It’s that time of year again. We’ve been publishing our predictions for the year ahead for some time now, and 2026 is no exception. Will they come to fruition? Only time will tell – but in the meanwhile, let’s take a look at five potential loyalty and personalisation trends for 2026 courtesy of Ben Snowman, dunnhumby’s Global Head of Loyalty and Personalisation.
We all know that customers love discounts. But the industry-wide push to deliver on that desire has created a world in which the majority of retail loyalty programmes look the same. As a result, customers can flit between those schemes with little sense of meaningful difference.
In 2026, this lack of distinction will be harder to sustain. Economic pressure is rising again, and discounts alone won’t keep customers engaged. Retailers will need to step back and re-examine what their programmes stand for; loyalty will need to be cemented as an extension of brand strategy, more than just a tool or tactic.
This shift will encourage a more thoughtful mix of programme features. Some brands will lean into community and experience. Others will rethink how member pricing works. A few will move away from blanket offers and focus on more distinctive propositions – ones that really align with what their brand represents.
The message is clear: loyalty can’t stay on autopilot. Retailers will need to build something that feels intentional, not interchangeable.
Going into 2026, make sure you know this phrase: “continuous relevant customer engagement”. What does it mean? That loyalty is moving from a programme to a relationship – and that retailers are beginning to reconnect with what loyalty is supposed to be: continuous engagement that goes beyond just programme mechanics.
To make this a reality, personalisation and loyalty will be even more tightly knit in 2026. We’ll see more personalised benefits and rewards inside loyalty apps, alongside tailored content, journeys, and recommendations. In-store screens and devices will be increasingly used to personalise the experience, flexing based on customers’ entire shopping patterns, not just one retailer’s data.
This won’t be limited to offers and coupons. It will shape how customers are engaged across digital and physical environments. Loyalty will become something customers feel across the entire journey – not just in an app message every Thursday.
Behind the scenes, retailers have been making rapid progress building out their loyalty infrastructures. They’ve invested heavily into first-party data, Customer Data Platforms, identity, and analytics. That work has created strong foundations. And in 2026, the effort spent on building those foundations will start to pay off.
Native AI inside marketing and personalisation platforms will help retailers streamline and automate decisions, shortening workflows and serving more relevant messages. AI agents will begin to assist with low-code journeys and campaign optimisation. These won’t replace marketers, but they’ll take on repetitive tasks and move retailers closer to real-time personalisation.
Another major shift will be the growth of a more mature use of “blended” data. Retailers will combine first-party data with new sources, including location and weather through to banking data and cross-retailer spend, as well as deeply specialised third-party datasets. Startups are already pushing the envelope with what’s possible when you understand the shopper’s full world – not just their basket with one retailer.
As retailers modernise their loyalty approaches, they’ll rethink how value is delivered. Expect more experimentation in five key areas:
• Funding mixes that combine retailer budgets, supplier investments, and retail media spend.
• Member pricing, used more strategically and backed by supply-side support.
• Social commerce, where retailers need to show up on platforms like TikTok Shop.
• Product-based rewards, where points unlock items or experiences, not just money off.
• Embedded loyalty, where benefits flow across ecosystems, like mobile, travel, finance, entertainment.
We’ll also see more retailers take inspiration from non-grocery categories. Brands like North Face use loyalty to deepen community, not just drive transactions. Banks like OCBC in Singapore blend loyalty with travel and financial services. These models deliver value that feels more personal and more relevant to customers’ lives, not just their shopping baskets.
The lesson for 2026: loyalty needs to feel bigger than points and discounts. It needs to fit the brand, the customer, and the moments that matter to them.
Agentic has been everywhere and nowhere all at once. Agentic AI shopping has been one of the most talked-about topics of recent months. With OpenAI’s partnerships with Shopify, PayPal, and Stripe, the idea suddenly feels closer. Could this break the link between retailers and customers altogether?
In 2026, agentic shopping will be everywhere in the media… just not everywhere (or even anywhere) in real life. Where agents may gain ground more quickly is in fashion, gifting, and marketplaces with large product ranges. Over time, agents could help consumers manage baskets across retailers – balancing cost, delivery times, and even loyalty point redemption.
So how do you build loyalty when an agent is the one doing the shopping? The answer is in two parts: first, optimise for the agent, so your data, pricing, and loyalty mechanics work well inside AI-driven decision systems. Second, train the agent by shaping the signals it receives and influencing how it recommends or selects your products.
Right now, agentic is less of a reality and more of a concept. But in 2026, retailers will at least need a point of view on this potentially disruptive trend.
Stay tuned for more predictions from across the world of grocery retail soon.
Explore how AI-powered loyalty programmes enhance customer experiences and drive sales with dunnhumby’s personalised, data-driven solutions.
