I remember the day our CIO Leonardo Naressi wrote about the challenges of advertising in the age of privacy control a few days after the official announcement that Google Chrome, the browser with the highest market share, would no longer accept third party cookies. I was almost in despair because I work with online campaign optimization and help clients understand that last-click measurement is not always ideal. Without cookies to measure user journeys, how was I going to be able to understand them?
Here at DP6 we have since developed ways to deal with this new data scenario for Marketing. Ultimately, the buzz about the end of cookies was bigger than the practical effects on our routine (at least until now). We would like to share some of this content about Integrated Marketing Measurement.
Era of consent
One of the great evolutions in Marketing was the change from campaigns with little segmentation and measurement to one with hyperpersonalization, where cookies provided more opportunities to understand the effectiveness of campaigns. However, we are entering a new era of regulation, one where the consumer understands the value of their data.
3 trends exemplify this change:
- People are concerned about privacy and want more control over how their data is used.
- There is more legislation that gives people options to limit sharing their data with companies.
- Platforms are removing identifiers and bundling data to be shared with companies.
In practice, however, we see greater acceptance of terms of use in Brazil, with few people rejecting cookies and adopting adblockers, unlike consumers in Europe and North America.
We have just implemented a multi-touch attribution model. Was this money wasted?
Although identifying unique users in attribution models with third-party cookies is more direct, tracking a user’s origin is still possible with first-party data. One of the ways to understand a user’s journey towards a conversion is to cross your tracking tool’s identifier with an internal identifier and store this in your Data Warehouse. We can still manage to get a view of the media origins that contributed to the action. MTA (Multi-Touch Attribution) remains relevant for performance campaigns and provides fast data to be used in the day-to-day activities of marketing analysts.
Following this reasoning, building customer loyalty within your environment is the key to having a clear understanding of your customer’s journey.
What about maturity in experimentation?
Experimentation and testing, techniques that are very accurate in assessing the performance of your campaigns’ effects, have gained more strength. However, it is very costly in terms of time and money, as it requires raising hypotheses, designing experiments, aligning teams, measuring results and carrying out new iterations in the process.
The rebirth of MMM
Marketing Mix Modeling is a traditional econometric technique that seeks to understand the relationships between factors such as media investment, macroeconomics, and competitors using your desired KPI. The technique was used quite strategically for decision-making at a management level by many CMOs in the past.
MMM has been gaining relevance again as it does not depend on data at the user level like MTA does, and with new theoretical implementations using Bayesian statistics it is possible to incorporate previous learnings, via experimentation for example, to evaluate and calibrate your model.
But then what is Integrated Marketing Measurement?
It corresponds to the measurement triad that every CMO wants in their marketing routine. As the name suggests, it is an integration of marketing measurement efforts with the aim of getting a complete understanding of your landscape.
Each of these techniques has strengths and weaknesses, but when worked together, they gain strength and complement each other.
- Experiments provide learnings that can be incorporated into your MMM model.
- MMM helps to evaluate the impacts of Awareness and Consideration campaigns that the MTA model does not evaluate so well.
Now the biggest challenge is to integrate this assessment routine into your day-to-day schedule. We at DP6 can help you, so let’s talk about it!
Profile of the author: André Tocci| With a Bachelor’s degree in Business Administration and a Post Graduation in Data Science, I have been working with data for more than 6 years and I love to automate everything I can using Python.
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