Chris Mellish, MD, Marketing Practice Lead UK and Ireland, Accenture Song takes a look at what OpenAI’s move into advertising means for retailers and brands – not least in terms of the data in brings to the party
OpenAI’s move into advertising has understandably set brand and retail marketers talking. What makes this particularly interesting is not simply the arrival of another advertising channel, but the type of information that this new ‘conversational AI’ can bring into the purchase journey.
Advertising has always relied on understanding signals about what people are interested in, but adding ads into LLMs potentially adds another layer to that understanding as people don’t just tell an AI assistant what they are looking for, they often explain why they are looking for it.
Our own research shows just how significant this shift could become. 71% of people expect generative AI to influence at least half of their spending over the next year, while 26% say AI has already led them to buy a more expensive product.
For brands, the opportunity is therefore to understand not just what someone is searching for, but the context around that decision.
But context is not the same as behaviour.
An AI assistant can become very good at understanding why somebody might choose a particular product, as it can understand the options, they are considering and the features that matter. What it cannot necessarily see is what happens when that intention meets reality.
People don’t always make purchasing decisions in the way they initially expected to as the product they intended to buy might be unavailable or they might see an alternative in store. This is where retailers have an important advantage. They have a direct view of what customers actually bought and over time, how those purchases develop into patterns of behaviour.
Conversational AI can provide a much richer understanding of the ‘why’, but retail data provides the evidence of what actually happened. For brands it’s about bringing those two perspectives together.
From targeting to influence
This also changes what advertising within conversational AI could mean for brands.
For many years, digital advertising has become increasingly sophisticated at identifying the right audience and reaching them at the right point in the journey. The next opportunity may be about influencing what consumers consider in the first place.
When somebody asks an AI assistant which product they should buy, the important question for a brand is whether it is part of that conversation. Recommendations have always played an important role in helping people navigate choice, particularly when there are too many products, reviews and opinions to consider. What changes with conversational AI is the scale and immediacy of that recommendation.
That creates a different challenge for brands as being visible online is no longer necessarily enough. Brands need to be relevant to the context and trusted enough for the recommendation to influence the eventual decision.
People are more likely to trust technology when they understand how it is being used and feel that they have some control over the experience and the same will apply to AI-led recommendations. If consumers feel that a recommendation is simply an advert dressed up as advice, the value of the experience quickly diminishes.
Retail’s role becomes more important, not less
It is understandable that retailers might look at the growth of conversational AI and see a potential threat to the value of their customer relationships.
As more of the consideration process moves into AI, the value of understanding what happens at the point of purchase arguably becomes greater and retailers are in a position to connect intent with outcome in a way that AI cannot necessarily do on its own, giving brands a way of grounding the new world of AI-generated intent in real customer behaviour.
The human understanding advantage
There is a temptation to think that as technology gets better at understanding people, we need to understand people less. The opposite is likely to be true.
As targeting and optimisation become increasingly automated, human understanding becomes more valuable. Marketers still need to understand motivations, but also the value exchange they are creating.
Technology is very good at delivering efficiency, relevance and frictionless experiences. But people don’t always make decisions in the most efficient way. We choose products because they feel familiar, because we trust the brand, because they fit how we see ourselves, or simply because something about the experience feels right.
That human understanding becomes particularly important when technology starts to play a more active role in the decision itself. If an AI assistant is helping someone narrow down their choices, brands need to think not only about whether they can be surfaced in that conversation, but why someone would feel comfortable acting on that recommendation.
And perhaps that is the more interesting implication of ChatGPT’s move into advertising. For brands, it’s not about creating another place to advertise, but about getting closer to the decision itself and understanding what makes someone move from consideration to action.
