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Why eCommerce Brands Are Investing in AI-Powered Decision Making Across the Customer Journey
By Gaurav Belani
eCommerce brands have no shortage of data.
We can see which ads customers clicked, which products they viewed, what they added to their baskets, how often they buy, what they return, and whether they opened the last five emails.
AI changes that model. Its real value is not producing another dashboard or writing more marketing copy. It is helping us interpret signals faster, predict what is likely to happen next, and choose a relevant action while there is still time to influence the outcome.
That could mean changing which product a customer sees, deciding whether to offer a discount, identifying an order likely to be returned, or recognising that a loyal customer is starting to disengage.
What AI-Powered Decision Making Actually Means
AI-powered decision making is often grouped with generative AI, but the two are not the same.
Generative AI creates something new: an email, product description, image, or customer service response.
Decision-making systems analyse available information and determine what should happen next.
Basic automation might send every customer a reminder 24 hours after they abandon their basket. An AI-powered system can also consider the products involved, the customer’s previous behaviour, their likelihood of returning without an incentive, and the cost of offering one.
It might then:
Send a reminder immediately
Wait before contacting the customer
Recommend an alternative product
Offer free delivery instead of a discount
Take no action because the purchase is already likely.
The difference is context.
Traditional automation follows a fixed instruction. AI evaluates several signals and adjusts the action.
In practice, these systems usually do one or more of three things:
Predict: What is likely to happen?
Recommend: Which action is most likely to improve the outcome?
Execute: Can that action be triggered automatically within defined limits?
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