With ever-increasing startups & businesses around the globe, the B2B market is in its prime time. What it also means for the companies is that the significant increase in their so-called “prospects” is just an increase of noise, supported by the fact that the conversion rate in the SaaS space is just at 12%As lead qualification continues to be a pain point for the marketer, various marketing platforms are coming up with their own ways to deal with. The rule-based scoring is one such approach that various marketing platforms have adopted in order to provide their customers with some kind of lead qualification criteria. Generally, this is how a rule-based scoring works its way to qualify a lead
- Define a set of rules based on historical lead/customer data, eg:
- If a lead is from the US, give it a score of 10
- If a lead has filled a contact-us form, give it a score of 5
- If a lead does not have a “CEO”, give it a score of -5
By this strategy, you can build your own rule-tree & score every incoming lead. Once you have the rule-tree setup, you can come up with a threshold score to qualify a lead, for eg, you can say:
- If a lead has a score of more than 50, it’s a high-quality lead
- If a lead has a score less than 50, it’s a low-quality lead
NOT REALLY A CURE…
This approach will get you through a day or two but will soon become a liability for your sales process, and we say this because the rule-based scoring doesn’t:
- Give granularity to your rule-tree
- Know the right combination/nesting of different rules
- Take into account external factors, factors independent of the actual business
- Scale well enough, re-iterations may be required as the business grows
This is a story of the past. Since the introduction of AI into the global market & the marketing sector specifically, a lot of companies are trying to incorporate AI into their software to automate marketing processes but intelligently!With this thought in mind, HubSpot came up with it’s new & improved version of lead scoring called by the name Predictive Lead Scoring. In a few words, PLS is part of the predictive analytics domain that aims to not only automate the process to qualify leads but also takes into account the behavioral, personal, firmographic data of a lead to qualify it. PLS outperforms the traditional rule-based scoring only because of the fact that it has the ability to learn and improve using historical data. While HubSpot also offers a PLS product as part of their automation software, it doesn’t really work as an AI & performs as good as a toss of a coin!HubSpot’s version of predictive lead scoring seems to be nothing but a glorified version of it’s rule-based scoring. The factors that this product takes into account for qualifying leads are either irrelevant to one's business or are not interpretable to the user.
Yet another problem this product is suffering from is the lack of ability to take into account the custom forms set-up on a website & the lead’s response to these forms and how they interact with the website. The biggest loophole this product seems to have is that it generalizes it’s AI-based lead qualification criteria for every business. You cannot have the same type of variables & assume they’d have the same impact on every business. While this might not be the case and something “intelligent” might be brewing, the numbers are still questionable.