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Commercial Analytics – the new, cooler, faster, kid on the block

December 5, 2022


Maggie Merklin, Chief Customer Officer

 

Marketing has long been a core part of any business’s success because it builds brands, supports sales and drives consumer engagement. Measuring marketing’s impact has always been a challenge, with tools evolving over time as marketing tactics also evolved. Today however, the complexity of a marketing team’s activities is unmatched. CMOs need to balance the benefits and risks of multiple marketing activities, delivered via dozens of channels, to target a diverse customer base who vary not just in what they buy, but where, when and how they buy it. Robust, flexible measurement tools are essential to do this effectively.

 

Unfortunately, existing tools simply don’t work. The volume of data and the complexity of marketing programs mean traditional measurement tools are out of their depth. The need to assess and understand what is really happening with brands in a manner that offers both strategic and tactical insights is what drove us to create an entirely new form of marketing measurement tools and analytics, which we call Commercial Analytics.

 

An entirely new approach to marketing measurement and analysis

 

It's common knowledge that organizations understand that they have an incredible, possibly untapped, asset in the form of the data they are generating. How to make this data actionable in such a way that it drives business decision-making is the harder part. Most struggle with understanding what data is important, how to organize it, how to use it and how to transform it to empower growth.

 

At its core, Commercial Analytics is an adaptive, unified approach that empowers brands by incorporating customer, operational and touchpoint data across the entire business. We also integrate external data points as varied as economic conditions, location and consumer data. Combined, this gives us a unique view of the entire business via a single source of truth. We use this to holistically (and very quickly) review, analyze and predict the impact of marketing activities.

 

Previous marketing measurement and analysis approaches made some effort to use data in an impactful way, but did not go far enough. Marketing Mix Modelling (MMM) is popular because it takes an analytical approach to quantifying the impact of specific marketing activities. However, MMM only offers a high level satellite view and can’t adapt for the complexity of data available today.

 

25+ years ago, it might have been relatively easy to see the direct impact on sales of a TV advertising campaign, but today’s marketers are using multi-channel and omnichannel campaigns across both the in-person and online worlds. It’s an entirely new environment in which analysis needs to identify and measure the impact and ROI of specific activities. Is the streaming tv campaign more or less effective than the linear TV campaign? What is the impact of the overall brand campaign in amplifying the messaging of the online campaign? Which tools work better for in-store purchases? MMM simply cannot provide the detail needed.

 

Multi Touch Attribution (MTA), has enhanced granularity and detail because it tries to track and analyze each marketing touchpoint a consumer experiences before a sale is made. Of course, for this to work, marketers need exceptionally good data which, with changes to privacy regulations around the use of cookies and other tracking tools, and the increase in walled gardens, isn’t available. It's also limited in how it can track and ascertain the impact of non-addressable marketing channels, particularly those that take place offline. Finally, it certainly doesn’t incorporate other messages the consumer is receiving nor external non-controllable factors like economic conditions or physical location. In effect, it’s like trying to follow a stranger on a crowded city street – it’s way too easy to lose them because of distractions or because they look similar to someone else, and even if you keep them in sight, following them won’t tell you why they’re on that street or where they’re going next.

 

MMM focuses on upper funnel activities and metrics and MTA prioritizes lower-funnel activities so the next, apparently obvious, step seemed to be to merge them to get the best of both worlds. But they’re just so different it’s impossible – the metrics they use, the data they analyze, and the way they do these things are completely incompatible. In fact, trying to unify them actually compounds the weaknesses of both: MMM is a statistical economic model looking at pattern recognition to understand outcomes. MTA is a probabilistic model looking at what individual users have done and then assesses the probability of what they’d do next. They just don’t speak the same language.

 

Understanding the whole business to maximize impact

 

Commercial Analytics is the way forward by placing marketing at the center of the business in a way that was not possible before. This approach uniquely replicates the customer experience by taking a holistic view of product, sales, customer and operational data and a wide array of factors that are out of the marketer’s or the business’s control, shining a light on the effectiveness and impact of specific marketing activities.

 

By collecting data across all potential business drivers, we can quantify a wide array of factors to not only retrospectively analyze ROI of specific marketing activities but to predict the effect of other activities under a wide range of conditions. Unlike with any other marketing analytics tools, we can now answer far more of the questions that marketers need the answers to, whether those are inside or outside their business – what happens if fuel prices rise or if the consumer price index moves? Can I adapt my marketing to accommodate these trends? How does weather impact sales online and in bricks and mortar stores and how should this drive targeted pivoting in marketing tactics? Are all TV channels the same or should some be used at different times and in different ways?

 

Commercial Analytics offers a previously impossible level of granularity, giving marketers the kind of in-depth, flexible and insightful tools, they’ve always wanted but that today are essential considering the complexity and diversity of marketing campaigns and tools. Being able to identify and adapt for the myriad factors that drive customers’ decision-making drives is transformational for brands, empowering better decision making and driving long-term growth.