The ultimate goal of funnel measurement within a demand marketing team is predictability: How can I take what I see and translate that into future expectations? And then, how can I take those expectations, pull a few levers, make some adjustments and beat those expectations?
For example, if you know you’ll need 3000 leads next month to hit your pipeline goals next quarter, and currently you’re only on track to deliver 2000, then you know you’ve got to add another program.
Or maybe you’re brimming with MQLs, but sales-acceptance rate is low. How do you decide whether to plan a webinar, invest in a content syndication program or redesign a process to eliminate the bottleneck happening at the marketing-to-sales hand-off?
You look at the data, pinpoint the need and act.
But before you can achieve predictability, you first must establish consistency in everything from terminology to business processes to data collection. Without consistency, your data is worse than useless – it’s misleading.
In the example above, if the sales team is inconsistent when it comes to accepting leads because they don’t all understand what an MQL is, then your MQL-to-SQL conversion rates will be all over the place for reasons completely unrelated to the quality of those leads. And your demand team could end up spinning its wheels endlessly tweaking the lead scoring formula based on bad data.
(By the way, it’s completely normal to uncover additional gaps in process or tracking as you go about building your reporting framework – many of them are impossible to see until you try to measure something else. Just keep chipping away at it. As Lena Waters will tell you on the Move to Demand Orchestration Webinar, us marketers are often building the airplane mid-flight.)
So how do you get started on this path to reliable funnel reporting?
Start with making sure the entire marketing and sales teams have a clear understanding of what each stage of your funnel represents. It’s especially critical that everyone knows what is and is not a “lead,” and what the parameters are for a “marketing qualified lead.”
I highly, highly recommend involving sales in developing these parameters, because if you don’t, they will not trust what you are sending their way.
Get marketing and sales on the same team
Marking & Sales Integration: marketers can’t just generate qualified leads and pass them over to sales and call it a day. Before you even start generating demand, you’ll need to establish SLAs (service level agreements) that define expectations for both sides of the table.
Sales must understand the terminology established in #1, and when and how they’re supposed to act at each stage of the funnel. If this doesn’t happen, you’re guaranteed to end up with a gap between MQL and SAL. Nothing will ever be done with the MQLs, and all the opportunities will be created independently of the leads marketing qualified.
Decide what’s important to measure
Every business is different, so what matters most to your executive team will vary. One of the most common needs in recent times is the ability to demonstrate marketing’s role in expanding pipeline.
Many B2B businesses find the SiriusDecisions “Demand Waterfall” framework helpful. If your team is at a higher level on the demand marketing maturity curve, this is practical but you’ll want to look at some advanced measurement tools that give you the ability to understand and predict funnel movement.
It’s quite difficult to get accurate conversion numbers manually since the buyer journey is never linear and perfect. If you don’t have access to or budget for that software, you can still gather some funnel insights with manual effort, if you have the ability and discipline to timestamp lead entries and exits at each stage.
Worksheet L in the Demand Marketing Assessment Guide and Workbook is designed to help you track at an even more basic level. In the first section of the worksheet, you’ll log the total database balance in each stage of your funnel.
This will give you a snapshot of how many people are in each stage total, regardless of how long they’ve been in that stage or how they got to that stage. The percentages demonstrate the change month-over-month, and for that reason it’s important to do this on the same date each month (or use quarters) so the timeframes are comparable.
Here you’ll want to look for consistency – meaning each part of the funnel is staying similar in proportion to each other part over time. In the screenshot example above, it looks like Leads and MQLs are inflating faster than the rest of the funnel. Could this indicate a bottleneck at the point of hand-off to sales?
The second section is where you evaluate all the new leads you generated during the previous month, and where they currently fall in the funnel.
This will give you an idea of how successful your recent efforts were at generating new, qualified leads. Here you’ll be considering whether you met your “net new” lead goals, plus also gaining an idea of the quality of those leads. Again, the percentages demonstrate the change month-over-month – they are not conversion percentages!
It’s best to use both reports side by side to get a more accurate picture. For example, you saw the number of Leads and MQLs start to inflate respective to the rest of the stages on the first report, but when you look at the second report realize that you just generated an unusual amount of highly qualified leads in May, which the sales team is likely still working through. Without the second report, it would be hard to see that the numbers return to normal in June.
As you go through this process, you could add in a 3rd chart to calculate conversion metrics if you have the ability and computing power – but it’s not as simple as #SAL/#MQL for example, because that doesn’t factor in individuals taking non-linear paths.
Also, be sure to remember that the while the SiriusDecisions conversion benchmarks can serve as a useful guide, they should not be a goal. Your processes and personnel are different, so you need to set your own conversion goals based on that.
For example, we don’t have a BDR team at Integrate, so I keep the MQL parameters tighter, resulting in a lower lead-to-MQL percentage, and higher percentages throughout the rest of the funnel.
If your team is ready to advance to a higher level of analytical requirements that includes the ability to visualize, understand and predict funnel movement, technology will be necessary.
There’s simply too much data shifting constantly between audiences, programs, teams and systems to track and analyze manually – especially since the buyer journey is never linear and perfect. Consider checking out Funnelwise, BrightFunnel, Full Circle Insights, or Bizible for these advanced reporting needs.