We’re in a time when AI is being used to lay the foundations of new technology. We love seeing it! AI – as it stands right now – is the next step in automation. It’s also being used to close the gaps in service delivery which were logistically expensive enough to not invite closure.
We’ll be talking about one such usage of AI today – in e-commerce catalog discovery – and how it closes the gaps therein.
Let’s begin with a general flow of online shopping:
- A consumer wants/needs something
- They go to a corresponding online retail point
- They ‘search’ the item, and when they find something they like, they buy it
The term ‘search’ here is essentially a replacement for text-based SEO driven catalog discovery. That’s a mouthful I’m sure, but the idea is that you type in descriptors or words to help the engine figure out what you want. That’s a lot of pressure on the consumer.
That also means there’s room to remove that pressure on them.
The idea here is visuals (images/videos) based search, but that isn’t exactly a new technology. That said, the existing version we’ve had lacks a certain… intelligence to it. Let’s clarify what that means.
There’s a reason visual-search is seeing an increasing popularity now, with the improvements we’re making in AI. Fundamentally, the old technology behind visual-search was highly inaccurate. Comparing a pair of sneakers and a pair of boots would’ve been a monumental task in programming a visual-search engine based on pre-AI tech. Without going into much detail, let’s understand their differences like this:
- Pre-AI tech would have to know what a pair of sneakers looks like to tell that it’s a footwear. If it has never been shown a sneaker, it might confuse it with a baseball cap.
- AI tech is more intelligent in how it knows that sneakers are footwear, even if the training given to it was with, let’s say, boots. It’s possible it’ll have troubles, but it would most definitely be more accurate in its assessment of sneakers than pre-AI tech.
And that makes a world of difference!
One thing to be certain of is that nobody enjoys the process of using descriptors and spending copious amounts of time looking for what they want. It’s a major turn-off from online shopping. A research on the importance of the search systems in online shopping platforms gives us the following information:
Reference: https://www.nosto.com/blog/new-search-research/
The same research suggests that 80% of customers leave these shopping sites because of a poor experience. It also suggests that the fashion shopping platforms are the biggest contributors to customer attrition due to poor search experience.
Changing a singular metric (that of search accuracy) could bring these numbers down significantly. AI visual search is designed to do just that.
And the technology is already out there, right now!
So, we believe it’s time to start rebranding the online shopping experience today, because the domain has seen a breakthrough that could completely overhaul the experience for an online customer.
And as business owners, improving customer experience is an offering you can’t afford to ignore. If it’s not to gain a competitive edge, it’s at least because this is the future of shopping.