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Complete Guide to Product Qualified Leads - How SaaS startups turn product usage into qualified leads.

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Free trial signups ≠ sales, so how do you build pipeline from trial users? The answer: product qualified leads. The open guide, insights and playbooks from DigitalOcean, Typeform, Moz, Mention, and more how they use product usage to drive sales.

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Maker
Thanks for hunting us Matt! Working at Hull and Love Your Customers, we noticed a common pattern amongst our SaaS clients - a firehose of free trial signups, but this doesn't convert through to sale pipeline. Most advice around improving trial conversion rates focuses on the tactical - "improve your user onboarding", "make your signup frictionless", or "use email nurturing". But, we didn't feel this was prescriptive or useful. After interviews with a range of SaaS startups at all different stages, like DigitalOcean, Typeform, Appcues, AdEspresso, Contentful, Moz, Mention, and more, we put together this complete guide to product qualified leads. We wanted to pull together the insights and methods into one definitive playbook. It's free and open to read - the first seven chapters are live and ready to read. You can subscribe for more (we're publishing a few chapters each week) Product qualified leads are *very* specific to your company and your market, so if you've got any questions on how to implement PQLs at your company, we'll be around all day today/tomorrow to answer your questions - We are Ed Fry and - Ask Us Anything!
excited to dive into this. Curious to hear what surprised you the most (if anything) from the interviews?
Maker
Thanks for the questions - Most surprising for me certainly was around the lengths people went to for organizing their data. Once they'd found something in a model, everyone struggled with getting that data into the tools that their sales teams used. No one wants sales reps in databases and analytics tools - least of all sales reps themselves! Chapter 4 digs into this a little more. One favourite (we weren't allowed to name) was dumping it all into a data warehouse, then resyncing that to their CRM - a process which took EIGHT HOURS. They'd start this overnight so their Bay Area office would have the "right" data the following data. But, European sales were screwed over by two sets of data that was updating throughout their working day. Lesson learnt: PQLs need to be synced and acted on in as close to real-time as possible :) what was your most surprising moment?
Maker
Great question, Jonny. To hone in on a specific anecdote, what I found most surprising was DigitalOcean’s experience with testing sales outreach to PQLs — in a space that’s notoriously sales- and marketing-averse. Essentially, once DigitalOcean identified which user actions indicated a higher spend, they set up an A/B test: the control group received no sales outreach after completing trigger actions, and the experimental group received outreach. Marketing and sales teams conduct tests like this all the time, but what I found surprising was the *result* they saw from their outreach experiment. While the outreach recipients who DID reply to sales communications proved to be the highest-value, even the group that received outreach but DIDN’T reply *still* performed 50% better than the group that received no outreach (!) Really interesting to hear about this account of outreach to PQLs and how much of an impact it made, even on the group of users who chose not to reply to said outreach at all.
Nicely done 🙌 . Reading over the comments here. Lessons learned through the interviews. Biggest surprises. Would be good to turn this into a webinar / video format so people can watch. I know you are both excellent presenters / great at articulating your points :)
Excited about the guide! What do you see happening in the SaaS space that made you want to focus on PQLs?
Maker
Hey Ty - What we see happening is a try-before-you-buy software world powering SaaS startups everywhere. But, for companies with pricing models that support a sales team, those sales teams have to make sense of a firehose of trial signups. Who should they talk to? What should they say? That data exists! It's just in a backend database, or analytics tool... something a rep isn't in, and doesn't want to go in. How can you take those streams of data and package them up in a CRM-friendly, rep-friendly insight that clues them in with WHO to talk to and WHAT to say. It's sales enablement meets SaaS enablement. And not enough people are talking about it. had this problem first hand at Calendly, so together we went about creating the ultimate playbook.
Maker
We also noticed that the challenge doesn’t seem to be a lack of awareness on the marketing/sales teams’ part. Rather, the challenge for many folks we spoke with was knowing that communications with PQLs could (and should) improve…but lack of process, or even a sense of where to start, = roadblock.
Sounds awesome! Really good job & 🙌
I started reading it too. Great resource and huge work. 💪
Maker
Thanks so much, Jice! Would be interested to hear whether you've encountered similar challenges when working on growth strategy for clients?
I know for a while. He's an amazing guy. They made an magnificent work with If you would like to improve your skills and growth strategy, this is a "must" guide. Congrats mates!
Maker
Appreciate the kind comments Metehan!
Maker
Thanks so much, Metehan!
This is awesome . Love reading everything you & the Hull team put out into the world. Can't wait to dig in.
Maker
Thanks Colin - means a lot coming from the Halifax SaaS mafia! ;) Are you guys using product usage data to qualify leads at Manifold?
Just starting to get our feet off the ground with it to determine when someone should reach out. Product usage + data from Clearbit to give us insight into the org. I'm sure Ill have a lot to think about as I read through this!
Maker
Checkout Chapter 5. Every SaaS startup of any size can find an "aha!" moment through analyzing their data. For you guys, you might be similar to Contentful. Clearbit data will give you account size, but the number of active signups + API calls/connected services might be interesting places to start looking.
Great work guys!
Maker
Thanks Yoav - would love to hear more how Yotpo leverages product usage data to qualify accounts :)

I loved the guide. While quite long, it's fast to read and you can dive deep into chapters that interest you most at a particular moment. Looking forward to more guides from this team!

Pros:

Comprehensive, all-in-one overview over the topic

Cons:

Focus even more on actionable steps people can implement right now.

Maker
Thanks for sharing Jakob! More of the juicy actionable steps coming after the intro chapters. 4-9 go into detail with takeaways.
This is awesome. Excellent and helpful resource with relevant insights
Maker
Thanks Yaniv - curious how you guys can dig into product usage data as a Wordpress plugin.
Great question. Analyzing product usage is a real challenge for any WordPress developer. You can't use any fancy solutions on WordPress, so it's just UTMs & customer centric approach (support and active communities).
Well done! Can't wait for chapters 8 and beyond :)
Maker
Thanks Fred!
Maker
Much appreciated, Fred!

Guaranteed to be informative; always offers super insightful & actionable content

Pros:

Deep-dive into a super common pain point for SaaS start-ups

Cons:

n/a not finished reading yet

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