Amazon and Google ruined it for everybody. In a good way.

Customers now expect to be able to find exactly that thing they’re looking for with just a quick search. They expect smooth, fast user interfaces that react to the first letters they type with, “I bet this is what you’re looking for! How about this?! Or this other thing?!” Consumers expect the browsing, shopping, buying, delivery, and customer service phases of the customer journey to be smooth as silk and completely personalized to who they are, their wants, and needs.

Customers desire a uniquely personal experience.

Surveying the industry landscape and hearing first-hand from our customers (some of the world’s biggest retailers) here are the two main reasons it’s time to think about deploying a new ecommerce search system (or divorcing your old one).

Terrible Search Results

If they can’t find it, they can’t buy it.

Online search functionality should feel seamless. Type what you’re looking for, and watch it appear instantly—like magic. No stumbling through category hierarchies or landing pages. Just fast, accurate search results pointing you to exactly what you want, even if you spelled it wrong or didn’t call it by the exact right words

Unfortunately, the search functionality of many ecommerce sites isn’t quite there yet.

But if they can’t find it, it doesn’t exist. Or even worse, they assume you don’t have it, but somebody else might and they’re gone, likely to never return.

Finding what a user needs in response to a query is called relevance. Basic relevance is rooted in matching product descriptions to search keywords. This isn’t enough anymore. What humans think is relevant and the words they type in the search box don’t always match the words that product marketers use to describe the product in the catalog listings. A modern ecommerce search system should look at what users click for the terms they’ve searched and boost those results for all users. That means that users who don’t click to the next page, or even look beyond the first result, will see better results based on what other users clicked. This kind of collaborative tuning requires capturing user “signals” like click-stream events and purchases in order to improve search.

And on the business side of things, delays in turning insights into action can waste valuable time. Your search and analytics team runs some analysis on your log and finds some experiments they want to test that might increase conversions. So you wait for engineering resources to become available to code it, they roll it live to development servers and you test it there, then deploy to production and it’s live. But it’s probably weeks or months later and the assumptions you wanted to test were based on outdated data so you have to start all over. Another backend bugaboo is stale inventory data showing products that are no longer available.

Terrible Customer Experience

Going beyond the quality and relevance of search results, we also find that retailers are in a constant battle to continually improve and optimize the customer experience across all channels – web, mobile app, in-store, or on the phone.

When customer data and behavior data isn’t united with the customer experience, the overall feel is inconsistent and uninformed. There’s no historical perspective of the customer to establish where they are in the customer life cycle and the customer’s potential lifetime value. Without this data you also can’t deploy accurate personalization and effective user segmentation. Marketing campaigns and customer support efforts are clumsy, muddled, and middling. Customers experience a bland, boring, generic shopping experience and when they go to get customer support they get the same thing: a generic, inconsistent, experience.

Ignore the quality of your search results or the overall search experience at your peril: it could result in low brand loyalty rankings, tenuous brand loyalty, and low NPS scores – and terrible conversions.