With the help of user analytics Onsite Optimization has prospered to be an extended umbrella term having huge overlaps with product recommendations and personalization.
Onsite Optimization ( also known as on-page optimization) is the craft of optimizing the elements on your e-commerce site to gain a more advanced user experience and to increase user retention and conversion. It needs to be separated from offsite optimization that aims to gain higher search engine results (SERP) to drive more relevant traffic to your e-commerce site.
Well-mastered Onsite Optimization also improves search engine results, but its impact is more extended: the goal of onsite optimization is to make the comprehension of the site easier for both onsite search engines and customers plus make the content structure ideal for the customer. The latter two aspects will be more important in the view of personalization.
Onsite optimization prominently aims to:
-Optimize the content of the pages of your e-commerce site to enable users to find the relevant elements more easily.
-Help customers to clearly understand what the site is about.
-Help those active customers who already made efforts to find a certain content (who searched on the keyword and want to see relevant contents)
-Help those customers who haven’t made any efforts to find a certain content yet, but they already have some footprints on the site. So the content structure will be tailored to match the customer’s preferences and behavior. This means that the more advanced the customer event tracking and customer analytics is, the less the customer has to search to find the intended product(s).
With the evolution of Onsite Optimization customers ( especially tracked and analyzed customers ) have to make less and less efforts to find the relevant content. Both Customer Tracking- and Analytics Tools and Product Recommendation Tools get more affordable for even the smallest e-commerce ventures.
15 years ago Onsite Optimization meant appropriate keyword and tag management which helped the users to find the content or product they literally looked for. Typing keywords into the search engines within the site found the contents the user wanted to see, but not more. User experience looked very impaired in comparison with today’s e-commerce sites.
As user tracking- and analytics tools evolved, Onsite Optimization evolved too: beyond keyword repetition or placement it started to focus to understand who the users are, what might they be looking for, and how to fulfill this need with direct and adjoining keywords. What has become important is relevance. The development of machine learning was necessary to reach this maturity.
15-20 years earlier the deficiency of user information, nowadays the abundance of user information is the leading challenge which can also be settled by the filtering methodologies powered by the rapidly evolving machine learning.