PLG and Sales in 2023: How to Combine Them for Efficient Revenue Growth
Slack, circa 2016: “I think we can get away without having a sales team in any kind of traditional way probably forever.”
Slack, circa 2023: 900+ people in sales.
Well, that took a turn…
Gone are the days when it was PLG versus sales. Also gone are the days when PLG companies (over)hired sellers with a growth-at-all-costs mindset. You might not realize that PLG companies actually outspent their traditional SaaS peers on sales & marketing as a percentage of revenue as of July 2022.
Today, the new frontier is how to combine PLG and sales for efficient growth.
Over the last year I’ve had a chance to feature stories about PLG and sales from some of the top SaaS startups including Figma, ClickUp Webflow, Zapier, Supermetrics, and Hotjar. Now I’m distilling those learnings into a concrete guide to PLG and sales in 2023.
Your five step plan:
- Start with the customer journey
- Validate that sales is incremental
- Identify product signals to drive engagement
- Define the right sales plays
- Be thoughtful about comp & operations
This post recaps my keynote at Pavilion’s CRO Summit in London. Special thanks to those who provided feedback on an earlier version.
Anti-patterns to avoid
Before jumping into what to do, I wanted to start by highlighting what not to do. Here are six anti-patterns I see when SaaS companies try to combine PLG and sales motions.
1. Hide pricing and force all users to talk to sales.
2. Water down PLG offerings so they don’t “compete” with enterprise deals.
You might notice great logos who are sitting on your free plan or on a cheap self-serve plan. Sales’ instincts will be to cut away at self-service offerings and hide your pricing in order to force these high-value prospects into paying more.
This is certainly tempting, especially if the sales team is under pressure to hit this quarter’s revenue goals. But it ultimately leads to a disinvestment in PLG and subsequently a smaller and smaller pool of new prospects entering the sales pipeline.
3. Call on every new free user independent of what they’ve done in the product.
4. Over-index on commercial conversations rather than customer experience and delivering value upfront.
5. Get too greedy on the initial purchase.
PLG and sales requires patience. You’ll attract users earlier in their purchasing process, often well before they’ve generated buy-in for enterprise-wide adoption.
Rather than go for broke right away, give these folks time to find value in the product and advocate for broader adoption inside their organization. You might find that in time they’ll resurface as a Product Qualified Account that is ready to buy.
6. Only talk to existing product users rather than navigating to the buyer.
As the hype grew around Product Qualified Leads (PQLs)—that is, existing users who signal buying intent based on their product interactions—selling into PQLs became the default starting point for many PLG companies looking to add sales.
While selling into PQLs does generate quick wins for sales, the reality is that those who use your product within a large organization are generally not the same people as those who buy your product. You’ll want to work with those product users to navigate to the buyer with dedicated messaging and enablement that speaks to the buyer’s priorities.
Step 1: Start with the customer journey
Sales doesn’t have to be in conflict with product-led growth. In fact, sales reps often enhance the user’s experience by helping guide them through the buying process rather than forcing them to go it alone.
Contract size used to dictate when procurement got involved. Now even free tools may be scrutinized if important data is involved. Users need help filling out security questionnaires, navigating purchasing processes, making a business case to the CFO, and working through legal requirements for things like GDPR.
The goal of sales should be to engage with the right person at the right time in their product journey. Ask yourself: what customers need more help?
There are three typical vectors to consider:
- The size of the organization
- The complexity of their existing systems
- The level of product sophistication
Adapted from my interview with Jesus Requena
Bring these vectors together into an ideal customer profile (ICP) fit score, which represents high-value target customers that you believe will benefit the most from sales assistance. Layer in product readiness data (more on that later) to identify both which customers to sell into and how to sell to them.
You can capture ICP data through two means: (1) data enrichment of your user sign-ups, for instance through tools like Clearbit or ZoomInfo, (2) profiling questions during new user onboarding.
Example profiling questions might include:
- What are you planning to use X for?
- What would you like to do first?
When a high ICP-fit customer signs up with an advanced use case in mind, they may not have the permissions or access to complete product onboarding without talking to someone on your team. In those cases, you may want to offer help immediately via a sales-assist resource or product specialist. This team’s goal is to help onboard and activate high-value users in order to unlock commercial opportunities in the future.
Step 2: Validate that sales is incremental
In my experience, users who opt-into a sales touchpoint tend to convert at far higher rates than ones who don’t. It can be tempting to extrapolate these signals and have sales reach out to nearly every qualified user as soon as they sign up.
At the same time, sales is an expensive resource. There are always trade-offs to consider between customer acquisition costs, conversion rates, and how reps allocate their precious time. Your highly efficient and profitable sales-assisted deals may be masking deals that are a drain on resources.
