PQLs are hot! The newest trend to hit SaaS marketing/sales world since…I don’t know…the SQL?

PQLs (Product Qualified Leads) are becoming an essential piece of the modern SaaS acquisition puzzle – and rightfully so. Any SaaS business using a free-trial or freemium model needs to have some way to assess leads based on their engagement with a product. This is quickly becoming a requirement of every modern SaaS operation. Incorporating product engagement data in their sales process not only helps their sales people become better informed about their incoming leads, but also helps them become more efficient overall. But while the demand for this data in the sales process continues to grow, execution is still hampered by (a) the challenge of getting product engagement data in a format that can be easily used and understood by a sales team; and (b) the difficulty of getting it in a place sales can easily take advantage of it.

In this post, we will outline the fundamentals of a PQL process and explain how Sherlock helps drive it.

WTF are PQLs?

While the point of this post is more tactical, I will give a quick overview of PQLs – as a concept – here. I will also link to some good articles at the bottom of this post that will allow you to dig in more. 

At a high-level, here is a quick definition of PQLs are:

PQL = Product Qualified Lead

For SaaS businesses with a “try before you buy” (ie – a free trial or freemium) model, a Product Qualified Lead is a user (or account) that is “qualified” based on how they are engaging with the product. And by “qualified”, we mean how likely they are to convert into a paying customer. The logic goes – if an account is highly engaged during a trial period, it is more likely to buy than an account that isn’t. 

The accounts that are highly engaged during a trial period would be considered “Product Qualified Leads”. 

MQLs, SQLs, and PQLs…oh my!

Of course, qualifying leads for a sales team is not a new phenomenon. In fact, qualifying leads, as a practice, has been around for as long as there have been sales teams. The practice of qualifying leads is an essential part of any sales/marketing process because it allows salespeople to prioritize their time and focus on the leads that are most likely to convert. And this ability to focus on the right leads results in higher conversion rates (and a more cost efficient sales process). 

Want to learn how Sherlock can help optimize your trial conversion? Click here.

Traditionally, there have been two main types of qualified leads – the MQL (Marketing Qualified Lead) and the SQL (Sales Qualified Lead).

Marketing Qualified Leads are leads that have shown an initial interest in your company, brand, content, or product – enough to “opt-in” to some marketing initiative. MQLs are usually created when someone signs up for your newsletter or downloads a whitepaper or drops a card at your tradeshow booth AND they meet some kind of demographic criteria like industry, company size, title, etc. These are leads that have expressed initial interest and have some relative fit with your target market. These leads deserve attention but are not quite ready for a personal touch from a salesperson. 

SQLs, on the other hand, are leads that have moved further up the interest curve and have taken actions that justify attention from a salesperson. Typically, a lead would move beyond an MQL to a SQL by visiting your site several times, perusing your pricing page, downloading subsequent whitepapers, or requesting a demo. Lead scoring models were developed to help quantify these activities and ease the SQL process. Once a lead scored above a 50, for example, he/she would become an SQL and trigger action from a salesperson.

For a long time, this was enough when it came lead qualification. But not anymore. Modern “try before you buy” SaaS models (which are most SaaS models these days) dictate that product engagement become a qualification vector (maybe THE qualification vector) for any potential customer. Thus the PQL was born as a natural extension of this qualification process.

Makes sense, right? No brainer. The vast majority of modern SaaS businesses should be using some kind of product qualification in their sales process. But the question is – what do you need to make this process work?

5 Things You Need for a Proper PQL Process

There are five basic requirements for building a proper PQL process. They are:

1. Ability to track and score product engagement 

Obviously, tracking engagement in your product is step one. You can’t qualify an account based on product usage if you aren’t tracking product usage. But this is just a starting point. You should also be able to score and rank your users based on how frequently they are using the most important parts of your product (learn how to do that here). Giving your product engagement data this context will allow your sales team to receive this data in a format they can actually use. Don’t dump a truckload of event data on your sales team and expect them to make sense of it. Won’t happen. 

2. Track and score product engagement at the account-level

This is super obvious – so much so that it’s very easily overlooked. As a SaaS business, you don’t sell software to individual users – you sell to teams, to organizations…to accounts. This means only tracking product engagement at the user level is not helpful. You need to be able to aggregate this engagement data at the account level. Without this ability, your PQL process will become more frustrating than helpful and your sales team will likely abandon it. 

