In the past few weeks, we’ve walked through the Valley of Terrible Relevancy and Even Worse CX for ecommerce search and emerged on the path to enlightenment with a wishlist for the ecommerce search platform of your dreams. Now let’s tackle ROI.
As you get ready to deploy an ecommerce search system, you’ll want to ensure you’ve put reporting in place to measure the success of your new search app – especially if you’re moving to a new search experience and want to prove that the return on investment was worth it.
There are a ton of ecommerce metrics you can spend hours – even days – slicing and dicing and analyzing. There’s the three you probably already know by heart:
- Conversion rate should be sliced to tie it back to just those sales that are coming from a shopper that used a search as part of their path to a purchase. This is another important metric to include in slide decks as you present quarterly results and reports about the value of search to the overall health of the business, and the need to continue to invest in search.
- Average order value or AOV is the total amount of orders received by the system in a period of time divided by the number of transactions. Again, you’ll want to see if user behavior like browsing by category or using search app functionality like search results, product recommendations, or other personalization features is having any effect on the amount of the orders coming in the door.
- Clickthrough rate is very important for measuring the quality of search results a shopper sees. Quality search results sort their items by how appropriate they are for what the shopper is searching for – and if the search results themselves are formatted and displayed in a format that entreats the shopper to go from a list of products to a particular product detail page.
Those are the three main stats to focus on as you’re putting in place a new ecommerce search app – or replacing an old one for a whole new experience. There’s three more we think are especially important for measuring ecommerce search performance and ROI.
- Search abandonment rate is how often a shopper searches the catalog, sees a set of search results and then simply bails. Are the search results obviously of low quality? Maybe the inventory offered, pricing… or even the visual presentation of the results. The search experience isn’t just the search box and button but what they do next. Differences in search query behavior and personalization may have an effect on encouraging customers to complete a purchase.
- Null results reports will tell you what queries return no results, leading a customer to a dead end. Most customers assume you don’t have what they’re looking for and simply leave your site. They’re not going to try different words to try and get the magic combination one to show them what they’re looking for. With manual rules setting or automated tuning with machine learning algorithms, you should be able to quick identify these queries and point the customer in the right direction.
- Search utilization is what percentage of site visitors use the search box as part of their shopping and browsing experience. This will be a key measure of the effectiveness of the search application as part of the overall site, shopping, and purchase flow. Low search utilization could be tied to the type of shoppers you attract, the UI of the site, or indicate the quality of the search results. The more people that use the search box, the more likely they are to purchase and the more revenue you’ll be able to tie back to the return on your search team and system.
That’s three and then another three, and also important – and often forgotten until it’s too late:
Don’t forget to baseline!
If you’re swapping in a new ecommerce search app or adding a new one, be sure you have at least a year of baseline data so you can measure the success of your new system and compare it to the previous solution.