Modern technology has drastically improved digital marketing efforts. Thanks to marketing automation, marketing departments no longer handle monotonous chores like individually sending out emails, planning out call lists, or manually creating sales reports. Despite its benefits, countless marketers have failed to capitalize on lead scoring.
What Is Lead Scoring?
Attracting new customers is an essential function of marketing departments. To guide potential customers through the sales funnel, they track leads, consumers who have shown interest in a company's products or services. Neglecting these potential customers is nearly equal to throwing money away.
Many leads show up on marketers' radars after company representatives reach out to suppliers or other B2B partners for price quotes, availability and product information. Although some of them trickle all the way through the sales funnel, most have no intention of buying goods or services.
When it comes to leads, separating the proverbial wheat from the figurative chaff is essential. Without grading the quality of leads, companies unknowingly waste resources.
Lead scoring is a method of valuing leads that involves assigning points based on sales-readiness. Contemporary lead scoring rarely uses single qualities or characteristics to rank potential customers. Instead, this process typically uses numerous variables to evaluate lead quality.
Developing lead scoring systems has proven valuable to business software creators. Large corporations often create their own proprietary models for scoring leads. Regardless of any company's or developer's specific methodology, the majority of these systems use in-house data from previous leads, both converted customers and their uninterested counterparts.
Lead Scoring Is All About Information
In today's advertising climate, there's no shortage of information. Application developers, website designers, and social media platform moguls designed this overflow of consumer data on purpose. Some have likened this data to oil as the next major commodity.
Without data, automated lead scoring wouldn't be possible. There are two major types of data in lead scoring: explicit and implicit.
Explicit data is information that's undeniably, unquestionably true. In other words, there's no guesswork involved with explicit information.
Collecting demographic is an essential part of digital marketing. Company representatives are used to providing their own details and corporate information to potential business partners. Thanks to this standard business practice, companies have few problems collecting this information.
When it comes to business-to-business commerce, the main types of demographic information include:
- Company revenues
- Representatives' seniority
- Geographic location
- B2B or B2C status
Some marketers receive leads' demographic data from other marketers. Although potentially costly, paying third parties for certifiable, already-collected demographic info simplifies data collection and may improve the accuracy of data. Data appending, as it's known, shortens the length of sales funnels without sacrificing important information.
Lead Source Information
Estimating lead quality is much easier when source data is available. Gathering this information is usually fairly simple. Companies create hidden functions for websites, emails, and mobile apps that automatically record their leads' origination points.
Companies also use surveys to collect source info, though participants might not answer correctly. That's why automatic data collection — the functions mentioned above — is so popular.
Using Explicit Data for Lead Scoring
Every company will value demographic and lead source information differently. Marketing departments that model their explicit lead scoring after others' models may receive less value from this tried-and-true digital marketing practice.
One of the most effective strategies for utilizing this information is developing average buyer profiles. With nothing more than basic data about companies' size or industry and their representatives' seniority or department, marketers can fit new leads into these profiles with limited information.
Companies that sell multiple types of products or services should use multiple personas. HubSpot suggests using separate lead scoring models for assessing how fit buyers are for each product or service offering and how much interest leads have in them.
Unlike its black-and-white, binary counterpart, implicit scoring isn't so easy. In simple terms, this lead scoring method analyzes consumer behaviors to determine lead quality.
Marketing Email Engagement
Virtually every company uses email marketing to interact with leads and established customers. For B2C purposes, consumers often glaze over emails. However, in the B2B realm, company representatives check and read their emails much more religiously.
Collecting data through emails is easy. Modern marketing platforms automatically record email open rates and email clickthroughs, for example.
Internet Use Behavior
Internet browsing behavior can be broad. Types of Internet use behavior marketers collect include:
- The number of web pages visited.
- Types of web pages visited.
- Attendance at company webinars.
- Requests for free trials.
- Downloads of whitepapers, guides, and other web content.
B2B companies often find that prospective buyers visit multiple web pages in certain orders before progressing through the sales funnel. Using this information, marketing departments may earmark leads with average buyer profiles using web page progressions.
Social Media Engagement
Not all leads will interact with companies' social media pages. However, for those that do, collecting social media engagement data is a must.
Although these statistics aren't available to consumers, most social media platforms provide businesses with advanced engagement information. For example, companies usually have access to lists of post views by name, whereas consumers only have numerical view counts.
Marketing automation platforms can readily be connected to companies' social media profiles to collect information in real-time. Businesses may append this free data by purchasing high-level, complex information about leads from social platforms.
Placing Numerical Values on Lead Characteristics
Companies should avoid following stock lead scoring models to value their potential leads. Basing lead scoring off of industry competitors' methods, however, is acceptable.
Marketing departments should work with sales staff to develop average customer profiles and solidify lead score values.
Using negative scores is common among lead scoring models. For example, a company may reduce a lead's score for unsubscribing from an email list or having a bottom-tier job title.
Ultimately, revising lead scoring models is the key to success. Although devising a model that works can take time, lead scoring remains one of the digital marketing industry's leading tools.
Our team of Marketing Automation specialists have lots of experience in Lead Scoring. Download our eBook, "How To Audit Your HubSpot Instance," to learn more about how Lead Scoring utilization can grow your bottom line.