Make the Most of Your Lead Lifecycle Management
Not all leads are created equal. Most organizations have lifecycle stages where leads move from lead to MQL to SQL to opportunity and finally customer. This level of labeling and staging is critical, but it’s only the tip of the iceberg in terms of how effective you can be with lead nurturing and sales engagement. Let’s dive into MQLs, SQLs, lead scoring, and why it matters.
MQL versus SQL
A marketing qualified lead (MQL) is a lead that has interacted with a marketing initiative and meets some set of qualifications. Those qualifications can depend on your organization’s goals but usually boils down to: 1) the lead isn’t spam 2) they look like a quality potential customer you’d like to target. MQLs haven’t interacted with your sales team yet and have not been vetted or qualified by sales specifically.
A sales qualified lead (SQL) is a lead that is ready to speak to sales. The biggest difference between the two is intention stage. MQL needs to be nurtured by marketing initiatives, learn more about your organization, and conduct additional research. But an SQL is ready to buy. In addition to stage, some organizations have further vetting by sales to ensure these leads are appropriate for sales follow-up.
The MQL to SQL stages might seem like enough but having an established and defined lead scoring process can help both teams be more efficient and effective.
What is Lead Scoring?
Lead scoring is the process of assigning values (or points) to each lead. You can then designate what value a lead must reach to become an MQL and SQL. So lead scoring doesn’t replace MQL and SQL, it compliments it. This is especially vital to organizations that have many leads, very busy marketing and sales teams, and specific marketing and sales goals.
Lead Scoring Models
To integrate lead scoring into your lead process, marketing and sales teams must determine what lead scoring model they’re going to use. Many models are based on a point system that ranges from 0 to 100 (but others can range significantly over 100). Major CRMs have lead scoring tools that can be integrated with the rest of the lead scoring capabilities. These tools will help guide organizations into defining their own model. Good lead scoring models must be personalized to your teams’ and business needs.
Lead scoring models are based on multiple qualities and behaviors of a lead. A common way to group these characteristics are as explicit points, implicit points, and negative points.
Explicit Points
These are points given on specific qualities of a lead such as company size, company revenue, job title, industry, geographic location. If we’re an organization that only targets large businesses, then having a lead that is a manager at a 5-person company might not be a lead we prioritize. If our major goal is boosting business in the northeast because we’re west coast heavy and overloaded in that region, then a lead that comes in from California might not be the lead sales should follow up with ASAP.
Implicit Points
Qualities about the lead’s organization and demographics should not be the only characteristic used for lead scoring because where they are in the funnel matters. Implicit scores should be given based on behaviors. Have they visited the website 3-5 times? Have they opened marketing emails? Have they clicked on lower funnel CTAs? Have they requested to be reached out to by sales directly? These are all great criteria for moving them into an MQL or an SQL stage depending on their actions.
While a prospect is usually only given explicit points once, a lead might have implicit points added multiple times based on different and additional behavior.
Negative Points:
Another scoring factor to consider is negative scoring. This actually removes points from the lead score based on lack of interest. Leads can go from hot to warm to cold, and you can track that based on activity or quality changes. Did they unsubscribe from your email list? Did they change title or industry to something not in your target list? Have they just not had any activity with your organization for 6 months?
A Lead Score Example
John Doe
Title: Vice President of Operations = +20 Points (Explicit)
Industry: Manufacturing = +5 Points (Explicit)
Company Size: >1,000 = +15 Points (Explicit)
Visited Website = +3 Points (Implicit)
Downloaded Case Study = +15 Points (Implicit)
Total Lead Score: 58 Points out of 100, MQL within this hypothetical model
If Mr. Doe visited a pricing page or filled out a contact us form then, likely he’d move into SQL territory. If Mr. Doe unsubscribed to emails, he’d lose points and you might deprioritize next steps with him in your marketing campaigns.
Make the Most of Your Lead Scoring
Lead scoring helps marketing and sales teams work smarter and meet goals using smart data. Focusing first and foremost on your most qualified leads saves time for everybody. Additionally, sophisticated lead scoring can help both sales and marketing teams know what the best next step is in their process in terms of either marketing campaigns or sales conversations.
Setting up and maintaining lead scoring takes time, and it’s also not a one and done process. Quality lead scoring takes continuous maintenance. If you need help setting up or improving lead scoring processes or integrating sales and marketing teams in aligned lead generation strategies, we can help. Cimarron Winter helps organizations adopt strategies, processes, and tools that can take their lead management to the next level.