3. Ability to identify the most engaged users on each account

When working a sale, salespeople are always looking for the right “entry points” into an account. They look for people who are going to become their internal champions – a user who will help sell the product internally. Therefore, having insights into the engagement of each user on an account is essential for driving a sales process. The users most engaged with the product will become the “case studies” to be used when trying to sell to other decision makers. This is key, key data for your sales team.

4. Ability to track Activation Rates

The goal of any trial process is to drive users and accounts toward “Activation.” Every product has a different definition of Activation, but it’s generally the three, four, five specific actions that allow a new account to experience “first value.” A good PQL process will include insights into the Activation progress for every trial account. Which accounts are fully Activated? Which ones are almost there? Which ones are way off? These are all essential questions your sales team are asking and which that should be easily answered in your PQL process. 

5. Easy access to all this essential data

Having this product engagement data is one thing. Getting it in the hands of your sales team is another. If your sales team doesn’t have immediate access, they aren’t going to use it. That is why you need to have all this data packaged up in a way that it can be easily understood and easily shared with the tools your sales team is using on a regular basis. 

Conveniently (🙂), Sherlock does all of these things. See below for how to use Sherlock to drive your PQL process.

How to use Sherlock to Drive you PQL process

Sherlock was built to help you truly understand the engagement level of your users and accounts – from first signup to conversion and beyond. As mentioned above, it does everything you need for shaping your PQL process. With Sherlock, you can:

  1. Create an engagement model which allows you to score and rank all users and accounts based on actual engagement with your product; 
  2. Easily access insights into the engagement level of all users on each trial account;
  3. Define “Activation” for your trial users and accounts and track their progress toward “first value”;
  4. Connect these engagement scores and activation rates with Salesforce, Intercom, Slack, and others to give your sales team easy access to the data;

For those looking for a step-by-step guide for setting up this process in Sherlock, here it is (also here):

Step 1: Connect your product data with Sherlock

If you are using Segment.com for your product data, you can simply flip a switch and have your product data sent to Sherlock immediately. Alternatively, you can start implementing your data with Sherlock with our custom tracking script (coming soon). 

Step 2: Set up your first scoring profile 

This is part of the basic set-up for Sherlock. This is where you will score the engagement of your product events and create your first Sherlock scoring model. Once you do this, all your users and accounts will magically be scored based on how they are engaging with your product.

Step 3: Define Activation criteria for trial accounts

By defining what it means for an account to be “Activated”, you can start tracking the Activation rate of all your trial accounts. Activation rates will be displayed as a percentage (between 1-100%) based on what percentage of the activation criteria a user/account has met at any given time. 

Step 4: Connect Sherlock with your other tools

By connecting Sherlock with other tools (either directly or via Segment), you can get this essential data to your sales team where they can take action. You will send Engagement scores and Activation rates for all your accounts and users to these other tools. Your users and accounts will also be tagged with any Sherlock segments into which they fall. 

No Reason to Wait

At this point, you should have everything you need to build your dream PQL process. You’ll have all the essential data points on account and user engagement, activation, and adoption. And you will have a way to give your sales team easy access to this data. 

The next step will be building the internal process around this data. Obviously this will vary based on your existing team and process, but one thing is sure – you can’t wait any longer on this. If, at this point, you don’t have a PQL process in place – or you have a very poor one – you are behind. All modern SaaS operations are moving in this direction and we predict this will become standard in just a year or two. Not only will this type of process make the lives of your salespeople much more manageable, but it will also make them more efficient – which should translate to better conversion rates and, ultimately, and improved CAC.

Related Posts:

  • Beginner’s Guide to Product Qualified Leads (PQL) by Wes Bush: An amazing overview of PQLs (much better than I could do) from Wes Bush – someone who probably has more practical experience in this space than anyone.
  • Why product qualified leads are rapidly being adopted in SaaS: A good post from the Openview partners who specialize in product-led SaaS businesses – for which a PQL process is very important. 
  • The product qualified lead(PQL) by Tom Tunguz: And oldie, but goodie. Tom has been talking about PQLs since 2013! Talk about being on the right side of history. 
  • Marketing Qualified Leads Are Cool, But I’ll Take Product Qualified Leads Any Day by Emmanuelle Skala: One of the top SaaS sales and CS leaders weighs in on the PQL in this post.
  • MQLs are DEAD! Enter the PQL“Product Qualified Lead” = 10X+ revenue impact by Mitch Morando: A dramatic, but not inaccurate take on the subject from a seasoned SaaS sales leader.

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