How are your conversion rates? The average ecommerce store conversion rate is 2.5–3% — if you’re in that range, you’re not alone. But wouldn’t it be great to break away from the pack? Say, get to 5% or higher?
You can get serious about that goal by improving your search and discovery user experience with AI-aided technology. To help you implement this promising idea, it would help to know exactly how other retailers have done it. When it comes to high-quality ecommerce site usability and meeting higher conversion goals, seeing how other online stores have set up an optimization process can make a big difference.
In that spirit, let’s look at three ecommerce retailers: Algolia clients Everlane, Oh Polly, and Zenni. These companies have gone above and beyond ho-hum ecommerce conversion to bolster their bottom lines.
What’s their common secret? Upgrading their search functionality (the search box) and discovery functionality (browsing and navigating). They implemented industry best practices to improve the customer experience on their site (or in an app), and the result was significantly more impressive KPIs.
Here are highlights of how each organization pursued optimization efforts, along with key improvements:
Conversion increase: 5%
How they raised conversion:
Prior constraints: Before this US-based sustainable clothing company teamed up with Algolia, its engineers were needing to do loads of cleanup and implementation to get product data to feed efficiently.
Results: The company beta tested NeuralSearch. Now, customers who search are converting at a much higher rate. And along with the hefty bump in conversion, the amount of times customers reached the “No results” rate dropped 45% and their click-through rate increased 8%.
Conversion increase: 5.4%
How they raised conversion:
Prior constraints: Despite offering image-search capabilities, this UK-based women’s clothing retailer lacked customization and personalization functionality. Things happened slowly and various pain points were cropping up for website visitors. Management was receiving negative feedback from both their customers and their ecommerce team. They needed a robust, text-based search engine that could improve relevance, provide the right results fast, and reduce the demand on their human teams.
Results: The company upgraded its relatively obscure search icon to a larger search bar, resulting in a 30–40% increase in use. Now, search is used in about 7% of user sessions, with those sessions accounting for 20% of revenue. The company has seen a 5% gain in click-through and a 7.1% increase in revenue.
Conversion increase: 9%
How they raised conversion:
Prior constraints: This US glasses retailer had two search engines and needed to consolidate to only one. Their search results pages loaded slowly, and they wanted to support nuanced eyewear product variables.
Results: They simplified their search capabilities, improving the speed at which results pages appear. With SaaS, they got rid of pesky complexity, as now they no longer need to deploy anything. Along with their impressive lift in conversion, they’ve seen a 44% improvement in search traffic, a 34% gain in search revenue, and a 27% increase in revenue per user session.
There are lots more case studies where these came from. Reading them, you’ll see the same best practices being applied.
What are some of Algolia’s AI-powered capabilities that have enabled these retailers’ impressive successes? Here are key features and what they’ll give you the power to do:
What’s your prospective upside from upgrading search functionality with a proven industry leader? Find out the scoop on achieving a conversion rate increase that visibly elevates your ecommerce business. With customers who find shopping and buying on your site compelling, a sizable conversion bump is within reach. Let’s discuss!
Catherine Dee
Search and Discovery writerPowered by Algolia AI Recommendations