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3 Things E-commerce Businesses Need to Know About AI

November 28 2017

Over the last couple of years, buzz words among online retailers have been personalization, natural language processing, automated optimization and other terms piled up under the AI umbrella.

Retailers glance in fear towards Amazon.com and their massive amount of data, scared that it will be hard to compete without a data-driven approach in everything from marketing and traffic acquisition to how the website is presented to the user.  

The answer is often to quickly implement some sort of AI solution. In this article, Nikki Baird raises the question that AI may suffer from “Silver Bullet Syndrome” – that businesses turns towards AI for AI’s sake. 

“…whenever retailers make technology investments along these lines, they invariably fail, mostly because the retailer expected a lot more from the technology than what it realistically could deliver,” Baird explains.

Although the point is valid, and that AI won’t solve every problem, it can be a powerful tool for online vendors. There are, however, some things to have in place before venturing into this – for almost everyone – unchartered territory.

Understand in Which Areas Ai is (And Isn’t) Effective

This might be stating the obvious: AI relies on data. To be effective, the system needs to process and base its decision on information – the more the better. Due to this, e-commerce websites should preferably implement AI solutions on sales channels that are “always on”. 

Interested in our personalised on-site product search? Learn about our features  and functions in our complete spec sheet.

For shorter campaigns, say, over Black Friday, you probably won’t get sufficient data to optimize it properly. And even if you have data from previous year, there is a risk that the conditions were completely different then and the information retrieved does you more harm than good.

In your everyday business, however, you will get an increasing amount of data to process.

Setting Goals Is Incredibly Important

Traditional optimization efforts were a lot about defining demographics and customer groups to be able to provide different people with different messages, products or online experiences. This is something you (probably) won’t spend much time doing in the future. A properly set-up AI will outperform any manual analysis you previously did.

However, you will need to put more effort into defining your goals – in essence, what you want to achieve. A poorly defined goal will make the AI work towards something not beneficial for the business whereas a “good” goal will take it in the right direction.

Some goals, such as “sales”, are pretty straightforward. But if you’d like to increase brand recognition or other softer values, make sure to set – and continuously review – your goals. Again, the system will optimize for what you put into it. If crap goes in, crap will come out.

Correct Measuring is a Must 

It’s not unusual that businesses are unsure whether or not they can trust their own data. Think about it: Is what you define as a sale actually a sale and is a conversion really a conversion?

Previously this may have been viewed a minor problem. When reviewing the website performance, you might have said something like: “We know this isn’t exactly correct, but it gives us the general trend and that’s good enough.”

If you have AI that base its decisions on this measuring, your entire business might be optimized in the completely wrong direction. And the better the AI becomes (the more data it has available,) chances are that problems only will escalate.

Bottom Line

AI will change how we work with e-commerce websites. A lot of the heavy lifting when it comes to analyzing who people are and their behavior will become unnecessary. A human can’t beat a computer in this regard.

On the other hand, you need to be more creative and strategic when analyzing what you want to achieve. Setting proper goals for the AI to work towards will be the most important task for any marketer.

If you succeed, AI may be more than just a silver bullet. At Loop54 we accomplished precisely this.

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Topics:

eCommerce Site-Search
Machine Learning
Ecommerce

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