As customers’ conversion journeys continue to grow in complexity, one of the main challenges for marketers is to fully understand where spend is really working. Although marketers have control over some factors which affect sales, such as budget, or advertising formats, a lot of variables can be more difficult to measure, such as weather, or holidays making it difficult to provide accurate diagnostics on past campaigns and predict the impact of future ones.
What is MMM?
Marketing Mix Modelling (MMM) is a statistical analysis technique which illustrates the effectiveness of both online and offline marketing channels, across a wide range of variables. It highlights historical trends and enables marketers to prioritize spending across their most efficient channels.
Fospha’s MMM algorithm could help online-training company AVADO to increase their customer base by more than 29% a year, without increasing their marketing budget.
Unlike single-channel analysis, MMM looks at the performance of different marketing channels in a wider context, aggregating data from a range of different sources, including cost and revenue information, external data feeds (relevant to the client’s business), and historical consumer figures. It also provides visibility on the incrementality of different channels, with important insights into the level of saturation helping to predict the potential outcome of further spend.
The predictive capabilities of MMM also enable marketers to integrate data-driven decision making into their future campaigns. The significance of replacing human-led decision making with data-driven machine-learning is that advanced algorithms provide a far more holistic view of how marketing channels complement one another, and external factors can be used to boost revenue. They also, unlike humans, improve in accuracy with each new ingest of information.
Why is aggregated analysis important?
As opposed to attributing sales success to singular channels (which might seem most successful), MMM creates a more 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.
External events can have a massive impact 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 also paints a clearer picture of the effectiveness of marketing channels such as Facebook or Google, where impressions and display data are not actively shared.
With most customers expecting a seamless brand experience on their journey to conversion, an understanding of how marketing channels complement each other enables marketers to build a unified strategy, providing better customer experiences.
How to implement MMM into your marketing strategy
According to The Forrester Wave: Marketing Measurement and Optimization Solutions, Q2 2018, most marketers find combining and analysing data from a diverse range of sources, in a variety of formats, to be one of their biggest challenges. Fospha’s MMM product works seamlessly with their existing customer data platform, integrating consumer figures, cost and revenue information, and external data feeds relevant to the client’s business.
Homogenizing the data-gathering process through Fospha’s existing Customer Data Platform helps businesses to break down data silos, giving marketers more time to find and implement key insights instead of searching for the right data.
Once this data has been ingested, the product can be used to carry out diagnostics on historical campaigns or predict the success of future campaigns using Fospha’s advanced machine-learning algorithm. These results are then made available through a custom dashboard, which can be used to access raw data, perform advanced cross cuts, or use automated analytical tools.
MMM diagnostics show which of the main factors affecting sales can be leveraged to optimize return on investment or reduce cost per acquisition. The dashboard visualization shows how much budget should be spent on each marketing channel and paints a clear picture of how this spend is likely to translate into leads.
AVADO wanted to maximize leads by spreading their existing budget across specific channels, they also wanted to increase visibility on whether their sales goals were achievable.
Fospha’s MMM product predicted in real-time how a set amount of spend would translate into leads, helping AVADO to anticipate the outcome of their campaigns and to manage expectations by setting realistic targets.
This predictive planning tool can run simulations based on a range of external and internal factors, expediting the transition between insight and action, helping marketers to build more future-proof campaigns.
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.