customers pay attention when the message speaks to their needs or interests – for instance, a push notification about a sale on running shoes right after a customer bought running shorts.
• Competitive advantage: In crowded markets like fashion retail or banking, personalisation sets companies apart. A seamless omnichannel experience – where a customer’s preferences carry from an online store to a physical storefront’s omnichannel retail tech systems – can be a key differentiator.

Crucially, personalisation isn’t just a nice-to-have feature; it’s increasingly a strategic imperative. Retailers, banks, tech platforms – virtually all sectors – are investing in data analytics and AI to deliver more customised experiences. A recent industry survey showed nearly 74% of digital marketing leaders have ramped up investment in personalisation tools and tactics. From mobile apps that remember user settings to sustainable fashion brands tailoring product suggestions to match a customer’s eco-friendly values, personalisation is driving the future of customer experience. But this bright side comes with a shadow: delivering such customised service relies on collecting and using personal data, which brings us to the privacy piece of the puzzle.

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The Importance of Privacy in the Digital Age

Data privacy refers to an individual’s right to control how their personal information is collected, used, and shared. In an era of big data and hyper-personalised services, privacy has become a paramount concern for consumers, regulators, and businesses alike. High-profile data breaches and scandals – from social media mishandling user data to retailers exposed in cyberattacks – have heightened public awareness of privacy issues. As a result, consumers today are far more cautious and protective of their personal information.

Multiple studies reveal the depth of consumer concern:

• Trust deficit: Only about 37% of customers trust companies with their personal data. In other words, a majority are sceptical about whether businesses will safeguard their information or use it responsibly. This trust gap has widened in recent years due to persistent news of hacks and questionable data practices.
• Fear of misuse: Surveys by groups like Pew Research have found approximately 80% of people feel the potential risks of data collection outweigh the benefits. Many users worry that their data could be sold, leaked, or exploited in ways they never agreed to.
• Loss of control: Nearly half of consumers feel they’ve “lost control” over how their personal info is used by companies. For instance, shoppers might provide an email to a retailer and later find it was shared with third-party advertisers without their clear consent – a feeling of being “in the dark” that breeds resentment.
• Changing behaviour: Privacy concerns are no longer abstract – they’re impacting purchasing decisions and brand relationships. About 48% of consumers have stopped shopping with a company due to privacy worries or a data mishap. Similarly, over a third of people say they have outright ended a relationship with a business because they felt their personal data was misused. These figures underscore that privacy isn’t just a legal box to tick; it’s directly tied to customer loyalty and brand reputation.

On top of consumer sentiment, the regulatory environment has grown stricter. Governments worldwide have enacted tough data protection laws: the EU’s GDPR, California’s CCPA, Australia’s Privacy Act, and many others. These laws require businesses to be transparent about data practices, obtain consent for data collection in many cases, limit data usage to specified purposes, and ensure strong security for stored data. Non-compliance can lead to hefty fines (in GDPR’s case, up to 4% of global annual turnover) and legal penalties – not to mention public relations fallout.

Privacy has thus become a core strategic concern for executives. It’s not just the domain of IT or legal departments; CEOs and boards discuss privacy as a matter of trust and risk management. In the age of AI and advanced analytics, businesses handle more customer data than ever – making responsible data stewardship a critical part of maintaining customer trust. In fact, forward-thinking organisations now see privacy as an opportunity to differentiate: by treating customer data with respect and care, they can strengthen their brand’s credibility. For example, Apple’s marketing has famously emphasised privacy as a selling point, appealing to consumers who value that protection.

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The Personalisation–Privacy Dilemma

Balancing personalisation with privacy often feels like a tightrope walk. On one side is the push to know your customer deeply, anticipating their needs and delighting them with bespoke experiences. On the other side is the mandate to respect customer boundaries and comply with privacy norms. These two goals can conflict, because personalisation inherently requires data – and data collection can encroach on privacy if not handled properly.

