Pick me, pick me: What AI is doing to your shopping carts - Hindustan Times

Pick me, pick me: What AI is doing to your shopping carts

Aug 04, 2023 08:36 PM IST

Algorithms aren’t just screening what you see. They aim to soon monitor purchases well enough to say, ‘It’s time to order toothpaste’, then tell you which one.

Over the past year, images have gone viral of shoppers checking out purchases at automated counters, in giant stores that stand completely empty.

What does the future of e-commerce look like? It could end up being a place of sameness, where what you see is a lot like what you have; and a place of heavily vetted viewing. This representation was generated by Midjourney. PREMIUM
What does the future of e-commerce look like? It could end up being a place of sameness, where what you see is a lot like what you have; and a place of heavily vetted viewing. This representation was generated by Midjourney.

Flip that picture. Could machines soon begin to shop for us too, with less and less involvement from the paying customer?

Across 27 Amazon Go stores in the US, there is no human interaction at all. Artificial-intelligence (AI) systems monitor the store. Patrons needn’t even pay on the spot. The final bill can be charged to their Amazon account.

These buyers can expect to soon be bombarded with recommendations generated within the same AI-led system. “It’s time to order the next batch of toilet rolls,” a text might say. Or, “Aren’t you nearly out of cereal?”

Already, across e-commerce portals, whether for groceries or fast fashion, cosmetics or travel, algorithms are clambering into shopping carts. At the most basic level, items are added to carts as “recommendations”. One level of engagement above this, are the “reminders” that something one searched for once is “now available on discount”.

Specific order recommendations are the next frontier, says London-based Shibu Nambiar, chief operating officer at the technology services company Genpact. In the UK, the app for Waitrose, the gourmet groceries chain, is attempting to use AI to craft customised recommendations.

“The app could then tell me, ‘You have been ordering a particular kind of cereal for your children for the last 12 months. Our recommendation based on dietary requirements is to not buy this product anymore but buy this other one instead’,” Nambiar says.

So not, “Aren’t you nearly out of toothpaste” but rather “Shouldn’t you be ordering XYZ brand today?”

A version of this is already in play, in segments such as beauty and fast fashion. Myntra’s digital stylist, for instance, has a stated mission of suggesting new purchases based on previous ones, as well as on the buyer’s input on parameters such as preferred colours and styles. It can thus essentially look at what’s in a customer’s cart and go: “Oh, but surely you need this too?”

The promise, with each of these advances, is of assistance, convenience, speed. At certain Whole Foods stores in the US, for instance, checkout staff have been replaced by Dash Carts, intelligent trolleys that use sensors to track what is placed in them. The premise here is quicker billing.

The underlying mission, across platforms, is intelligence-gathering. The carts, for instance, yield data on what a specific consumer buys, how they pay, how long they may take to make a decision; all of which goes towards building a profile, for use in future recommendations; with the aim of encouraging more purchases, purchases of a specific type, or eventually of a specific brand.

“Through opaque algorithms, internet companies steer our attention. While this could be convenient, choice is also taken away in the process. The algorithm decides what content we see,” says Michelle Khoo, Southeast Asia director of Deloitte’s Center for the Edge, the arm of the professional-services giant that explores the intersection of business and technology.

The opacity of those algorithms is key. What data tech companies collect from users, how wide they cast their nets (are they scanning our email, for instance, much like they track our web-browsing habits?), how this data is anonymised, scraped and logged are aspects that regulators in many countries are struggling to decode and monitor.

In July, US lawmakers reintroduced the Algorithmic Justice and Online Platform Transparency Act, which would make it mandatory for online platforms to disclose how their algorithms work to collect data from and thereby generate contextual suggestions for individual users. The European Union has gone a welcome step further. With new elements of the Digital Services Act coming into effect across the EU in 2024, it will become mandatory for all online platforms to disclose the structures of their algorithms.

For now, based on your history, certain portals have likely created a shadow version of you, and are aiming to both predict and influence how that you moves through their virtual shelves.

This has happened before, to a lesser degree, offline, when stores first began studying retail atmospherics, or the science of how factors such as light, music, piped fragrances and the placement of items influenced shopper behaviour.

Look carefully and one can see how the digital world is reordering its approach to its inventory too.

If you suspect, for instance, that clicking on a product a few times has caused its price to go up or discounts to disappear, you may be on to something. In a few months, some of the mechanics of these algorithms may be forced into the public domain. Until then, we can’t even know for sure.

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