CMOs lead organizations that collect, manage, and extract insights from vast quantities of data to inform their marketing strategy. Today, their mandate extends far beyond generating leads to proving the ROI of every marketing initiative.
The need for accurate measurement has never been greater. Yet traditional media measurement strategies such as last touch are extremely inaccurate and unreliable. This leads many marketing organizations to make the wrong decisions when it comes to allocating budget across the channels, campaigns, and tactics that drive the best performance.
What are the best approaches to garner meaningful insights and take smart action? How do marketing leaders foster change, innovation, and growth?
Modern marketing measurement and optimization solutions offer advanced ways to answer these questions. Unlike traditional methods, these solutions can quantify the effectiveness of marketing efforts by identifying the channels, tactics, and media interactions that have the greatest impact—and the ones that have the least.
Marketing Mix Modeling and Multi-Touch Attribution Meet Different Needs
Today, there are two distinctly different approaches to measurement in the marketplace: marketing mix modeling and multi-touch attribution. Both of these approaches enable marketers to make more informed decisions, and each has its own unique advantages.
Big picture: marketing mix modeling provides high-level strategic insights for budgeting and long-term planning. Multi-touch attribution offers tactical insights for short-term optimization. Each approach was designed to meet a specific purpose.
This is because marketers have different needs for information, at different speeds, based on where they sit on the team and the business challenges they are attempting to solve. When used in tandem, both measurement approaches have their place in an organization’s game plan.
Marketing Mix Modeling: Strategic Planning
Marketing mix modeling uses aggregated historical performance data on a quarterly or annual basis. It calculates the total effect that every marketing channel and its key dimensions, such as product and geography, have on sales and other performance metrics, while controlling for exogenous factors like weather and holidays that impact business performance.
Using summary-level data, marketing mix modeling provides broad recommendations for how marketers should allocate their budgets to optimize performance. In addition to high-level recommendations, this approach is also useful for understanding the effectiveness of media on non-direct performance measures, including brand affinity.
Multi-Touch Attribution: Tactical Optimization
Multi-touch attribution, on the other hand, uses granular, person-level data in near-real time.This approach incorporates data from digital (addressable) channels such as online display and paid search to measure and predict marketing performance at the most granular level, such as creative, offer, keyword, and more.
It does this by calculating the impact of every touchpoint and dimension on each key performance indicator (KPI) and producing a set of metrics that reflects the credit each channel and tactic deserves for its contribution.
Multi-touch attribution provides visibility into the path to conversion and how each user is responding to media impressions. Marketers can then use this insight to make tactical decisions – such as which keywords to bid on or which creative or call to action to use – in order to produce the best response.
Different Data at a Different Cadence
While the recommendations derived from marketing mix modeling can answer questions about the performance of particular channels (TV versus Print versus Digital) or even the sub-channel (Snapchat versus Youtube) at the macro level, it does not offer the same granularity of a multi-touch attribution model.
Another significant difference between these two approaches is the modeling frequency. Multi-touch attribution models refresh on a much faster cadence than marketing mix models—usually on a daily, weekly, or monthly basis. Daily is preferred, as it reveals the nuances of what drove each day’s conversions so you can base your optimizations on what’s happening today, versus last week or last month.
This frequency and granularity of insight enables you to pinpoint the channels and tactics that are most (or least) effective while the campaigns are still in-market. You don’t have to wait until the end of a campaign to analyze results and determine what changes to make next time.
How Two Approaches Work Together
While there isn’t a one-size-fits-all strategy for marketing measurement, any brand that relies on online and offline channels should consider both methods of analysis. Because of the distinct advantages of each approach, marketers realize the highest returns when they are used in tandem.
Marketers that have both summary-level and person-level insights gain a comprehensive view of media performance. You can identify the synergies between digital and offline channels and tactics and how they work together to drive conversions, as well as how a change made to one or more of the tactics will impact the performance of the others.
Armed with this insight, you can make a broad array of strategic and tactical decisions to maximize efficiency and effectiveness across your entire marketing portfolios.
For example, consider a brand that is running multiple campaigns across a number of online and offline channels and markets globally. Using marketing mix modeling, the brand can assess how to best allocate its budget between all of these channels globally.
With multi-touch attribution, the brand can also tactically optimize each ad group, publisher, placement, keyword (or other dimension) to maximize performance within each individual market, adjusting its strategies and campaigns on the fly.
A majority of marketing organizations today run multi-channel campaigns. By leveraging a holistic measurement approach, CMOs can enjoy a truly comprehensive view of marketing performance and enable their marketing organizations to deliver consistently better results that they cannot achieve by using either approach alone.
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