Why is this balance so tricky? Consider a few scenarios:

• An online fashion retailer could track a user’s browsing and purchase history to recommend new clothing items they’ll love. That can boost sales and make the customer happy – unless the customer feels spied upon or never consented to such tracking. If those personalised recommendations suddenly appear on every website (via retargeting ads), the customer might find it “creepy,” eroding their trust.
• A supermarket chain uses loyalty cards and phone number inputs at point-of-sale to gather detailed profiles of each shopper’s buying habits. This data helps the chain send highly relevant discount coupons (personalisation win). But if the shopper never realised how much data was being aggregated about them, a news story about “supermarkets collecting intimate shopping data” could spark backlash (privacy fail).
• A mobile app might ask for location access so it can personalise content based on where the user is (say, showing restaurant deals when near a mall). If users understand the benefit and agree, great. If the app quietly harvests location in the background without clear permission, it violates privacy expectations and possibly laws.

The crux of the dilemma is consumer trust. Personalisation without privacy can feel exploitative – like a friend remembering your birthday by secretly looking at your ID rather than because you told them. Privacy without any personalisation can make interactions feel impersonal and generic, missing opportunities to serve the customer better. Companies must find a sweet spot where customers feel both known and respected.

Notably, the consequences of getting it wrong are high. Overstepping on privacy can lead to:

• Reputation damage: News of a privacy breach or misuse of data can severely damage brand image. Customers may label the company “untrustworthy” and flee to competitors.
• Regulatory action: Regulators are increasingly vigilant. Using personal data beyond agreed purposes or suffering breaches due to negligence can result in investigations and fines.
• Lost customers: As mentioned, many customers will walk away if they feel their data was mishandled or if personalisation crosses into “too intrusive.”

Conversely, failing to personalise at all (or doing it poorly) carries its own risks:

• Customer attrition: Today’s consumers—especially younger generations like Gen Z—are quick to switch brands if they feel experiences are not tailored. About 49% of Gen Z shoppers say they’re less likely to buy from a brand if communications are impersonal, and more than a quarter will stop engaging or even spread negative word-of-mouth about a one-size-fits-all approach.
• Missed revenue: Without personalisation, businesses miss chances to upsell or cross-sell relevant products. Marketing campaigns become less effective when they don’t speak to specific interests, leading to lower ROI.
• Competitive disadvantage: If your competitors are personalising and you’re not, you may appear out of touch. Customers might gravitate to services that remember their preferences and make life easier.

Finding the balance is therefore not optional – it’s essential for sustainable success. The goal is personalisation with privacy: delivering the tailored experiences customers crave, in a way that makes them feel safe and in control of their data. It’s the art of being personal, not creepy; data-driven, not data-intrusive. Fortunately, these two priorities aren’t mutually exclusive. With thoughtful strategies, companies can satisfy both objectives.

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Strategies for Balancing Personalisation and Privacy

Achieving a balance between personalised service and robust privacy protection requires deliberate strategies and a customer-centric mindset. Here are key approaches executives and managers should consider:

1. Transparency and Consent First

Be upfront with customers about data collection and give them control. Transparency is the foundation of trust. This means:

• Clear Privacy Notices: Communicate in plain language what data you collect and why. Instead of burying details in a 10-page policy, surface the essentials in a concise, easy-to-understand format. For example, “We use your birthday to send you a special discount on your special day – you can opt out anytime.”
• Consent and Preferences: Whenever feasible, operate on an opt-in basis. Ask for permission to use data for certain purposes, and respect the answer. Modern consumers are more willing to share data if they feel in charge of it. Implement robust preference centres where users can toggle on/off various types of personalisation (e.g. “recommendations based on my browsing,” “email offers based on purchase history”). 87% of users say they want to manage how their data is collected and used – so empower them to do so.
• Explain the Value Exchange: Let customers know what they get in return for their data. For instance, a streaming service could say, “Help us learn your taste, and we’ll suggest new movies you’ll love.” When people see a clear benefit, they are often more comfortable with personalisation. In fact, nearly 48% of consumers are willing to share personal data for better brand experiences – but usually only if they understand and agree with how it will be used.

