Everything You Need To Know About Product Qualified Lead (PQL)

What Is A Product Qualified Lead (PQL)

Keeping the lead pipeline full is critical for business continuation, but it is even more important to generate high-quality leads which will easily convert into sales. If we begin from the beginning, the lead flow is initially generated through engagement with a SaaS brand’s marketing activities. However, not all the leads are equally valuable. 

Some prospects explore SaaS products/services without the purchase intention. When they are weeded out and the remaining leads are fostered, some will be keen to experience new products through free trials or product walkthroughs. These people/businesses are known as product-qualified leads, or PQLs, who are more inclined to turn into paying customers as they have already invested their time researching a product and experienced its full value. Consequently, the conversion rate among PQLs could be as high as 30% compared to marketing qualified leads (MQLs), with conversions around 5% or less. 

Quite often, SaaS players offering software in the cloud set a benchmark for PQL criteria. These include how well persons/businesses match the SaaS company’s ideal buyer persona and whether they qualify for the lead score threshold determined by several parameters such as product engagement, profile fit and buying intent/behaviour. As and when prospects meet/surpass the threshold, they become target prospects for sales efforts.

The PQL rate of a SaaS company is an essential metric for predicting conversion success and bringing down customer acquisition costs (CAC). It can be easily measured as the percentage of new signups reaching the PQL status in a given timeframe, say, weekly or monthly. For instance, if there are 50 signups in a month and 30 reach the PQL status, it indicates a 60% PQL rate. 

On the other hand, an abysmally low PQL rate underscores a gap between product worth, product engagement and product experience. If the product experience fails to deliver an aha moment, the PQL activation rate (the number of prospects becoming qualified leads) will be low, thus affecting the lead pipeline.      

Why SaaS Needs A PQL Strategy & What It Takes To Determine PQL Eligibility

Developing an effective PQL strategy is crucial as it helps SaaS players target their best prospects, increase conversions and bring down CAC. A great product experience before purchase leads to more conversions and drives upselling and cross-selling in the long run. In fact, monitoring PQLs is a field testing of sorts, allowing SaaS companies to improve products, optimise product experience and refine the overall customer journey for quick value realisation. These lessen the revenue churn caused by cancellations and downgrades, eventually leading to better ARPU, MRR and ARR.  

The PQL criteria of a SaaS business depend on various components, such as setting up an ideal customer profile (ICP), scrutinising prospects’ behaviour, procuring quality data and its in-depth analysis. Here is a quick look at what makes PQL criteria most effective for tracking best-quality leads.       

• Creating ICP: A SaaS company can create an ideal customer profile based on real-life customer data such as industry, business size, demographics, interests, buying habits and more. Once a detailed profile of a typical customer is up there for benchmarking, it is easy to understand whether prospects match those parameters and tailor offerings and marketing messages accordingly.
• Good quality data gathering through communication: Although the scope for direct interactions is limited at this stage, SaaS players can communicate with potential customers via targeted marketing materials, automated email messages and in-app notifications. Besides, a company can get in touch whenever prospects want to interact for better product engagement, issue resolution (complex onboarding and paywalls are major issues during free product trials) or hand-holding. Good quality data can be gathered throughout these journeys to analyse the percentage of conversion probability.
• SaaS companies can collect two types of data at this level. First, there is explicit data or the information users provide at signups, like names, email IDs and other details. One can explore and understand user requirements better by communicating with prospects at a later stage. SaaS players can further leverage implicit data derived from user behaviours/activities such as login frequency, product/service usage duration, page view, pricing review and more, revealing a prospect’s genuine interest in a product.
• In-depth analysis of user data: Most SaaS companies use AI-based tech tools to analyse user data and get valuable insights into their requirements, preferences and intent. These data-led insights help build an effective guide to identifying product qualified leads.

What Are The Key PQL Criteria: Ask These Three SaaS Giants

Slack says deep involvement is the key: This B2B SaaS platform (thriving on communication and collaborations among colleagues, clients and vendors) considers people/businesses as product qualified leads (PQLs) when they engage deeply with the platform. This should involve creating multiple channels, inviting team members, actively participating in conversations and sending more than 2K messages. These actions indicate users’ commitment and active usage, showing they may pay for premium features.

For HubSpot, action speaks the loudest: This sales, marketing and CRM giant identifies PQLs through specific actions signalling a readiness to consider premium features. For instance, when free users request sales conversations or try premium features in-app, they qualify as PQLs. Additionally, engagement metrics like the number of contacts added, messages sent and important page views (product comparisons, pricing and more) are monitored to understand users’ interest and their potential to become paying customers.

Userflow focusses on user behaviour & engagement: For this SaaS platform helping SaaS companies onboard, retain and communicate with users, PQL revolves around user behaviour and platform engagement. Spending a significant amount of time (more than 30 minutes) to build a flow demonstrates a user’s commitment to exploring its functionalities. Factors such as login frequency, team member additions and the number of flows developed and deployed for production demonstrate active usage and alignment with the ideal customer profile. These indicate that a user may gain value from the product and become a paying customer.