MIM Multiple Business Units | Is Organizational Level Optimization right for me?
Organizational Level Optimization (OLO) allows your multi-business Marketing Impact Model to produce results at both the client level and an aggregated level. What does that mean? Let's look at an example.
Example Use Case
GreenGenius is a bio-friendly furniture company that sells products to other retailers. They have three divisions: Southeastern US, Northeastern US, and the Midwest US. Each division has a Marketing Director who reports to a CMO who oversees Marketing for the entire company.
The CMO and the Aggregated Model
The CMO is having company-wide strategic conversations about the budget. She uses the aggregated model to discuss with other C-suite executives what percentage of the total budget should be allotted to marketing. For example, if GreenGenius invests x number of dollars in marketing within the company, they can expect a ballpark of y number of leads overall across all divisions.
Once the CMO establishes a budget and divides it between the three divisions, it's up to the directors to further allocate that budget.
The Directors and the Multi-Business Model
Once the directors have their budgets, they can use their division-specific model to help allocate spend across marketing channels.
FAQs
- Does this mean that all the multi-business models will add up to the aggregated model?
Not exactly. While the aggregated model is trained off the same data as the multi-business model, it does not split the data out at an individual client-level. Therefore, the aggregated model ignores the individual client-level data. It learns separately from the multi-business model, so the two do not directly interact. So while the numbers will be similar, since our models use machine learning to look at trends we cannot see with the naked eye, the aggregated data trends might vary slightly from the client-level trends. - If the numbers will vary, why should I even use the aggregated model?
There are a couple of reasons to use this aggregated model. The first is if you are new to ChannelMix, we know you are excited to receive good model results as fast as possible. This aggregated model allows us to provide you with a better model sooner rather than later after all your clients have been onboarded.
The second reason is that if the budgets of various locations are tied together, it helps provide a solution for high-level strategy, such as with the GreenGenius CMO above. Without the aggregated model, the CMO would have to run each individual model for each location and add them together to have the same conversation that could much more easily be had with the data all in one place.
In short, the two models may be for two different audiences.