Sponsorship measurement has always been a strangely mute discussion area within the world of sponsorship – which has been largely dominated by two tropes.
It’s not helped of course that the larger agencies productize their services into standard formats – syndicated reports, global panels and dashboards such as Nielsen Fan Insights – because their business model is then predicated on showcasing their ‘proprietary’ IP and methodology. This dominance ensures that evaluation thinking is largely confined to making logical improvements within the existing parameters – and it’s pretty much the kiss of death for real innovation. And agencies which have a distinctive approach tend to … keep that distinctiveness to themselves.
Two tropes of sponsorship measurement generally cover the subject, each bizarrely at odds with each other : firstly, the assertion that sponsorship measurement is impossible and secondly, that there should be a standard methodology for all sponsorships.
Weird when you think about it.
#1 ‘Sponsorship evaluation is impossible’
This belief is based on sponsorship’s intrinsically integrated nature and the fact that sponsorship operates concurrently with other brand communications, increasing the challenge of isolating its impact. For sure, correct sales attribution can be a challenge for non FMCG products – and meaningful movements in key brand metrics can be a slow process, so it’s a tempting argument.
But if we break down the challenge, the objection shrinks.
In broad terms, sponsorship targets three areas of value: increased sales, improve brand perception and better employee engagement. There are outcomes beyond these, but most objectives are derived from these three.
Brand perception and employee engagement are both subjective measures, so we can argue about the methodology, but they can certainly be measured. Which leaves sales and sales attribution.
Ironically, sales is the only one of the three that can be directly tracked to sponsorship. Sales promotions, redemption mechanics, targeting of direct sponsorship audience … and more… all offer ways to connect sales directly to sponsorship. But that’s not the whole picture of course, because many sales channel can’t be connected in that way, and because the journey to purchase for non FMCG goods is more circuitous, especially for larger ticket items, services or B2B products. So, as direct sales attribution is impossible, how do we measure sponsorship’s impact on these?
Well, firstly there’s regression analysis, which can go a long way to isolating the impact of sponsorship. Regression analysis and marketing mix modelling produce a theoretical coefficient, so it’s not a solid, tangible, bold ROI number – but the models used for multi-variate regression analysis can be refined and evolved over time to produce a coefficient that builds internal confidence.
Another approach links to your Theory of Change or Logic Model – your understanding of how your sponsorship is going to deliver your outcomes. And particularly relevant if you use Multi-Touch Attribution modelling.
Let’s take home insurance purchase as an example. It’s an annual, distress purchase, with approximately a one month window to influence choice. Sponsorship can contribute to a number of the prerequisites : sponsorship comms can be used to identify the sales window for individual fans to sharpen targeting, and during this period it can create top of mind, deliver product messaging, generate web visits, provide tailored incentives etc.
For B2B service sales, sponsorship can generate and strengthen conversation. With one client that had recently adopted a CRM platform like Salesforce, the sponsorship was actively used to move prospects along the sales funnel, and build closer relationships at partner level.
These aren’t direct measurements of sales and they’re not claiming to determine attribution. But models can also be built on percentage fulfilment of these preconditions to sale.
#2 ‘We need a universal measurement methodology’
The second trope of sponsorship measurement is the search for the Holy Grail of sponsorship measurement – the universal methodology or metric. And here again, it’s a matter of examining the detail.
Given that sponsorship objectives vary so much, it’s clearly impossible to create a single standard measure of success. In the brand space, businesses may be targeting upper or lower funnel metrics, with different audiences.
Let’s take two notorious examples – Gazprom’s sponsorship of FIFA and BP’s sponsorship of the British Museum. In both cases, the macro-objective is obviously ‘washing’, improving corporate reputation. But each had an entirely different audience, different brand objectives and brand success metrics that weren’t directly measurable. Access to governmental, regulatory and institutional stakeholders would normally also be an objective.
So a single measure of success is impossible. What’s more, if we then look at the three outcomes of sales, brand and employee engagement, there is no single approach to measurement for any of these three.
The other way of interpreting the question is : is there a metric which is universally relevant, a single important measure of value?
For larger sponsorships, EAV was for some time the closest proxy to this. There’s a clear business opportunity to identify simple powerful metrics and Hookit has performed brilliantly in terms of positioning its ability to identify simple powerful metrics. Hookit only measures media performance, in this case social media and so, like Nielsen, it takes a black box approach to sponsorship. But by calibrating social media performance against the various forms of consumer engagement – likes, shares, memes – it’s able to provide at least an indication of sponsorship sentiment and engagement.
Incredibly useful, but it’s not the answer. We’ve posted on this before. Whether it’s the assessment of new sponsorships or the evaluation of existing ones, don’t be seduced into the single metric solution. Vendors which offer to condense data into a single score aren’t doing you any favours. They aren’t helping you to see and understand what’s happening within your sponsorship – they’re just asking you to accept a simplified view of what’s important.
We are on the same page with GMR’s Todd Fischer : ‘The best approach to sponsorships metrics, measurement and return on investment is typically grounded in a shared solution between the brand and respective agency and/or property resources. A brand’s ability to integrate proprietary sales data and consistent brand tracking methodology is a critical and non-replicable part of a holistic solution.’
The promise of AI to make it possible to understand and identify deeper predictive patterns of behaviour has still to impact sponsorship. The unique solutions which businesses such as Visa and online businesses are deploying can all take the discussion forward. There really is so much to learn. It’s about time these two tropes of sponsorship measurement fade to black.