Following best practices for lead scoring will ensure that your leads are nurtured in timely and helpful ways. If done correctly and with care, you and your sales team will drastically increase your chances of converting prospects into delighted customers.
Across the board, "the more the merrier" applies to aggregating data to better inform how we interact with leads, prospects, and customers. The purpose of lead scoring is to collect as much data as possible for any given lead, then assign point values based on that information in order to qualify and prioritize leads.
Demographic segmentation involves assigning gathered personal information to your contacts. Examples of demographics include age, gender, political affiliation, income, and more. The more you know about your contact, the better equipped you'll be to nurture them. Demographic information will inform everything from your sales outreach process, to your marketing initiatives, to customer retention.
Company information for any given lead can help you and your sales team strategize the language and means of your outreach. Nurturing a lead at a Fortune 500 corporation will look much different than nurturing a lead at a 10-person company. If accessible, knowing the company's revenue can help you predetermine the best offering when your prospect reaches the decision stage in their buyer's journey.
Does your lead (and their company) have an active digital presence? Find more information on how your lead interacts with the web — find their social channels and discover their blog content. You might be able to uncover pain points, giving you the opportunity to add value to their digital experience and start building trust.
Dig deeper into how your lead engages with your emails. Do they open them multiple times, or do they leave them unread? Depending on how your lead interacts with you, you'll get a better sense of when to ramp up communication or when to ease up.
Check out whether your lead is engaging with your company on social media. This is a great way to gauge their interest in your company's offerings. If your lead is active on social media and posts often, this is a great opportunity to have a more candid and informal conversation with your prospect to start building rapport and trust.
Consider all of the above points when setting up lead scoring. When leads reach a specific point value, or threshold, they are considered a qualified lead and should be routed to sales. Ideally, the routing process should be triggered automatically. Knowing when to reach out to a lead can help salespeople focus their attention on the right leads at the right time, thus increasing their productivity and success rates.
Once you've gained a better understanding of what types of information go into building your lead's contact record, you'll be ready to set up your lead scoring criteria. To be sure that your scoring is correct and consistent, follow these tips below:
Real data on your prospects may take longer to find, but it's generally worth it to determine the best ways to communicate with, and ideally delight your prospects so much so that they give you their business.
Additionally, data helps to remove human biases that could affect your team's outreach. You can find data from their demographics, attribution reports, social media, industry knowledge, and more. Get creative! Your efforts will be rewarded when your lead turns into a sale.
This will allow you to further define the scores assigned to each prospect, and make sure they accurately reflect a prospect’s fit and/or interests. An effective way to do this is to use calculated scores to merge multiple score models into one. Examples of this include:
When it comes to lead scoring, not all activities are made equal. Your lead will score higher if your analytics show they are seeking out high-value parts of your company's website. Examples of high-value actions/engagements include:
While an email open does indicate some measure of engagement with your brand, it can mean a lot more than a lead is sales-ready or a good fit for your product/services. To avoid over-inflating lead scores, assign a point value after an initial number of emails have been opened, account for a combination of opens and clicks, or even look at submissions or page views generated from the email.
Lead scores that rely solely on positives as a means of scoring lead to score inflation. In order to offset score inflation, you must apply the necessary negative attributes to any given lead to help decrease scores based on inactivity or lack of fit. There are many ways to combat score inflation. An easy one is to include industries you don't serve as negative scoring criteria.
If your contacts don’t stay engaged, they’re likely not interested in talking to your sales team and shouldn’t be considered a qualified lead after a certain point. Scores should decrease over time to reflect that. Determine a specific amount of time after which inactivity will dock points from a lead score. Your point decay rate should be set based on the length of your sales cycle.
An example of point decay for a 6-month sales cycle would look like:
Having a lead score threshold in place ensures that leads are only getting assigned to sales for outreach when they’ve met a qualification threshold that your sales team has agreed upon. This makes it easy for sales to prioritize the leads that are most qualified, and takes the guesswork out of lead assignment for the marketing team.
Thresholds should be set to mark a contact as an MQL and route the contact to sales at the right time. Beyond that, don’t use Lead Score to define Lifecycle Stages (SQL, Opportunity, etc). These later stages should be set based on where a contact is in your sales process, not an automated scoring model
Revisit your lead scoring model on a regular basis to ensure that you’re not qualifying leads too soon or too late. If you are qualifying tons of leads but your sales team isn’t converting many of them, you aren’t qualifying leads enough before handing them over to sales, i.e. your threshold may be too low. Look at your conversion rates for MQLs to SQLs, and SQLs to customers!
Now that you've learned the best practices for building your own custom lead scoring model, it's time to build your own! A custom lead score model will create an organized system to help deliver relevant content according to your prospect's position in the buyer's journey. Not sure where to start? We can guide you through the process. Schedule time with our team below to get started.