Digital marketing optimization is actually an assembly of various improvements, including customer journey optimization, conversion optimization, A/B testing, propensity and churn scoring analysis and more. For example, customer journey optimization is the process of connecting and mapping customer interactions, across multiple touchpoints, in order to direct or influence the end-to-end experience. We use sophisticated approaches to analyze marketing data to map out what makes a customer buy your products and why some touchpoints fail. Consolidating data from various sources, de-noising the data, folding sets into multi-dimensional cubes, applying Markov chains and portfolio techniques…these are just a few of the steps we typically apply to optimize your marketing and to find the proverbial needle.
Depending on the size of your data and the long-term aims:
- we analyze things in R or Python or some well-known libraries
- use mid-range applications like Rapidminer to consolidate data, analysis and reports.
- switch on the Spark cluster to crunch your terrabytes.
Communication is key to any good data science project and we bring solid (scientific) arguments to the discussion, report results, collaborate with BI teams, stakeholders and executives.