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As more and more B2B SaaS companies invest in their PLG strategy, the concept of Product Qualified Leads is gaining traction.
This concept is simple – leads are scored based not only on demographics and firmographics but also on intent signals coming from product usage.
Leads with the highest intent scores become product-qualified leads (PQLs) and automatically pushed to sales reps, so they can spend more time selling and less time prospecting.
A PLG strategy is an essential part of the larger sales funnel, so it's important to understand how predictive lead scoring works and how you can leverage it to generate product-qualified leads.
PQL scoring can either be done manually or by leveraging predictive analytics solutions that utilize automation and machine learning algorithms to measure behavioral patterns.
Such patterns include a wide array of data points, like website interaction history, email engagement, firmographics, demographics, account-level insights, and now - product usage.
By analyzing these patterns, predictive lead scoring solutions can accurately assess which leads are the most likely to convert into valuable customers in the future.
When you think about it, predictive lead scoring is nothing new. Still, the reality is that not enough companies take advantage of it to generate opportunities from all the data they own.
This is particularly critical for companies offering a free trial or freemium offering, as they tend to generate a large volume of leads.
The downside of generating so much demand is that it can be challenging to know which one of these leads to focus on. That's where predictive lead scoring can help to identify folks most likely to convert into paying customers.
By evaluating individual user behavior, product usage data can be used to understand which users would benefit most from extra support and special offers.
This helps maximize how well the product is being marketed, allowing companies to focus their resources on the right prospects at the right time.
For those looking to use 'PQL' as a demand generation metric, predictive lead scoring is an excellent tool for surfacing the leads that are most interested in engaging with your product or service, among all others.
By using predictive lead scoring algorithms, businesses can quickly assess hundreds of leads in a matter of seconds and pick out those best suited for a sales call.
This means that sales reps are no longer forced to fly blind, rely on intuition, or waste time manually qualifying leads that will never convert—enabling them to focus their energy on selling to those likely to become customers in the near term.
Advanced automation can run this methodology on autopilot, routing qualified opportunities to sales reps, saving them time and energy and dramatically improving performance.
Ultimately, this helps to boost efficiency and optimize marketing costs incurred by companies hoping to acquire valuable customers through PQLs.
Predictive lead scoring can be a powerful tool for B2B SaaS companies offering free trials or freemium offerings—enabling them to identify prospective customers who are likely to convert based on product usage data and behavior pattern analysis, ultimately increasing the chances of successfully acquiring new customers or expanding existing ones!
Learn more: www.forwrd.ai
