Product-Led Sales (PLS) AMA: Marie Gassée

Advice on everything from PQLs to sales compensation

Alexa Grabell
November 30, 2021
Product-Led Sales (PLS) AMA: Marie Gassée

Alexa, CEO of Pocus, hosts Product-Led Sales (PLS) AMAs with PLS experts to share best practices, frameworks, and insights on this emerging category. These AMAs are an opportunity to ask PLS leaders any question - ranging from hiring to sales compensation to tech stack - in a low-key, casual environment.

The PLS AMAs are for members of the product-led sales community, the go-to-place to learn, discuss, and connect with GTM leaders at product-led companies. The goal of the community is to bring together the most thoughtful and innovative GTM leaders to build the next generation of sales together.

Interested in joining? Request an invite here.

Introducing Marie

Marie is the former VP of Growth at Confluent where she led PLG & cloud self-serve, sales development (inbound & outbound motions globally), lifecycle marketing, and digital (paid, SEO, web optimization). Prior to Confluent, Marie was a sales and product leader at Box. Marie has an incredibly unique perspective as she has led sales, marketing, and product teams in PLG organizations. Marie worked alongside another one of our favorite PLS experts GC Lionetti - catch up on our conversation with him here

In this AMA, Marie discusses:

  • Sales compensation in PLG
  • Building a PLS team
  • PQLs & activation metrics

Sales compensation in PLG

Customer segmentation is key to sales compensation.

Marie mentioned that it’s much more important to think about the sales compensation framework rather than the exact percentage split between base and variable compensation in a product-led world. To be more specific, Marie mentions the importance of thinking through customer segmentation prior to jumping into compensation. Segmentation and sales compensation go hand-in-hand in a PLG world.

Companies must decide where to segment between self-serve and sales as the foundation.

This could be based on a variety of metrics including company size, dollars spent, pricing plan, etc. In product-led companies, self-serve / free trial users become a pool that the sales team can fish from. It's very important that leadership positions the self-serve business as a source of pipeline for the sales team, and not as competition. 

The idea is for more expensive resources (i.e. account executives) to be focused on the highest potential accounts. They should prioritize upselling strategic customers, focusing on enterprise expansion, not on handholding low potential customers that could be nurtured in a self-serve way. SDRs can be very effective in Product-Led Sales, both in  guiding self-serve users and collecting insights on areas of friction to feed back into the company. Marie mentioned “people don’t like talking about ‘expensive resources’... but you need to address it upfront to think through sales / marketing efficiency”.

The good, the bad, and the ugly of sales compensation

Marie enlightened us about some experiments she ran with sales compensation at Box - there were some things that worked and others that did not... 

Didn’t work: Compensating Account Executives (AEs) if they interacted with an account. AEs could game this easily and it incentivized the wrong behavior to put a ton of touches on accounts that may not have had long-term potential.

Did work: Compensating AEs if and when their account reached a set threshold in ARR ($5K at the time).

Let’s dive into why this worked…

Although this might seem overly simple, there are a number of interesting nuances. AEs have to think “will this account one day get above the $5K threshold?” - if yes, it’s worth their time, if not, the AE should leave the account in the self-serve funnel. 

So, AEs had to evaluate the account and whether there was a chance it could be a high-value customer. For example, a big company may only spend $200/year, but based on their use case and other attributes, they are likely worth an AEs time because they will get to $5K or more in the next 6 or so months.

This strategy aligned the business incentives with the AE incentives. This strategy also helped Box hire the right AEs as they should always be thinking about an account's long-term potential and rather than how to close quick deals that should have been left in self-serve.

Deploy resources like a layered cake

Deploy resources against the customer segments you identify as you go upmarket. Identify the less strategic tasks and automate them for self-serve users. Then, as you go more upmarket, get more and more strategic and personalized with outreach. 

Layers of the cake:

  1. Automated: Leverage Product and Marketing levers to create a customer journey (including onboarding, upgrading, etc) in a thoughtful and automated way. 
  2. 1:Many: Leverage low-touch teams (such as SDRs for pre-sales, digital CSMs for post-sales)  to handhold customers who need a little bit of help, perhaps with pricing questions, getting activated in the product, or with additional use cases.
  3. 1:Few: Offer your most important accounts a dedicated AE pre and post-sales to partner closely and ensure they have a highly personalized experience with the company. 

Caveat for startups

Although efficiency is always top of mind for Marie, she mentioned that all of this advice goes out of the window if you’re an early stage company. If you're at an early stage, you need to prioritize feedback loops over efficiency. So, you should put your best salespeople on deals where you can learn about the users and inform the future of the business.

For example, at Confluent in the early days, they spun up anSDR team focused solely on activating their smallest customers. This was not very efficient, but they were still figuring out the go-to-market motion, pricing, product features, onboarding, and more. So, Confluent needed SDRs to work on small accounts to capture learnings and feedback, even though they weren't necessarily resulting in large deals. Although the team did not at first generate significant revenue, they found ways to automate certain touch points, improve the experience with Confluent and ultimately make the process more efficient and  drive long-term revenue. 

