Case Study | SEMrush

SEMrush increases conversion rates by

optimizing the sales funnel and reallocating

ad budget About SEMrush

• competitive research and Business Challenge Intelligence software that provides data on competitors’ and industry leaders’ online Most companies face the not so trivial task of assessing the effectiveness of traffic marketing activities sources. For SaaS companies it is especially important because the sales funnel can be • based in PA, USA divided into two different processes: freemium subscription and conversion into

• www.semrush.com paying customers. It usually takes more than one session for the average user to complete the funnel and Goals each visit is a different interaction type (pageviews and events). • eliminate sales funnel bottlenecks that That is why it is crucial to create custom sales funnels. In addition to that it is essential prevent visitors from becoming customers to analyze customer behaviour inside the sales funnel to eliminate possible • increase the precision of their calculations bottlenecks. by working with unsampled data

• evaluate the efficiency of traffic channels in To evaluate the efficiency of each traffic source, the following questions need to be driving conversions answered:

Approach 1. Which traffic sources bring in the most leads?

• collected visitor data using Enhanced Ecommerce module 2. What is the share between the traffic sources? Does the share stay the same for different steps in the sales funnel? • stream real-time data to BigQuery

• process data and visualize the results 3. Which traffic sources produce the most payable conversions? Results 4. Do the traffic sources interfere with each other? If so, where is the overlap? • ability to identify the traffic source for each step inside the sales funnel 5. How to attribute revenue to traffic sources in cases where more than one • sales funnel optimization traffic source was involved. increased conversion rates

To provide answers, we needed to use a tool where we could analyze raw user interaction data. Taking into account the sampling issue, we chose Google BigQuery. Step by step implementation:

1. Set up Enhanced Ecommerce module to Solution capture customer shopping behavior By using the sequences and discrete main steps from the buying process flowchart, 2. Set up OWOX BI Streaming to collect we worked with SEMrush to identify the main groups of traffic sources for analysis and unsampled data in Google defined the sales funnel. After that, we defined the list of the most popular exits that BigQuery for further analysis visitors took when they left the funnel. 3. Process & analyze data in Google BigQuery To send data to Google BigQuery, SEMrush used OWOX BI Streaming service. Since 4. Create reports and visualize results in with OWOX BI BigQuery they have the timestamp of each separate interaction with the website’s content, it Reports add-on was possible to build any sequence of user actions and combine them into one report across several sessions.

For building graphs and making sense out of the data SEMrush used the OWOX BI BigQuery Reports add-on that exported data from Google BigQuery into Google Sheets. OWOX created queries that were available to every- one who had access to the SEMrush project in using the add-on’s feature of including dynamic parameters. This way requests could be modified in the interface without touching the query.

It allowed even non-technical marketing and man- agement users to create and customize reports based on queries to Google BigQuery.

The last step was to build and visualize reports in Google Sheets, using the OWOX BI BigQuery Reports Add-on.

Checkout Behavior

Exit Path

Results

SEMrush’s analysts are now able to automate and visualize reports using OWOX BI BigQuery Reports add-on for Google Sheets based on their datasets from Google BigQuery. For instance, SEMrush can identify the traffic source for each step inside the sales funnel to evaluate the efficiency of each step and determine potential exit paths. It helps optimize the sales funnel and increase conversion rates using customers behavior data.