- Understanding Lead Scoring: Lead scoring is a methodology used to rank prospects against a scale that represents the perceived value each lead represents to the organization. The resulting score is used to determine which leads a receiving function (e.g. sales, partners) will engage, in order of priority.
- Choosing Scoring Criteria: Work closely with your sales team to identify the actions and attributes that truly indicate a quality lead. These might include:
- Behavioral data: Website visits, email engagement, content downloads, webinar attendance
- Demographic data: Job title, company size, industry
- Firmographic data: Annual revenue, number of employees, location
- Point Values: Assign point values based on the importance of each action or attribute. More significant actions (like requesting a demo) should be worth more points than less significant ones (like opening an email).
- Negative Scoring: Don't forget to incorporate negative scoring. This helps to keep your scores current by reducing points for inactivity or for actions that indicate a lead is not sales-ready.
- Testing and Refining: Your initial scoring model will likely need refinement. Monitor how well your scores correlate with actual sales outcomes and adjust accordingly.
- Integration with Sales Process: Ensure your sales team understands what the lead scores mean and how to use them. You might want to set up automatic notifications or tasks for sales when a lead reaches a certain score.
- Dynamic Scoring: Remember that lead scoring should be dynamic. Scores should be able to go up and down based on ongoing behavior and changes in attributes.
- Multiple Scoring Models: As you become more advanced, you might want to create different scoring models for different products, services, or buyer personas.
- Avoid Over-Complication: While it can be tempting to create a very complex scoring model, start simple and add complexity only as needed. An overly complex system can be difficult to maintain and explain to stakeholders.
- Regular Reviews: Plan to review and update your lead scoring model regularly (perhaps quarterly) to ensure it remains aligned with your business goals and accurately predicts sales-readiness.
Remember, effective lead scoring can significantly improve the efficiency of your sales process by helping prioritize leads and ensuring sales teams focus on the most promising opportunities. Good luck with setting up your lead scoring workflow!
Real World Scenerio
Lead Scoring for a B2B Software Company
Let's take the example of a B2B software company, TechSolutions, that offers a project management tool designed for medium to large enterprises. Their marketing team uses HubSpot lead scoring to identify which leads are most likely to convert into customers.
- Step 1 - Scoring Criteria: TechSolutions works with its sales team to define the most valuable lead attributes and behaviors. They agree on the following key criteria for scoring:
- Behavioral Data:
- Website visits to the pricing page (+10 points)
- Downloading an eBook or case study (+5 points)
- Attending a webinar (+15 points)
- Requesting a demo (+25 points)
- Demographic Data:
- Job title: C-level or VP (+20 points)
- Job title: Manager (+10 points)
- Firmographic Data:
- Company size: 100+ employees (+15 points)
- Industry: Technology or Finance (+10 points)
- Location: US-based (+5 points)
- Negative Scoring:
- No activity for 60 days (-10 points)
- Job title: Student or Intern (-20 points)
- Unsubscribed from marketing emails (-30 points)
- Behavioral Data:
- Step 2: Assigning Point Values: TechSolutions assigns higher point values to actions that indicate strong buying intent, like requesting a demo (+25 points), compared to actions that show moderate interest, like downloading a case study (+5 points). Similarly, higher-level job titles such as VP or C-level are worth more points than lower-level roles.
- Step 3: Testing and Refining the Scoring Model: After implementing the lead scoring model, the marketing team monitors the correlation between lead scores and actual conversions. They notice that leads who attended a webinar but didn't request a demo often convert later in the process, so they increase the score for webinar attendance from +15 to +20 points.
- Step 4: Integration with Sales: The marketing team sets up automated HubSpot workflows to notify the sales team whenever a lead's score exceeds 60 points. At this threshold, the lead is considered "sales-qualified" and ready for direct outreach. A task is automatically assigned to the relevant sales rep.
- Step 5: Dynamic Scoring: The lead scores are dynamic, meaning that if a lead stops engaging (e.g., no activity for 60 days), their score decreases by 10 points. Conversely, if a lead re-engages by visiting the website or attending a webinar, their score increases accordingly.
- Step 6: Regular Review and Optimization: Every quarter, the marketing and sales teams review the lead scoring model. After analyzing sales data, they find that job title has been overemphasized. While many C-level contacts did convert, the largest deal came from a department head. They adjust the scoring model to give department heads more points and lower the points for C-level roles slightly.
Outcome: By refining their lead scoring model, TechSolutions ensures that the sales team focuses on high-quality leads. This leads to a 20% increase in sales-qualified leads (SQLs) and a shorter sales cycle, as sales reps can engage with leads at the right time.
Best Practices
- Start with a simple scoring model and refine over time
- Align scoring criteria with your sales team's definition of a qualified lead
- Regularly review and update your scoring model based on actual sales outcomes
- Use both positive and negative scoring to keep scores current
- Consider using different scoring models for different product lines or buyer personas
Remember to communicate the lead scoring system to your sales team and provide guidance on how to use the scores effectively.
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