Casey Carey is currently the Director of Adometry Marketing, Google, a platform that optimizes advertising campaigns with the most accurate marketing analytics platform, providing top agencies and advertisers remarkable results. Prior to Adometry, Carey was responsible for generating business value at several successful technology companies, most recently serving as the VP of Marketing at Monsoon Commerce. The Makegood recently spoke with Carey about measuring true performance statistics.
The Makegood: Facebook has recently been criticized as “failing marketers”. However, data suggests that Facebook impressions actually perform strongly when measured on a fully attributed basis. What does this mean, and why has the industry confused a channel issue with a measurement issue?
Without question, advertising dollars tend to follow new audiences first and then shift focus to performance once the investments reach meaningful levels—Facebook is no exception. Facebook offers an unprecedented level and unique approach to targeting which was previously not available. As a result, many marketers went into Facebook expecting better performance on LFAs (lower funnel activities) such as conversions. This is somewhat true for existing customers or those with an existing affinity for a brand, but has been less so for prospecting and acquisition marketing. The reality is Facebook typically performs well on UFA when measured on a full-funnel basis that takes into account the impact of impressions on introducing consumers to brands and ultimately, how they influence conversions. Unfortunately, that context is invisible to marketers unless they have invested in measurement methodologies capable of evaluating marketing performance holistically.
The Makegood: Adometry measures marketing performance down to the impression level. How are marketers struggling to practice modern measurement?
There are many big challenges facing measurement for modern marketers who are looking to get better clarity and insights about the performance of their marketing investments. Specifically, the challenges are:
- Data in Silos — Much, if not most, of marketing is organized and measured in silos. Marketers have done a great job of optimizing performance within each channel (email, paid search, affiliate, display), but they are unable to optimize across channels.
- Attribution Model – Most marketers, 50-60%, continue to use last-touch or other simple attribution models which arbitrarily allocates credit to marketing activities and is thus the basis for performance measurement, budget allocations and optimization. More advanced predictive and algorithmic models offer opportunities to improve the accuracy and efficacy of measure performance by considering all marketing touches (impressions and clicks) as well as converting and non-converting customer journeys.
- Device Proliferation – The advent of smartphones and tablets have multiplied the number and uses of devices across a consumers experience with a brand. Modern measurement must move beyond looking at devices and improve its ability to not only measure new devices, but also understand how these devices map to a single user.
- Offline Impacts – We are now moving beyond looking at digital as a standalone activity. The reality is offline media such as TV, print, and direct mail have direct impacts on online conversions and transactions. Similarly, digital marketing has direct and indirect impacts on offline conversions in stores, branches, dealerships, and call-centers. Bringing offline data into the measurement model provides a more holistic and complete view of what is working and what is not.
The Makegood: How is data-driven attribution designed to help brands keep pace with changing consumer behaviors and a constantly expanding media landscape?
As the media landscape expands and becomes more complex, both by adding channels and increasing interaction of consumers across those channels, marketers need new approaches to help make sense of all this complexity. Data-driven attribution models are able to look at millions of ad sequences across channels and better determine what is working and not working. Even more so, these insights and clarity go well beyond channels and can include sub-channels, tactics, campaign, offers and creatives. This level of insight across channels has previously been unavailable and opens up a whole new view of performance and reveals real opportunities for significant improvement in performance.
The Makegood: Could you elaborate on the different levels of measuring marketing performance? In other words, what performance data could you collect other than impressions?
Adding viewed, display impressions to the data provides tremendous value given its relative volume and impact on UFAs. Other considerations can include but are not limited to:
- Email impressions (opens) and clicks
- Affiliate impressions and clicks
- Video views (start, mid-points, completion)
- Social post impressions and clicks
- Direct mail (impressions)
- Paid and organic search clicks
- Direct site navigation
- External data such as seasonality, economic factors, and promotions
The Makegood: How has Adometry improved marketers reach and ROI thus far? What do you see for the future of Adometry and performance measurement?
It feels like we are entering the era of Marketing Performance Management. The reality is most marketers do not have one place to go and answer the question, “How is my marketing doing?”. Rather the answer currently exists in many channels, using many disparate metrics, with no consideration for interplay and lift between efforts. The new era is characterized by have all channels and all data in one place, advanced attribution models, user level views of performance, and a true understanding of the incremental value of each dollar spent. The markers who have begun the journey are realizing remarkable results ranging from 20%-40% improvement on ROI within specific channels and tactics, and overall across channels.
The Makegood: Thank you, Casey.