5 Questions Your Marketing and Sales Funnel Insights Should Answer
While most businesses can likely pull up the basics of their marketing funnel data—how many qualified leads and opportunities they create, how volume has changed over time, and even how to attribute those results to specific channels and campaigns—the majority can’t make clear decisions based on their current insights.
Funnel quantities are nice, and attribution helps to surface which activities are getting the most credit, but neither actually drive a single decision. Just as understanding how many leads you have is a great baseline (and knowing if that number is higher or lower than it was last quarter is a good start), the actual insights come from knowing how many leads you need to hit your goals and how much more to spend in each channel to hit each goal.
Joanna Fankhauser, VP of Rev Ops at Instructure told us, “Unless [your data insights are] literally driving somebody to do something they’re accountable for, [they] won’t have lasting stickiness.”
It really boils down to visibility. And most businesses struggle to quickly see if their funnel totals are good or bad. They can’t easily see what they should do more of and where they should do it or even when they should expect results. And they can’t ask new questions as their company grows because they’re stuck in the framework of their marketing and CRM software.
Let’s get into some examples of questions your marketing and sales funnel insight should answer (hint: when your data is organized in a dedicated database and you use a solution like Tableau or Power BI to visualize it, these questions are easy to answer):
Question 1: Do we need more top of funnel leads to hit our bottom of funnel targets?
Marketing funnels are far from new. In fact, most marketing funnel solutions will show you stage counts quickly. And from those it’s even easier to calculate your conversion rates. But how do you know if those numbers are accurate?
Knowing if the funnel looks good or bad still isn’t easy, even if funnels have been around a long time. It typically requires pulling data into Excel to manually create targets and report the results. But those Excel reports can become disjointed from the reporting solution you are using, making for a disjointed end-user experience.
Instead, if you use a solution like Tableau or Power BI (pulling data from a dedicated marketing data mart), you can have your targets live in a table either in the visualization tool or in your backend database. These targets can then be part of your main funnel report, allowing users to stay in your main reporting repository to understand if the quantity was good or bad.
Question 2: What content, campaigns, and/or channels should I be prioritizing?
Attribution is important. But if we’re being honest, attribution alone really doesn’t drive action. If your field marketing got 30% credit, is that good? Should you be shooting for 35%? It’s often difficult to report channel performance andspend at the same level. Getting ROI at the level of your attribution model isn’t as easy as most solutions might pitch it. (Many have tried doing this at fortune 100 companies for years and it’s never easy.)
An easier approach would be to quickly compare how a marketing activity (channel, asset, campaign, etc.) performed against the average for the category. With a comparison that allows you to quickly identify top and bottom performers, you can easily decide which activities you need to ramp up and which activities you need to slow down.
Question 3: What is progressing deals to the next stage? (Not just sourcing your funnel.)
Attribution into a funnel is table stakes, but understanding what is helping opportunities progress between stages is also important. Of course, this is a harder insight to get to when your data is siloed or your marketing reports aren’t making the cut. It’s an essential question to answer because marketing isn’t just tasked with sourcing. Marketing is tasked with creating content that progresses and closes deals.
How can you understand the performance of those assets if you’re only looking at activities that happened before your leads were created? Even more, how can you understand the performance of those assets if you’re only looking at everything that happened prior to a specific stage?
Ideally, you should be able to see what activities a prospect performed between a stage. If you structure your data correctly, you can filter it to see what content or channels have a higher conversion rate when they occur directly before a stage. Once you know this, you can segment accounts that have opportunities you need to progress to the next stage and target them with the highest performing content and channels. The ability to isolate specific actions creates easier decision making and more effective marketing.
Question 4: How long does my funnel take and what activities can speed that up?
Understanding how long it takes to get through the funnel is imperative. It allows you to set targets based on future quarter revenue goals. But it can be tricky. What should you do with opportunities that skip stages? And again, how do you know if the time through the funnel is good?
If you extract your CRM data into a data warehouse, you can easily calculate the time each opportunity takes between stages. This then becomes a metric in your visualization tool that is easy to analyze. You can look at averages, anomalies, and ranges. You can also slice it by channels and assets, helping you to know which channels might produce leads that are more ready and will close faster. It also helps you to forecast better. Knowing how many leads you have today allows you to forecast how many opportunities will be created next month or quarter.
Question 5: What customer journeys are most effective?
To me, pathing has historically felt overwhelming. There seems to be as many paths as you have contacts! Are there insights to be had here? What action would you take if you understood the paths?
When you organize your data correctly, you can start to look at pathing and then you can find some incredible insights. For example, in a specific client’s case, we restructured the marketing database and then found that two-thirds of the paths were actually a single channel. But the highest conversion rates were found from paths that had more than one channel. We recommended an adjustment to the company’s current lead scoring to score multi-touch contacts higher. And, with the new database, we identified the top performing assets and campaigns in the most popular paths, helping the client understand which content was actually converting and working the best.
Speed to insight is important. With faster insights your marketing team can spend less time trying to find your data and compiling that data into a report and more time acting on the data with data-driven decisions.
At Align BI, we’ve found that the key to getting these deeper insights is to push your marketing tech data into a data warehouse where the data relationships and logic can create quick insights that are readable, accessible, and actionable. And with this approach, the solution scales as your company grows. No more tools that lose their effectiveness when your company matures to a new level. When it’s time to answer new questions, your data warehouse is ready to meet your company’s new maturity level.
Upleveling your marketing and sales funnel insights requires the perfect balance of technical information and marketing context. With Align BI, you’ve got both.