Retail media professionals are missing out on AI’s potential to drive advertising performance, with fewer than one in six (16%) using the tech to boost targeting but nine out of ten (88%) embracing it to analyse data and write reports.
That is according to a snap poll of professionals quizzed during Particular Audience’s AI in Retail Media Town Hall, which reveals a worrying lack of trust is preventing many professionals from using AI to its full potential.
The session, led by Particular Audience founder and CEO James Taylor in Amsterdam, attracted 89 participants and generated 953 live contributions, with between 52 and 74 people responding to individual questions. PA was a headline sponsor.
Traditional targeting is still widely used. Among 68 respondents, half (50%) use manual keywords or categories and 54% manual audience segments. Only 22% use AI that predicts relevance from live shopping signals. Respondents could choose more than one option.
Taylor said: “AI is already doing plenty of work in retail media, but there is a vast gap in using it for the decisions that actually drive performance.
“The bigger opportunity is in deciding which products and ads are most relevant to a shopper, how they should be ranked and when an offer makes commercial sense. Retailers need to own those decisions, set the commercial rules and let AI optimise within those boundaries.”
Over eight out ten respondents (83%) said they would delegate campaign reporting now or within 12 months, and two-thirds (65%) product or ad ranking. That falls to 42% for bids and budgets and 41% for supplier-funded offers. Trust and control were the most cited barriers, alongside accuracy, transparency and proof of performance.
Asked whether AI would make decisions safer or riskier, on a scale where 1 is “much riskier” and 5 “much safer”, attendees scored AI product and ad ranking at 3.4 and AI deciding what advertisers pay at 2.8 (66 responses).
Particular Audience’s insists its research demonstrates how moving beyond traditional targeting can improve product discovery. In a grocery search test involving over 700 real customer queries, its Adaptive Transformer Search technology identified 80% of the relevant product catalogue within the first 120 search results, compared with 48.5% using traditional keyword search, a 65% improvement.
Rather than relying on fixed keywords or audience segments alone, AI can use live signals, including what shoppers are searching for, browsing and adding to their baskets, to predict relevance as their intent changes.
Combined with automated ranking and decisioning, this allows retailers to make better use of their inventory and advertising placements while keeping the shopping experience relevant, the company maintains.
However, it seems trust remains a major obstacle to wider AI adoption. While 83% of respondents would delegate campaign reporting now or within the next 12 months, just 42% would hand over bids and budgets and 41% supplier-funded offers. Trust and control were the most frequently cited barriers, alongside concerns about accuracy, transparency and proof of performance.
Particular Audience believes that, as AI takes on a greater role in retail media, the priority is to build confidence in the decisions it makes. That means clear commercial rules, transparent decision-making and measurement that proves incremental value.
The firm adds that retailers which establish these guardrails will be better placed to capture the benefits of automation while retaining control of product selection, ranking and monetisation.
The full findings and presentation are available on the Particular Audience website>
Related stories
H1 digital spend tops £21bn as retail and video clean up
Convenience shoppers ‘more open to retail advertising’
Decision Marketing at 15: The ‘Big Bang’ for retail media
Ocado signs up Epsilon for retail marketing expansion
Retail media: From shopper marketing to $141bn sector
Be the first to comment on "‘Trust issues’ holding back AI potential in retail media"