SaaS companies are increasingly offering free trial periods or freemiums.
Considered as the cornerstones of Product-led Growth, these offers are used as acquisition channels – and are proven to be very efficient – as it widens the top of the funnel.
In this scenario, marketing and pre-sales teams’ efforts are primarily focused on dragging as many users as possible to the trial or freemium.
If your product or solution is great and has virality – or at least does not solely appeal to a niche market – signups may be numerous.
As a result, prioritizing your conversion efforts to the users most likely to do so isn’t just logical – it is a necessity.
And this can be a challenge…
Thankfully there are solutions
And Product Qualified Leads (PQL) is definitely one of them.
=> Discover how to know, find and activate them.
A Product Qualified Lead is a user who matches your target customer profile and has experienced the value of your SaaS product through his actions and completion of key events.
Obviously, a user who matches all the above criteria and thus falls into the PQL list is someone that is much more likely to convert to a paid plan than any other user.
Indeed, if you want to follow SaaS success recipe “doing more with less”, your conversion efforts should go to the user “most likely” to convert rather than wasting resources into a “not so likely” user which will at best convert in the end – or at worse, not convert, while having pulled away energy you could have put into something else – namely, at converting a PQL
By uncovering this perfect fit, PQLs help SDRs focus on the biggest opportunities.
Pulling out your Product Qualified Leads is a process that requires a deep dive into your product usage data.
So hold your breath!
It generally takes place in 3 critical stages.
Your target customer profile is a compilation of firmographic, geographic, and demographic segmentation.
It should answer a simple question: who is more likely to need (hence buy) my product or service?
You must start by using your knowledge and perception of the macro trends of the market in which you operate.
For instance, as an American SaaS provider, you are very unlikely to end up with “North Korean public servants aged 60+” as a target segment
But creating your unique target customer profile needs more precision.
Use churn and retention analysis to refine your target customer profile.
Check out who your most successful customers are and what they have in common: country, company size, roles, etc…
Similarly, uncovering a pattern among your churned customers will be of considerable help in this process.
After all, your churned customers were once willing to pay for your product – you can thus assume an initial broad product market fit – try to see why and where you were wrong.
The criteria which describe your target customer profile are the ones to be used while setting up your Customer Fit Score, which reveals trials matching your ideal customer based on its demographic, and company information.
To detect a potential for conversion, it is also paramount to determine the actions that a user must undertake in your product to experience its value – and monitor the users who have reached this crucial point.
This is basically all the key events – particular to your product or solution – that a new user or customer must have completed before he is considered up and ready for conversion.
This could take the shape of the numbers of users invited, or the connection to a certain API, etc.
Get your Product Adoption Score based on account and user behavior, usage frequency, feature activation, NPS, and more signals.
There. You’ve reached the tipping point of the process!
Yet, it is the hardest to achieve – at least manually.
You have to combine all the data above or the 2 scores – Customer Fit Score and Product Adoption Score – to reveal your Product Qualified Leads!
While doing so you’ll probably be surprised to discover that no more than 20% of all your trial or freemium users make the cut.
But focusing on converting these 20% super qualified users is evidently much more worth it than dissipating efforts to all your user base.
Or (even worse!), putting efforts into a user that is not a good fit and would never convert while missing a great opportunity with someone else.
Well, it is not because we make it sound easy on paper that you haven’t already guessed that the process is long and multifaceted – hence rather impossible to set in motion manually.
For starters, analyzing and evaluating every new user would take way too much time. Also, the number of actions and events to take into account when assessing a user’s product adoption creates a very high level of complexity. And you have not even started scoring nor crossing all this data!
It would therefore end up being quite counterproductive when we know that PQLs are actually built to help you gain time.
On the other hand, Salesmachine connects to your product and enrichment solutions (CRM, NPS, and billing solutions) to gather and consolidate all the relevant live data about your customers (firmographics, revenue..) and their product behavior (events, actions..).
It then processes this information according to your criteria (ideal target customer profile, and product adoption milestones) to reveal scores dashboards (product adoption score and customer fit score) and ponderated Product Qualified Lead matrices.
To go further, the Salesmachine collaborative working environment empowers you conversion teams with automated engagement actions and notifications.
So that you’re always in the know and able to act accordingly to maximize your conversion.