By Harry Hanson-Smith, Vice President UK&I and Northern Europe at Dynamic Yield by Mastercard
The consumer world is chock full of choices. There is an answer to every problem and much of it is available at consumers’ fingertips. However, retailers have to take care not to cause decision fatigue which, in the worst-case scenario, can cause users to abandon their shopping journeys altogether. Instead, it’s time to become the consumer’s partner in choice, helping them navigate their shopping journeys more effectively – and more enjoyably.
Consumers are often willing to go all out when it comes to making the right shopping choice. Most (89%) check product reviews before buying and more than half (57%)will visit a few sites to make price comparisons. Social media and search both figure highly in customer journeys, with 84% hunting for products via platforms like TikTok and Instagram, and 29% likely to buy the same day as a result.
However, consumers can have too much of a good thing, with one study suggesting that consumers left as much as a week between product searches. And even when they came back, there must still be an echo of that tiredness. This isn’t ideal for retailers because that decision fatigue impacts conversions – after that delay, 76% of fashion shoppers didn’t go further than the first click.
Of course, brands know that one of the best ways to win market share is to have the most comprehensive offering possible. But it’s in how they deliver that offering that can be the difference between sale or no sale. One of the best ways to reduce decision fatigue and guide consumers to a sale is to become their virtual personal shopper.
How might we assist you?
Delving into the data to hone the online shopping experience through personalisation is just the start. This is an area where natural language processing (NLP) and AI can excel. Personal conversational experiences that imitate that personal shopper is particularly useful for customers who don’t have a specific product in mind. These sift through the sprawling product catalogue, eliminating irrelevant options and guiding the shopper right to what they’re looking for.
How, you may ask, can an ecommerce site deliver personalised recommendations without using personal data? It all comes down to context.
AI can start making initial recommendations after receiving permission from the user, based on contextual data such as geolocation, local weather conditions, basic demographic information and modelling based on similar user profiles. It then adapts as its interactions with the user continue. These can be surprisingly nuanced. When the consumer hovers over an item but ultimately doesn’t click, AI can serve products according to different variables – size, colour, price, reviews – and make an assumption as to what did and did not appeal, thus refining its recommendations without asking any further effort on the consumer’s part.
It’s all a question of balance
It’s important to recognise that consumers will have varying levels of comfort with an AI-powered shopping experience. While the aim is to streamline and remove decision fatigue, retailers need to recognise that the AI experience is additive, not alternative. While potentially tiring, many consumers will still prefer ‘old style’ search, manual filters and a good old scroll.
Nor should the AI experience stray into the realm of the creepy. Consumers are already railing against the constant pestering by retailers asking for reviews and feedback, desperate to add that all-important social proof to their sites and NPS score. Pursuing them with endless product suggestions or incentives is the same – it smacks just a bit of desperation. Similarly, messaging that has too much of a hint of “I know what you wore last summer” is to be avoided.
As with everything, there is a balance to be struck. But the adoption of highly capable, AI shopping assistants could spell the end of consumers’ shopping woes – if retailers are willing to take the plunge.
