Anything that takes the guess work out of prospecting has to be a good thing, right?
At Sopro, we’re ceaselessly exploring new tech that can make our deliverability more certain and our targeting more accurate.
This is why we’re so excited about predictive lead scoring.
Here’s what it promises to do:
👉 Predict with greater accuracy than ever before which leads we should be jumping on and which we should be holding off.
New technologies mean that businesses no longer have to guess which leads are worth pursuing and which leads have turned cold. It’s the Derren Brown of prospecting. Find out who will want to buy from you before they even know themselves! Well, maybe not that soon – but certainly sooner than your competitors.
We’re going to talk about two kinds of lead scoring processes:
Traditional lead scoring
Predictive lead scoring
Each can transform your business’s marketing and sales systems from the inside out.
Traditional lead scoring
Lead scoring is nothing new in itself: it’s the way that we can now do it that’s new.
Lead scoring is simply a systematic way to rank your leads according to where they are in your sales funnel aka how ready they are to buy.
This score will be determined by implicit and explicit factors such as demographics, firmographics and behavioural clues.
Knowing how your leads compare is key to understanding who you should be prospecting to and when.
Explicit vs Implicit data
Explicit data could be collected from:
Online registration forms
Other demographic and firmographic information such as job title, company and industry
Implicit data can come from:
The prospect’s behaviour on your website
The prospect’s engagement with other marketing channels
Here’s what’s wrong with our current scoring methods:
Traditional lead scoring has – by and large – proved to be more effective in identifying poor leads than those with the most potential. And, it is those with potential that is where the real money is at.
It also harvests its data manually and is based on a small dataset, which makes it less accurate when faced with our fast-changing markets.
Its ranking factors are heavily biased toward a prospect’s interaction with you rather than an objective assessment of their needs.
Lead scoring + machine learning = predictive lead scoring
Predictive lead scoring adds in machine learning to the algorithms used to score leads. It represents the automation of the scoring process.
Instead of relying on small datasets and humans collecting data, predictive lead scoring gathers and analyses many sources of data to evaluate the behaviour of prospective leads. These data points are then ranked on a scale that pinpoints those who are more likely to purchase something from your business.
Here’s where it wins hands down against its traditional counterpart:
It produces meaningful metrics that are based on samples from large and varied datasets
Reacts rapidly to changes in the market
Continually compares past and current customers and your active leads to adjust the profiles it uses to assess its scoring
Identifies patterns and connections you might have missed trying to analyse a wide set of data points
Such an approach, of course, assumes some investment in tech. Predictive lead scoring is premised on the quality of the data you hold – and you will need to use external data sources to gain the high volumes required.
You will also need the necessary technology to crunch, analyse and manage this.
There are many ways that you can immediately get to work on your current lead scoring model without calling in the big guns of martech.
Tweaks and improvements to your lead scoring can deliver immense value in making your sales process more efficient and increasing your conversion rate.
We’re really excited the role prospecting can play in predictive lead scoring. Sopro helps you build a pipeline of high quality leads by sourcing a live audience of your ideal customers. When they reply wanting to know more about your business, it’s a clear sign of intent and interest.
Prospecting ranks highly on the lead prediction charts. No crystal ball required.