Measuring the success of any specific marketing communications channel in isolation is tough to say the least, but there’s at least one type of measurement that has taxed our own industry’s biggest brains.
How do you measure experiential marketing with any certainty of success, especially when you’re trying to calculate the ROI of a brand experience campaign? It’s an important question. As the CAANZ Marcomms Leadership Group identified in 2011, measurement must assess impact, understanding, be forward focused and – no matter what – measurement must happen.
Part of the problem is that so far no one’s developed a single methodology or algorithm which allows results to be incontrovertibly calculated, making it difficult to prove to clients that they are receiving value and results in return for their experiential investment. This is a challenge that we have faced in the experiential marketing industry for a long time but seems to be coming to prominence now. According to the IDM, 79% of experiential marketers worldwide see problems with measuring and/or demonstrating ROI as their biggest hurdle.
At smp, we’ve developed a way that allows us to measure and prove ROI to our clients. Even more importantly, perhaps, our process combines our past experience and evaluations, industry statistics and client data to predict how well any given experiential campaign will return on investment prior to embarking on the project. In this way, our clients not only know whether their investment has paid off, it allows them to decide whether they should commit to the activity in the first place
Our model revealed
Our ROI model relies on three key sets of inputs:
- Client financial data
- Predicted on-the-day results
- Expected post-activity behaviour
No ROI model can be accurate without a client’s input. Knowing the annual weight of purchase from a consumer and the average profit per product sold are priorities, while looking at ROI over a period of longer than 1 year to assess lifetime value relies heavily on the availability of retention rates. These figures allow us to calculate the value of those that we convert through an experiential campaign.
Our spectrum of engagement model enables us to fine-tune our results by looking at how and where shoppers will interact with the campaign and to predict the number of people who will interact at each stage. Common sense would suggest that, the more deeply they engage, the higher the likely conversion rate. For example, someone who comes onto a stand, speaks with an ambassador, receives a demo, receives a sample and enters a competition, is far more likely to go on to buy the product than someone who just takes a sample and walks away.
Collecting data at every touch point that we can enables us to follow-up with those that engage and find out important facts such as whether they went on to buy, how many friends they told about the campaign/product and how highly they rated the activity for engagement. All of these figures enable us to predict the total number of people that will be reached by the campaign and how many will convert to purchase.
Using this follow-up research post-validates our initial prediction, and also adds that element of science that will help us make the model even more accurate.
This process enables us to work collaboratively with clients to optimise the success of campaigns and it’s a process that you could find invaluable when you’re considering your next experiential marketing activity – not least because it could ensure that your budget is allocated in the most effective way.
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