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Sponsors Need More Data?


Sponsors can be overwhelmed with too much data


If only we knew the hair colour of the left-handed fans who watch team-sports highlights in landscape mode on their phone in bed on Sunday mornings – with breakouts by phone brand and model. Then we could REALLY make this sponsorship work.


We just need more data.


No, you don’t.


I know that opening scenario was ridiculous (if not a bit creepy) but it leans toward the crazy level of data that many are now pushing and collecting… but not really using. We live in a data-driven world and we know we can’t make decisions without it – just ask Billy Beane – but in the world of sponsorship data I’m a believer in the old adage of ‘less is more.’ Or at least it can be. Let me explain.


Do’s and Don’ts

To effectively assess the performance of a sponsorship, you’re taking a view on how well the partnership or campaign helps to move you toward your objectives.


Assuming you do this thing right, your objectives will each have KPIs, and those KPIs will typically be measurable. You know, SMART objectives and all that.


So, if you want to get a clear picture of sponsorship performance in order to make quality decisions about renewal and future activation, you need the data that corresponds to those KPIs. Seems straight forward enough.


The flip side of this obvious statement is that any data that does not directly relate to your stated and agreed KPIs is largely irrelevant to the sponsorship. In other words, you don’t need it. More importantly, you shouldn’t be paying for it.


Sometimes it’s fun to know the global TV audience of the event you sponsor, but if your objectives are confined to the domestic market, you don’t need to know it.


Similarly, we’re often drawn to engagement rates on social posts because they are seen as indicators or ‘validators’ of the quality of our content… but we have to be careful. Are 1,000 ‘likes’ on a piece of humorous content by unknown scrollers outside your target demographic really proof that your sponsorship is working? It might feel good, but probably not.


Is awareness of a sponsorship an indicator of success? Usually, but not always. I remember very clearly during the financial crisis circa 2009 that awareness of our RBS sponsorships – especially those like golf and F1 seen as ‘elite’ – was actually dragging DOWN our brand perception because it made us look wasteful and out of touch. For that reason, at one point we were paying production agencies rush fees at the last minute to take our logo OFF some assets. Crazy, but true.


F1 is often seen as an elite sport

Framework First

Now I know what you’re thinking. It’s not always that clear and easy. The art of this science is very nuanced. Yes, it is. Sometimes the route to the data you need includes other data that one might say is ‘less essential’, but it comes with the package. Some level of extra data is obviously unavoidable.


That said, when we built SponsorLab, the idea was to create clarity around this process. Establish a framework to make sure you know what you need to measure before you measure it. In other words, draw the circles around the bullseye before before you draw back the arrow.


The wrong model is to first gather all the data you can get your hands on and then try to sift through it to figure out what does and doesn’t tell you how you’re doing. If you are clear on your objectives, and you know what success looks like for each, then your data requirement becomes much clearer. Nearly crystal.


Using a framework to work through this process can initially feel like an impossible task. “How are we ever going to quantify our vision of success? So much of it is intangible!” Struggling with questions like this is not reason to avoid or abandon the process – It is even more evidence as to how essential and valuable the framework is. If you don’t work through the process and agree a scoring system at the outset, the questions don’t get any easier at the end of the sponsorship. In fact, they become more difficult and more lethal. Ouch!


Process diagram for KPIs & Performance


Bonus Benefit

Once you’ve made it through this version of ‘the process’, you’ll have a much tighter set of meaningful data points to focus on.


As one who has been on both the purchasing and selling side of sponsorship data, I honestly think this ‘less is more’ approach helps both parties to the research transaction. Research agencies don’t win by selling every possible data point for the biggest possible fee. They win by consistently helping clients use data effectively and efficiently to make meaningful strategic decisions.


So no, more data isn’t always helpful. Extra non-essential data can be interesting but also distracting. It can lead you astray. At worst you might end up putting resources into something your sponsorship was not purchased to achieve. At best you’ll waste money and time perusing irrelevant numbers.


You don’t need more data. You just need to use it better.


Are you clear on your needs?



Bruce Cook is the founder of SponsorLab - a simple yet powerful online tool to help

sponsors, agencies and rights-holders drive more impactful partnerships.



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Guest
Sep 19

!00% Agreed with Señor Brook , "Quality Data vs Quantitive Data" is more effective.

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Guest
Sep 17
Rated 5 out of 5 stars.

This article is on point, well articulated and clearly backed by experience. It's so easy to get lost in a myriad of data and not know how to track sponsorship results

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