Examples of proven sales plays to create a sales pipeline on top of self-serve usage
This post covers real-life sales playbooks from Miro, Unity, and Clay, the data you’ll need, benchmarks, and personalization examples. Test these ASAP!
This post is sponsored by Clay's new scheduling feature, which launched TODAY. Now, you can keep Salesforce (and HubSpot) automatically updated with fresh data at any time interval - hourly, daily, or weekly - to enable your Sales teams. 🤯
No more manually updating your CRM and rebuilding prospecting lists. Now your first-party data (e.g., product usage, marketing activity) and 3rd-party data (e.g., announcements, job changers) will refresh automatically. Learn more here!
This post is written in collaboration with Jesus Requena (SVP Marketing @ Sanity, ex-Figma & Unity). Jesus has more than 15 years in B2B SaaS Tech companies and has worked in scaling PLG and PLS motions. Follow him on Substack!
Enterprise Sales is all the rage in B2B - always has been, always will be. Sure, product-led growth burst onto the scene with its shiny self-serve transactions and freemiums, but the end goal in B2B hasn’t changed: close those 6-digit contracts. At the end of the day, self-serve usage is just another way to feed that ever-hungry pipeline (which is called Product-led Sales, or PLS).
Yet many businesses are swimming in self-serve users, but when it comes to generating pipeline from them for Sales? Crickets. Turns out, end users couldn’t care less about your enterprise security and admin features. Gasp.
Why is this happening? Here are some common mistakes companies make:
Mistake #1: Pitch slapping every user
Sending every signup directly to Sales is a disaster waiting to happen. Anyone can sign up for a free trial or freemium product – it doesn’t mean they’re willing, interested, or ready to buy. Pitch slapping every user not only wastes Sales resources and time but also creates very frustrated users.
If Sales gets too many of these leads, they’ll begin to think all of the leads coming from the product are… trash. This is a major failure point.
Instead, create a qualification system that evaluates both the fit and behavior of your self-serve users.
Fit: Determines whether an account aligns with your target persona and ideal customer profile. A “good” fit moves into a sales funnel. A “bad” fit stays in a self-serve funnel.
Behavior comes into play once users are categorized by fit. At this stage, you start gathering first-party data, such as product usage and marketing interactions. This allows you to build targeted tactics that nurture users, deepen their product engagement, and uncover their key pain points - ultimately enabling you to craft messaging that resonates.
When first-party product or marketing data is limited, trustworthy third-party data is critical. This is where companies like Clay have gained traction, serving PLG-driven businesses like OpenAI and Anthropic. These companies have reported 2x to 3x improvements in data enrichment rates to help both Fit and Behavior criteria.
Mistake #2: One-and-done email
A common misconception about product-led sales is that it’s a straightforward, one-and-done email motion. Send one email to that self-serve user, and BAM, you got that $100K deal on your hands. Ha, not so fast. In reality, getting true engagement demands more effort: think 10 or more touches across multiple channels (email, social, calls, etc.). We will cover this more in Sales Plays examples later.
Mistake #3: Sales aren’t product trained
In PLS, Sales teams need to be product experts - there’s no way around it. They're interacting with users who are deeply proficient with the product and so Sales will look like idiots if they cannot answer product questions.
Andrew Reese – one of the longest tenured Account Managers at Miro who brought in some of their largest accounts - shared this example:
"Our templates mapped to specific Jobs-to-be-Done. So when I noticed a cluster of people using the retrospective template, I looked at their titles, LinkedIn profiles, and their product activity. If they hadn’t already reached out with a question, I would reach out with relevant messaging and offer a mini product session on how they could use certain facilitation features to improve their retros. The conversations from this approach helped make an authentic connection, build trust, and spark that “Aha” moment that often turned them into champions.”
Educating the user on product functionality was just the beginning. Andrew added,
“These interactions helped expand Miro across their teams, positioning me as a consultant rather than a salesperson.”
But not everyone is like Andrew. Most sales teams stick to outdated techniques. So, as a response, some companies are taking a brute-force approach by introducing a new role: the “GTM Engineer.” This role, which is rapidly gaining traction in B2B, places product-savvy professionals in sales to bridge the gap. Just look at Clay - they’ve revamped traditional sales roles like SDRs, AEs, and sales engineers into this new single, high-leverage function. Everett Berry, Head of GTM Engineering at Clay, says:
“What's particularly interesting is that our customers view GTM Engineers not just as sellers, but as strategic advisors. Customers often tell us that working with GTM Engineers helps them implement their own revenue automation initiatives. These aren't traditional sales conversations - they're collaborative sessions where GTM Engineers are thought leaders on how to build scalable revenue systems.”
Data you need for sales plays
Let’s start with the data you will need.
First of all, know that not every end user is a buyer (wouldn’t it be nice if they were?). However, every end user does have the potential to become a champion – they’ll be the advocates Sales needs to drive the opportunity.
Then, leverage demographics, product usage, and marketing activity to give Sales the specific insights needed to craft relevant messaging for their outreach.
Demographics
When new users create an account, it’s critical to collect data about them during onboarding as well as enrich their company and contact information with reliable data. Products like Clay can help you go-to-market with unique data across multiple dimensions:
Additionally, you can leverage Clay’s AI agent to find non-traditional information about companies or people (i.e., if someone was on a podcast recently). Essentially, if you can give a prompt to something like ChatGPT or Claude to research one person or company, you can do that inside of Clay for thousands of companies at scale.
