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Avoiding cognitive bias in sponsorship measurement

According to research, sponsorship awareness begins to plateau after the second year of a partnership. How can sponsors continue to drive recognition and recall amongst fans and supporters beyond the initial stages of an association?

“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 within your organisation, 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?

With such significant investment involved, the company’s future and your position within it often ride on the outcome. Given that you were most likely the driving force behind last year’s campaign, and with the stakes so high, 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?

Quantitative KPIs

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 and provide a consistent readout of your campaign’s vitals at regular intervals.

Measures can involve brand impressions such as website visits and social mentions as well as marketing and sales leads such as mailing list subscriptions and fan-based special offer take-up. If your budget allows, this process should involve market research weighted to your campaign objectives.

Multiple Data Sources

In addition to retrospectively setting KPIs at the point of measurement, another common mistake 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 with their future revenue and often commissions riding on the outcome.

It is also not uncommon to see a business event, for example, overemphasise the seniority of their audience to give the impression of decision-making authority when in reality, many of the attendees may be more accurately described as Manager level.

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 upon to unconscious bias.

Competitor Benchmarking

One of the most reliable methods of eradicating cognitive bias from our evaluation and measurement process is to use the same metrics to assess our campaign and our competitors' campaigns.

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 just 1,000 impressions over the same period and invested a similar amount, 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.

Many of the 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.


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