When implementing advanced attribution models to better assign marketing credit across touchpoints, marketers grapple with choosing the best metrics among overabundant data points. To avoid getting overwhelmed by a sea of clickthrough rates (CTRs), impressions, likes, shares and viewthrough rates, marketers are performing metrics mapping exercises to assess the relevancy of these channel-level metrics against a larger company goal.
“There are so many different data points you can consider,” said Frank Puma, investment business lead at ad agency Mindshare. “Data will mean different things for every client, depending on what they have. But realistically, you need to focus on the key data points that matter for the job at hand.”
Finding meaningful channel-level metrics is impossible without first identifying the broader business key performance indicators (KPIs). For most companies, such goals often focus on driving greater customer lifetime value (LTV) or brand affinity. Marketers in North America cited business objectives such as customer engagement, brand loyalty and customer retention as the top metrics used to measure marketing success, according to an April 2018 poll conducted by research and advisory firm 451 Research.
But oftentimes, these larger company objectives are not so easily translated down to the channel level. As marketers adopt attribution metrics that better reflect the larger company KPIs, it’s important that they not swap one simplistic metric for another, according to Lauren Fisher, eMarketer principal analyst and author of our recent attribution report series. Instead, marketers must choose the metrics that best indicate the value of any given channel in multiple stages of the customer journey.
For example, a marketer working toward a company goal of growing customer LTV must look beyond a metric like CTR to something more indicative of revenue, Fisher said. Oftentimes, that means looking at online sales. But for companies where online accounts for a sliver of total sales, relying on this metric alone is insufficient.
In these situations, marketers need metrics that are indicative of driving in-store purchases. For example, a marketer can pair location data with paid search data to arrive at a proxy measure of foot traffic. In doing so, the marketer can better quantify search’s influence on offline sales.
“A lot of companies just take the numbers as they come in and base their investment decisions on them,” said Andreas Reiffen, CEO of retail performance ad company Crealytics. “That leads to a situation where you’re focused on driving efficiency, but based on the wrong set of numbers.”
But the process doesn’t stop at identifying the right metrics. From here, marketers must make sure they validate the importance of those metrics—and their results. For many firms switching to an advanced attribution practice, a healthy dose of skepticism about those newly-generated analytics and insights is a common byproduct. This is more pronounced when third parties analyze results. In general, a lack of trust pervades data analysis and insights among most firms, according to a January study published by MIT SMR Connections and SAS. In the poll, fewer than two-thirds of business leaders and managers worldwide trusted internally generated data, and far fewer trusted vendor-provided insights.
Jeff Greenfield, COO of attribution data cloud company C3 Metrics, said part of onboarding new clients includes equipping his team to handle doubts and criticisms about the insights they’re providing. He said it’s not uncommon for CMOs to spend months questioning results and requiring further evidence of the validity of such insights, before they can take them at face value.
“You have to have a team that can be resilient, that’s willing to get yelled at and willing for a marketer to call bulls**t on them,” Greenfield said. “These companies are using all of this for planning and every single dollar they spend across paid, owned and earned media, and they need to trust it.”
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