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Not every website visitor turns into a lead, not every lead turns to a sale – So, we’re left with the question, “How can we close the gap to improve CVR?”
For most clients, digital media and conjointly, online behavior, are the primary focus for Net Conversion. However, online activity may only be a stepping stone for a client’s overall business objective. The entire customer journey is rarely isolated to just a website and digital engagement; therefore, we need to continue looking at how customers perform offline.
As was the care for one of our clients in the insurance industry, the online funnel did not capture the whole story. Not every website visitor turns into a lead, not every lead turns to a sale – So, we’re left with the question, “How can we close the gap to improve CVR?”
The answer lies with connecting that offline customer journey data to their website behavior and optimizing it towards this behavior.
Implementation
Integrating offline sales and consumer behavior can come in a variety of shapes and forms. Many ad platforms (Google Ads, Facebook, etc.) have an offline conversion import feature to help tie together Ad Performance and improve targeting based on offline data. Efforts like these collect relatively low-hanging fruit since the offline import process typically requires minor implementation.
To thoroughly tie together onsite behavior with offline data requires a slightly more advanced approach, where the offline data is injected into the online analytics platform. This client uses Google Analytics, and the process for injecting data is known as Measurement Protocol. The same process occurs when a user visits a website. The user’s activity is sent to Google’s servers as hits which can come in the form of events, page views, hits, or transactions for e-commerce.
We set up an automated process that sends artificial hits through measurement protocol using Google Sheets and a Google Apps Script. The first step is to capture and store the user’s Google Analytics ID (essentially their cookie). This information can then be passed on along with the online lead information to a CRM system. The offline conversion is then also tracked in the CRM, and there is now a tie between the Google Analytics ID and the offline conversion data. Using an FTP source + Bigquery, the CRM data is connected to a Google Sheet where a Google Apps Script reads the information and passes it back into Google Analytics through the measurement protocol process.
Results
The results from our strategy have proven that offline attribution does lead to quantifiable benefits. Previous approaches have been focused solely on lead volume and not quality. 75% of policies occur offline, so we want to be able to attribute those back to online behavior and media efforts. Our current findings are being optimized and have streamlined the automating process across multiple clients.
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