Transparency isn’t just ethical; it’s strategic. Companies that are open about data practices tend to build stronger relationships. Customers appreciate honesty and are more likely to opt in when they’re confident there’s nothing sneaky going on. Additionally, being transparent helps ensure compliance with laws like GDPR, which require specific consent for different data uses and mandates that consent be informed.

2. Data Minimisation and Quality over Quantity

A key principle of modern privacy regulation (and good sense) is data minimisation – collect only what you need to deliver the service or personalisation, and no more. Many organisations historically took an “collect everything just in case” approach, but that era is over. Now, the focus should be on quality, not quantity of data:

• First-Party Data Focus: Wherever possible, rely on data you collect directly from your customers (with their consent), rather than extensive third-party data. 78% of businesses now consider first-party data (like information from your own website, app, or store) as their most valuable personalisation resource. First-party data tends to be more accurate and comes with implicit trust because the customer gave it to you directly. Examples include purchase history in your loyalty program, preferences a user sets in their profile, or responses they gave in a survey. In contrast, third-party data (like buying profiles from a data broker) is more likely to raise privacy concerns and may be phased out by regulations and browser changes.
• Zero-Party Data: This refers to data that customers proactively and explicitly share about themselves, often through interactions like quizzes, style or size preferences, or account settings. For example, a sustainable fashion retailer might invite users to input their style preferences (colours, sizes, favourite eco-friendly materials) to get more tailored product suggestions. This information is gold for personalisation and comes with clear user intent, since they volunteered it. Using zero-party data is a privacy-friendly way to personalise because it’s fully transparent – the customer knows what they told you and expects you to use it to improve their experience.
• Avoid Unnecessary Sensitive Data: Evaluate if certain personal data is truly needed for personalisation. For instance, a music streaming app might not need to ask for a user’s exact birthdate when just the birth year would suffice for basic age-based recommendations. The less sensitive data you hold, the lower the privacy risk. If certain data doesn’t directly enhance the customer experience, think twice about collecting it.
• Anonymise and Aggregate: When analysing user data for trends (especially in marketing analytics), do so in an aggregated or anonymised way whenever possible. Rather than focusing on who did what, look at patterns among similar users. For personalisation at the individual level you do need personal identifiers, but those should be handled carefully (more on security later). For broader insights (like “what products often go together?” or “which features are most used by 20-30 year olds?”), you can often use de-identified data. This reduces privacy impact while still yielding useful business intelligence.

By minimising data collection and focusing on user-provided, relevant information, companies reduce the “attack surface” for privacy issues. There’s less data to protect, and customers feel more comfortable knowing you’re not siphoning up every detail about them. It’s a win-win: lean data practices are easier to secure and manage, and they signal respect for customer privacy.

3. Privacy by Design (and Default)

Privacy by Design is a principle that means building products and processes with privacy considerations from the ground up, rather than as an afterthought. It’s about proactively embedding privacy into the design and operation of IT systems, business practices, and customer touchpoints. Some ways to implement this:

• Default to Privacy-Friendly Settings: Make the default user experience one that protects privacy, requiring the user to actively opt in to share more. For example, an app might have location tracking off by default until the user turns it on for added functionality. This way, privacy isn’t something the user has to fight for; it’s the baseline.
• Limit Data Access: Within the organisation, ensure that personal data isn’t freely accessible to all employees. Only grant access on a need-to-know basis. Use role-based access controls so that, for instance, a marketing analyst can see aggregated campaign results but not individual customers’ identities unless necessary. By limiting internal exposure of data, you reduce the risk of misuse or accidental leaks.
• Build with Compliance in Mind: As you develop new customer-facing technologies (like a new mobile shopping app or an AI chatbot that uses customer info), consult privacy experts and legal teams early. Ensure features comply with relevant laws from day one. This might involve incorporating modules for consent management, audit logs for data access, or encryption for data storage right into the design.
• Frequent Privacy Audits: Periodically review your data practices and systems to ensure they meet current privacy standards. Regulations evolve (for example, more countries introducing GDPR-like laws, or new rules on AI data usage), and so do consumer expectations. Regular audits can catch issues early and demonstrate accountability. Some companies even invite external auditors or offer bug bounties to find privacy vulnerabilities – a practice that can bolster trust.

