Improving Marketing Campaign Effectiveness

Learn how data analytics helps marketers improve marketing campaign effectiveness.

Marketing Manager


Marketing Manager

The Situation Today

Erin recently took the lead of marketing efforts for a new custom clothing brand, ClearClothing, located in San Antonio, Texas. ClearClothing recently took on external investment and knows that the best way for them to drive awareness of the brand is by increasing their social media presence and running targeted ads against the demographics that are most likely to purchase the brand. Erin has been on the job a few months now and sales have been increasing, but it has come at a pretty high cost with conversion rates not exceeding 1%.

Most of the analytics tools provided by social media platforms unfortunately don't give enough flexibility for Erin to ask the types of questions she needs to in order to make adjustments in campaigns and it's excessively time consuming having to switch between each of them and compare results. On top of all this, Erin also wants to present findings to the executive team to help justify her spending goals.

ClearClothing's investors are savvy in the retail industry and know that if the store can't get above an average conversion rate of 3%, they're going to struggle to survive in the long run. The founders have a significant amount of pressure on them to ensure the continuity of the company which results in extra pressure on Erin to deliver more effective conversions. Without a significant increase in conversions, it is unlikely that ClearClothing will be able to secure additional investment to continue its growth.

Enter ClearQuery

Using the variety of data connectors in ClearQuery, Erin was able to connect to all of the social media platforms and digital ad accounts to consolidate marketing campaign results. With this data consolidated, she is able to start investigating immediately.

  • Erin starts by asking ClearQuery "What is the average number of clicks by month and age group over the last 6 months?" which provides some immediate insights that the most likely age group to purchase ClearClothing is between 25 and 34. After identifying this insight, she further notes that males and females are just as likely to purchase from the brand and that other demographics have little to no delta on conversion.
  • Using Relationship Discovery in ClearQuery, Erin was able to uncover the particular product SKUs that are most often purchased by multiple demographic data points including gender, race, and location. This provides Erin with enough information to further target specific ads for products at the demographics that are most likely to convert.
  • By saving a few Automated Insights and asking some specific questions, Erin created a dashboard that she could use to monitor campaign effectiveness across the board and set up alerts if the average conversions fell below a certain threshold.
  • Finally, Erin was able to create a living presentation that updated with the data using ClearQuery's Insights Canvas which cut down on the time it took to gather the data she needed to present to the ClearClothing's founders which they used to demonstrate the improved effectiveness of advertising campaigns to their investors, thus securing future funding rounds.

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