After spending most of their careers trawling through ambiguously useful marketing-qualified leads (MQLs), sales reps are hugely excited about a new kind of individual: the product-qualified lead (PQL).
You’ve probably seen the buzz and might be wondering why the novel-sounding PQL is being suggested as the replacement for MQLs, and perhaps even SQLs.
The problem with SQLs (despite their apparent heat) is that sales reps generally only convert around 6% of them.
Put simply, PQLs are far warmer and deeper in the sales funnel than traditional leads.
A PQL has displayed a high level of usage and appreciation for your actual product. Many companies rely on an individual’s time with your freemium or free trials for establishing PQLs, but that’s jumping the gun.
You need to outline the level of product usage that indicates a lead is seemingly ready for conversion.
As with any hyped concept, it’s important you gain a practical understanding. While there’s a loose definition for PQLs, identifying them within your funnel largely depends on your company and product-related definitions and benchmarks.
We’ll help you double down on your first set of PQLs, and how best to convert them into loyal customers with a developed business model.
The qualified quality of PQLs
The problem with traditional scoring models and definitions is that they often don’t factor in real buying intent. With the modern sales focus now on product-led growth (PLG), the PQL definition is a natural development of lead scoring definitions.
Do you know what hasn’t developed much? That’s right, MQLs and SQLs.
The “wasted potential” of MQLs and SQLs
You don’t have the sales involvement capacity to waste on anyone that won’t join your potential customers group. Unfortunately, that failed engagement strategy applies to most MQLs.
The scoring benchmarks your marketing teams use to identify MQLs often don’t translate to a sales opportunity.
Events like opened emails, downloaded white papers, courses taken, and website visits don’t factor into the product-led growth model.
None of these actions can be labeled as product engagements. They’re often a random series of steps completely isolated from your product features.
MQLs and SQLs might fit your ideal customer profile (ICP) but don’t factor in product behaviors. You could have the most impressive MQLs at hand that your product teams would happily ignore.
The sales qualification process of nurturing MQLs into SQLs is painfully slow and laborious. Only 13% of MQLs ever make that leap.
It can take months before prospective customers are ready for the sales process. In the end, you’ve got mounting customer acquisition costs and time with few wins.
Do you see where we’re going with this? PQLs have skipped this entire drawn-out sales cycle schlepp and are often on the verge of the activation process.
Focus on your already enriched leads
The beauty of a PQL is that they’ve already experienced enough product adoption goodness to be sincerely interested. Imagine having a sales conversation with someone already familiar with your types of product services and what they need from them?
Before you reach out to a PQL, or even begin scoring them accordingly, you need to nail the product actions that are most likely to convert.
You might know a software company that relies on its freemium model and tracks product usage patterns. Many businesses identify and act on their “PQLs” that have simply signed up for a free trial or jumped on their freemium model.
It’s like a cheese vendor being convinced a random passer-by that enjoyed the piece of burrata they were offered will purchase a kilogram of the smelly stuff.
PQLs might be hotter than MQLs and SQLs, but that doesn’t mean the freemium version of your product is a self-fulfilling prophecy. It would be best if you still worked hard at defining what a PQL means to you and your teams.
How to identify and activate your specific PQLs
For starters, there are three key sales metrics you need to consider when establishing your PQL scoring model:
- Customer Fit: a lead’s relevance within your ICP according to firmographic metrics
- User Engagement: the number of active users, signups, and activity level with your product
- Purchase Intent: whether a lead indicated purchasing behaviors like visiting your pricing page or actively reaching out to sales
The best practice for spotting PQLs starts with adequately defining these three parameters. That’s when your customer success or sales efforts can begin.
It all comes down to your company goals and the kind of segmentation you need.
Assign teams the right PQL
As PQLs come in all shapes and sizes, you need to identify each primary type within your funnel and who will take care of them.
Segmentation is as much about defining internal roles as it is lead criteria and behavior:
- Your Account Executives should handle ICP-friendly users or accounts that have displayed impressive product usage - your diamonds in the rough
- We recommend that SDR/BDRs handle prospects that have enthusiastically used your product but might not entirely fit your ICP. You can bounce this kind of prospect between marketing and sales until they’ve been nurtured to ICP-approval levels.
