The landscape of marketing measurement is undergoing a transformative shift. Marketing Mix Modelling (MMM), a proven methodology that has grown increasingly sophisticated due to technological advances, is set to take centre stage over the longstanding dominance of Touch Attribution.

This transition is fuelled by the fact that evolving privacy policies make touch attribution less reliable and the capabilities of next-generation MMM tools continue to grow stronger. The industry is witnessing a pivotal moment that will redefine campaign analysis and marketing investment strategy.


Marketing Mix Modelling

At its core, MMM is a statistical analysis technique that identifies the impact of multiple variables on sales. It considers numerous factors, including offline and online advertising and external influences like seasonality and weather. MMM operates on the principle that a brand’s sales funnel is influenced by a combination of these factors. This differs from touch attribution, which attributes sales to individual touchpoints, often giving 100% of the credit to the last touchpoint. For example, consider a B2B software company. The company may invest in various marketing strategies, including social media, paid search, and email marketing campaigns. Using MMM, the company can analyse the sales data and truly understand the influence of each of these marketing channels on the overall sales performance.

The MMM analysis could reveal that some of the company’s online activities had less impact on sales while offline advertising played a greater role than previously assumed. By analysing all these factors together, MMM models provide highly informative insights into the most effective marketing strategies. This then helps the company to decide how to allocate its marketing budget for optimal results.


Touch Attribution

Touch Attribution, on the other hand, focuses on attributing sales to the final touchpoint in a customer’s journey, assuming that this is the sole incentive behind a sales conversion. For instance, if a customer sees a TV ad twice, then searches for the brand online and buys the product, Touch Attribution will attribute the entire sale to search. While Touch Attribution provides marketers with uncomplicated reporting, it oversimplifies the complex interactions that drive consumer behaviour, often over attributing to the last touch point.

Today’s customers often go through various stages before a conversion. These interactions, even if they don’t directly lead to a sale, can be instrumental in building brand awareness and trust, which ultimately influence the final purchase decision.

Relying solely on Touch Attribution can lead to an insufficient understanding of the customer journey. Recognising these limitations is essential for marketers to make well-informed marketing decisions.


The Evolution of MMM

Historically, the analytical process underlying MMM was tedious and time-consuming, demanding a data science team to scrutinise marketing campaign data over many months.

Fortunately, the narrative has dramatically changed, with technological advancements pushing MMM into the forefront of marketing measurement methods. Modern analytics tools, such as machine learning algorithms and predictive modelling, can uncover complex relationships between marketing activities and outcomes, enabling marketers to analyse vast datasets more effectively. Furthermore, MMM now integrates data from various sources, including online and offline channels, CRM systems, and third-party data providers, which in turn provides a more comprehensive view of the marketing performance.

To implement MMM successfully, B2B marketers should consider gathering data from all relevant marketing channels, including but not limited to advertising spend, website traffic, email marketing, events, and lead generation. Implementation may also require expertise in statistical modelling and marketing analytics, which may help in building efficient, dynamic and reliable models.

The next generation of MMM addresses previous obstacles, reshaping how campaigns, budgets, and the holistic customer journey are evaluated across diverse media platforms. Rather than singling out a solitary touchpoint, MMM now grasps the intricacies of multiple touchpoints and their collective effect on sale outcomes. To fully understand the complexities of these touchpoints, it’s a good idea for marketers to identify all relevant touchpoints in the customer journey. These can include website visits, email interactions, webinars, conferences, and content consumption. Marketers can then use attribution models to assign credit to multiple touchpoints in a way that reflects their true influence on conversions. Another way to interpret the true influence of each touchpoint is to examine how they interact with each other. For example, how might a webinar’s impact change when it’s preceded by an email campaign? This broad approach equips marketers with real-time suggestions for optimising marketing investment across an array of platforms.

To illustrate the effectiveness of MMM, consider the case of a leading brand that experienced stagnant growth and rising costs, prompting them to seek a solution to optimise their ad spending and adapt to evolving data privacy regulations. They conducted a 13-week test using AIM (Always-On Incremental Measurement) to evaluate its impact on sales and integration with existing user acquisition workflows. During the AIM period, they achieved an 11.3% increase in average weekly sales, despite only a 0.3% rise in ad spending. The cost per acquisition (CPA) also decreased by 11.62%, indicating better targeting and higher returns on advertising spend. These results underscore AIM’s success in boosting sales and improving advertising efficiency with minimal ad spend fluctuations, highlighting its strategic significance in the company’s growth strategy.


Navigating the Transition

The legacy of Touch Attribution may cause marketers to hesitate before embracing the potential of MMM. Nevertheless, the convergence of technology and methodology offers a compelling argument for this transition. Removing previous barriers allows marketers to examine campaigns, make data-driven decisions, and develop strategies based on seeing the whole picture.

While Touch Attribution has left a lasting impression on the marketing landscape, MMM emerges as the clear path forward. The rapidity of change within the marketing realm means that choosing MMM is not just beneficial, it’s essential for staying ahead of the curve. As marketers step into this new era, equipped with real-time data and comprehensive insights, the future of marketing data is brighter than ever. The transition may require time as marketers learn a new skill, but it’s a decision that will undoubtedly redefine the trajectory of their business.

Gary is General Manager for AIM at Kochava
General Manager for AIM at Kochava | + posts

Gary is General Manager for AIM at Kochava Inc.