We analysed the microconversions on the website of a web bookstore. Thanks to this, we learned how customers move around it. We got to know their behaviour.
We found a group of “fugitives” who did not complete their transactions. Depending on the moment of abandoning the basket, we ascribed them to a group with a high chance of returning to the store (they left the basket at a very-advanced stage) or with a low chance of returning (they left at the initial stage).
We focused our communication on people with a high chance of returning to the store. The more activities on our website, the higher the rates we were prepared to pay. We sent them sponsored adwords links.
40%
The number of transactions grew by 40%.
We increased our total sales revenues by 25%.
25
We will analyse the traffic in your site in terms of the budgeted targets.
We will combine data from various sources – your CRM, website or media activities. We will identify user segments with high potential for your objective.
We will create a search-engine advertising-purchasing strategy for the more-promising segment of users. We will reach them with a precise message, maximally tailored advertising at the place and time when they need it. This way we won’t waste your budget.
We will improve solutions according to the data from your campaigns. The purchase-learning model will maximise spending where it identifies the greatest purchasing potential for your consumers.