Implementing privacy by design and default not only helps avoid violations, but it also often improves the overall architecture of your systems. Designing with privacy constraints can drive more efficient data flows and better data hygiene. Moreover, when customers and regulators see that a company takes privacy seriously at a fundamental level, it builds confidence that personalisation efforts are being done in an ethical, responsible manner.

4. Robust Data Security Measures

Privacy and security are closely intertwined. Customers’ privacy can be compromised not only by intentional misuse of data, but also by failing to protect data from malicious actors. A well-balanced personalisation strategy means nothing if a data breach exposes customers’ personal information. Thus, investing in strong data security is non-negotiable:

• Encryption: Always encrypt personal data, both in transit (as it moves through networks) and at rest (when stored in databases or servers). Encryption ensures that even if an unauthorised person accesses the data, they can’t read it without the decryption key. Modern cloud services and databases often provide built-in encryption tools – use them.
• Access Controls and Monitoring: As mentioned, limit who can access sensitive data. Additionally, monitor access patterns to detect anomalies – for example, if an employee account suddenly tries to download the entire customer database at 2 AM, that should raise flags and trigger an immediate investigation or automatic lockdown.
• Regular Security Audits and Updates: Cyber threats constantly evolve. Conduct regular penetration tests and security audits to find vulnerabilities. Keep all systems patched with the latest security updates. Many breaches happen due to known exploits in software that hadn’t been updated.
• Incident Response Plan: Despite best efforts, breaches can happen. Have a clear plan in place for how to respond if a data incident occurs. This includes technical steps (like isolating affected systems), as well as communication strategies to notify customers and authorities if required. A swift, transparent response can help contain damage and maintain trust.

Strong security underpins privacy. Customers may never see your firewalls, encryption keys, or security protocols – those aren’t visible personalisation features – but they will certainly feel the impact if those measures fail. Ensuring rigorous security is a behind-the-scenes aspect of balancing personalisation and privacy: it allows you to collect and use data to personalise, while minimising the risk that this data could be exposed or stolen.

5. Customer Control and Choice

Empower your customers to shape their own experience and privacy level. Beyond the initial consent, keep giving them ongoing control:

• Easy Opt-Outs: Every personalised marketing message (emails, SMS, targeted ads) should provide a straightforward way to opt out or adjust preferences. For example, include a “manage my preferences” link in emails where users can fine-tune the frequency and type of content they receive. If a customer wants to stop seeing personalised product recommendations, make that option accessible without hassle.
• Allow Data Review and Deletion: Privacy laws increasingly grant consumers the right to view, download, or delete the data companies hold on them. Even if not legally required in all jurisdictions, offering this capability is a powerful trust-builder. Consider providing a self-service portal where users can see key data points stored about them (purchase history, personal details, etc.) and request deletion or correction of data. When people feel they have transparency and control, they are less likely to be surprised or angered by how their data is used.
• Granular Personalisation Settings: Not all personalisation is one-dimensional. Some customers might love personalised product recommendations but dislike location-based offers, for instance. Offer granularity in settings: maybe a toggle for “use my in-store purchase history for recommendations” separate from “use my location to alert me of nearby deals.” This granular control lets users customise the degree of personalisation they’re comfortable with.

By giving customers meaningful choices, you send a message that you respect their autonomy. This can turn personalisation into a collaborative effort between the business and the customer. The customer essentially says, “I’m okay with you personalising in these ways, but not those ways,” and the business honours that. Such an approach can convert even privacy-cautious individuals into willing participants of personalisation – because they architected it to their comfort level.

