Avoiding cognitive bias in sponsorship measurement
“It is an acknowledged fact that we perceive errors in the work of others more readily than in our own.” Leonardo Da Vinci.
As a sponsorship leader, the burden falls upon you to make the tough decisions. Was last year’s campaign a success? Should we renew for another year or start a new campaign with a different partner? How do you make these decisions free from cognitive bias?
With such significant investment, the company’s future and your position within it may ride on the outcome. Given that you were most likely the driving force behind last year’s campaign, it is only natural that you should want to declare the campaign a resounding success. This desire affects every marketing leader, so you are not alone; I have even seen it consume entire boardrooms. So how do we alleviate this flaw in our evaluation and decision-making process?
The importance of quantitative KPIs in measuring sponsorship is not to disregard the role of qualitative measures; both are important in forming a well-rounded view of performance. However, the cold hard facts of number-driven data points are hard to dispute even for the most avid believer.
Performance indicators must be set at the formation of the campaign as opposed to retrospectively at the point of measurement. Quantitative KPIs give a baseline of performance to measure the success upon conclusion. Such measures also provide a consistent readout of your campaign’s vitals at regular intervals.
Quantitative KPIs are the hard performance measures such as website visits, social mentions, mailing list subscriptions and sales data.
Multiple Data Sources
Another common mistake that allows cognitive bias to creep in is obtaining all data from a single or unreliable source.
The most common example occurs when the metrics used to measure performance are obtained from the event organiser. Like ourselves, these individuals have a vested interest in the perceived success of the sponsorship. In most cases, their future revenue and commissions are riding on the outcome.
For example, a business event organiser may classify a delegate with an Account Director job title as Director level. This could give the wrong impression that the event contained many decision-makers making it a success. Therefore, multiple data sources are required to alleviate the cognitive bias hidden within the stats.
Even when looking internally, we must be rigorous about how our data is collected. What exactly do we define as a positive social media mention? By failing to set the parameters at the beginning and relying on one data source, we leave ourselves open to unconscious bias.
One reliable method of eradicating cognitive bias is to assess our competitors' campaigns using the same metrics.
Data in isolation is mainly redundant when assessing the strength and performance of a sponsorship. Your activity generated 10,000 brand impressions last month. Is this good? If your fellow sponsors generated 1,000 impressions over the same period, then it would be fair to say so. However, if the competitor group averaged 100,000 impressions over the same time with equal investment, then you have a problem.
It can be challenging to obtain the more sensitive information related to the sponsorship dealings of other organisations. However, many metrics mentioned above are publicly available, and even limited data gives a better picture than no data. In some cases, and especially where there is sector exclusivity, you may find that a simple non-disclosure agreement allows you and your fellow event sponsors to share performance data for mutual benefit.
The bottom line is that while every effort can and should be made to remove cognitive bias from your sponsorship decision-making, it inevitably has a habit of creeping in without your knowledge. The most effective solution is to hire an external measurement agency or consultant to manage the process. Without the validity of a third party, you will forever be marking your own test paper. Take a look at two measurement approaches offered by external agencies in our article, Which methodology should you use to calculate sponsorship ROI and its impact on brand and business value.