- Finally, your sales assist or customer success team can engage prospects that fit your ICP but haven’t reached the desired product usage threshold.
Let’s take the example of one of the most commonly used types of segments: the free trial user that would make an incredible customer.
A rough qualification process would begin with a prospect signing up for your free trial. Make sure that your signup form requests all the needed firmographic details.
If you find that your leads would rather not fill out hefty forms, then a simple form with an email address and company name entry will do. You can then send said prospect’s firmographic entries over to Clearbit for complete data enrichment.
Polish your PQL Diamonds
Once you have this firmographic data in hand, you can match it with your ICP. A good fit is essential, but leads need to meet your preferred usage parameters and other types of behaviors for your ideal PQL.
You can establish your most popular features by using services like Mixpanel or Amplitude. These tools collect usage data that will provide insights into your product’s most used features.
You’ll also be able to establish which success milestones users reach before converting into paid customers.
Being data-driven is essential, but your old-school tactics are valuable, too. You can call up or message your customers and establish which aspects and features of your tool they found the most beneficial.
This direct communication is a great way to learn more about valuable features that your product analytics tool might not identify as high-usage ones.
There are a lot of loose ends and opportunities to keep track of with various tools, even with a solid CRM.
This complexity is where Breyta comes in. You can integrate Clearbit, Mixpanel, and Amplitude with Breyta to consolidate all this essential CRM data.
Trim your PQLs down to a high-conversion list
Now it’s time to refine your PQLs. Remember those “three key metrics” we discussed earlier?
You can use Breyta to set your Customer Fit and User Engagement scores and filter your PQLs accordingly.
Your Customer Fit score is based on your lead’s firmographic details, screened against your ICP, like:
- The type of industry they’re in
- The amount of annual revenue their company produces
- How many employees work there
- The plan they’re currently on
Your User Engagement score is an evaluation of activities like:
- How many users are active within your product
- How many of them actually signed up
- And the most recently active users
We always recommend scoring entire accounts, as well as individual users. There might be several product-qualified users within each company you’re targeting, and so Breyta provides PQL account scoring.
“80% of your company’s future revenue will come from just 20% of your existing customers.” Gartner Group
We’ll also reveal the “Most Engaged User” in each account. Your teams can focus on and nurture this particularly active customer as a champion for your product.
Shape your PQL game plan
With the refined Breyta-forged PQL list at hand, it’s time to start working on these accounts.
You know that these PQLs are very hot, but your salespeople need pre-defined triggers. Find the product usage patterns that have a high conversion correlation.
These significant product events include:
- Major results like landing sales using your app
- When power users have hit usage limit walls
- When a particular feature has been predominantly used
Set up a notification system for when users hit these behavioral triggers through your preferred channels. Breyta will notify you via Slack and email when users or accounts pop up on your signal lists.
You can then write a well-timed personalized message or call script for a PQL that has reached these end-goal usage benchmarks. Check out this example of an engagement email from Segment:
Source: Really Good Emails
PQLs comfortably fit in your scoring
Sales teams need to focus their time and efforts on leads that are most likely to convert based on informed and calculated engagement levels. This isn’t a tall order when you consider how many resources and tools you have available today.
PQLs don’t need to replace your lead scoring goals but can fill in MQLs’ and SQLs’ gaps.
This type of lead has a far lower chance of churning due to the personalized sales assistance they receive. Leads enjoying a fantastic customer experience before they even buy a product are more likely to join the customer acquisition process.
Our guide to a highly refined PQL list also helps you remove non-starters from your customer base. Segmentation isn’t just for finding your power users. It’s also essential to isolate duds.
Take Bonjoro’s team, for example, which reduced its churn rate by 60% by focusing on the PQL model. Bonjoro not only identified its power users but realized which customer segment was churning the most.
You can enjoy personalized and intimate relationships with leads with the PQL method, achieving a comprehensive and actionable understanding of their user experience and overall customer journey.