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Demand Generation Measurements that Matter with SiriusDecisions’ Jen Horton

Jen Horton

In a sea of demand generation metrics and measurements, how do you know which are critical to success – and which will just get in the way?

We spent some time with Jen Horton, vice president and group director of demand services at  SiriusDecisions, to get her unique perspective on sorting out the confusion.

Arketi Group: Why does measurement matter in demand generation?

Jen Horton: First and foremost, you measure so you can prove your impact, you can get more budget, and you can demonstrate your overall effectiveness. Those are the obvious reasons. Less obvious but just as important is the notion of building a model of how demand creation works in your organization, so that the right targets can be set for different teams in terms of how they're hitting that contribution.

Many clients we talk to are still just “licking their finger and sticking it up in the air” to determine questions like how much Marketing should contribute versus how much Sales should be contributing. And the answers they’re getting are not necessarily grounded in a realistic baseline, given the markets they're selling into or the resources that they have.

To me this is why measurement is important – because when an organization has its baseline, then it can work to hit those growth and scale targets in a more realistic fashion, and it can better understand what levers to pull in order to hit those targets effectively.

The second less obvious reason for measurement is that an organization has a good baseline and measurement in place, this allows the organization not just to become "data driven," but to foster a culture of testing and optimization. Having a strong baseline encourages people to take risks, try new things, things that may be out of the norm, to see if they can create a breakthrough in performance. And if that breakthrough doesn’t arise, they can dial it back pretty quickly.

Without the discipline of looking at data on a regular basis, in many organizations the program owners or the demand creation people get trapped in the day in, day out of what they know always works because they just have to hit their number. Having a strong understanding of measurement and a baseline and level of contribution empowers the organization to be bolder and take more risks.

What are the three measurements that matter most in demand generation?

Our standard guidance to clients is to focus both on sourced and influenced, both pipeline and revenue. And a lot of organizations have a maniacal focus on marketing sourced. Many are looking at influenced as well, especially as account-based marketing has gained traction. There’s a general recognition that Sales also plays a role in demand creation. So start by understanding marketing-sourced and marketing-influenced, as well as sales-sourced and sales-influenced.

From there, we need to understand conversion efficiency and the velocity of leads moving through the lead management process. Again, these could be marketing-generated at first, or sales-generated, or channel-generated. The key is to able to isolate that and understand the dynamics of the end-to-end lead management process. 

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What red herrings should we avoid in measuring demand generation?

The first one may be obvious, but it’s worth repeating, and that is focusing only on activity and ignoring business impact. Among demand creation people, I think it’s widely understood that you must get to business impact.

There's also the notion of activity and impact measures from at a reputation and awareness perspective, as well as from a sales enablement perspective. For example, you have so many followers on your brand handle – well, that's great, but what does that mean in terms of overall sentiment, or what your NPS scores are from a reputation perspective?

Similarly with sales enablement: for example, “we did the following things to get reps onboarded but what was their actual productivity in terms of quota attainment and how long it took them to get there?” You have to go beyond activity measures and look at what happened and translate that into business impact.

The other danger is focusing on measurement for the purposes of – I’m going my air quotes again – "credit." As in, "Oh, marketing gets the credit," or "Sales gets the credit," or "This effort gets the credit." That shouldn't be the spirit of what measurement is about. Measurement is about getting a handle on the efficiency and effectiveness of the things we're doing so we can take more risks, set better goals, and so on.

A third red herring is the belief in a perfect attribution model. I remind my clients that all attribution models are inherently flawed because they can't account for every possible interaction that a buyer has with your brand. No matter how granular you get, there will still be some inherent flaws. The goal is to pick an attribution model that works best for the things you're doing – for your sales cycle, for your business – and create some degree of consistency in how you measure against that. 

If you could only measure one thing, what would it be?

Ah, it would have to be influence. I hate to say that though, because sourced and influenced are two very important sides to the story and we use them for different needs.

When we talk about demand generation, we look at all the programmatic efforts you're undertaking to identify that demand, nurture that demand, accelerate that demand – even once it's gone into pipeline. If you only look at sourced you're missing a huge part of that picture.

It also depends on the type of accounts that you're selling into. If you're selling into a small, finite universe where Sales is identifying the majority of the demand, then the efforts to support that demand and engage those buyers aren't represented clearly. Influence tells a broader story about all the different things we're doing and their impact on the pipeline and revenue story.

What’s the most cost-effective measurement in demand generation?

We tend to look at cost per qualified lead – in other words, the cost of a lead that Sales is ready to invest some time in. We consider all our programmatic investment over a period of time and what output that generated, which helps us quntify the cost efficiency for all of the things we have done to get that lead progressed to that point – the acquisition costs, the nurture investment, the tele follow-up that may be involved in the process. 

“The other danger is focusing on measurement for the purposes of – I’m going my air quotes again – ‘credit.’ As in, ‘Oh, marketing gets the credit,’ or ‘Sales gets the credit,’ or ‘This effort gets the credit.’ That shouldn't be the spirit of what measurement is about.”

Jen Horton, vice president and group director of demand services at SiriusDecisions

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What tools do you recommend for demand generation measurement, and why?

Well, no one does it all perfectly. For a long time, many clients were happy – and a good many still are – with what they get out of their marketing automation platforms (MAP) and salesforce automation (SFA) investments. But both systems have limitations in terms of what they can yield, so now there are many new players trying to put processes in place to support those reporting environments.

A couple of years ago, we did a survey on the state of marketing automation, and satisfaction with reporting capabilities was very low. We updated that survey this past fall, and satisfaction was way up. But we also saw that the investment in third-party reporting environments was up – 72 percent of respondents said they’re investing more in reporting capabilities.

I believe the expectations for what a MAP or an SFA should deliver in terms of reporting capabilities has decreased because people are now starting to invest in a distinct measurement layer – whether it’s a full-on business intelligence platform or they're adding in analytics tools to help piece things together. We are also seeing more companies using attribution tools and predictive platforms, because they've become comfortable with looking at data. Now they want a higher level of accuracy and get deeper insights, so they are investing in those third-party applications.

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