How brands can take a step back from the decline of identity-based marketing and measurement, and reframe the challenge of marketing effectiveness in a cookieless world?
Conduct an audit. Are you able to access holistic measurement now? How often? How can you get to the right level of data? What process changes are needed?
What is the right level of frequency, data weight and granularity for the decision you are making? Are they the decisions you need to make? And when?
Does your measurement solution have the backing of those who control budgets? What about finance? How can you get access to the data you need through IT partners or third parties?
Are you able to see that you are creating an impact and return, rather than validating what has gone before? Make sure you understand the value of your measurement program.
How easily can you answer new questions? Or take a closer look at the different levers impacting channels or campaigns? Develop the ability to examine complex interactions.
Don’t hire profiles. The world of data science requires a host of technical skills, from data architects, engineers and wranglers, to analysts and econometricians. Have you got the breadth of skills you need?
Are you looking at long time scales before you can make use of data? Can you take a more incremental approach to delivering benefit along the way with complete, if imperfect in granularity, solutions?
Implementing an actionable, adapted, reliable, and scalable marketing measurement solution, augmented by AI and data science, means equipping yourself with a powerful tool to make better and faster decisions for the whole organisation!