Marketing Mix Modeling & Optimization FAQ

02/24/2022

Question 1: What is Marketing Mix Modeling?

Marketing Mix Modeling, also known as Media Mix Modeling— or “MMM” for short— is a statistical method for building predictive models using multi-variate regression. The models evaluate media impressions and spend, non-marketing factors such as economic conditions or other elements that move business performance more broadly, and converting activity over time to measure the contributions of each of these elements towards conversions (sales, traffic, customer acquisitions, engagement, branding impacts, etc.). These measures then allow the marketer to understand potential outcomes by evaluating different marketing investment levels or other scenarios.

Marketing Mix Modeling has been used by large brands for many decades and has historically been a means to understand how large traditional media campaigns (TV, Print, Radio) impact sales activity. MMM can be highly accurate and is a well-proven approach to marketing measurement.

Question 2: How does Marketing Mix Modeling work?

MMM uses a time series modeling approach to examine whether changes in media reach (impressions, GRPs, etc.) over time correlate with conversion changes. For a simple example, consider the case where a brand places a billboard next to the highway. The model can examine sales before the billboard and now whether sales have increased with the placement of the new billboard. If the brand takes the billboard down and sales drop accordingly, puts the billboard back up and sales increase again, the brand can be reasonably confident that the billboard is impacting sales positively— and incrementally. Marketing mix models work in the same way to see how the reach of advertising affects sales outcomes. Well-designed Marketing Mix Models also account for other factors besides media. In this case, the brand may also try to account for other factors such as the weather, traffic patterns, promotions, seasonality, holidays and day-of-week effects before confidently concluding that the media (the billboard) is the reason for changes in sales versus these other factors that may be playing a part in sales changes over time.

While this method is probabilistic in nature and does not attempt to match media consumption at individual customer levels using PII, it can provide a very accurate measure of the incremental contribution of marketing investments on many different types of outcomes. Also, Marketing Mix Modeling has a major advantage over other measurement approaches such as Multi-Touch Attribution in that it can measure both digital and traditional media as well as online and offline conversion outcomes. And because it uses no PII, it is fully privacy-safe.

Question 3: Where is Marketing Mix Modeling used?

Marketing Mix Modeling is best used when a brand wants to understand and measure the incremental contributions of their marketing, and in particular, when the brand has a mix of digital and traditional marketing channels as well as online and offline conversion points. With a more complex media mix, MMM is an ideal fit and can handle this kind of marketing complexity, and most importantly can help the brand get more performance and efficiency from their marketing budget.

Question 4: Can it be used to measure digital marketing?

Yes. Marketing Mix Modeling can be used to measure a mix of both digital and traditional media. And modern MMM solutions, like those from OptiMine, can measure digital campaigns in deep levels of detail.

Question 5: What is Marketing Optimization?

Simply put, Marketing Optimization is the method of optimizing the various parts of a marketing campaign or budget to get the most performance out of your spend.

Question 6: How does Marketing Optimization work?

More specifically, Marketing Optimization is the process of improving the marketing efforts of an organization (by optimizing the various parts of marketing campaigns) in an attempt to maximize the desired business outcomes. The optimization process works by simultaneously evaluating every marketing effort against a desired outcome and automatically considers thousands or even millions of potential decisions about campaigns, investment levels, timing, channels etc. to determine the optimal mix of investments to drive the best overall performance.

Question 7: Isn’t this just for traditional media?

No, Marketing Optimization is for both traditional and digital media. In fact, it works best with a combination of the two and best with a complex set of channels and budget considerations.

Question 8: Isn’t this just for CPG brands?

No. While CPG brands have been using these techniques for decades, modern technology and data science now makes these advanced approaches available to any brand seeking to improve its marketing performance, and at much lower costs that make these solutions more accessible than ever before.

Question 9: What are Marketing Mix Modeling strengths and weaknesses?

Strengths:

Accuracy— properly built MMM models are very accurate, especially in today’s era of privacy-driven data loss
Complete coverage of digital and traditional marketing channels
Complete measurement of online and offline conversion outcomes
The ability to estimate and measure media saturation and yield levels, which allows marketers the ability to pinpoint optimal investment levels
Advanced MMM approaches also provide scenario planning and budget optimization capabilities to allow marketers to run simulations to forecast different outcomes
MMM uses no PII

Weaknesses:

Expensive: there is a reason that only the largest brands in the world have used MMM- they can afford to cover these significant expenses as part of their large marketing and analytics budgets. Specialty MMM consulting vendors are prohibitively expensive, but modern solutions like OptiMine’s have provided sophisticated MMM solutions at lower costs making these sophisticated analytics more accessible than ever.
Slow: because traditional MMM is a manual consulting exercise, building models or changing them over time takes a significant amount of time. It is common for brands using MMM to get the measures many months after the period being measured.
Inflexible: new data, business questions, KPIs and outcomes are all part of the real-world facing marketers and brands. And all of these present challenges to traditional Media Mix Models because they all represent more manual changes, tasks, time and new costs. As a result, many MMM deployments are highly static and don’t change much because brands don’t have the resources to evolve the models over time.
Not Actionable: nearly all Marketing Mix Models use highly summarized data typically rolled up by week or by month. And because the models are built using highly manual efforts, it is nearly impossible to get deeply detailed guidance from MMM measures. As such, teams get very high-level recommendations that are frequently difficult to execute at any level of precision. This is an even bigger issue within digital marketing channels that frequently have hundreds or thousands of different campaigns, targeting elements and execution approaches, all with very different performance characteristics. These important nuances are missed completely with traditional MMM models.

Question 10: Isn’t MMM just for large enterprise brands?

With advances in AI and high-speed computing, Marketing Mix Modeling & Optimization are no longer just for larger global enterprises but are now an option for all brands that need advanced marketing measurement and optimization.

Question 11: How is OptiMine’s approach different and unique?

OptiMine’s measurement approach is 100% privacy-safe and future-proof, as it is completely unaffected by the constant stream of new consumer privacy changes (such as Apple’s iOS 14.5 or Google Topics) and state-by-state privacy regulations.

Also, OptiMine delivers high-speed solutions in a fraction of the time and delivers deep levels of detailed, actionable guidance to brands that need to make tactical short-term decisions in addition to longer term strategic budget allocations. Models are rebuilt on the fly, keeping you current with the market and ahead of your competition.

Finally, OptiMine does not rely on tracking, consumer/device identity data, or PII, which sets us apart from all other marketing measurement vendors in the industry (and, will protect you and your brand from any compliance risks).

Additionally, OptiMine has recently been named a Contender in The Forrester Wave™: Marketing Measurement & Optimization Solutions, Q1 2022. This puts OptiMine among the top 10 marketing measurement vendors in the industry—our highest scores directly indicating our platform’s agility and future-proof nature.

“References are happy with the tool’s speed, flexibility, and ease of use. And they told us that OptiMine’s fast data integration and data access is a selling point because advertisers need to maneuver data within their own environment.”

– The Forrester Wave™

To read the full report, click here.

Interested in learning about how OptiMine’s agile solution can help you and your brand? Contact us today!

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