Data to Audience conundrum – using a DMP – The need

Many organisations who invest in data management platforms struggle with the process of converting their vast amount of data into effective audiences for personalisation. Some feel that DMPs would magically convert their data dumps into audience personas and it is disheartening to realise converting data into audiences, even while using a DMP, is still largely manual process. While we all eagerly wait for AI to help us achieve fully automated “segment of one marketing, I will like to share the data led audience approach I have seen work well across my clients. The technicalities are specific to Adobe DMP but concept applies to any DMP. Some companies also use alternate approaches like use case led or persona based, and I will share my thoughts on them at the end of this post.

What is needed

If you have invested in a DMP, hopefully you have large sets of data that you are looking to consolidate and build powerful, marketing relevant audiences. The data sets may be one or more of online behavioural, offline customer, campaign performance, modelled data, survey, app engagement, partner, 3rd party etc. Each data set may have different identifier, data quality and business relevance. The scenario could be simplistically represented as below where companies are still figuring out how best to use their DMP for building audiences from data.

Data to audience