You may be losing out on 22% of your revenue with dated tech
Written by: Guest Author
All businesses, online or not, struggle to find ways to grow. Whether or not they have investors to please, external factors such as inflation require businesses to find ways to continue growing. Of course, there are countless ways to increase revenue, particularly when your business is run online. New SaaS providers reach out every day claiming to have a way to help, and there’s noise from every corner of the web telling you how a small change can increase your site conversion rate.
Of course, not all of these software solutions will work for you, and not every blog post will contain a novel optimization tip. In truth, most of the growth avenues that ecommerce merchants explore are stale. Many retailers find themselves spending hours each week looking for small tweaks they can make that will increase conversions from search, social, or on their checkout pages, but there’s one avenue that’s largely unexplored, and it could be causing you to miss out on 22% of your revenue according to multiple reports.
What is this avenue? AI.
What does AI have to do with ecommerce?
AI still seems like a marketing buzzword designed to get honest business men and women excited about nothing, but it’s been making a real difference to many businesses for years.
So why haven’t you heard about real implementations of it?
AI makes the biggest difference in two key areas that are usually put on the backburner, namely, search and merchandising. The average ecommerce site sees search usage hovering around 8% of their traffic. This causes many decision makers to think of it as being an insignificant portion of traffic. In other words “it’s not worth my time”. This is a BIG mistake.
Across the board, ecommerce studies show that search visitors are 2x as likely to make a purchase compared to non-search visitors. Search visitors also spend twice as much money. Reports all over the web corroborate this story, but how does AI factor into this?
The basic search algorithms that are driving search for 90% of ecommerce websites don’t use AI, but online retailers that ARE leveraging this technology see an even more drastic divide between their search visitors, and non-search visitors. Our own study of sites utilizing AI-driven search revealed that search visitors spend 3.24x as much money, convert at a rate 3.48x higher, and are responsible for roughly 40% of total site revenue even though they make up only 7.84% of total traffic.
What exactly does AI do?
AI can do a lot of things, but what does it do in the context of ecommerce? As mentioned above, it’s primarily being used today to make search and merchandising algorithms smarter, or more natural.
A search bar that’s truly leveraging next-generation AI technology will better understand search queries, and will return far superior results. How?
Traditional keyword based search systems will take a basic search for something like “red nike running shoes” and return results for any products that contain the words “red”, “nike”, “running”, and “shoes”. In this example, rather than seeing products that match the query, results will usually contain a seemingly arbitrary assortment of shoes, Nike branded items (which might include gym bags, shirts, etc), and other items that contain these words in their searchable fields.
While some custom work can improve the relevancy of the search results, it can never completely fix the innate problem that the algorithm does not understand what the shopper wants.
In this real-world example, the image on the left shows results from a basic keyword matching engine that’s currently used by most major ecommerce platforms. The returned results include a few helmets, but accessories are also included since the keyword from the shopper’s query appears in the title and product descriptions as well.
AI search engines tackle this problem with custom algorithms that read the product data in a retailer’s database and build an understanding of what each item is. In this scenario, the engine understands the relationship between each of the words in the query. This enables the AI search engine to return only the products that the shopper wants, rather than a mixture of products that are relevant and irrelevant to the shopper’s search.
Comparing search performance before and after integrating AI into their search bars, the average retailer sees a 22% increase in search-driven revenue.This represents the single greatest application of this technology in terms of dollars and cents today, but this isn’t the extent of what this technology can do.
But AI isn’t just for search. It’s being used by top retailers to drive marketing and merchandising campaigns. Retailers like eBags.com have used AI and machine-learning algorithms to increase their customer lifetime value by as much as 30%.
Perhaps one of the best applications for this technology is to learn from user behavior. By granting access to analytics data, these engines can see view counts, click-through-rates, add-to-cart rates, purchase and return data, and page view time among many other data points. From there, an algorithm is applied to this data that can see which products are most likely to be purchased in any scenario.
However, optimizing for the highest possible conversion rates isn’t always in the best interest of a retailer. Some would rather sell higher margin products, such as house brands. AI can come into play here and merchandise an entire site, or only specific sections of a site with specific business goals in mind.
Other retailers are using it to automatically generate and rank ecommerce filters, or to create personalized product recommendations. In any case, in addition to increasing conversion rates, revenue per visitor, and general user engagement, AI can help retailers by automating tasks that currently occupy hundreds of hours per year. For example, AI can take over the task of programming and managing synonyms, savings dozens of hours per month while also making the site easier to use.
In reality, there are likely many more applications for this technology that haven’t even been discovered.
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