The conversation about loyalty programs has shifted. For years, the debate centred on reward economics: are points too expensive? Is the tier structure right? Are members actually redeeming? These are still valid questions, but they miss something much larger at the centre of boardroom conversations across retail, financial services, travel, and FMCG right now.

Your loyalty program is not just a retention tool. It is, arguably, the most commercially valuable data infrastructure your business owns.

This matters more now than ever for structural reasons. The digital advertising ecosystem that most companies built their acquisition and re-engagement strategies on is breaking down. Third-party cookies are gone or going. Walled garden platforms continue to raise prices while restricting the data signals marketers relied on for targeting and attribution. Regulatory frameworks in the EU, the US, and Australia are tightening the rules around how customer data is collected, held, and used.

Loyalty programs are becoming the antidote, and the gap between brands that recognise this and those that don’t is widening fast. While some brands are watching their cost-per-acquisition climb and their targeting precision fall, others are quietly building member databases that reduce their dependence on paid media entirely. The irony is that the brands investing least in loyalty right now are the ones who will pay most to reach customers later.

How has the data landscape changed?

The death of third-party cookies is not a future event. It is happening now. Apple and Mozilla removed cookie tracking years ago, and the broader ecosystem has followed. Consumers increasingly understand that their data has value, and regulators are legislating to give them more control over it.

This creates two cascading effects for marketers. First, the cost of digital advertising rises as targeting precision falls. Brands that relied on programmatic retargeting, look-alike audiences, and cookie-based attribution are finding their cost-per-acquisition climbing. Second, the competitive advantage shifts toward companies that have already built direct, consented relationships with their customers through owned channels.

Loyalty Programs: The Complete Guide (2nd Edition) by Philip Shelper addresses this directly. The book explains that the rise of walled garden data and the erosion of cookie-based tracking are increasing demand for zero-party and first-party data, and that loyalty programs are positioned to lead that shift by capturing this data and managing member consent to use it (Shelper et al., 2023, Chapter 13). That framing, written before the current market dynamics fully crystallised, now reads as a precise description of where the industry has landed.

The programs best placed to capitalise are those that have invested in building rich, consented member databases over time rather than relying on rented audiences through paid media. As we explored in one of our previous blogs: When Everyone Has a Loyalty Program, the Program Is Not Enough, differentiation increasingly comes from what a program knows about its members, not just what it offers them.

What Makes Loyalty Data Genuinely Different?

Not all data is equal. Loyalty programs generate a specific category of customer data with properties that make it commercially superior to almost anything else a company can collect. Understanding those properties is essential before making the case for investment.

• Consented. Members join voluntarily and agree to terms and conditions. Their data is first-party, collected directly from the relationship, not inferred or purchased from a third party. This is critical in an environment where regulators are specifically targeting non-consensual data collection.
• Transactional. Loyalty data captures actual purchase behaviour, not just browsing intent. You know what members bought, how often, at what price point, with what basket composition, and through which channel. This depth separates loyalty data from social media engagement or website analytics.
• Longitudinal. Member data compounds over time. A member who has been in a program for three years carries a rich transaction history, preference signals, and lifecycle markers that make their profile exponentially more useful than a newly acquired contact.
• Identity-resolved. Unlike anonymous web analytics, loyalty data is tied to an individual. This enables true personalisation, lifecycle management, and accurate attribution across channels.

Consumers understand their data has value and most are willing to share it, but conditionally. PwC’s 2025 Customer Experience Survey found that while 53 per cent of consumers consider sharing personal data worthwhile for a better experience, 93 per cent say they will lose trust in a brand entirely if that data is mishandled (PwC, 2025). Getting this right matters as much as the data architecture itself. eMarketer’s 2026 loyalty analysis describes loyalty programs as primary vehicles for first-party data collection, capturing transaction data, preference signals, and cross-channel behaviour at a scale no other owned channel can replicate.

How Do Leading Programs Commercialise Their Data?

