MMA Modernizes Marketing Mix Models


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I’ve been spending a lot of time recently looking at marketing measurement systems. This means that you, Dear Reader, will be spending a lot of time reading about them. A good place to start is Marketing Management Analytics, known to its friends as MMA.

MMA was founded in 1989 and is one of the pioneers in marketing mix modeling. Mix models remain the heart of the company’s business. But while traditional mix models look at direct correlations between advertising and sales, MMA’s current approach takes a more layered view. This includes what the company calls “multistage” attribution, which looks at intermediate touchpoints between an advertisement and the final purchase, and “customer cascade analysis”, which measures the long-term impact of advertisements on brand equity. The company has also beefed up its consulting services to help make its findings more actionable.

MMA’s foray into attribution is intriguing, since it puts the company into some degree of competition with attribution specialists like VisualIQ, Adometry, and ClearSaleing. But MMA works with aggregate data such as total spend and impressions, with a major emphasis on mass media like television. Those other vendors work primarily with data about individual buyers, which comes largely from digital and direct media. MMA’s clients are traditional mass media advertisers, in consumer packaged goods, automotive, financial services, retail, pharmaceuticals, and communications, and it is working for CMOs who are allocating budgets across channels. The other vendors’ clients are concentrated in ecommerce and they are answering more tactical questions about spending within the digital channels. What they all share is the goal of measuring the incremental impact of expenditures in specific media.

MMA recently released the latest version of its flagship software, Avista. The system is still focused on traditional marketing mix models, although it can incorporate the “multistage” approach of measuring the impact of one channel on another. The new release, Avista 8, was designed to make it easier for marketers and media planners work directly with the system, rather than relying on technical experts. The main interface displays curves that represent the relationship between spending on each tactic and final sales. Marketers use sliders to adjust the spending levels and the system then estimates the sales that would result.

Avista can also run optimization routines to automatically find the most effective spending mix. Users can limit how much spending on any one tactic can increase or decrease, can create groups of tactics that draw from a shared budget, and can choose the target of the optimization (maximum profit with a given budget, minimum spend to reach a target revenue level, etc.). Outputs can show details by brand, product, region, sales channel and time period. Users can save scenarios and compare them to each other. Once they’ve chosen a scenario, Avista can convert it to a high-level media plan for buyers to execute.

The system also has a forecasting feature that runs the same models but also lets users change assumptions about factors other than marketing spend, such as weather, competitive behavior, and distribution channels. Results can be displayed on reports, which in turn can be assembled into custom dashboards.

MMA also offers its clients a data access tool called MarketView, which lets them view and lightly analyze the data assembled as model inputs. This is a popular service by itself, because model inputs often include data the marketers have never seen before. Giving them early access helps to speed the modeling process by letting them verify the quality of the data.

Republished with author's permission from original post.


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