It’s no secret that marketing executives are feeling the heat. Budgets are down, and it’s tougher than ever to make the case that they should go up. Marketing budgets as a percent of revenue fell from 11 percent in 2020 to 6.4 percent in 2021—the lowest in Gartner’s history of tracking CMO spend—and 71 percent of B2C marketing executives say it’s very or extremely challenging to demonstrate marketing’s value to the board.
Successfully defending the marketing function requires measuring marketing effectiveness. This means accurately measuring all marketing channels in a mutually exclusive, collectively exhaustive way, increasing spending where there is marginal room for efficient growth, and cutting ineffective spending. Of course, that’s easier said than done. For businesses looking for innovative ways to measure and optimize marketing effectiveness across channels and up and down the funnel, here are five strategies that have been proven to work:
1. Bring upper funnel brand investments into play.
It is significantly harder to measure “upper funnel” marketing impact than it is to measure down-funnel direct marketing. However, we know that brand-focused messaging without a clear call to action is critical; we also know that driving awareness, consideration, and affinity are critical for long-run market share growth. In “The Long and Short of It,” Les Binet and Peter Field found that brands whose share-of-voice exceeds their share-of-market grow at a fairly predictable rate over time, while brands whose brand share-of-voice is lower than their market share shrink.
To measure brand’s impact, use a two-stage modeling approach that measures (1) brand spend’s impact on consumer attitudes, and subsequently (2), attitude’s impact on direct marketing performance and sales. The spend > attitude model can be tuned to take long-term impacts into account, making this approach superior to simply attempting to measure “brand lift” over a few weeks or months.
While it’s true that upper funnel investments take sustained effort over time to change consumer perceptions and purchase behaviors, if measured effectively, they can feed marketers’ lower funnel efforts for months or even years to come.
2. Move beyond third-party cookies.
Third-party cookies are on their way out. As governments pass GDPR-like legislation and advertising companies revert to walled gardens, the days of following consumers around the internet are clearly over. Most strikingly, Google will phase out third-party cookie support from its Chrome browser by 2023. Marketers will still be able to purchase data from Google through its Privacy Sandbox Initiative, but in the interest of security, they will only be able to get data at the cohort level (which will be very helpful for measurement, in theory.)
Instead of continuing to rely on outside sources, marketers may be better off transitioning to in-house cookies, which has benefits for accuracy and ultimately is the right thing to do from a privacy perspective. The best place to start is by investing in a syndicated or partially owned cloud system, which allows tracking of first-party data to develop consumer identity graphs—albeit with less scope than third-party cookies allow. For industries dealing in sensitive information, developing a data-clean room (virtual or physical), where data is locked and accessible only by encrypted IDs, is another best practice.
No matter how marketers gather their data from online shoppers, chances are their strategy will need to change as privacy regulations become the norm. Starting the transition to in-house now will pay off later.
3. Harness the power of earned media.
Today’s consumers turn to their friends and family for recommendations, and with the amount of information available online, it’s possible they might make a purchase without even exploring a business’s website first. One Facebook post from a user with 700 friends raving about the new bakery in town can have a bigger impact than a paid campaign because the recommendation came from an independent source they trust.
Social listening tools are a good investment to understand sentiment in earned media. Careful construction of the queries in these tools serves two purposes: first, understanding the health of brand advocacy online, and second, understanding how overall sentiment drives demand—a key input for understanding marketing’s contribution to sales.
Off-the-shelf, publicly available indices can also drive value. For instance, the University of Virginia’s hedonometer, which measures overall societal happiness driven by textual analysis of tweets, has been shown as a key predictor of overall engagement with media.
A final note: Don’t assume all earned media has to be good. While new brands can’t afford bad press as they’re establishing themselves, larger brands can find value in “steering into the skid” and making changes based on negative feedback.
4. Cut out the noise.
Consumer distraction is increasing year after year, like a kind of Moore’s law of marketing. A recent Microsoft study found consumers now have an attention span of eight seconds—one second less than a goldfish. And while it may seem like potential impressions (ad supply) are higher than ever, many of these impressions are basically junk, crammed into the side of pages or apps, or appearing in streaming video with high frequency but extremely limited reach. This environment of short attention spans coupled with low-quality and hard-to-decipher inventory makes quality reach difficult.
To succeed, “think big” and “plan small.” It’s no longer possible for most brands to achieve the kind of reach a Super B owl ad provides. Instead, invest in many publishers that reach quality audiences with quality content. Podcasts, long-form content pubs, and specific lifestyle-focused OTT are all good ideas.
Finally, double down on “CRM” content—the media that consumers have already opted into and shown interest in. While this may not broaden an audience, it can deepen consumer intimacy, and if content is good enough, word of mouth can carry opt-in to a prospective audience.
5. Think beyond proprietary technology solutions.
Hundreds of online data management solutions and marketing tech stacks have been developed over the past two decades, all claiming to help users gain a better picture of their customers’ online buying habits. However, marketing is maybe only the business discipline without any common data framework, like accounting’s FASB or operations’ ISO standards. Thus, these tools, while effective in silos, struggle to integrate, and fail at cross-channel measurement and optimization.
The reality is that marketers need to all channel their inner data engineer, and recognize that a marketing data warehouse, fed by a marketing data lake, is required to measure and manage multichannel marketing. Marketing data should be (1) comprehensive of all consumer touchpoints; (2) flexible enough to effectively monitor new channels as they come online; (3) keyed, specifically to identify a specific consumer across their marketing journey; and (4) well labeled with metadata to drive strategic insights.
Quality marketing data is necessary for MMM (marketing mix modeling) and MTA (multi-touch attribution) techniques—two complementary approaches to measure marketing effectiveness across multiple channels. Using open-source approaches to MMM and MTA allow companies to leverage their own data structure and data science teams, while leveraging expertise, packages, and libraries that grow over time.
Be Bold, but Be Smart
Today’s marketers have incredible amounts of data and amazingly effective technology to design and measure marketing, but that can be both a blessing and a curse. Analysis paralysis is a very real problem for complex marketing organizations. A rapidly changing consumer and media environment calls for bold action. Getting back to basics with clear targeting, high-quality data, and up- and down-funnel, multichannel measurement will enable clarity when making these moves in an incredibly complex technology environment.
As chief analytics officer, Andy Hasselwander leads the marketing data and analytics functions at MarketBridge, joining the firm (for the second time) in 2018. Hasselwander brings 20-plus years of marketing strategy, data science, and software development experience to the firm.
The following Andy Hasselwander from 2022 provides their research perspective. HERE
