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Should AI be creating your product content?

21 May 2019

By Drew Smith

Drew is the Director of Product Strategy at Volo and focuses on how technology can help brands and retailers deliver what their customers want.

Artificial Intelligence

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Predicting what technology will or won’t do is a pretty good way to look foolish years later – just look at Bob Metcalfe, a legendary figure in technology and network computing, who in 1995 made the following call:

“I predict the Internet will soon go spectacularly supernova and in 1996 catastrophically collapse.”

Luckily for us, Bob was wrong about the Internet. The fact that even experts and foundational figures in their field can be spectacularly incorrect shows that we still lack accuracy in our predictions of the future of tech. This makes it all the more confusing that many in retail confidently assert that AI technology will never be able to replace the role of a copy writer, or be able to create copy which is the equal of or better than a human’s output.

Today, the question is not about whether or not this could, will or should happen – but retailers and brands selling online should certainly be thinking about what AI could be doing for them today.

The action gap

While ecommerce leaders are happy to agree that AI has the power to transform the success of an ecommerce operation, only a minute percentage are actually deploying it in their day-to-day organisational processes.

At least some of this is due to the way AI is typically represented as either some sort of arcane magic, known only to data science wizards and MIT graduates; or alternatively an omniscient entity which can hold a conversation indistinguishable from a person.

These misleading perceptions obscure the fact that AI is already helping businesses fix practical problems, particularly with repetitive problem solving and numbers-based tasks.

Behind the smokescreen, AI is already able to solve some pressing issues for retailers and brands. It’s capable of sorting their product data out – something many brands will admit that they need help with.

Whether they’re currently outsourcing or struggling in-house with large teams, brands spend massive amounts of time and money manually adapting products to different channel requirements. On top of that, the same teams have to find time to manage campaigns and promotions across sales and marketing channels like Google Shopping, Amazon and social media.

Fashion retail guide to online success

What does AI have to do with an ecommerce team’s day-to-day?

We know that brands spend hundreds of hours getting their digitised products ready for consumers to find them online. Most of that time is absorbed in adapting fragments of data to fit each channel. For example, let’s say that both Amazon and Google all have a data field that tells the channel what material a jumper is made from. The problem is that one might call it ‘Outer Fabric’ and the other labels it ‘Primary Material’.

This doesn’t seem like too much of a problem. Of course, you can just create two versions, one with the Google field names and one with the Amazon names. Unfortunately, this starts to become problematic when you multiply the number of potential fields on each product by the number of channels and then again by the number of products. Very quickly, the retailer is faced with literally millions of data points to get right.

If someone handed you a task to do and told you it involved manipulating “millions of data points”, you probably wouldn’t feel too confident. For AI, it’s ideal. The more data you have the better, and the bigger the difference a trained AI can make thanks to its improved accuracy and massively improved speed. Given a long enough time, people will work through product collections and get them online with the bare minimum of data required to do so. AI can automate the process to such an extent that it becomes twenty times as fast, according to the latest Volo tests, and it delivers higher quality product data at the end of it.

Futureproofing, not futurism

AI’s role in the operation of brands and retailers isn’t confined to the realm of grand predictions any more – there are real applications and clear business cases to make, significant advantages to be captured and customers to delight. Brands and retailers can’t afford to think of AI as a buzzword for much longer.

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