Building a Product-Led Sales team


When building the Cloud SDR team at Confluent, Marie hired a different SDR profile to focus on capturing feedback, driving customer happiness, and hand-holding activation… they were not traditional enterprise SDRs

Marie identified two characteristics of being a successful Product-Led Sales SDR:

  • Technical appetite: people that were excited about the technology… a tech evangelist that wanted to geek out with developers (the end user of Confluent)
  • Customer facing desire: although these people were technical, they also had an innate desire to be customer facing and make their customers successful.

Separately, Marie mentioned they hired ex-military folks and some Flockjay graduates for the SDR teams at Confluent, and they were some of the most successful reps on the team.

Career progression

Marie excitedly mentioned that “I’m a huge fan of SDRs… they are such a fun team and they become an integral part of the company”.

SDRs can take various career paths - the “Cloud SDR”  could fit better with a Sales Engineer role than a traditional Enterprise AE career path. Marie often worked with SDRs to find the next role they could jump into. 

PLS SDRs have an advantage in that they have been both quite technical and customer facing, so many teams were willing to “give them a shot”. Some career paths that Marie has seen for SDRs:

  • Sales enablement
  • Sales engineer
  • Account executive
  • Developer advocacy
  • Product marketing
  • Customer success

PQLs & Activation Metrics

Open source software = free users in SaaS = your TAM

Marie mentions that free users in regular SaaS businesses can be thought of similarly as adopters of open-source software… and for OSS-based businesses, this can be viewed as the TAM.

Especially in open-source, if users are not adopting the open-source product, they are unlikely to buy your software (so it’s not worth spending any time on them). At Confluent, they dedicated a lot of effort in building the OSS community, and separately had teams focusing on converting OSS adopters to Confluent customers.

Marie emphasizes the importance of having a user play with your product before trying to sell. 

Through an analysis at Confluent, Marie saw that the consumption rate of accounts that started using the product before engaging with the sales team  were far higher than those that talked to the sales team first. This was her favorite metric to advocate for product-led sales. 

Identifying & tracking PQLs

Although, at the time, Box didn’t use the term PQLs, they were tracking the same metrics. There were 2 types of motions sometimes both occurring in the same account

  1. An account with many free users that the AE aggregated and took to someone higher in the organization
  2. Users starting a free trial / lower level plan, but have a high likelihood of spending a lot more

Confluent’s qualified leads depended on a number of factors, including:

  • Volume of downloads or cloud sign ups (product engagement)
  • Web engagement metrics
  • A variety of firmographic elements

Confluent came up with qualified leads through a lot of trial & error and internal feedback. They analyzed historical data and found correlation between certain metrics / attributes and conversion to paid accounts. Marie admits this was not always an easy exercise, with some misfires.

PQLs vs. Activation Metrics

The cloud activation metric at Confluent was called the “production active orgs” which was 7 straight days of data streaming through the platform. This measured that the account was using the product in a regular way. It’s important to find an activation metric unique to a company, that is a milestone that is correlated with longer term user retention.

Marie states that activation metrics are an input into PQLs. Certain features or usage thresholds (activation metrics) can be an indication that a user / account is ready to spend more or upgrade, and they should therefore be routed to sales. 

Surfacing product usage data to sales

Marie admits that she tried to do this at Box, but it did not work that well… “which is why Pocus is so dope”.

She mentioned that it’s hard to actually surface information to the sales team once you determine PQLs. For example, if you wanted to be alerted every time an account increased usage in the last 7 days, the information could be made available, but it was often hard for sales teams to find. Sales teams had to dig through various internal tools and Tableau or other visualization tools were never sticky enough for the sales teams to continue to use. AEs have a lot to do, and they don’t want to spend time digging through data when they could be talking to customers. Although growth / analytics / product teams love dashboards, it’s very hard to get in the hands of sales teams.

Key takeaways

  • Invest in your SDRs. This is a team that will pay dividends no matter what stage you are in (early stage startup or scaling). Marie made it very clear she is passionate about hiring product curious and well rounded SDRs (particularly if you have a developer tool or more technical product). Hire for the more technically curious profiles and they may go on to "graduate" beyond the sales team into roles like enablement, product marketing, and sales engineering. 
  • Spend time on customer segmentation up front. You can’t do Product-Led Sales well without understanding your customer segmentation. If you don’t understand which customer segments should be routed to sales and which should stay in self-serve, you might end up putting expensive resources on the wrong accounts. This also makes it easier to align your sales compensation and incentive structure. 
  • Don’t chase users who aren’t using your OSS technology. Especially if you're an open source product like Confluent, there is no way prospects will buy from you unless they are using the open source tool. Measure healthy open source adoption by tracking metrics like visits to the open source site, volume of meetups, and GitHub stars, etc.

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About the author
Alexa Grabell
Co-Founder & CEO at Pocus
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