Setting Up Predictive Lead Scoring Using Machine Learning
You acquire leads from several different platforms. While some of these leads would be buying candidates, most of them are not going to buy. Depending on your type of customers and their LTV (lifetime value), you may also have a lot of leads to deal with.
It is not resource efficient to have your sales reps speak to all leads. Some leads would also need to be nurtured before they are ready. As a lead is nurtured, they are likely to move further along the sales funnel. They will have questions answered and reservations settled, and nurturing can also help educate leads so they can better understand how the product will work for them.
To ensure only leads who are likely to buy are engaged with resources, businesses opt for a lead qualification strategy.
Why Qualifying Leads is Important
If a lead is not ready to buy yet then sales are less likely to get the desired outcome. Not only will this mean a deal is not made in the short term but, in some cases, it might even mean losing the lead altogether. With the high cost of acquiring leads, it makes sense to avoid losing as many as possible, making it a good idea the lead is qualified for a sale before the sales team moves in. Also, like we mentioned earlier, not all leads are buying candidates. If you spend time on unqualified leads instead of prioritizing qualified leads, you might end up losing customers and wasting resources.
Perhaps the most effective way of qualifying leads is with lead scoring. Lead scoring is a system that gives each of your leads a score depending on certain criteria. These criteria can include factors like the industry the lead works in, the company’s size, the lead’s job role and decision making capabilities, the company’s turnover, and which pages they have been looking at on your website. Traditional lead scoring involves arbitrarily deciding how many points a lead will gain or lose according to predefined criteria. If the lead has accrued enough points it is considered qualified, and a sales offer is often triggered.
Another, more recent option is predictive lead scoring, with lead scoring machine learning.
What is Predictive Lead Scoring?
Predictive lead scoring is a system that involves the use of algorithms to score leads instead of arbitrarily decided frameworks. The algorithms take the existing data and use it to determine which of your leads are sales qualified. The algorithms tend to use the same data that traditional lead scoring uses and matches this data against how leads have performed in the past.
One of the key advantages of predictive lead scoring is that it removes the need for humans to create the scoring system themselves. Predictive lead scoring can look deeper into past data and identify patterns that humans are likely to miss, helping to make the leads more accurately qualified. More accurately qualified leads, in turn, means more sales.
What is Machine Learning?
Computers are able to process vast amounts of data in a fraction of the time people can. Advanced calculations can be completed in less than a second, making even the most intelligent of humans look slow. But computers are still very limited in some ways when working with data.
Machine learning allows computers to adapt and adjust to data they are processing without being actively programmed to do so. The software will get to learn about your leads’ behaviours and what it means in relation to how well qualified they are. The system can continue to enhance its algorithms according to its past experiences, helping it to qualify leads increasingly accurately as it processes more data.
Predictive Lead Scoring Platforms that use Machine Learning
With accurate lead scoring services in high demand, a number of platforms have been created to try and meet that demand. Here we take a look at some of the best platforms available and some of their features.
Salespanel comes with its own data (thanks to partnerships with 3rd-party data solutions) that can then be used in conjunction with a lead’s behavioral data and the data in your CRM. The software’s Quality Score features processes the data to score leads accurately and then updates your CRM with the scoring information. In addition to looking at demographics, the software also looks at behaviour including activities on websites, clicks on newsletters, and email activity along with a lead’s firmographic information. Machine learning helps the software to continually improve results, and you can also create your own scoring criteria for more control over the results.
Salespanel offers both predictive and manual rule-based lead scoring.
Hubspot is one of the best-known names in online marketing, offering a range of software platforms that helps in making marketing and sales easier and more effective. HubSpot’s predictive lead scoring software does much of the hard work for you, using thousands of data points to determine how qualified each of your leads are. HubSpot’s platform also gives you a degree of control over the scoring system by allowing you to create your own criteria for the software to incorporate. The system also allows you to create multiple score sheets, letting you use the same database to get accurate qualifying for different products.
Infer uses the data in your CRM platform to score the leads with predictive lead scoring using thousands of data points. The company has its own vast database of data points it uses against the data in the client’s CRM to score the leads. The scores are automatically updated onto the CRM so it can then be used by sales and marketing teams.
Madkudu takes data from thousands of data from your CRM, including attributes like demographics and behaviour. The software takes data points from multiple vendors and uses this data to help re-compute the signals that are related to your business specifically, helping to qualify leads according to your businesses’ needs.
Predictive lead scoring can help to qualify your leads without you needing to set up any workflows. When used in conjunction with marketing automation features, it can also help to take a lot of the work away from you by helping Sales and Marketing in prioritizing leads. With accurately qualified leads, your sales teams will have what they need to close more deals – providing you with a significant boost in revenue.
Sell more, understand your customers’ journey for free!
Sales and Marketing teams spend millions of dollars to bring visitors to your website. But do you track your customer’s journey? Do you know who buys and why?
Around 8% of your website traffic will sign up on your lead forms. What happens to the other 92% of your traffic? Can you identify your visiting accounts? Can you engage and retarget your qualified visitors even if they are not identified?
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- Setting Up Predictive Lead Scoring Using Machine Learning