?? Demystifying & Building a Lead Scoring Model for SaaS companies

In the high-octane world of a burgeoning SaaS business, lead scoring forms the vital link between your marketing and sales endeavors. It is arguably one of the most challenging concepts to land on because of the constant tension between sales and marketing teams that want to get the right attribution in order to get the credit for the lead and conversion of it. And rightfully so, because both teams want to be measured on a specific KPI and want to deliver a successful result against it!

Lead scoring is not simply about attaching a numerical value to each lead; it's about grasping the nuances of your customer's journey and recognizing the crucial behaviors signaling a strong conversion propensity.

As a CMO, CRO, and CEO, here's a detailed, iterative model that you can implement to ensure lead scoring becomes your secret weapon:

1?? Define Scoring Criteria: In tandem with your marketing and sales departments, delineate what defines a 'qualified' lead. Demographic information such as job title or industry might be worth between 1-10 points, while behavioral data like a whitepaper download or webinar attendance could garner 10-20 points. In this stage, consider the customer journey touchpoints that best signal buying readiness. These can be signs of engagement (repeated website visits, newsletter sign-ups), content interactions (downloading ebooks, viewing pricing pages), or explicit inquiries (contact form submissions, demo requests). Ensure each touchpoint is assigned a value reflective of its indication towards sales-readiness.

ACTIONS:

• Demographics: Focus on key demographics that align with your buyer persona, such as industry, company size, job title, or geographic location.
• Behavioral Indicators: Use metrics such as website visits, time spent on site, downloads, form completions, email clicks, and social media engagement.
• Explicit Indicators: These include actions that signal clear buying intent, such as requesting a product demo, signing up for a trial, or filling out a contact form.
• Email Engagement: Track metrics such as email opens, click-through rates, and email responses to gauge interest.

2?? Assign Lead Status: Depending on the cumulative score, assign a lead status. For instance, 0-20 points may constitute a 'Marketing Qualified Lead' (MQL), to be nurtured by marketing, while 21-50 points designates a 'Sales Accepted Lead' (SAL), where sales initiates the engagement. Scores of 51+ could indicate a 'Sales Qualified Lead' (SQL), ripe for a direct sales approach. The scores corresponding to each status should be determined by the statistical analysis of your lead conversion data, ensuring an objective and data-driven approach.

ACTIONS:

• Identify Trends: Analyze your historical data to identify the behavior patterns associated with each stage of the lead lifecycle.
• Customize Lead Status: Create a lead status taxonomy that reflects your unique sales cycle and customer journey.
• Monitor and Adjust: Regularly revisit the lead statuses to ensure they're still effective and tweak them as needed based on new insights.

3?? Distinguish between a Good Lead and a Bad Lead: A good lead consistently interacts with your content, exhibiting buying signals like demo requests or pricing inquiries. A bad lead, on the other hand, may engage in an initial download but shows no further interest. For the latter, consider strategic nurturing campaigns to reinvigorate their interest. For the former, propel them directly to sales for an expedited pitch. Your understanding of a 'good' or 'bad' lead should be fluid and adapt as you gain deeper insights into your customers' buying behaviors and the success of your sales conversions.

ACTIONS:

• Engagement Levels: Monitor the frequency and quality of a lead's engagement with your content and sales team.
• Buying Signals: Track clear buying signals such as requests for pricing information or product demonstrations.
• Fit: Assess whether the lead fits your ideal customer profile based on demographic data and behavioral signals.

4?? Set Lead Attribution Guidelines: To preemptively counter conflicts over lead attribution, establish clear rules. If a dormant lead re-engages due to a marketing campaign after six months, attribute the success to marketing. However, if sales have been consistently engaging with the lead, they should receive the credit. The attribution model should be founded on transparency and clear communication between the two teams, facilitating harmony and shared objectives.

ACTIONS:

• Establish Clear Rules: Define the parameters for attributing leads to either the marketing or sales team.
• Transparency: Ensure the lead attribution process is transparent and that both teams understand and accept the rules.
• Continual Communication: Encourage regular communication between teams to discuss and resolve any attribution issues.

5?? Adopt a Data-Driven Strategy: Harness the power of your CRM (because you're already paying an arm and leg for it) and marketing automation tools to track and analyze customer behavior. This data will be crucial in informing and refining your lead scoring model. Supplement this with advanced AI tools that can process vast amounts of data and draw meaningful insights to augment your lead scoring model's accuracy and efficiency.

ACTIONS:

• Leverage CRM and Automation Tools: Utilize these tools to collect and analyze data on leads and customers.
• Predictive Analytics: Consider using predictive analytics to identify potential high-value leads based on historical data.
• AI Tools: Use AI tools to process large amounts of data and generate insights that can improve lead scoring (there are an incredible number of tools out there now).

6?? Periodically Review and Refine: Your lead scoring model should evolve in tandem with your business growth and market trends. Regularly review the model to ensure it's accurately identifying high-quality leads. This could involve A/B testing different scoring models, updating the lead score triggers based on new product features or market demographics, and recalibrating the scores based on shifts in your sales cycle or customer behaviors.

The ultimate objective of lead scoring is to prioritize leads with the highest likelihood of conversion. This not only boosts your sales team's efficiency but also becomes a potent tool for driving growth in a SaaS business.

ACTIONS:

• Track Changes: Monitor changes in customer behavior, sales cycle, and market trends to adjust your lead scoring model accordingly.
• Feedback: Regularly gather feedback from the sales team to understand how accurately the lead scoring model is predicting sales readiness.
• Test and Tweak: Continually test and tweak the scoring criteria and weight based on the insights you gain.

My ask this time from you, if you found this article to be effective, is:

1. Tag your CRO or CMO who is working on your lead scoring model in the comment section below
2. Subscribe to the newsletter and share!

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