6. Educate and Communicate Continuously

Balancing personalisation with privacy isn’t a one-time checkbox; it’s an ongoing process that benefits from continual communication:

• Educate Customers: Occasionally remind your users what data-driven personalisation you’re doing and how it benefits them. For instance, a banking app might have a short note: “We’re showing you this content based on your recent interest in home loans. We never share your financial details without permission.” These little nudges reinforce the transparency and help customers make the connection between data use and personal benefit.
• Train Employees: Make sure your team understands the importance of privacy. From marketing staff to customer service reps, everyone should be aware of policies on customer data. For example, a customer support agent should know not to reveal too much detail in a conversation just because they see it on file – if a customer calls about an issue, the agent can use information to help but shouldn’t casually mention, “I saw you bought X product yesterday” unless relevant and appropriate. Training ensures personalisation efforts are executed considerately at all touchpoints.
• Feedback Loops: Encourage feedback on both personalisation and privacy. Let users easily report if a personalised suggestion was off-base or made them uncomfortable. Perhaps an e-commerce site can have a small “Why am I seeing this?” link on recommendations, giving a simple explanation (“Suggested because you bought Y”) and an option like “Don’t use my buying history for suggestions” if the customer feels it’s too invasive. Likewise, allow users to report privacy concerns or ask questions. This dialogue helps you refine your approach and shows customers that their comfort is a priority.

Continuous communication demystifies your personalisation processes. The more customers understand what you’re doing, the less likely they are to be surprised or creeped out by it. Think of it as bringing them on the journey – when personalisation goes from a black box to an open conversation, it becomes far more palatable.

7. Stay Compliant and Ahead of Regulations

Finally, keeping the balance means never letting privacy compliance lapse. It’s not just about avoiding penalties, but about demonstrating your commitment to doing the right thing:

• Keep Updated on Laws: Data privacy laws are evolving globally. Ensure your legal and compliance teams monitor changes in legislation (such as new state laws, updates to GDPR-like regulations, or industry-specific privacy rules). Adapting early avoids frantic scrambles later and keeps customer trust intact.
• Use Compliance as Innovation Driver: Instead of seeing privacy laws as obstacles, use them as a catalyst for innovation. The push to comply can spur creative solutions. For example, Google’s phase-out of third-party cookies in Chrome (partly driven by privacy pressures) has encouraged marketers to innovate with privacy-preserving ad targeting techniques. Likewise, stricter email consent rules have nudged companies to improve content quality to keep subscribers engaged by choice. Look for ways that meeting privacy requirements can actually improve your products. Perhaps the need for explicit opt-ins will lead you to develop more compelling value propositions for customers to voluntarily share data.
• Document and Demonstrate: Have clear documentation of your data practices, security measures, and personalisation algorithms (at least high-level logic). In the event of audits or customer inquiries, being able to readily demonstrate what you’re doing and why builds confidence. Some companies even publish transparency reports or briefings on how they personalise and protect privacy. While not every business needs a public report, the exercise of documenting internally is useful to ensure all departments are aligned with the privacy-personalisation balance.

Staying ahead of regulations also means anticipating future trends. For instance, there’s growing discussion about AI ethics and privacy – if your personalisation uses AI to profile users, be aware of emerging guidelines on fairness and explainability. By proactively aligning with the spirit of privacy laws (user rights, minimisation, security), you essentially “future-proof” your personalisation strategy.

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Personalisation with Privacy in Practice: A Balancing Act

To illustrate how these principles come together, imagine a modern retail scenario:

An omnichannel fashion retailer operates both a website and brick-and-mortar stores equipped with cutting-edge tech. Through its loyalty program (which customers voluntarily join for perks), the retailer collects data: online browsing history, past purchases, style preferences customers saved in their profile, and in-store transactions recorded via mobile POS systems. With this data, the company provides valuable personal touches:

• The next time a loyal customer walks into a store, a sales associate’s tablet (the mobile POS) shows that the customer often buys sustainable organic cotton items and prefers the colour blue. The associate can then mention any new arrivals in that category – a personalised recommendation enhancing the in-store experience.
• Meanwhile, the retailer’s website and app show personalised product recommendations (“We think you’d love these new blue organic cotton sweaters!”) and content about caring for sustainable fabrics, aligning with that customer’s interests.