The most sophisticated loyalty operators are no longer treating member data purely as an input to marketing. They are treating it as a commercial asset in its own right, with multiple revenue pathways available to programs willing to invest in the infrastructure to activate it. There are four distinct commercialisation opportunities: selling loyalty currency to coalition partners, selling marketing and data analytics services to partners, earning affiliate commissions, and providing reward fulfilment services to third parties (Shelper et al., 2023). The first two are most relevant in the current environment.

Retail Media: The Tesco Clubcard and Woolworths Everyday Rewards Model

Retail media is one of the fastest-growing advertising segments globally, with spending projected to reach €25 billion in Europe alone by 2026 and exhibiting over 30% annual growth through 2024 (RMIQ, 2025). The model is straightforward. A retailer uses its first-party loyalty data to sell targeted advertising inventory to suppliers and brand partners who want to reach members in a contextually relevant, consented environment.

Tesco Clubcard now reaches 23 million UK households, and in the first half of 2024, the retailer posted profit growth of 10% and sales growth of 4%, with its retail media platform explicitly credited as a contributor to that performance (Marketing Beat, 2024). Through Tesco Media and Insight Platform, over 450 brands have partnered with Tesco, achieving a return on ad spend of £6.60 for multichannel campaigns compared to £3.80 on other platforms (Grocery Doppio, 2024). In 2024/25, the platform delivered over 9,000 campaigns with increased advertiser engagement, positioning it as a growing standalone revenue stream (Retail Insight Network, 2025). That is the commercial consequence of three decades of activated Clubcard member data.

In Australia, Woolworths Cartology operates on the same principle, leveraging Everyday Rewards member data to offer suppliers targeted access to one of the country’s largest grocery audiences. In the US, Kroger Precision Marketing captures 96% of in-store transactions and 100% of e-commerce transactions through its loyalty card program, giving it a depth of real household purchase data that few networks can match (The Drum, 2025). Albertsons, with 49 million loyalty members, has described its program explicitly as “a rich data source for our merchants and for our media collective, enabling targeted marketing and monetisation” (Digital Commerce 360, 2026, para. 6).

For brands at smaller scale, full retail media infrastructure may not yet be accessible. But the underlying principle applies broadly: a consented, identified, transactional member base has commercial value that extends well beyond driving repeat visits.

Selling Marketing and Analytics Services to Partners

Programs that have built sophisticated analytics capabilities can generate revenue by providing those services to partners. Promoting targeted offers to an engaged, points-seeking member base generates incremental acquisition and spend for the partner while boosting earn activity for the program. Helping partners derive insights from member data is a commercially valuable service in its own right.

The dunnhumby business is the clearest evidence of where this trajectory leads. What began as the data science operation behind Tesco Clubcard grew into a global customer data science company operating across 30 countries. Kroger recognised the same potential when it acquired key dunnhumby assets in 2015 and built 84.51°, its wholly owned data science company, on that foundation. 84.51° now feeds insights directly into brand innovation planning, with Kroger describing its ambition as going beyond campaign execution toward “growing brands” and being pulled into R&D conversations from the start (The Drum, 2025). The data infrastructure created by a loyalty program can itself become a scalable, standalone commercial business.

Personalisation at Scale: The Internal Revenue Case

The third commercialisation pathway is internal, but no less commercially significant. Active loyalty program members generate 12% to 18% more incremental revenue each year than non-members, with top-performing programs reporting revenue increases of 15% to 25% from engaged participants (Netguru, 2026). Antavo’s Global Customer Loyalty Report 2025, based on a survey of over 2,600 loyalty professionals globally, found that program owners who measure ROI report their programs generate 5.2 times more revenue than they cost to operate (Antavo, 2025).

These outcomes are not driven by the existence of a program. They are driven by the quality of data activation behind it. The EY Loyalty Report 2025 found that only 16% of corporations have achieved hyper-personalisation, and that the primary blocker is operational rather than intent: most brands lack the integrated platforms, governance, and real-time decisioning required to turn personalisation ambition into consistent customer outcomes (EY, 2025). The programs closing that gap are the ones generating the numbers above. Those that have not are likely subsidising behaviour that would have occurred anyway.

