Black Friday has become one of the most influential moments in the global retail calendar, with millions of shoppers relying on online platforms and mobile apps to find the best deals. At the heart of this digital shopping surge are AI-driven recommendation systems, which predict what customers are likely to purchase based on their browsing behaviour, purchase history, loyalty activity, and engagement patterns. 

These systems play a key role in capturing customer attention and driving conversions. But behind the convenience and commercial impact lies a less visible reality—the growing scale of personal data collection and profiling required to fuel personalised shopping experiences. As retailers deploy increasingly sophisticated algorithms to stay competitive, it’s also important to recognise their responsibility to safeguard consumer privacy, ensure fairness, and comply with data protection laws. 

Personalisation, profiling, and the privacy challenge 

AI recommendation engines operate by building detailed customer profiles, analysing everything from product views and social interactions to geolocation and in-store behaviour. While this enables retailers to deliver truly tailored experiences, it also raises critical privacy questions, including: 

  • Do customers understand the volume and types of personal data used to drive personalisation? 

  • Are they aware that they are being profiled and how those profiles are constructed? 

  • Can they opt out or control the level of personalisation applied to them? 

Without clear transparency, meaningful choice, and responsible data controls, personalisation can become intrusive and create significant compliance risks. These risks could expose retailers to huge regulatory penalties, particularly under frameworks such as the EU GDPR, U.S. state privacy laws, and global equivalents.  

However, AI does not have to be a privacy risk. When deployed ethically and lawfully, recommendation systems can strengthen customer loyalty, increase basket size, and reinforce a retailer’s reputation as a responsible brand. The cornerstone of responsible innovation is good governance, which facilitates embedding privacy protections into every stage of AI design, integration, and vendor management. 

The following governance checklist outlines the essential steps for retailers aiming to enhance personalisation while staying compliant and maintaining customer trust. 

Governance checklist 

Lawful basis and consent:

  • Have we identified the correct lawful basis for personalisation? 

  • If using consent, is it explicit, granular, and easy to withdraw? 

 Transparency & notices: 

  • Do customers understand what data is collected, how profiling works, and how recommendations are generated?  

 Data minimisation: 

  • Are we collecting only the data necessary to deliver personalisation, or are we building profiles excessively or opportunistically? 

 Purpose limitation: 

  • Is personal data being used solely for personalisation, or is it being repurposed for unrelated marketing, advertising, or third-party commercial gain?  

 Algorithmic fairness: 

  • Have we tested for bias to ensure recommendations do not produce discriminatory or exclusionary outcomes? 

 DPIAs & risk assessments: 

  • Have we conducted Data Protection Impact Assessments (DPIAs) before introducing new types of data or profiling? 

 Retention and deletion: 

  • Are we applying clear retention limits to behavioural, preference, and transaction data? 

 Security and access controls: 

  • Is profiling data encrypted, access-controlled, and logged to prevent unauthorised use?  

 Children and vulnerable groups: 

  • Do our systems include controls to prevent profiling of minors or individuals in vulnerable circumstances?  

 Vendor and third-party management: 

  • Do contracts restrict vendors from reusing personal data and require deletion at the end of service?  

The role of the Data Protection Officer (DPO) 

Strong privacy governance does not happen by accident; it must be led. DPOs can provide expert support to ensure strong privacy governance is in place for the implementation of AI recommendation systems in retail. An effective DPO can support in the following ways: 

  • Conducting DPIAs to assess and mitigate risks associated with profiling, automated decision-making, and behavioural analytics before deployment 

  • Defining lawful basis strategies, including when consent is required and how to design consent interfaces that are intuitive and customer-centric 

  • Reviewing consumer transparency language, ensuring privacy notices and preference controls are understandable, visible, and actionable 

  • Establishing governance guardrails to prevent repurposing of data and to ensure alignment with data minimisation and retention requirements 

  • Assessing and managing vendor risk, negotiating contracts that prohibit data reuse, mandate security standards and enforce deletion at termination 

  • Monitoring algorithmic fairness, helping identify and address potential discriminatory impact or unintended exclusion 

  • Embedding privacy-by-design into system architecture, ensuring security and data protection controls are engineered directly into workflows 

When DPOs are involved early as strategic partners, they can help retailers implement personalisation tools lawfully and with customer trust at the centre. 

A defining moment for responsible retail 

This Black Friday, retailers have a unique opportunity not only to boost sales through AI-powered personalisation but also to demonstrate leadership in consumer privacy. Responsible recommendation systems are not just about compliance; they are also about earning long-term trust and building resilient customer relationships. 

At HewardMills, we support organisations, including retailers, in deploying AI technologies that are ethical, compliant, and commercially effective. Our team of global privacy and AI governance experts advises on the full lifecycle of personalisation systems, DPIAs, lawful basis selection, vendor risk management and transparent consumer communication. If your organisation is integrating or scaling AI-based tools and would like expert support to assess readiness, strengthen controls, or enhance responsible personalisation practices, our DPO team is here to help. 

To learn more about the evolving relationship between data protection and AI governance, read our whitepaper The regulatory landscape and responsible governance of AI  or contact our team for expert guidance.