Annalect and Omnicom Media Group companies have conducted over 300 Marketing Mix Modeling projects in the Nordic Countries every year for the past ten years. This has created a vast benchmark database on the impact different parts of the marketing mix have on sales of companies willing to invest in data driven marketing approaches to fuel their business growth.
This database can be used to not only help our clients to guide the marketing actions, but to derive industry and channel specific insights in a scale not found anywhere else in the region.
To increase the knowledge of our customers on the effectiveness of data driven marketing, we conducted a meta-analysis through over 300 modeling projects, with the focus on the impact data driven marketing mix optimization has had on marketing ROI in the short term.
What is Marketing Mix Modeling
Media mix modeling (MMM) and sales modeling – often also known as marketing ROI measurement – use historical data on marketing investments and corresponding sales results to put a number on what work, and how well. Modeling takes into account all accessible and relevant information on investments in different media, other marketing activities, and brand performance, as well as external factors such as competitor actions, the economic environment, and weather.
Once data have been collected, statistical analysis is carried out using regression techniques, supported by other analytical methods or machine learning tools if the case warrants their use. The result of the analysis process is a mathematical model of how marketing activities lead to sales results for the given business. These findings, including the ROI mechanics of different media channels and past campaigns, allow us to draw scenarios on how media, advertising campaigns, and other marketing actions should be used to get the best return for every euro invested throughout the year.
Results of the Data Driven Marketing Meta-Study
Measuring the results of over 300 marketing mix modeling projects in the Nordics allowed us derive insight not possible to have had in the region ever before. Not only could we measure average increase in marketing ROI data driven marketing mix optimization has brought, but it also allowed us to isolate and segment the effect based on the type and size of strategic and operative actions that were done together with our clients.
Our marketing mix optimization assignments can be assigned to three main categories
Based on the type of actions done as part of the marketing mix optimization and marketing mix modeling projects, we can classify the projects to three main categories:
- Significant strategic Change: 40% of our assignments dealt with implementing significant strategic changes to the marketing mix of our clients. This meant changes to the overall marketing, marketing communications or media strategy, significant changes to budgeting and/or portfolio level investment allocations.
- Activity mix optimization: 50% of our marketing mix modeling, or impact analysis, results in us recommending and helping our clients to implement small changes to budgeting allocations and focused more on optimizing the operative activity mix per brand, category or division; optimizing the timing of activities and investments inside campaigns and utilizing synergies between different parts of the marketing mix.
- Fine tuning marketing plans: 10% of our assignments derived results where only fine-tuning the existing activity mix or investment allocations was needed. These were almost predominantly companies, who had taken ROI measurement and optimization as a part of the marketing process and optimization had been done through the course of many years before the analysis period.
The Average Increase of Marketing ROI in the 1st Year After Optimization Was +18%
Based on the over 300 projects analysed in the Nordics we can see that data driven marketing has significant impact on Marketing ROI already in the short term. By taking customer data and efficiency optimisation practices into use, we see an average marketing ROI improvement of 18% in our clients during the first year alone.
The impact on ROI varied depending on the assignment type:
- Significant strategic Change: In companies where significant strategic changes were implemented and needed, the increase in marketing ROI (return on revenue) was over 25% in the first year and in some cases went upwards of +60%. Changing the role marketing had as a short-term revenue generator to a completely different level.
- Activity mix optimization: Activity Mix optimization resulted in the increase of Marketing ROI by 10% to 25%, depending a lot by client and industry, with gains of over 10% even from slight timing optimization exercises.
- Fine tuning marketing plans: Maybe the best news was, that the marketing mix optimisation process, where the short-term benchmarks are derived from, yields significant results year after year, as more granular optimisation becomes possible. In these cases the average year on year increase in Marketing ROI was 6%, varying between 4% and 10%.
The payback time for the projects could always be measured in months and in most cases in weeks.
Our results align with the results McKinsey published on a similar study in 2013. Based on their analysis of more than 250 engagements over five year, they saw that companies, which put data at the center of the marketing and sales decisions, improve their marketing return on investment (MROI/ROMI) by 15 – 20 percent.
Conclusion: Data Driven Marketing Improves results Both in Short- and Long-term, With Average Improvement of Marketing ROI +18% During the 1st Year
Our meta-study of over 300 Marketing Mix Modeling projects in the Nordic Countries during the past ten years revealed that companies can derive significant improvements to their marketing ROI and increase the company revenue significantly both in the short- and long-term by moving their marketing decision making from gut-driven to data-driven.
The level of impact to the ROI was, not surprisingly, firmly linked to the level of changes that were needed to be made to the marketing strategy and operational practices. Companies in all maturity levels of marketing benefited from optimisation, with even small changes bringing results in scale and project paying themselves back in months and in most cases in weeks.
The average return on marketing investment improved by 18% during the first year; when marketing mix decisions were based on data and recommendations from marketing mix modeling projects. More significant changes to marketing strategy and marketing mix yielding ROI improvement of over 25% and year on year optimisation in fully established data driven processes improving ROI in average by 6%. The results were in line with a similar study published by McKinsey in 2013.