What is Marketing Mix Modelling (MMM)?
Marketing Mix Modelling (MMM) is a predictive planning and budgeting interface which is used to measure and forecast the impact of marketing activities on conversions and return on investment (ROI).
Marketing Mix Modelling looks at the performance of different marketing channels, aggregating data from a range of different sources, including cost and revenue data, external feeds, and historical customer data.
It provides visibility on the incrementality of channels, with important insights into the level of saturation, how channels interact and complement each other, and it identifies cannibalisation.
While Multi-Touch Attribution (MTA) is a powerful observational tool, Marketing Mix Modelling provides strategic insight into the broader interactions between marketing channels and external factors, allowing marketers to carry out diagnostic analysis on past campaigns and predict the success of future campaigns to boost revenue and grow ROI.
This allows marketing teams to create plans based on historical data that can provide visibility into the impact of incremental investment.
Fospha’s Marketing Mix Modelling recommendations showed online-training company AVADO how to increase their customer base by more than 29% a year, without increasing their marketing budget.
Why is Marketing Mix Modelling important?
- MMM creates a holistic view of which marketing mix is most likely to deliver results, helping marketers to understand past performance and to build data-driven strategies for the future.
- MMM allows marketers to visualise the impact external events can have on the efficacy of sales channels. By analysing factors that might play a role in conversion, marketers can see whether the success or failure of a channel is due to external conditions and anticipate the performance of future campaigns more accurately. For example, a successful campaign might fail in a different season.
- MMM provides a more ‘joined-up’ view of the interactions between channels. This is especially important for lower-funnel channels which, although they rarely lead to direct sales, often play an important part in a customer’s route to conversion. This paints a clearer picture of the effectiveness of marketing channels such as Facebook or Google, where impressions and display data are not actively shared.
Customers expect seamless brand experiences across all channels on their path to conversion, understanding how marketing channels complement each other enables marketers to build a unified strategy, providing better customer experiences.
How to implement Marketing Mix Modelling
Fospha’s MMM product is powered by a Customer Data Platform, which can integrate cost and revenue data, external data feeds, and existing customer data.
Streamlining the data-gathering process through Fospha’s existing Customer Data Platform helps businesses break down data silos, giving marketers more time to find and implement key insights instead of searching for the right data.
- Marketing Mix Modelling can be used for diagnostics on historical campaigns or to predict the success of future campaigns with results accessed through a custom dashboard for predictive planning and budgeting.
- MMM diagnostic tool shows which of the main factors affecting sales can be leveraged to optimize return on investment or reduce cost per acquisition.
- MMM predictive planning tool:
- The dashboard shows the optimal budget that should be allocated to each channel and how this spend is likely to impact on conversions.
- The tool can run simulations based on a range of external and internal factors to help marketers to plan future campaigns with data-based tools drawing on historical data.
- With Fospha’s predictive budget planner tool clients can use data to redistribute their existing marketing budget, to optimize leads and sales and direct additional spend to increase revenue.