Demand Gen Report's 2018 Marketing Measurement and Attribution Benchmark Survey makes one point abundantly clear: Measuring marketing performance is both a top priority and an ongoing challenge for most B2B marketers. Eighty-seven percent of the respondents said that measuring marketing performance is a growing priority for their company, but more than half (54%) also said their ability to measure and analyze marketing performance "needs improvement" or is "poor/inadequate."
The Demand Gen research also revealed that the two most widely-shared motivations for improving measurement capabilities are:
- The desire to show marketing's impact on pipeline and revenue (70% of survey respondents)
- The push to show ROI from all marketing investments (67%)
Both of these objectives require the use of financial metrics, and for years, the gold standard for measuring the financial performance of marketing has been return on investment (ROI). However, measuring the ROI of marketing accurately can be quite challenging.The heart of the challenge is attribution, which is the process of assigning both revenue and costs to marketing programs. It's simply not possible to calculate marketing ROI accurately unless you can accurately attribute revenue and costs.
Assigning costs to marketing activities and programs isn't always easy, but it can be done accurately using principles of activity-based costing. Revenue attribution is more difficult to do accurately because of the number of variables that must be considered and the volume of data that's required.
The two most robust methods for attributing revenue to marketing and advertising programs are marketing mix modeling (MMM) and multi-touch attribution (MTA).
Marketing Mix Modeling
Marketing mix modeling involves the application of advanced statistical techniques to estimate the impact of marketing and advertising programs on incremental sales. Marketing mix models are based on several months of historical data about sales and about marketing/advertising spending across both digital and offline channels. The models also typically incorporate factors such as weather, competitive activity, seasonality, and economic conditions.
MMM is a "top-down" approach. These models do not evaluate the actions of individual prospects or customers. Because MMM is backward-looking and doesn't consider the behavior of individual prospects and customers, it doesn't provide the timeliness or level of granularity that is required to support tactical marketing decisions.
Unlike marketing mix modeling, MTA is a "bottom-up" approach that involves the analysis of data about the behaviors of individual prospects and customers. Most MTA solutions focus on digital marketing activities, and therefore they may overstate the revenue impact of online marketing programs. MTA solutions can also produce inaccurate estimates of revenue impact because they don't usually account for a baseline of revenue that would exist without any marketing efforts.
Most robust MTA solutions use advanced statistical techniques and computer algorithms to attribute revenue to marketing activities rather than relying on simplistic, pre-set rules that often produce wildly inaccurate results.
The Best of Both?
Because of the inherent limitations of MMM and MTA, the current state-of-the-art is to use a combination of both methods. But this can raise a significant cost issue. Gartner has recently estimated that companies pay between $100,000 and $250,000 on average per year for an MMM or MTA solution. And the costs can be much higher. Therefore, these solutions will be beyond the reach of many small and mid-size B2B companies.
What to Do? Measure Influence and Impact, not ROI
The marketing measurement space is evolving rapidly, and we may soon have revenue attribution tools that produce more accurate results, and are less complex to use and less costly to acquire. But, what should B2B marketing leaders do in the meantime?
The obvious solution is to use an approach to measurement that avoids or minimizes the need for revenue attribution, while preserving the ability to make sound decisions about the marketing mix and construct a persuasive business case for the value of marketing.
The key is to use a measurement system that captures the influence and/or impact of marketing programs on important business outcomes. In a future post, I'll describe the process for building this kind of measurement model, but here are the four basic steps:
- Identify strategic business outcomes
- Identify key outcome drivers
- Link marketing programs to outcome drivers
- Measure program influence/impact on outcome drivers
This methodology will not result in an ROI calculation for individual marketing programs, but given the inherent challenges of revenue attribution, the accuracy of most marketing ROI calculations is questionable at best. This approach will enable marketing leaders to understand the impact of their activities and programs and build a compelling business case for the value of marketing to the business.
Illustration courtesy of Kari Bluff via Flickr CC.
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