All this is highly personalised across channels (omnichannel retail tech at work) – but it’s done with privacy in mind. How?

• The customer was informed at sign-up exactly what data would be used (and agreed to it, possibly selecting preferences herself, thereby providing zero-party data).
• The company’s privacy settings allow her to toggle off in-store personalisation if she ever feels uncomfortable with associates knowing her preferences.
• The data collected is limited to shopping-related info; the retailer doesn’t, for example, scrape her social media or track her phone’s location without consent.
• Strong security protects her profile data in the backend systems.
• And if she has questions, the retailer’s app transparently explains “You are seeing these suggestions because of your past purchases and preferences. Manage your data here.”

In this way, the retailer reaps the benefits of personalisation – higher sales, a delighted customer – while maintaining the customer’s comfort and trust. The personal touch feels welcome, not invasive.

This balanced approach is increasingly being adopted in various industries:

• Financial services: Banks and fintech apps personalise product offers and financial advice based on a client’s data, but they are extremely careful with security and explicit consent, given the sensitivity of financial information. Many banks allow customers to opt in to share certain data (like transaction history) in exchange for budgeting insights or personalised investment tips, all under strict privacy safeguards.
• E-commerce and consumer tech: Online marketplaces use algorithms to curate each user’s homepage, but they provide settings to adjust recommendation types and ad preferences. Tech companies like Apple and Mozilla are introducing more privacy features (like mail privacy protection or blocking third-party trackers) to empower users, forcing marketers to rely more on consensual first-party data.
• Healthcare and wellness: Health apps personalise fitness or diet recommendations based on personal metrics – a deeply personal form of customisation. Here, privacy is vital; users must give clear consent for any health data use, and trust is won by showing that their sensitive health info is stored securely and not shared without permission.

Across all examples, the common theme is earning customer trust as the prerequisite for personalisation. When customers trust that their data is safe and used in their interest, they are more likely to embrace personalisation rather than shy away from it.

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Conclusion: The Path Forward

Balancing personalisation with privacy is indeed a challenge, but it’s also an opportunity. Companies that navigate this balance well stand to strengthen customer relationships in a way that competitors cannot easily replicate. In a future where customer loyalty is won by both intelligent service and ethical practice, mastering this balance will be a hallmark of leading brands.

As you refine your organisation’s strategies, remember that personalisation and privacy are not enemies – they are two sides of the same customer experience coin. Personalisation is about showing customers you know them; privacy is about showing you respect them. Both are necessary to truly put the customer at the centre of your business.

Executives and managers should champion a culture that values data privacy as much as data insights. By implementing the strategies outlined – from transparency and minimisation to security and user control – you can create personalised experiences that feel helpful, not intrusive. This fosters the kind of trust that turns first-time buyers into long-term brand advocates.

In the end, achieving the right balance is an ongoing journey. Technology will continue to evolve (think AI-driven personalisation, new data regulations, etc.), and consumer expectations will likewise shift. Stay adaptable, listen to your customers, and treat their data with the care you’d want for your own. Do that, and you’ll prove that businesses don’t have to choose between personalisation and privacy – you can, and must, excel at both.

Key Statistics

• 71% of customers expect personalised experiences from brands, and 76% feel frustrated when they don’t get them.
• 37% of customers say they do not trust companies with their personal data, highlighting a major trust gap.
• Nearly 48% of consumers have stopped purchasing from a company due to privacy concerns or data misuse.
• 50% of companies report that recent privacy regulations have made personalisation more challenging to implement.
• 78% of businesses consider first-party data (data they collect directly from customers) as their most valuable resource for personalisation.
• Personalisation pays off: companies adept at personalisation see 5–15% higher revenues, and around 40% of fast-growing retailers’ revenue comes from personalisation, outpacing slower competitors.

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