Learn more about our Loyalty and Personalisation solutions
| Cookie | Description |
|---|---|
| cli_user_preference | The cookie is set by the GDPR Cookie Consent plugin and is used to store the yes/no selection the consent given for cookie usage. It does not store any personal data. |
| cookielawinfo-checkbox-advertisement | Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category . |
| cookielawinfo-checkbox-analytics | Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category . |
| cookielawinfo-checkbox-necessary | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
| CookieLawInfoConsent | The cookie is set by the GDPR Cookie Consent plugin and is used to store the summary of the consent given for cookie usage. It does not store any personal data. |
| viewed_cookie_policy | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
| wsaffinity | Set by the dunnhumby website, that allows all subsequent traffic and requests from an initial client session to be passed to the same server in the pool. Session affinity is also referred to as session persistence, server affinity, server persistence, or server sticky. |
| Cookie | Description |
|---|---|
| passster | Set by Passster to remember that a visitor has entered a correct password, so they don’t have to re-enter it across protected pages. |
| wordpress_test_cookie | WordPress cookie to read if cookies can be placed, and lasts for the session. |
| wp_lang | This cookie is used to remember the language chosen by the user while browsing. |
| Cookie | Description |
|---|---|
| fs_cid | Set by FullStory to correlate sessions for diagnostics and session consistency; not always set. |
| fs_lua | Set by FullStory to record the time of the user’s last activity, helping manage session timeouts. |
| fs_session | Set by FullStory to manage session flow and recording. Not always visible or applicable across all implementations. |
| fs_uid | Set by FullStory to uniquely identify a user’s browser. Used for session replay and user analytics. Does not contain personal data directly. |
| VISITOR_INFO1_LIVE | Set by YouTube to estimate user bandwidth and improve video quality by adjusting playback speed. |
| VISITOR_PRIVACY_METADATA | Set by YouTube to store privacy preferences and metadata related to user consent and settings. |
| vuid | Vimeo installs this cookie to collect tracking information by setting a unique ID to embed videos to the website. |
| YSC | Set by YouTube to track user sessions and maintain video playback state during a browser session. |
| _ga | The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors. |
| _ga_* | Set by Google Analytics to persist session state. |
| _gid | Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously. |
| _lfa | This cookie is set by the provider Leadfeeder to identify the IP address of devices visiting the website, in order to retarget multiple users routing from the same IP address. |
| __Secure-ROLLOUT_TOKEN | YouTube sets this cookie via embedded videos to manage feature rollouts. |
| Cookie | Description |
|---|---|
| aam_uuid | Set by LinkedIn, for ID sync for Adobe Audience Manager. |
| AEC | Set by Google, ‘AEC’ cookies ensure that requests within a browsing session are made by the user, and not by other sites. These cookies prevent malicious sites from acting on behalf of a user without that user’s knowledge. |
| AMCVS_14215E3D5995C57C0A495C55%40AdobeOrg | Set by LinkedIn, indicates the start of a session for Adobe Experience Cloud. |
| AMCV_14215E3D5995C57C0A495C55%40AdobeOrg | Set by LinkedIn, Unique Identifier for Adobe Experience Cloud. |
| AnalyticsSyncHistory | Set by LinkedIn, used to store information about the time a sync with the lms_analytics cookie took place for users in the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
| bcookie | LinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognise browser ID. |
| bscookie | LinkedIn sets this cookie to store performed actions on the website. |
| DV | Set by Google, used for the purpose of targeted advertising, to collect information about how visitors use our site. |
| gpv_pn | Set by LinkedIn, used to retain and fetch previous page visited in Adobe Analytics. |
| lang | Session-based cookie, set by LinkedIn, used to set default locale/language. |
| lidc | Set by LinkedIn, used for routing from Share buttons and ad tags. |
| lidc | LinkedIn sets the lidc cookie to facilitate data center selection. |
| li_gc | Set by LinkedIn to store consent of guests regarding the use of cookies for non-essential purposes. |
| li_sugr | Set by LinkedIn, used to make a probabilistic match of a user's identity outside the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
| lms_analytics | Set by LinkedIn to identify LinkedIn Members in the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland) for analytics. |
| lpv[AccountID] | This cookie is set by Salesforce Marketing Cloud Account Engagement. Prevents counting multiple page views within a short window to avoid duplicate tracking. |
| NID | Set by Google, registers a unique ID that identifies a returning user’s device. The ID is used for targeted ads. |
| OGP / OGPC | Set by Google, cookie enables the functionality of Google Maps. |
| OTZ | Set by Google, used to support Google’s advertising services. This cookie is used by Google Analytics to provide an analysis of website visitors in aggregate. |
| s_cc | Set by LinkedIn, used to determine if cookies are enabled for Adobe Analytics. |
| s_ips | Set by LinkedIn, tracks percent of page viewed. |
| s_plt | Set by LinkedIn, this cookie tracks the time that the previous page took to load. |
| s_pltp | Set by LinkedIn, this cookie provides page name value (URL) for use by Adobe Analytics. |
| s_ppv | Set by LinkedIn, used by Adobe Analytics to retain and fetch what percentage of a page was viewed. |
| s_sq | Set by LinkedIn, used to store information about the previous link that was clicked on by the user by Adobe Analytics. |
| s_tp | Set by LinkedIn, this cookie measures a visitor’s scroll activity to see how much of a page they view before moving on to another page. |
| s_tslv | Set by LinkedIn, used to retain and fetch time since last visit in Adobe Analytics. |
| test_cookie | Set by doubleclick.net (part of Google), the purpose of the cookie is to determine if the users' browser supports cookies. |
| U | Set by LinkedIn, Browser Identifier for users outside the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
| UserMatchHistory | LinkedIn sets this cookie for LinkedIn Ads ID syncing. |
| UserMatchHistory | This cookie is used by LinkedIn Ads to help dunnhumby measure advertising performance. More information can be found in their cookie policy. |
| visitor_id[AccountID] | This cookie is set by Salesforce Marketing Cloud Account Engagement. Unique visitor identifier used to recognize returning visitors and track their behavior. |
| visitor_id[AccountID]-hash | This cookie is set by Salesforce Marketing Cloud Account Engagement. Secure hash of the visitor ID to validate the visitor and prevent tampering. |
| yt-remote-connected-devices | YouTube sets this cookie to store the video preferences of the user using embedded YouTube video. |
| _gcl_au | Set by Google Tag Manager to store and track conversion events. It is typically associated with Google Ads, but may be set even if no active ad campaigns are running, especially when GTM is configured with default settings. The cookie helps measure the effectiveness of ad clicks in relation to site actions. |