Predictive Lead Scoring is the Future of Lead Prioritization
Big data groups, busy sales and growth teams, dozens of analytics tools, spending a lot of money, and still, a lot of manual work and indefinite results. This is how lead prioritization is (hope it will be “was”) done (to be honest, cannot be done very properly) in most SaaS companies.
How do we know? Because we experienced the same. We were working days and nights to understand which of our newly onboarding users were closest to buying, ready to buy, or why not ready to buy.
We first tried to prioritize users based on fitting our ideal customer profile, but this is the worst thing that a SaaS business can do. If a user is a CEO of some tech company, experiencing a problem that your product solves, it doesn’t mean that they love your product, and they will give their precious money to you.
Then we tracked the activity of users, activity per session, and sometimes last visited pages, and tried to contact them via messages, but couldn’t get a real answer. I mean, the percentage was very low.
We found about tracking product usage, interactions, patterns, key actions, onboarding completion, and uh… This means a lot of data, a lot of tools, a lot of people, and insufficient time and money to invest in.
One thing we weren’t aware of was it isn’t JUST about ICP, activity, or product usage, it has never been… It is about gathering them TOGETHER to predict who is to prioritize now and generating historical prediction data in the long term.
Not a new thing, but this is why predictive lead scoring is something you should use in your SaaS sales and growth, starting from now (2023).
What is predictive lead scoring?
As explained in “What is Predictive Lead Scoring?”, predictive (We will mention AI in the following sections), lead scoring is a machine learning algorithm that uses customer and product usage data to score and prioritize high-intent leads among a pool of cold and unprocessed leads.
We can also call it all customer and product data gathering together to understand every aspect and angle of a lead's likelihood to convert into a paying customer.
The exciting part comes in the long term: the predictive lead-scoring algorithm starts working as a PROVEN way of increasing sales efficiency and effectiveness. Over time, as more data is fed into the system, the algorithm becomes more refined and accurate.
With every interaction and data point added, the system becomes smarter. For instance, if a particular lead scored high but didn’t convert, the system will take that into consideration and adjust its future predictions. Similarly, if a low-scoring lead becomes a customer, the model will learn from that anomaly.
Why it is the future?
As the SaaS market grows and gets more competitive, there will be less room for mistakes. Companies can’t waste time on leads that aren’t likely to turn into sales, and they also can’t afford to miss out on high-potential leads that they might have missed with traditional methods.
Predictive lead scoring evens the playing field by making lead prioritization more systematic, efficient, and, most importantly, accurate.
As Artificial Intelligence (AI) and Machine Learning (ML) continue to improve, they will be used more and more in lead scoring. They will give more nuanced insights, spot patterns that were hard to see before and automate the process in ways that were unthinkable before.
So, if the future of SaaS is going to be data-driven, highly personalized, and focused on efficiency, then predictive lead scoring is without a doubt going to be its core. To ignore this would be like holding on to a past that is quickly disappearing.
Predictive lead scoring is not just the future; it’s also the present and the only way for SaaS businesses to grow in a very competitive market.
In conclusion, as we move further into the age of data and AI, predictive lead scoring stands out as the lighthouse that shows us the way.
It sums up the most important parts of modern business operations: speed, accuracy, and planning ahead. So, the idea that predictive lead scoring is the future of lead prioritization is not just a claim, but a fact.
How to start?
There are many predictive lead scoring tools out there with easy integrations, setups, and usage. I won’t mention them one by one, but this is the sign to search and find one that fits your needs. If you would like us to discuss them and their difference/similarities, we are ready to share quick lists with you.