The 2025 Deloitte Consumer Loyalty Program Survey reinforces this: 72% of consumers say loyalty programs make them more likely to spend with their preferred brand, and over half increase their spending directly because of the program (Deloitte, 2026).

Why Do Most Programs Leave Data Value on the Table?

Despite the commercial opportunity, most loyalty programs are not yet operating as data businesses. A handful of structural challenges explain why, and they tend to show up consistently regardless of program size or sector.

• Fragmented technology stacks: Member data is typically spread across the loyalty platform, the CRM, the point-of-sale system, the marketing automation tool, and the mobile app. Without integration, the data cannot be activated cohesively. The Open Loyalty Trends 2026 Report identifies fragmented tooling and operational complexity as the leading challenge for loyalty teams heading into 2026, and it is easy to see why: data that cannot be connected cannot be commercialised.
• Organisational silos: In many companies, the loyalty team sits within marketing and the data insights the program generates are used only for loyalty-specific campaigns. There is no structured pathway for loyalty data to inform media strategy, commercial partnerships, product development, or pricing decisions. The program becomes a cost centre rather than a commercial platform.
• Weak member profiles: Programs that have not invested in zero-party data collection often have member databases that are transactionally rich but contextually thin. You know what members bought, but not why, what they aspire to, or what they want from the brand relationship. As our piece on Why Customers Ignore Most Loyalty Programs explores, real personalisation requires data that goes beyond surface-level tactics. Using a member’s first name in an email is not personalisation. Reflecting their actual preferences, adapting offers based on past behaviour, and acting on zero-party data they have willingly provided is.
• Governance gaps: Consumer demand for data control is rising sharply. A 2024 global analysis of over one million respondents found that 87 per cent of consumers want the ability to manage how their data is collected and used, and 76 per cent believe companies must do more to protect them (PrivacyEngine, 2024). Separately, DataGrail’s 2024 Data Privacy Trends Report recorded a 246 per cent year-on-year increase in data subject requests, whether for deletion, access, or opting out of data sales (DataGrail, 2024). Programs without clear consent architecture face rising compliance risk on all fronts. More practically, members who do not trust a program with their data will limit what they share, reducing the commercial value of the database over time. Trust is not just a compliance obligation, It is a commercial input.

What Does a Data-First Loyalty Strategy Look Like?

Repositioning a loyalty program as a data asset does not require a complete redesign. It requires a change in how the program is governed, what data it collects, and how that data flows into commercial decision-making across the business.

• Design earn mechanics with data collection in mind. Every member interaction is an opportunity to learn. Surveys, preference centres, gamified data capture, and progressive profiling at key lifecycle moments all build the richness of the member profile. The earn structure should create ongoing reasons for members to share more of themselves over time, not just at the point of enrolment.
• Build the right technology foundation. A modern loyalty data strategy requires the program’s data to flow into a CDP or data warehouse where it can be combined with other signals and activated across channels. As we note in Designing DTC Loyalty Programs for Scale, Profit and ROI, programs that treat the technology architecture as secondary to the rewards proposition tend to discover later that they have built a program they cannot scale or mine effectively.
• Structure commercial agreements to reflect data value. If the program operates with commercial partners, data-sharing and targeting agreements should reflect the value of what is being provided. This is consistently underdeveloped. Partners paying for access to a program’s marketing database are paying for something genuinely scarce. The commercial terms should reflect that.
• Measure and report at a commercial level. The data the program generates should be reported to leadership in commercial terms, demonstrating what incremental revenue and margin the member database has enabled across direct marketing, partner targeting, and retail media or analytics service revenue. Loyalty programs measured only by engagement metrics will always struggle to justify investment at the executive level.

For a comprehensive grounding in the data collection methods, analytics frameworks, and commercial structures underlying these recommendations, see Loyalty Programs: The Complete Guide (2nd Edition) by Philip Shelper, which addresses these topics across Chapters 11, 13, 14, 15, and 16.

Why Is Now the Right Time to Act on Loyalty Data?

