e-Commerce Site Search – Quantitative benefits

Posted on January 11, 2017 by

One of the services we offer at Tagalys is a Personalized search for e-commerce. Interested already – SIGNUP NOW, join a free plan or a free trial to know whats best for you. 

This is the ability to showcase unique, relevant and accurate search results for each visitor that are personally relevant. The reason we stress on personalized search is because of its impact on business metrics. All our clients ask us how much of an upliftment in buy conversion can be expected from Tagalys search. Truth is we do not control that directly, but we do control conversion to product discovery, that leads to uplift in buy conversion rate. So what metrics do we directly or indirectly influence?

  1. Bounce: Tagalys will reduce the bounce rate for visitors who search due to the quality of search results
  2. Product views: There will be an increase in product views as product thumbnails shown in results are personally relevant to each user and not standardized for the entire site.
  3. Listing page to View Conversion rate: Our goal is to ensure more visitors view products. There is a direct correlation to product views and conversion rate, especially for visitors who search. More the product views per visitor, higher the buy conversion rate. Our primary goal at Tagalys is to improve this conversion rate as that is what our engine has control over.
  4. Order value: We have noticed a 20% to 40% improvement in order value or basket value, with personalized search.
  5. Frequency of visits: As results are identifiable by visitors and user experience has improved, we have noticed a 10% to 20% rise in frequency of visits before purchase. Our hypothesis here is that this segment is probably undecided visitors who revisit the site and continue shopping. There is an increased probability that this segment could have been lost after the second visit.
  6. Reducing time to transact: While the frequency of visit has increased for a small subset of the search audience, there is overall decrease in the time to transact by over 40%. Our hypothesis here is that these visitors are more decided, who find products faster, convinced by details on the product page and trust the retailer. Improved product discovery, helped reduce time thus time to transact.
  7. Visitors who search: Across most of our clients, search volume is between 6% to 15% of overall traffic, there has been a 50% jump in the overall percentage of search. While returning visitors will continue to search, our hypothesis of this increase is due to increase in new visitors who search. This behavioral shift is driven by UI changes, the addition of a clear call to action and best practices of site search for ecommerce
  8. Revenue: We cannot directly take credit for all the increase in revenue. It has also be tied with the trust a retailer has created with its audience, the details (images, specs etc.,) in the product page to make the decision easy, the design of the product page, internet connectivity and payment gateway reliability. But, due to the increase in metrics 1-7, there is a direct correlation to increase in revenue.

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Posted in eCommerce Site Search