Many of the fastest growing SaaS teams over the last 10 yrs have leveraged the concept of the PQL (Product Qualified Lead) but they rarely talk openly about it as it’s been a material competitive advantage for their Sales teams.
What is PQL?
A product qualified lead (PQL) is a lead who has experienced meaningful value using your product through a free trial or freemium model.
As a result, PQLs are more likely to become a customer than other leads. Unlike Marketing Qualified Leads (MQLs) which base buying intent on arbitrary factors like filling in a web form, downloading content, signing up for a newsletter or having virtually place items in the shopping cart, PQLs are tied to meaningful value.
Conceptually it’s based first on monitoring the user’s behavior (actions, clicks, etc) inside your SaaS product = “What (happened)”. Actions that match a pattern indicating readiness to buy.
Then you apply the “Who (is involved)” filter to see if they fit your Ideal Customer Profile
These leads can then be prioritized immediately to the top of your Sales team’s queue because they Act and Look like custom`ers you have previously converted. With each new conversion you have more data to reverse engineer the most optimal buying process.
The much-needed middle ground
PQLs are much more powerful than MQLs
Here are 4 reasons how:
If a product sells itself, and no hand-holding is required to convert a PQL into a paying user, then the company wins a “free” customer — one with little to no labor cost involved (apart from product development costs). You yourself are probably a “free” customer of many SaaS solutions — e.g., Netflix or Amazon Instant Video, your project management platform (Asana, Basecamp, etc), your doc service (Google Drive, Dropbox Paper), and the like.
Because PQLs require little to no human touch to convert, they’re scalable in a way SQLs — which require a dedicated rep to guide the buying process — can never be.
Redpoint VC Tomasz Tunguz found that when a human touch is needed, and sales reps do make calls to PQLs, those customers “typically convert at about 25-30%.”
This may happen because of the equally useful reverse effect: when sales reps qualify leads based on product usage data, they can unqualify leads much more effectively — as Appcues did, which allowed them to concentrate their small sales team only on the accounts most likely to close.
Align the entire company
Finally, PQLs align outward-facing and inward-facing teams around the same goal: revenue.
As Tomasz Tunguz puts it:
“Typically, the product and engineering teams don’t have goals tied to revenue, which bisects a team into revenue generating components (sales and marketing) and cost centers (eng and product). Aside from potentially creating cultural challenges, this structure is less effective than it could be. PQLs pull product and engineering into the fray. Everyone in the company has the same goal.”
When you reach out to a PQL, they should have already experienced meaningful value in your product. This makes the sale easier because there’s no need to sell the user on the value of the product.
Before we learn how to identify a PQL, lets see what PQLs are NOT:
- PQLs are not people who upgrade their free plan;
- PQLs are not marketing qualified leads;
- Someone who signs up for a free trial does NOT qualify as a PQL;
First step in Identifying a PQL
To get started with PQLs you need to design an effective process of gathering data. To be able to do that you require a deep understanding of:
- Who your users are
- What they’re doing on your marketing site + inside your product
- Why they were motivated to sign up
- Which big goals they’re trying to achieve with your product
Without a clear understanding of these details, you’ll struggle to effectively personalize, segment, and craft experiences that convert trial users to paying customers.
To identify these details and begin setting up a strong PQL system, gathering and leveraging quantitative and qualitative customer data is key.
Quantitative data: trends in HOW people use your product
By collecting and leveraging quantitative customer data, you’ll be able to answer questions like:
- Are your most successful users taking certain actions, while less successful users aren’t?
- Do ideal users share common traits — goal with using your product, job title, industry, company size, stage of growth, etc?
- Which actions and traits indicate long-term usage? Which indicate high value spend?
For example, Mixmax team knows that for a new trial user to get value from the platform — and eventually upgrade — she has to do more than simply click around her account, exploring the features available to her. To get value from MixMax, she has to actually integrate at least one of those features into her daily workflow.
“What we’re looking for,” says Olof Mathé, Mixmax CEO, “Is whether a user has actually used calendaring. Have they actually set up an automated email sequence? Are they actively using any email templates? Did they co-opt into Salesforce, or set up our Slack integration?”
Beyond this first action, a new user might take additional actions that hint at greater account value — like inviting team members to join Mixmax with her.
Qualitative data: trends in WHY people use your product
By collecting and leveraging qualitative customer data, you’ll be able to answer questions like:
What was so painful about users’ old lives that pushed them to seek out a solution like yours?
- How did they discover you in their search?
- Why did they trust your product, as opposed to other options?
- What happened in their early days of use that convinced them “Yes, this is exactly what I needed”?
- What event motivated them to take out their credit card?
This knowledge allows you to perfect your communication with PQLs, so your team can be as relevant and helpful as possible. As Emmaneulle Skala says:
“NEVER offer help if it’s not needed – There’s really nothing worse than ‘fake help.’ Please do not just say ‘I see you downloaded and want to learn more about your needs.’ If you don’t have any relevant context or reason to call, then don’t! In my experience, when there is no context it means the person is likely not going to convert or they’ll reach out on their own when they are ready.”
How to identify what a PQL is for your business
Product Qualified Leads can be a competitive advantage for your business. If defined correctly, you can align your marketing and sales team, close a high percentage of free users, and understand what prevents your users from becoming successful in your product.