I recommend validating that sales is both incremental and efficient before fully scaling up the team. If you’ve already scaled up the sales team, try running tests where you carve out certain customer types as self-serve only in order to validate what happens in your business when reps aren’t involved in every deal.
Deputy, staff management software for shift-based businesses (and OpenView portfolio company), did exactly that. The company began their journey by carving out all trial sign-ups for owner-operated small businesses as self-serve only. Conversion rates didn’t budge between before and after the self-service experiment.
As Deputy has moved up the self-service threshold, they’ve measured the trade-off in terms of conversion rate, revenue, and efficiency. At this point, 70% of new customers and over 33% of Deputy’s new MRR can be attributed to self-serve. These changes have also freed up sales capacity to go more upmarket with the same size sales team.
Step 3: Identify product signals to drive engagement
From there you’ll want to identify product signals to drive your sales engagement (the product readiness score I referred to earlier). I recommend treating these as a score rather than as a binary yes/no.
If you already have a self-service motion in place, you should look retroactively at what product activity was most predictive of future revenue generation. But don’t worry about being overly scientific or precise if you’re just getting started.
I find that there are six types of product signals which apply across most products.
- Usage frequency: they’re a heavy user of the product (log-ins, time spent, etc.) in a way that indicates they’ve realized significant value/ROI.
- High-value features: they adopt—or try to adopt—high-value features such as advanced reporting or integrations.
- Growth: usage and/or users have hit a sudden spike relative to the last week or the last month.
- Multi-product usage: they start an in-product trial of a product or feature that the account doesn’t pay for yet.
- Team or multi-team use: they invite multiple users within the same team and/or from additional teams within the same company domain.
- Product CTA: they engage with a call-to-action in the product, ex: click to request a demo, ask to talk to support, send a chat, view the pricing page but don’t buy.
Step 4: Define the right sales plays
Knowing that a user is product-qualified is just the starting point. You’ll then want to tailor who from your team reaches out and with what messages according to the data you’ve collected.
There are a number of potential sales plays to consider.
I’d recommend starting with one of these four plays, validating that the play works for your business, and then scaling the play across your user base. From there, expand into more sophisticated and more personalized product-led sales plays. (Pocus has some great resources on this topic if you want to go deeper.)
- Inbound hand-raisers: User opts into a sales touchpoint via requesting a demo, clicking a CTA, replying to an automated email, etc. → this is more of a traditional sales motion.
- Sales-assist: User is at a high-ICP fit account and needs more help setting up the product → help onboard and activate users in order to unlock commercial opportunities later.
- Warm outbound: Account meets your Product Qualified Account threshold, but your user(s) are not the buyer → run outbound sales & account-based marketing into decision makers within the organization.
- Support → Sales hand-off: User requests help by contacting support → create a feedback loop between support and sales; sales follows up after the issue is resolved.
Step 5: Be thoughtful about comp & operations
Managing RevOps in a growing SaaS company is hard enough. Handling it when you’re combining PLG and sales – well, that’s not for the faint of heart.
A number of operational challenges will likely come up as you work through the org structure, hiring, compensation models, account assignment, and more.
I’ll explore the compensation and operations piece of product-led sales in a future piece. With that in mind, here are my quick takes on three common questions:
- Should reps get commission for deals that decide to buy via self-service? Yes, if the account has been assigned as part of their patch (defined based on the ICP-fit and/or product readiness) and there was meaningful sales engagement prior to the purchase. Don’t create artificial channel conflict for customers.
- Should we compensate based on revenue, customer experience KPIs, team performance, or something else? Comp models depend on the maturity of your sales motion and your specific business objectives. When your motion is in its early stages, I like either MBO or team performance KPIs. As the motion is scaling, individual KPIs tend to work best. These days most at-scale PLG companies stick with MRR-based sales comp, although there are notable exceptions.
- Should we reward reps for the initial land vs. ongoing expansion? Only paying reps on the initial land doesn’t play well with a land-and-expand motion. I like to have a longer window (ex: 4-12 month tail) so you don’t incentivize reps to go for broke on the initial transaction.
Four parting tips for folks combing PLG and sales in 2023:
- Sales will be closest to the customer. Product-led companies tend to be data-driven rather than customer-driven. Sales’ experience can bring PLG companies closer to their customers. Create feedback loops to bring sales’ learnings into the product and self-service experience.
- Work towards shared goals. Everyone is after the same end goal. Avoid KPIs that create misalignment across teams (ex: self-service versus sales-generated revenue).
- Don’t abandon your PLG efforts as you move upmarket and close bigger deals. This can be especially tempting right now as folks navigate the current economic and fundraising environment.
- Pay close attention to PLG pricing & packaging. You want to offer real value to your target customers, and then create bridges to future monetization.
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