“It is critical as a company you understand the mix of your funnels, how one funnel can feed another, and where to focus your energy,” shared Francis Brero, Co-Founder and CPO at MadKudu.
There are typically four funnels of PLG (Product-Led Growth) companies; self-serve, sales-assisted, bottom-up, and top-down.
Companies have different processes, and individuals have different affinities, making some funnels more relevant than others. For example, the self-serve funnel is less common in an industry like banking, where there is a higher degree of regulation and less chance of an individual swiping a credit card.
Knowing which funnel a user or team should go down and how to develop the right source mix is essential to driving conversions and, ultimately, revenue.
So, what are the four funnels? Here’s a deeper look.
Self-serve funnel: This funnel is usually the biggest in volume but the smallest in pipeline contribution. In this funnel, solo users adopt the product until they get enough value to swipe the credit card. The data for this funnel is hosted in a central data warehouse where analysts run cohort reports to identify bottlenecks in the onboarding process.
The sales-assisted funnel is very common in PLG companies. The idea is to deploy sales reps against heavy product users to get them to buy the product or possibly help them early on by providing a white-glove onboarding. Since this funnel involves salespeople, data is presented in the CRM so that reps can deliver personalized outreach campaigns.
The bottom-up funnel is the most advanced strategy and the most challenging on the instrumentation side. The idea here is to go beyond users to look at account-level activity. Having one person from Facebook active in your product is great, but it doesn’t mean Facebook is ready to buy your enterprise plan. Most of the customers we’ve seen run this internally have analysts put together a Tableau dashboard that displays accounts by the number of active users in the past 30 days, enabling reps to target engaged accounts.
Top-down or ABM funnel: This funnel involves defining a set of target accounts and identifying the right people to reach out to from those accounts. Companies often have a separate ABM solution to run these campaigns, and these solutions typically don’t integrate well with the data layers from the bottom-up motion.
While understanding the core of each funnel is one piece, it is essential to know how to find the right mix to scale your Product-Led business.
Hand-raisers (MQLs) typically make up most of the enterprise pipeline, around 90%. However, marketers have little control over generating hand-raisers.
We’ve seen this as a common challenge, even in leading PLG organizations. InVision was grappling with this exact challenge a few years ago.
While MQLs had the highest conversion rates, the InVision team had maxed out the value they could get from them. They had already optimized routing, prioritization, and speed to lead.
And the same thing was happening with PQLs (product qualified leads). They found that when sales reached out to product users (they were hitting a 95% SLA), they weren’t ready to sign up for an enterprise plan. The sales team was constantly hearing the objection “our company is not yet ready to upgrade to an enterprise plan.” Product users will likely never be a high percentage of the overall enterprise mix. As we said earlier, one person being very active at Facebook doesn’t mean Facebook is ready to buy.
InVision wasn’t going to be able to scale just by focusing on hand-raisers and PQLs.
Focus on active accounts.
If you can generate activity within an account and the right people to reach out to, your sales are much more likely to have a repeatable and scalable enterprise PLG motion.
InVision built a PQA (product qualified account) score that identified active accounts that had not yet raised their hand.
InVision worked with us to connect data from Segment, Salesforce, and HubSpot to build a predictive score that identified accounts ready to talk with sales based on fit and likelihood to buy. They also surface relevant signals, like the number of active users and the number of links shared, indicating why an account is qualified.
This account-centric approach enabled the InVision team to identify the 15% of target accounts that generate 90% of enterprise opportunities.
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