How to Overcome the Time-to-Measurement Challenge of Measuring Marketing Performance

Marketers need to be revenue-driven. This is the message we’ve been hearing for the last few years from vendors, analysts and peers alike.

At the same time, everyone agrees that measuring marketing performance all the way to revenue impact, and then using that data to make smart and timely strategic decisions is anything but easy.

The struggle, in my mind, can be separated into two parts:

The first challenge is understanding and calculating the impact, from defining what success really means, to then connecting a bunch of campaign responses to closed-won opportunities and translating that data into meaningful insights.

This is extremely hard, both in theory and in practice.

Luckily, a whole segment of MarTech promises to solve this entire challenge for marketers, and having used a few of these tools, I believe we’re getting close… at least on the technical side.

There’s also no shortage of content on this subject, so I’m not going to look deeper into this particular issue in this post. Instead, I want us to focus on the second piece: Time-to-Measurement.

The Challenge of Time Delay in Understanding ROI

The second challenge, more prominent in complex B2B sale environment than a high-velocity B2C selling, is the time delay to fully understanding ROI.

A lead you acquire through LinkedIn Sponsored Updates promoting your ebook might spend six months being nurtured before finally requesting a demo and becoming an opportunity, and then another three months before that opportunity is closed-won.

So as much as you’d love to immediately and accurately measure the ROI of both the digital advertising and the content investments you make today, you have no way of knowing the true impact on revenue for months and even quarters after the money is spent.

The velocity of enterprise demand generation cycles is just too low to have any instant gratification from running a program. Measuring ROI is a waiting game.

So what should you do?

Your ultimate goal should be to shorten the delay between the time you make an investment and the time you can accurately, empirically measure returns.

Of course, the best way to do this is to actually increase funnel velocity and maybe get your leads to convert in four months rather than six, but that’s a huge topic on its own and I don’t want to get into it here.

Proxy Metrics in Marketing Performance Measurement

The next best thing is the use of “proxy metrics” a.k.a. “leading KPIs” to measure marketing performance.

For example, Pipeline and Opportunities is a one degree removed proxy metric for Revenue and Deals. If your sales teams has a solid track record of closing opportunities at a certain rate, you can pretty safely use Pipeline to cut the ROI measurement delay by the length of the sales cycle.

You can then measure the ROI of your ebook program in six months rather than nine. Not bad.

Of course, you need to account for the close rate to decide if the program was a success. If a $10,000 ebook leads to $10,000 in Revenue, you break even. But at a 20% close rate, you’ll need drive $50,000 in Pipeline to consider the investment recouped.

A reasonable question after looking at pipeline as a proxy metric is “?”

There are many other leading KPIs you can look at, as you move up the conversion funnel and further away from Revenue.

As much as marketers tend to diss on “leads” as a KPI, it’s nothing but a proxy metric that enables you to understand the impact of your activities sooner rather than later.

The problem is that with every degree of separation, you trade off accuracy and confidence in favour of quicker time-to-ROI.

If you choose to look at Impressions or Email Opens as proxy metrics, for example, you’ll get the instant gratification of measurement, accompanied by weird looks from other teams, and rightfully so. !

On the other hand, if you only look at Pipeline, you risk not having the agility necessary to run your marketing organization effectively.

Adding Leads into the Mix

Let’s go back to leads for a second, because they can be either incredibly useful or incredibly useless as a KPI.

The businesses that have stable, consistent processes and scoring models in place to acquire and qualify leads can rely on the “# of MQLs Generated” to predict future Revenue. Unfortunately, there are still many marketing organizations that struggle to keep the quality of their MQLs consistent over time.

One solution to this is Predictive lead scoring. The vendors in this space can use large amounts of data and machine learning to evaluate the likelihood of generating Pipeline and Revenue from any particular lead.

This can make leads a much stronger proxy metric, Without a massive amount of historic data, you might end up with an expensive model that isn’t any better at predicting conversion than what you can build in-house.

In case predictive lead scoring is not a feasible solution for your business, remember that good old-fashioned lead scoring combined with strong Marketing/SDR/Sales processes and SLAs still work to improve lead quality and consistency.

Checklist: Solving the Time-to-Measurement Challenge

There are many ways to measure marketing performance, and you’ll need to find the right one for you.

Here are a few final tips on how to approach solving this topic:

• Work with peers and leaders, both in marketing and at the corporate level to find the right approach to measuring marketing success.
• Pick KPIs together and make sure people truly understand the definitions and measurement rules around them.
• Weigh the need to be agile against your risk-tolerance. There’s a balance to be struck.
• Only tie personal compensation and incentives to metrics you can trust.

If you have any thoughts on the subject, please leave a comment! We’re all still figuring this out, so talking about it helps.

Good luck measuring your marketing performance!

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(I originally published this post on Allocadia's blog.)