One of the main challenges when calculating event return on investment (“Event ROI”) is attribution.
That is, “to what extent can we prove that this event directly led to this result?” The result might be a new client, an increase in business from an existing client, a change in behaviour within a workforce, or simply an increase in brand recognition.
Let’s take a real-life scenario: you have a marketing booth at a trade conference and scan the details of 400 delegates. Fifty of those delegates then watch your CEO’s presentation, and five of those delegates become new clients over the following 12 months.
The event led to the new business, right?
Wrong.
Your sales team indicate that they’ve already had numerous meetings with four of the new clients, and the last was someone they’d be leaving messages with for months. It’s all there on the CRM system as proof. They won the client, so you can’t claim it was the result of the marketing effort put into the conference.
So who’s right?
Well after the sales and marketing teams have had a heated debate, the outcome is usually that a combination of sales and marketing activities will have contributed to discovering and nurturing that prospective customer over the line. It’s rare, especially in B2B marketing with multiple decision makers, extensive decision making criteria, and long deal cycles, for any one action to be alone in contributing to the success.
Now we’re all friends again, how do we even start to calculate whether the ROI for the event was positive? Surely we need to know this if, as a marketing team, we’re going to make a decision on whether to do that event again next year, and how much to invest in it.
So should we say that the deal was 50% the result of marketing activity and 50% sales?
Or maybe 75% sales and 25% marketing, with 10% attributed to the event?
Now it’s getting complicated, and arbitrary.
So here’s the trick…
You don’t actually need to assign a specific attribution value to your events.
That’s right – breathe a sigh of relief. There’s absolutely no need to have any more sales and marketing attribution showdowns.
Instead, just use this template attribution calculator to review and compare multiple events, or even your entire event portfolio, on one single sheet.
So take a quick look, then we’ll explain how it works…
Going across the columns:
This is just an example for an organization interested in generating new business revenues, with a secondary metric of generating that business from new customers at events. With this information, there are all sorts of additional calculations that could be made, but we’re just keeping it simple here.
The model can be adjusted for other metrics, or other measures of return. The point is that you’re clearly recording a cost attributed to the event, and some consistent score of the desired outcome, ideally with a financial value applied to that.
* There’s always the tricky question of timing – how long should you count deals, new clients, or other outcomes after the event, and still attribute them to the event’s influence. We’ll cover this later in the ‘limitations to the model’ section.
Now for the good bit. The model does not require you to attribute a set, pre-determined, or even arbitrary contribution to the event. Instead it outputs a contribution based upon a range of attribution percentages.
In other words, it models the amount of money the event has generated for a range of different percentage attributions.
In this case, we’ve set the lowest attribution value to 0.5%. That is, the event has only contributed a tiny fraction to the deals that followed.
We’ve then set the highest attribution value to 10%. In this column we’re assuming all the events provide about 10% of the influence over the new client deals that follow. This is still very conservative.
Then we model various options in between. You’re welcome to adjust these columns, adding as many as you like, for contributions ranging from zero to 100 per cent.
Using a quick colour scale, we can see which events break-even (i.e. deliver a positive event ROI) at the various contribution levels. So events that produce a positive ROI, even when they are considered to only be contributing a small percentage to winning the deal, are better than those that never produce a positive ROI, or do so at a higher contribution level.
What’s really powerful about this approach, is that it provides a simple comparison between multiple events using the same scale.
Let’s take the example:
This is really just the start of the analysis, and additional information could be collected and added to make the data even more insightful.
For example, event feedback (through live polling onsite) could allow us to start applying delegate satisfaction score to the events, to see if there was a correlation between event ratings and subsequent new business.
And in a later post, we’ll also talk about how we can start analysing individual delegate metrics for an extensive contact-driven approach to event ROI.
A data-driven model like this can never cover all scenarios – especially when we’ve boiled down the analytics to something ultra-simple just to give a flavour of what can be done. So it’s really important we cover off some of the obvious limitations, so you can account for them when using it.
Here’s a list of the main ones – feel free to get in touch with other thoughts:
Ultimately, the model just gives you a quick visualisation from a limited data set, and from that you can start to interpret things in a meaningful way for your particular business.
We’d always recommend combining revenue metrics like this with delegate feedback metrics for a fuller picture – for more information on how you can collect better feedback and data at your events, and how technology can help you do that, click here.