case study

Impact Online Sales for eCommerce Company

Impact Online Sales for eCommerce Company

The Challenge

Evaluate Simulmedia’s Effect on Quarterly TV Advertising Performance

An e-commerce company wanted to determine the difference in its TV advertising’s performance between a quarter when it ran with Simulmedia versus a quarter when it did not. It also wanted to tease out the difference of Simulmedia’s campaign compared to its traditional media buy.

The Solution

Use Custom Targeting and Data Matching to Prove Simulmedia’s Impact

Simulmedia designed a campaign to reach the client’s custom target of heavy internet users and small business owners.

Custom Target

Execute a quarter long campaign, designed to efficiently reach the client’s custom target of heavy internet users and small business owners.

Data Matching

Match client’s first-party CRM data to TV viewing data in order to prove both TV’s impact on online activity, and Simulmedia’s effect on the client’s business.

The Results

Simulmedia Drove Lower CPMs, Higher ROAS, and More Efficiencies

The quarter with Simulmedia on the plan proved out its value, with double-digit increases in Return on Ad Spend (ROAS) compared to the quarter without Simulmedia on the plan, as well as double-digit increases in efficiency, new customer acquisition and transactions. Just as importantly, CPMs decreased by double digits as well.

38 %The quarter with Simulmedia on the plan had a 38% lower Cost per Thousand Reached compared to the quarter without Simulmedia.
11 %The quarter with Simulmedia on the plan had an 11% higher Return on Ad Spend (ROAS) compared to the quarter without Simulmedia.
55 %The campaign was 55% more efficient at driving incremental site visitors and 13% more efficient at driving incremental purchasers than the quarter without Simulmedia.

Future Optimization

Expand Target and Optimize Towards Higher-Income Audiences to Improve ROAS


Simulmedia analyzed the campaign’s performance against every audience reached, beyond just the guaranteed custom target, to further optimize future campaigns.

  • The client’s custom target was top 5 in ROAS performance when compared against other defined targets of interest. The client could improve the campaign’s overall ROAS by expanding the target to include more responsive segments.
  • Household income was a key variable in campaign responsiveness. Optimizing towards higher income individuals could improve the overall campaign’s ROAS.