Aug 5, 2022

Aug 5, 2022



Elena Verna

Elena Verna

What are PQAs and PQLs and how to use them in product-led sales

What are PQAs and PQLs and how to use them in product-led sales



In part 2 of this guest series, learn from Elena Verna about the fundamentals of PQAs and PQLs and how to use them in your GTM motion to fuel revenue growth.

Welcome to part 2 of a three blog series I'm partnering on with Endgame to help PLG companies better understand what product-led sales is and how they can incorporate it into their growth strategy.

Part 2 is all about PQAs and PQLs, but be sure to check out the entire series including:

  • Part 1:The difference between traditional enterprise sales and product-led sales

  • Part 2: What are PQAs and PQLs and how to use them in product-led sales

  • Part 3: How to know your PLG company is ready for product-led sales

Building a PQA and PQL Framework

Product-led sales is the evolution of Enterprise sales, leveraging Product-Led growth and end-user love/need to drive a more efficient and competitively defensible enterprise close. PQAs and PQLs are critical tools in that process and help PLG companies identify the right leads and accounts.

The first step to building a playbook for PQAs and PQLs is to understand the 3 types of customers in a PLG business.

Basic Customers

If you have freemium or trial acquisition, basic free users will not be the candidates for your monetization model. These customers often use your product for personal needs or try it out before they put their work email on the line. There is a lot of strategic value in having a thriving base of free basic customers, including:

  • Landing users early in their journey, growing with them to reach monetization potential

  • Engaging basic customers in viral or user-generated content flows, driving indirect monetization by monetizing users they acquire for you.

  • Capturing adjacent users to inform future monetization model use case expansion

  • Build network effects, where free usage increases value prop for paid users (hello LinkedIn)

In B2B companies, the easiest way to identify the basic users at the time of the acquisition event is to look at the email domain they used for the account creation: If customers put in their webmail email (i.e., they are likely not here for work reasons or are not ready to reveal their place of work. Capturing their use case within onboarding (i.e. work, personal, looking around) can be a great way to augment basic characteristics. Bottom line, you should not see or expect paid conversion happening from this segment.

Relevant Accounts

New relevant accounts are prime subjects for your monetization model. You will measure free to paid conversion rates on the relevant accounts only. Paid conversion events can be either self-serve or sales-assisted.  Relevant accounts are likely using their work email or have indicated in the onboarding that they are here representing their company.

ICP Relevant Accounts

The subset (not all!) of relevant accounts will interest your sales team by fitting the ICP (Ideal Customer Profile) criteria. ICP is often defined by a company’s segment, such as

  • SMB (1-200 employees)

  • Mid-Market (201-1000 employees)

  • Enterprise (1001+ employees)

Most ICP criteria are set in the Mid-Market and Enterprise segments, optimizing SMB for self-serve monetization (without sales involvement). ICP is set to indicate that the company is the target segment for sales team monetization offering and can bear minimum ACV (Average Contract Value), aka sales floor.

ICP accounts are the foundation for product-qualified accounts (PQAs). The goal for ICP-relevant accounts is sales-assisted monetization to maximize revenue and penetration.

"If you have performance paid marketing, they should only be oriented at driving relevant or ICP sign-ups!" - Elena Verna

What are Product Qualified Accounts (PQAs) and how do you use them?

PQAs or Product Qualified Accounts are the subsets of self-serve sign-ups that fit your ICP and have a strong product signal. PQA is ultimately about timing and knowing when sales should reach out based on a combination of product signals, including

  • Usage volume

  • The breadth of feature usage

  • The velocity of usage (i.e. big influx of new users)

  • Behavioral components (i.e. visiting ToS pages)

PQA may look like a simple score, say 1-100, which predicts the propensity of the account to materialize into a sales opportunity. The higher the score, the higher the chances of successful pipeline creation. Set the threshold of PQA where the account is a prime time target for sales (i.e. score of 80+). Ideally, it is calculated daily, giving sales hot-off-the-press information about the account's readiness to engage in the conversation.

If the account is scoring above PQA threshold, optimize for quick response times for your sales organization to reach out to hand-raisers (15 min or less!) or do manual outreach to the account within the same day.  Use the reasons for PQA score as your primary opening line (i.e. we’ve noticed an influx of new sign-ups in your team!) to make the conversation relevant. If you don’t close at first, sales should next reach out when PQA exceeds the threshold again.

PQAs are not static

Because product signal is a component of determining PQAs, PQAs are not a gate you pass through. Rather they are continuous scores and moments in time that sales need to seize to convert an ICP account into sales revenue.

How often to evolve your PQA model

Revenue teams should rotate the PQA model to create as much predictability in the sales purchase process as possible using qualitative feedback from reps and quantitative analysis of their pipeline and user base.

To do so, you should evolve the PQA model – not the ICP. ICP is determined by product-market fit and should be static. The way PQAs are calculated, on the other hand, does change. Sometimes you get false positives or hear from sales loopback that a PQA was a dead lead and changes need to be made to account for that.

Depending on the length of your sales cycle, you should think about iterating on your PQA model 1-2x per year. Shorter sales cycles (e.g. under 3 months) can tolerate more pressure testing, but longer sales cycles require more burn-in time to understand the changes impacted.

Keep your expectations realistic. It took Miro 12-18 months before we arrived at a PQA definition we were happy with.

What are Product Qualified Leads (PQLs) and how do you use them?

PQLs, or Product Qualified Leads, are the people within PQA’s that have buying power. The biggest mistake companies make is assuming that users are ready to talk to sales just because they are engaged with the product. This isn’t always the case; even those willing to talk to sales don’t always have the buying power.

Early success doesn’t mean long-term growth

Some PLG companies see early success with PQLs, and it feels amazing – you talk to a buyer immediately, they already use the product, and they are ready to purchase. But as you move upstream, this approach starts to break down, and you find yourself with a PQA that does not have a PQL’s. This is essentially a lame duck in your user base that cannot purchase even though they may want to.

Marketing plays a role in finding new PQLs

There’s enormous value in marketing in helping sales hunt for enterprise buyers. The right playbook is to connect enterprise buyers to existing product usage instead of selling them on transformation in the field.

The hand-raisers within PQAs are likely going to be your first PQLs, but you can’t grow them at an exponential rate. Hand-raisers are the people who submit a sales form, e.g. demo request. So it’s critical that marketing plays a role in uncovering PQLs and finding enterprise buyers to continue driving revenue.

Elena Verna is a Head of Growth at Amplitude, Growth Advisor to companies including Krisp, MongoDB, and Maze, and a Board Member at Netlify. She is also a former CMO & Advisor at Miro, SVP for Product & Growth at Malwarebytes, and SVP at SurveyMonkey. Elena has a breadth of experience in PLG models for B2B companies.

Automate your account research and planning with AI

Legal & security

© 2024 Endgame

Legal & security

© 2024 Endgame

Legal & security

© 2024 Endgame