The Elusive Measurement Dilemma of Sports Sponsorship ROI
For many companies, sponsorship marketing represents a major element or component of their marketing mix. This could involve significant licensing fees to have one’s brand name attached to a stadium, or for the right to be designated the “official sponsor of……, in addition to branded advertising of events and sports tournaments. Without a doubt, event and sports marketing is big business. Global sponsorship spending is projected to grow nearly 5% in 2016 to $60.2 billion (Media Agency Daily, 1/14/16).
While such large investments would seem to demand high accountability and a formal and financial ROI assessment, this has generally not been the case. In fact, the “gold standard” for “measuring incrementality” and ROI, marketing-mix models, have woefully fallen short in accurately and holistically measuring the return-on-investment to these activities.
Instead, marketers have more relied on indirect approaches to measuring sponsorship impact through various custom-survey and tracking metrics. These metrics include measures of media exposure generated, social media comments, brand awareness, awareness of brand’s sponsorship, attitudes towards the brand, and lead generation.
A Solution to the Dilemma
Despite the high stakes and investment in sponsorship marketing, sponsors are often at a loss in coming up with a viable means for measuring the ROI of these investments.
A recent study by Performance Research/IEG found that 40 percent of sponsors spend less than 1 percent of their sponsorship budgets on all of their sponsorship metrics, while more than a quarter of them spend nothing at all. This might well be a reflection of their frustration and disappointment in current measurement approaches. According to another recent study by the Association for National Advertisers (ANA) about 40% of sponsors are dissatisfied with their company’s ability to measure sponsorship and event ROI.
One of the key objectives of sponsorship marketing is to link brands to the passion and engagement that fans feel towards the sports, teams or events. It has therefore been this emotional component that has made sponsorship ROI measurement so difficult & elusive. This has often relegated sponsors to only measure aggregate awareness or recall. Such measures are a far cry and fall very short of tangible and financially-based ROI metrics.
A former colleague from a prior job introduced me to a new concept that I believe brings great promise towards actual ROI measurement for sponsorships. This approach actually uses social media as the raw material for building a more effective and predictive metric. This approach converts textual reviews (from social media or other similar textual sources) into a metric called the Semantic Engagement Index or SEITM.
What is different about this approach is that it uses a linguistics-based method for “scoring textual data”. The approach is based on the idea that it is not just words that matter, but also how customers write about brands and sports events. In other words, context is important; and the scoring algorithm recognizes and accounts for different levels of emotion (for example, “like” has a lower rating than “love”). Also, when personal pronouns are used or ownership is inferred (“My Coca-Cola” instead of “a Coca-Cola”) there is a higher score conferred due to a higher level of expressed personal engagement. By applying this to social media comments on the sport and brand, we should be able to arrive at a metric that scales customer engagement towards this sponsored sport or event.
Where we are leading this, here, is that we want to use the SEITM as an input into a marketing-mix model in order to get the full benefit and value measurement of sponsorship ROI. This makes sense because this metric can capture the engagement fans and customers have towards a sport or event. It also makes sense in that this SEITM has proven to link to and be highly correlated to brand sales across a number of different businesses, as shown below.
The client where I first applied this sponsorship ROI method was a major B-to-B services organization. Their marketing was unique in that 60% of every marketing dollar spent went towards 4 sports sponsorships, including (1) PGA Golf, (2) NASCAR, (3) NFL Football & (4) NCAA March Madness Basketball. We will call this company Alpha Corporation.
Alpha’s major objective was to come up with a better approach to measuring their substantial marketing investment and the ROI of these individual sponsorships. Facing a rather stagnant 2% year-over-year growth in their total business, Alpha was keenly interested in understanding how to better allocate their future marketing dollars towards their most productive sponsorships and marketing activities in order to recharge their business growth to a higher level of performance.
As shown below, our marketing mix model was able to demonstrate that these four sponsorship activities generated incremental sales equal to 13% of total revenu
and 64% of their total marketing-driven sales. Basketball and Football stood out with the largest impact. Overall, their sponsorship investment actually generated a positive ROI. This was in direct contrast to prior analytics and modeling efforts, which indicated that the investment was a substantial money loser. It is also interesting to note that the 13% overall sponsorship impact contrasted to just a 1% impact from all of Alpha’s sponsorship-tagged media.
The main impact of our modeling efforts, pointed towards a recommendation of how Alpha should invest its marketing funds going forward. The chart below illustrates this.
Our task was to isolate the sponsorship events with the highest ROI and which were most effective in driving enterprise growth. As shown above NFL Football was most effective in driving growth; while NCAA Basketball generated the highest net returns.
In the following year, Alpha substantially expanded its NFL investment and maintained a high level of spend behind NCAA Basketball; while cutting back spending on NASCAR. The good news is that growth accelerated from 2 to 6 percent the following year.
A New Approach to a Difficult Measurement Challenge?
After a number of years doing media mix models, and encountering a key short-coming of conventional approaches to measuring sponsorship ROI, I am very encouraged that a viable and effective solution appears to have been discovered.
Using the SEITM as a data input makes a lot of sense because it measures customer engagement both with the sport and sponsor brand. This is close to uncovering and objectively measuring the “passion” that fans feel toward a sport or event. Given the nature of what brands are trying to achieve with their sponsorship dollars, (i.e. connect their brand to the passion that fans feel toward the sport or event), I am very encouraged that this could be the solution that closes the gap.
Michael Wolfe, mjw@bottomlineanalytics.com