As prospects utilize your application, they demonstrate buying intent based on product behaviors which can include:
- Product interest
- Number of users
- Features used
- Spending patterns
- Usage patterns
- Velocity – How fast a user or team is adopting your product
If you have a good history of product data at your fingertips, try looking for what behaviors closely correlate with users becoming paying customers.
Although this process is time-intensive, you’ll be able to get a good handle on what behaviors are linked with users upgrading.
If you don’t have product data at your disposal, make sure to install a product analytics or product adoption platform to get a better handle on what behaviors link to users upgrading their accounts.
If you’re not getting into “machine learning” and complex modeling, an effective place to start is simply investigate who is logging into your product (let’s define this as “Engagement”).
Set up a system for tracking your product data
It’s elementary: You have to track product data if you want to qualify leads based on product usage. We’re not talking about an extensive audit — just focus on events that are important for setting up a new account and events that are core to your product.
Define Activation criteria for your product (and track it too!)
You don’t have a PQL until your lead gets the product set up and reaches “first value.” That’s called being “Activated.”
An exercise for you and your team to try :
Suppose you have a user (let’s call her “Sarah”) who sets up a trial so she could give your product a go. You gave her some breathing room — excellent. But how do you know when Sarah is “Activated”?
Grab a few of your team members (the more, the better) and ask them:
What are the three, four, five (maybe even six!) specific actions that allow a new account or user to experience “first value?” Is it inviting a team member? Creating a new workspace? Something that’s completely singular to your business? (Clue: If you’re an analytics tool your Activation criteria might be something like connecting data and creating a report.)
These actions are your Activation checklist. And because you’re diligently tracking product data (you are, aren’t you?), you’ll be able to track Activation progress for each of your accounts. You’ll be able to answer questions like: How many of my five Activation steps has my latest signup completed? What is the average Activation rate for this month’s signups?
Who should my sales team focus on?
Rank Activated trials by engagement
Create an engagement scoring model for your product and measure how engaged your accounts are. Compare them. Rank them. Look for trials that are not only more Activated, but also more engaged. The ones that are high on both axes are closer to being product qualified. The ones that are lower — not so much. This is how you can make a PQL spectrum. This is how your sales team can really start directing their actions intelligently.
A little tip: Creating an engagement scoring model is not a simple task. You’ll need to rank your product events based on how important they are and then keep tabs on the number of times each account uses your important features over time. Remember, “last active” and “login” are not acceptable substitutes for real engagement.
Do all of this at the account level
This is of the utmost importance. You’re a business. You sell to accounts — not just individual users. While a single user will sign-up for a trial, multiple users will work together to make the account “Activated” and engaged during the trial period. Multiple stakeholders in a company make the purchasing decision.
So track the product data not just at the user-level but also at the account-level? It’s even more so when you’re tracking PQLs. PQLs are accounts, not users. You’re selling to accounts, your leads are accounts — you need to track accounts.
How to implement PQLs across the organization?
Once you have your PQL definition, you need to put the systems in place so that all teams can play an active role in generating more PQLs. This is not a solo sport. In this section, I break down some of the key metrics each team can be responsible for.
To keep marketing aligned on driving quality signups, these are the top two metrics that need to be prioritized:
- Visitor to Sign up – Quantity Metric
- Sign up to PQL – Quality Metric
When setting up metrics for teams, I always recommend having both a quantity and a quality metric to ensure that each team isn’t sacrificing quality in order to attain the quantity metric. As you can see with marketing’s metrics, they need to prioritize the Sign up to PQL conversion rate to ensure that the signups generated are top quality.
Sales is in a unique position to help users who have experienced meaningful value in the product decide which plan is right for them and offer additional support.
The quantity metric that sales is responsible for influencing is below:
- PQL to Customer Rate – Quantity Metric
For the quality metric, there are a lot of different ways you can decide what is best for your business. Here are a couple options I’ve seen work well for B2B SaaS businesses:
- Length of contract for each user
- Average LTV per account
Regardless of what quality metric you choose, it’s important that it reflects that we’re upgrading users that become and stay as successful customers.
These metrics will help keep the product team aligned with delivering features and experiences that drive revenue. Having both a quantity and quality metric will ensure that the team is focused on driving the right kind of revenue through features.
- Sign up to PQL – Quantity Metric
- PQL to Customer – Quality Metric
Customer Success bridges the gap between helping both users and customers. As such, the team’s key metrics reflect helping users experience a meaningful outcome in the product and expanding accounts through upsells.
- Sign up to PQL Rate – Quantity Metric
- MRR Expansion Rate – Quality Metric
When it comes to monitoring the success of the free trial for the engineering team, these two metrics are helpful:
- Sign up to PQL – Quantity Metric
- PQL to Customer – Quality Metric
When engineers are responsible for key metrics that involve the product they’re building, I often find they can come up with brilliant ways to improve user adoption. If you’re a small organization, you can always start with one engineer who’s responsible for influencing these metrics and then involve more people as your organization grows.
You know everything, but what now?
Unlike the marketing qualified lead which is typically determined between the sales and marketing teams, the product qualified lead requires all teams to work together.
One of the best parts about PQLs is that it aligns teams to focus on helping the user become successful in the product.
Embracing the PQL model, will result in you having more successful users and more upgrades as a result.
It is Win-Win situation.