Pro Tip: Clay released Scheduled Sources, a new feature which allows you to monitor for new company or people signals. You have these “always on” alerts that are running which are customized to your company and can give Sales good hooks to engage with the user.
Product usage
What users *do* in the product gives a more accurate representation of how much evaluation they are doing of its capabilities than what they may self-report. Here’s a shortlist:
Free trial and onboarding signals: Frequency of logins, features explored, time spent in the product, and key milestones achieved during onboarding.
Feature adoption: Usage of premium features or reaching feature limits/thresholds.
Integration and data uploads: Types of tools integrated and data uploaded.
Users expansion: Beyond the initial cohort of users, who else was invited and what are their titles/roles, department, etc.
For example, three days into a trial, Clay’s GTM Ops team segments users into no, low, and high usage. For no usage, they send Claybooks (tactical guides). For low usage, they personalize emails based on user goals, offering guidance to deepen engagement. For high usage, they do the same but add extra credits to boost adoption. We’ll show you examples of the exact emails they send later in this post.
Marketing content signals
User behavior outside of the product can reveal how far an account is in their decision-making process internally, like checking out pricing or customer stories for validation. Consider monitoring:
Key website pages visited: Focus on pages such as pricing, case studies, specific product details, and the "contact us" or “book a demo” pages.
Content engagement: Pay attention to articles, white papers, and eBooks read or downloaded, plus webinars attended.
Examples of the sales playbooks you may use & data needed for each:
Who to talk to and how often
Engaging users based on product signals requires a multi-faceted approach. Instead of relying on single emails or messages, effectively communicate your key message through a variety of touchpoints and channels (a single email is NEVER going to cut it). This ensures your message resonates with users across different interactions.
How many times to reach out?
There's conflicting advice on the ideal outreach sequence length. Some research suggests 6-9 touches, but people often get annoyed after 3-4. With that in mind, we recommend aiming for 6-9 touches total, limiting any single channel to 3-5.
Remember: PLS doesn’t operate in a vacuum. Keep in mind that users will be getting comms from marketing drip campaigns and onboarding notifications (both in and out of the product), so consider when is the best time to initiate sales outreach.
Who should you reach out to?
Here is a simple version to know the personas you should contact via sales cadences.
Most successful sales playbooks will have a combination of personas that are key to engaging during the sales process. Multi-threading is powerful if you can name-drop and highlight the fact that you might be also discussing specific topics with the other person. This allows you to increase the internal conversations and awareness of the value as a team or from end user to business value.
Practical applications: Sales outreach sequences & templates that WORK
How Miro does it
Phase 1 - End user / practitioner outreach
Miro targets end users to find and build champions within an account, which allows Sales to leverage those insights for better decision-maker outreach.
Looking through the user base, find trends with user’s titles/roles (i.e., are there any organic hotspots within the org around specific roles?)
Understand their specific role by finding job descriptions, looking up LinkedIn descriptions for people in the role, etc.
Tailor the outreach to their goals and leveraged social proof to pique their interest
Phase 2 - Decision maker outreach
Talk to as many end users in this role as possible to deeply understand their current state, pain points, consequences, and ideal needs. Then, craft a hyper-tailored message to decision-makers (found directly or through user guidance) using this format:
The subsequent follow ups for this are essentially the same as the Phase 1 flow.
How Unity does it
Below is the example of 11-touch point sequence Unity deploys against their self-serve users:
How Clay does it
Here is an example of the personalization Clay applies in the first touch, sent to new users during their free trial.
Personalize much?
Generic, not personalized messages will not work here. The key to successful outreach sequences is tracking product usage signals and tailoring emails to address the team’s most pressing priorities.
Frances Brero, co-founder and CPO of Madkudu says:
“I have been surprised to see how much successful reps customize their messages. Many of them will have a specific playbook: I will personalize with A if B is true, with X if Y is true…”
Here are some real examples of personalizing your first couple of emails to be hyper-relevant and cut through the inbox noise.
Principles when adding value through personalization
Go beyond the first data idea. After you craft your first personalization idea, craft 5 more. Keep going until you find the most relevant and catchy angles. Test, test, and test some more.
No templates, not even the ones in this guide. Tailor your message, sequences, and messaging to your audience. Test and optimize until you learn what works.
Show, don't tell. The best way to convince any user, technical or non-technical, is to show them how to achieve value from the product; real examples, videos, or short guides are great. Make them as self-serve as possible.
→ See how Clay does point #3 with their Claybooks. They go even further, though: everyone in their enterprise sales funnel goes through a “data test” that compares Clay to another data enrichment provider to objectively demonstrate how their data enrichment percentage can be improved.
Measuring success: Input and output metrics
Here are some of the input and output metrics to measure your sales playbooks.
Keep calm and carry on
The journey of PLS is both challenging and rewarding. It demands more from teams, going well beyond basic user and product knowledge. Keep pushing and always be learning.
Edited by Melissa Halim
 | A guest post by
|
This e-mail could be a lesson in Sales University if it existed. So much value in a single email.
Agree with Fabio, this post is a MasterClass!