The window to build a genuinely differentiated loyalty data asset is narrowing. eMarketer’s 2026 loyalty analysis identifies first-party data scarcity as one of four structural forces elevating the strategic importance of loyalty programs this year, alongside mobile commerce dominance, rising customer acquisition costs, and what researchers are calling the loyalty deficit: a growing consumer perception that the relationship with brands is imbalanced.

The Open Loyalty Trends 2026 Report adds an important dimension. The number one challenge loyalty teams identify heading into 2026 is differentiation. Loyalty programs have become ubiquitous. A competent program is no longer a competitive advantage. It is table stakes. Standing out requires using the member data the program generates to deliver experiences, commercial partnerships, and insights that competitors cannot replicate. This connects directly to the argument we make in Building Emotional Loyalty That Goes Beyond Discounting: the programs that win are those that move beyond transactional mechanics toward something members actually feel.

Programs that invest now in data architecture, consent frameworks, and commercial activation will compound that advantage over time. Programs that continue to treat member data as a by-product of the rewards program will find themselves increasingly exposed as third-party data sources diminish and the cost of reaching non-members rises.

Loyalty & Reward Co works with program operators across sectors to develop data strategies that are commercially grounded and practically executable. Contact our team to explore how to turn your program’s data into measurable commercial value.

Referencias

Shelper, P., Lyons, S., Harrison, S., De Boer, R. & Savransky, M. (2023). Loyalty Programs: The Complete Guide (2nd Edition). Loyalty & Reward Co. https://loyaltyrewardco.com/insights/loyalty-programs-the-complete-guide/

Deloitte (2026). Reshaping Customer Loyalty Programs: 2025 Consumer Loyalty Program Survey. https://www.deloitte.com/us/en/insights/industry/retail-distribution/reshaping-customer-loyalty-programs.html

eMarketer (2026). FAQ on Loyalty Programs: Closing the Customer Retention Gap in 2026. https://www.emarketer.com/content/faq-on-loyalty-programs–closing-customer-retention-gap-2026

Open Loyalty (2026). Loyalty Program Trends 2026 Report. https://www.openloyalty.io/resources/loyalty-program-trends

PwC (2025). 2025 Customer Experience Survey: The Loyalty Illusion. PwC United States. https://www.pwc.com/us/en/services/consulting/business-transformation/library/2025-customer-experience-survey.html

RMIQ (2025). The Complete Retail Media Networks Guide for 2025.
https://www.rmiq.net/blog/retail-media-guide/

Antavo (2025). Global Customer Loyalty Report 2025.
https://antavo.com/blog/global-customer-loyalty-report-2025/

EY (2025). EY Loyalty Report 2025.

Retail Insight Network (2025). Tesco grows FY 2024/25 profit.
https://www.retail-insight-network.com/news/tesco-grows-fy-2024-25-profit-trims-debt-amid-rising-costs/

Digital Commerce 360 (2026). Albertsons digital sales grow. https://www.digitalcommerce360.com/article/albertsons-digital-sales/

The Drum (2025). Retail media isn’t media: Inside Kroger’s 100-year data advantage. https://www.thedrum.com/news/retail-media-isn-t-media-inside-kroger-s-100-year-data-advantage

DataGrail. (2024). 2024 data privacy trends report.
https://www.datagrail.io/blog/privacy-trends/privacy-trends-2024/

PrivacyEngine. (2024). Data privacy statistics worldwide for 2024.
 https://www.privacyengine.io/data-privacy-statistics-worldwide/

Grocery Doppio. (2024). What makes Tesco’s retail media strategy a game-changer. https://www.grocerydoppio.com/articles/what-makes-tescos-retail-media-strategy-a-game-changer-and-differentiator

Marketing Beat. (2024, October 3). Tesco praises Clubcard and retail media growth in solid interim results. https://www.marketing-beat.co.uk/2024/10/03/tesco-clubcard-retail-media/

Netguru. (2026). The ROI of modern loyalty programs. https://www.netguru.com/blog/roi-of-modern-loyalty-programs