Case Study: From Awareness to Conversion – Optimizing End-to-End Media Planning

Background

Our client had run numerous always-on digital campaigns, however their measurement was stuck in a last-touch world. They constantly questioned the value of non-traditional last-touch channels like Programmatic and Display, and had limited understanding of how the wider digital display ecosystem worked together to generate leads.

Opportunity

Our client wanted to see how the full digital journey, including Social impressions, worked in concert to shift consumers from awareness, through consideration, to conversion.

Solution

We created a unique Cross Walled Garden Multi-Touch Attribution solution based on Markov Chain Theory — to analyze how each digital touchpoint impacts the end result — taking into account channel, tactic, and position of the interaction along the consumer journey.

We also incorporated Bayesian Analysis of Social impressions, delivering even deeper analysis of digital media performance. Bayesian modeling is a holistic, purely statistical analysis that normally requires extensive data preparation and results calibration. By employing a sophisticated algorithm, we ensured all data was properly cleaned, transformed, and loaded for visualization and reporting.

The resulting output was a detailed analysis of the entire digital consumer journey; from first touchpoint to last — allowing our client to truly understand how all their digital investments worked together to generate leads.

Results

Conclusion

From this analysis, we made data-driven optimization recommendations for how to best split budget across the entire digital funnel — delivering fully optimized end-to-end media planning.