Data is everywhere and has grown exponentially all over the place. Did you know that 90% of the world's data was captured in the last two years? Companies will have to deal with and manage a 50-fold increase in data. According to IBM, 2.5 quintillion bytes of data are created each day, and it's not slowing down. This is what we have started to call 'Big Data'. Ironically, companies will and have never known more about consumers than today. But the ability for companies to leverage that in a meaningful way has imploded. Companies are drowning in their own data lakes, unable to unify, use, or interpret their data in a meaningful way and with a favourable outcome for the consumer. We don’t have a problem finding the data. We have a problem using data appropriately.
Data as a fundament: the data flood – sink, swim, or swallow?
The data flood has started, but forging it is possible. It’s time to embrace it and conquer it. It all begins with a moment of realization that understanding data does make marketing better. Realize that it can deliver better customer experiences, implement impactful marketing programs and automation, and gain more profound insights for more thoughtful decisions and increased results. According to ‘The Global Review of Data-Driven Marketing and Advertising’ paper, a majority of global panelists (53%) said that “a demand to deliver more relevant communications/be more ‘customer-centric’ is among the most critical factors driving their investment... outpacing all other relevant factors.”
However, the issue is building a robust data foundation and a central repository where all the data is connected to make that happen. This is crucial. There are solutions to make it easier for CMOs to collect, process, and understand the data. Too often – especially for marketing in the twenty-first century – the answer to a problem is throwing more technology at it. What do you end up with? Even more problems. Below you will find the 4 stages of data maturity in your business.
- You perform basic segmentation
- You use 1st party data only that is mainly demographic.
- You pull segments manually
- A contact is a mail address
- You do behavioural segmentation; you use cookie ID and have a first data governance model in place
- You CAVCAT your data
- You have linked your personae exercise to your data model
- You leverage transactional and engagement data for personalization
- You can create static segmentation lists
- You do RFM modelling for segmentation; you use cookie and device IDs to identify an individual and are able to do so across device
- You use operational data to segment and for personalization
- You are fully able to standardize, transform, link identities, aggregate and index your data
- You can automatically create dynamic segment lists
- You can distinct 1st and 3rd party data — and for example exclude existing customers from ad campaigns
- A segment of 1, you have access to unstructured data — and use sentimental, attitudinal and behavioural data
- You have a persistent customer database with a unified and complete holistic customer view
- You have data workflow models in place
- Your CDP is linked to your DMP to orchestrate and optimize your advertising campaigns
- You are capable of creating Look-alike models and do propensity modelling.