Payback Windows and Marketing Attribution

When you start getting into marketing attribution and reporting on how marketing campaigns have influenced pipeline and deals, inevitably you’re going to start talking about payback windows. These usually come up because some over-eager campaign strategist or executive starts asking about the ROI of a campaign that just launched. There is no ROI yet, so we start talking about how it’s too early to track ROI and that we won’t be able to track ROI for a few months. Thus, the beginning of the conversation of a “payback window”.

These conversations are usually reactive in nature… reacting to that over-eager person that’s looking for early returns. So, how can you turn these into proactive conversations? Well, first, we need to define the concept of a payback window so that we can have these conversation proactively.

What’s a payback window?

Most simply, a payback window is the period of time where we would expect to start seeing payback–or return–on a marketing campaign. The window represents the start date and end date where payback is expected to happen.

Calculating the payback window

Now that we know what a payback window is… we need to figure out how to calculate the payback window. It’s a little bit tricky, but also not too tricky.

First off, you need to understand the various velocity measures in your sales cycle. There are a few key velocity measures that you need, to be able to start calculating your payback window. Let’s outline a few, and how they relate to payback windows.

• Lead Creation (LC) to Opportunity Creation (OC) – This helps us identify when the pipeline window opens
• OC to Closed Won (CW) – This helps us identify when the pipeline window closes
• LC to Closed Won (CW) – This helps us identify when the deal window opens

With the above measures, you can start defining your payback windows. So, let’s start with the pipeline window.

The pipeline window opens after x number of days, where x is equal to the median number of days from LC to OC.

The pipeline window closes after y number of days, where y is equal to the median number of days from OC to CW.

This gives you a total pipeline window of x+y days. That’s the typical amount of time that it takes for an opportunity to be created and how long an opportunity typically stays open before it’s Closed Won. That’s your pipeline window.

Now, let’s talk about your deal window.

The deal window opens after x number of days, where x is equal to the median number of days from LC to CW.

The deal window closes after y number of days, where y is equal to the number of days we think it’s appropriate for a campaign to get credit for influencing a deal. This is subjective, because not all deals close according to the average. Some go longer. It’s a conversation that needs to happen though, so that we can identify when the deal window closes.

Therefore, your deal window is equal to x+y number of days.

Now, the above is fairly simple math, but can be difficult to calculate if you don’t already know these metrics. So, at its most simple level, your payback periods are 100% based on your average sales cycles. So, there’s no magic number for payback windows… they’re unique to each organization.

If you don’t have these metrics, then you can use your best guesses and intuition to define your payback windows.

Using your Payback Windows

Now that we know how to calculate our payback windows it’s time to start using them. Here’s how we recommend using them.

It all starts with campaign planning. When you’re planning out your campaign, you need to understand who your target audience is, and where they are most likely to be in the sales process.

Is this campaign designed to generate new leads? Is it targeting current MQLs? Is it targeting people in an open opportunity? This is important because it determines how you apply your payback windows.

So, let’s say your campaign is designed to generate new leads. As part of your campaign planning process, you should have a measurement strategy, and part of that measurement strategy should include when to start measuring pipeline payback and deal payback. So, this is where your payback windows come into play. You should outline in your campaign planning process exactly when to start measuring pipeline payback and when to start measuring deal payback.

For lead gen campaigns, this is super easy… because you’re using your whole payback window for both pipeline and deals. But, for campaigns that are targeting people in different stages of the funnel, it can be trickier. But, your calculations above are still your starting point.

Let’s examine how our payback windows would be altered if we’re targeting current MQLs.

The first thing we would need to understand is how long it typically takes to go from LC to MQL. Then, we subtract that number of days from our pipeline window and our deal window. Those are our new payback windows for this type of campaign.

Use the same process to adjust for different parts of the funnel.

What’s the point?

Now that you know what payback windows are, and how to calculate and use them, what’s the point? 

Well, the point is that you now understand when to start measuring payback for a campaign. This ensures that you don’t start too early and don’t let your attribution run too long.

If you measure your campaigns too early, before your payback windows have started or ended, you could determine that a campaign isn’t performing well, when in reality, it just hasn’t had enough time to generate results. Or, similarly, if you measure your campaigns after the payback windows have closed, you could give too much credit to those campaigns.

The goal here is to find the sweet spot for how/when to measure the performance of campaigns, and then measure them during that sweet spot.

If you have any questions about payback windows, or how to generate the data that helps you calculate these, please let us know!

Thanks!!