Author
Chris Mellish is MD, Marketing Practice Lead UK and Ireland, Accenture Song
You are in: Home » Retail Media » GUEST COMMENT From prompts to purchases: what LLM advertising push means for brands
GUEST COMMENT From prompts to purchases: what LLM advertising push means for brands
Paul Skeldon
Chris Mellish, MD, Marketing Practice Lead UK and Ireland, Accenture Song takes a look at what OpenAI’s move into advertising means for retailers and brands – not least in terms of the data in brings to the party
OpenAI’s move into advertising has understandably set brand and retail marketers talking. What makes this particularly interesting is not simply the arrival of another advertising channel, but the type of information that this new ‘conversational AI’ can bring into the purchase journey.
Advertising has always relied on understanding signals about what people are interested in, but adding ads into LLMs potentially adds another layer to that understanding as people don’t just tell an AI assistant what they are looking for, they often explain why they are looking for it.
Our own research shows just how significant this shift could become. 71% of people expect generative AI to influence at least half of their spending over the next year, while 26% say AI has already led them to buy a more expensive product.
For brands, the opportunity is therefore to understand not just what someone is searching for, but the context around that decision.
But context is not the same as behaviour.
An AI assistant can become very good at understanding why somebody might choose a particular product, as it can understand the options, they are considering and the features that matter. What it cannot necessarily see is what happens when that intention meets reality.
People don’t always make purchasing decisions in the way they initially expected to as the product they intended to buy might be unavailable or they might see an alternative in store. This is where retailers have an important advantage. They have a direct view of what customers actually bought and over time, how those purchases develop into patterns of behaviour.
Conversational AI can provide a much richer understanding of the ‘why’, but retail data provides the evidence of what actually happened. For brands it’s about bringing those two perspectives together.
From targeting to influence
This also changes what advertising within conversational AI could mean for brands.
For many years, digital advertising has become increasingly sophisticated at identifying the right audience and reaching them at the right point in the journey. The next opportunity may be about influencing what consumers consider in the first place.
When somebody asks an AI assistant which product they should buy, the important question for a brand is whether it is part of that conversation. Recommendations have always played an important role in helping people navigate choice, particularly when there are too many products, reviews and opinions to consider. What changes with conversational AI is the scale and immediacy of that recommendation.
That creates a different challenge for brands as being visible online is no longer necessarily enough. Brands need to be relevant to the context and trusted enough for the recommendation to influence the eventual decision.
People are more likely to trust technology when they understand how it is being used and feel that they have some control over the experience and the same will apply to AI-led recommendations. If consumers feel that a recommendation is simply an advert dressed up as advice, the value of the experience quickly diminishes.
Retail’s role becomes more important, not less
It is understandable that retailers might look at the growth of conversational AI and see a potential threat to the value of their customer relationships.
As more of the consideration process moves into AI, the value of understanding what happens at the point of purchase arguably becomes greater and retailers are in a position to connect intent with outcome in a way that AI cannot necessarily do on its own, giving brands a way of grounding the new world of AI-generated intent in real customer behaviour.
The human understanding advantage
There is a temptation to think that as technology gets better at understanding people, we need to understand people less. The opposite is likely to be true.
As targeting and optimisation become increasingly automated, human understanding becomes more valuable. Marketers still need to understand motivations, but also the value exchange they are creating.
Technology is very good at delivering efficiency, relevance and frictionless experiences. But people don’t always make decisions in the most efficient way. We choose products because they feel familiar, because we trust the brand, because they fit how we see ourselves, or simply because something about the experience feels right.
That human understanding becomes particularly important when technology starts to play a more active role in the decision itself. If an AI assistant is helping someone narrow down their choices, brands need to think not only about whether they can be surfaced in that conversation, but why someone would feel comfortable acting on that recommendation.
And perhaps that is the more interesting implication of ChatGPT’s move into advertising. For brands, it’s not about creating another place to advertise, but about getting closer to the decision itself and understanding what makes someone move from consideration to action.
Author
Chris Mellish is MD, Marketing Practice Lead UK and Ireland, Accenture Song
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