Not every lead is equally as good as others, and a good marketing department recognizes that sales teams treat every lead differently depending on its source and qualification.
If you flood your sales team with a large amount of low quality leads, they will waste their time making calls and emails to people that don’t have the means or inclination to purchase your product or service.
Conversely, your marketing team doesn’t have the time to manually go through every lead that comes in through your CRM system – qualifying or researching each lead to determine its suitability for the sales process. If you're getting hundreds of leads per month, your sales team might not have time to do that, either!
Lead scoring is an automated way of assigning a value to each lead in your system – gradually increasing or decreasing their "score" and ensuring that the sales team is alerted to leads that are truly “sales qualified” and ready to be worked.
Developing a Lead Scoring Model
A scoring system is a joint effort between the sales team and the marketing team since the sales team is ultimately responsible for working the leads that the marketing team passes over.
When you are developing a lead scoring model, you should start with an “ideal customer” profile, assigning points based on the amount of deviation from that ideal. You also need to base your scoring on whatever threshold you are planning on using for your “marketing qualified lead” status, so leads are passed to sales when they are warm but not stale, but not so soon that they haven’t had a chance to interact with your content.
Lead scoring is a long term initiative – and a lead that isn’t immediately qualified might stick around in your database for months until they finally see an email that sparks their interest, causing them to take several actions on your website that push them over your qualification threshold.
The first step of lead scoring is to assign a score to a lead based on information that the person puts into forms or implied through activity or a database entry.
For example, depending on your target market and the people that have been most likely to do business with you in the past, you might assign a different value for each industry – and a higher value for job titles that represent decision makers in their companies.
You might also assign values for countries (with lower/no values for countries that you don’t do business with), or other characteristics that represent the composition and description of the lead/account – like the size of the customer company or their total revenue.
Demographic scoring is basically your answer to, “Who is this person, and can we successfully sell to them?”
Behavioral scoring, on the other hand, is the answer to, “What is this person doing, and do they want to do business with us?”
In behavioral scoring, people are given points based on their actions on your website or in another sales channel. For example, you might assign a higher value to someone visiting more than one product related page and your pricing page, but a lower value to someone signing up for your newsletter.
Actions that imply willingness to purchase (based on past patterns) should be weighted more heavily than actions that represent curiosity or casual interest – so when someone fills out a free trial form for your software product, the lead score would be higher then if that person were to download an educational whitepaper.
The trick to behavioral scoring is to ensure that your leads have to make some interaction with your company and its content before they are passed to sales – so your sales team isn’t relying solely on a cold call to pique the lead’s interest.
Sometimes, you want to deduct points from one of your leads, and negative scoring allows you to decrease a lead’s score (and priority). For example, if a contact visits the employment page of your website, it is usually cause enough to subtract points from their lead score since job seekers aren’t exactly looking to purchase products or services.
Similarly, contacting people that unsubscribe from newsletters or marketing campaigns are not among a salesperson's highest priorities, so your lead scoring model might deduct points from that contact as well.
Lead Scoring and Marketing Analytics
As you can imagine, marketing analytics plays heavily into lead scoring. Having a business analyst that can work with both marketing and sales to identify patterns is important to getting a lead scoring model right the first time. Your analyst will be able to compare customer records with a lead's activity on your website, and can identify which activities lead to people become customers. Those activities are more valuable to your business, therefore their lead scores will be higher.
Check out our ebook on the 4 types of marketers you need on your inbound marketing team to learn a little more about the role of the analyst on your marketing team.
Automating Your Lead Scoring Model
Obviously, you aren't likely to score leads manually. Marketing automation software can aid in examining your contacts' profile and history, then assign a lead score accordingly. The lead score value then needs to be passed into your CRM system so your sales reps can use that intelligence as they work leads.
For example, HubSpot's CRM will show your sales rep a contact's lead score along with the contact record and complete list of interactions a contact has had with your website or email. HubSpot will also synch a lead score with Salesforce so your sales reps can get up-to-the-minute lead scores inside Salesforce.
Action item: Think about how lead scoring might help your sales team prioritize the leads they get. Properly researching and following up with leads can be a time consuming process. Could a lead scoring model empower your sales team to sell more?