By: Emmanuelle Skala
Following up with Marketing Qualified Leads (MQLs) can seriously suck! Especially when we only play the numbers game — trying to drive as many names as possible. In this post, I’m going to introduce the solution to this problem — Product Qualified Leads (PQLs) and why they’re absolute GOLD to sales teams. Modern day sales leaders, start paying attention.
The Problem With Marketing Qualified Leads
The problem is that we follow up with leads whose behavior doesn’t necessarily indicate interest in your product. No wonder conversion rates are so low, and getting worse.
Many of my peers in Sales & Marketing are struggling with top of funnel issues. Marketing Qualified Leads become a quantity over quality tactic because everyone is desperate to try anything, just adding more and more noise.
And with little context given to the sales person other than the lead source, too many of the follow ups go something like this:
“Hi, this is Emmanuelle from SaaStasstic, I’m calling because I see you downloaded our white paper.”
UGHHH! As a buyer on the other end of this — I want to scream!!!
The new buying reality is that no one buys anything anymore without either:
- Social proof – Reviews, references, recommendations, asking peers, etc.
- First hand experience – Which means that our Demand Gen strategies and Account Based Marketing strategies might help create awareness – but they aren’t creating enough buying opportunities.
And the cost to create a lead is skyrocketing…
The New Sales Qualification: Try Before You Buy
More and more companies like Slack, Dropbox, MailChimp, Hootsuite, Optimizely, SurveyMonkey, Skype and of course DigitalOcean all know that there is no better lead than one who’s tried your product.
Even companies like IBM, BMC, EMC and others now offer “Free trials” online. Why? Because we live in an on-demand world and access to information is unparalleled.
These companies know that buyers want first hand experience before making a big purchase.
Guess what else they want: a friction-free process. Buyers don’t want a salesperson holding the keys to the “Proof of Concept”.
At many of these companies, the salesperson’s job is to convert free-trials or freemium leads into higher spending customers. Unfortunately, too many sales organizations are using the exact same processes they did with MQLs to follow up with these leads. We’ve already proven this doesn’t work.
While the cost to acquire the lead may be lower, the conversion rates still suck because your sales person sounds like this:
“Hi, this is Emmanuelle from SaaStasstic, I’m calling because I see you downloaded our free trial.”
Introducing Product Qualified Leads (PQLs)
I wrote an article on LinkedIn introducing the concept of a PQL. In a nutshell, a PQL is a Product Qualified Lead and no, it’s not just another acronym.
The primary benefit of the PQL is that it can give the salesperson a TON of context to know who to follow up with, when to follow up with them and what to say to add value.
However, if all of the rich data from Product Qualified Leads are ignored (or not exposed to the rep) then they’ll fall into the same traps but the impact will be worse – you won’t be pissing off random people who downloaded your white paper, you’ll be pissing off actual customers/users. Ouch!
Marketing Qualified Leads (MQLs) have not already tried your product, while Product Qualified Leads (PQLs) have. Simple distinction. They are very different and need to be treated differently.
I’m building out a PQL model right now — while we’re just starting, I have learned a few things.
I can’t publicly share results – but I can say that in the first month, we’ve already exceeded expectations and more importantly, we are getting great feedback from the users we are reaching out to.
Building The Product Qualified Lead Model
- This is not just some fancy lead scoring – Don’t sit around in a room and try and make up criteria about what might determine a good lead. Look at the behavior and demographics of your existing larger/more committed/more strategic customers and find commonalities.
- Get the assistance of a Data Science team – Ensure you’re capturing rich data about your customers and their usage patterns so you can look for ‘triggers”. What features are they using, how often are they using, how many people are using, what volume are they using? The kind of data that can be pulled varies considerably company to company — but if you aren’t using this rich contextual data, you are missing a huge opportunity. If you don’t have a data scientist on staff – get one or check out a company called Whalr.
- Match users against 3rd party databases – Enriching your data is critical (especially if you get a lot of generic email addresses in the sign up process). We match against several data sources including Mattermark, Clearbit, Datanyze and others.
- Start testing – Learn what converts and what doesn’t. Even the most sophisticated data science models need inputs/results to continue to learn. Consider even having a control groups and doing a lot of A/B testing
- Expose as much as you can to the reps. – In our model, we have the analysis of the leads to determine if it’s a PQL and it’s priority in a Data Science model/database. PQLs then get pushed to Saleforce.com daily but ALL the contextual data does too. That way, the rep is informed. And if he or she wants more info, it’s just one click away to get right into our database of product usage where he or she can explore further to gather even more context
Perfecting The Follow Up
- NEVER offer help if it’s not needed – There’s really nothing worse than “fake help”. Please do not just say “I see you downloaded and want to learn more about your needs”. If you don’t have any relevant context or reason to call, then don’t! In my experience, when there is no context it means the person is likely not going to convert or they’ll reach out on their own when they are ready.
- Do Your Job. Be Helpful! Seems obvious, but these are CUSTOMERS. (Frankly, we should have never treated “leads” like cogs in a process to begin with as we are all just Humans buying and selling to Humans). Your job as a salesperson is to HELP the customer.
- Time the outreach with when you can offer real help.
Here’s some examples:
“I noticed that you turned on X feature, here is a great article on how to best leverage this capability”.
“It appears that you are trying to solve XYZ problem based on the fact that you are doing ABC with the product. If you’d like some help with that, we are happy to walk you through some best practices”.
Don’t Sell. Help.
I repeat, when your “leads” are your “customers” (PQLs), the salesperson does not SELL. The salesperson HELPS. The lines between Sales & Customer Success blur. With the assistance of data science, marketing and some great content, you can transition the experience of following up with leads from the inevitable “No thanks..Hang up” to “I’m glad you called, I’d love your help”.