What is lead scoring? a complete guide with 8 practical steps
What is lead scoring? A complete guide with 8 practical steps
Unlock the secrets to boosting your sales efficiency with our complete guide to mastering B2B lead scoring, packed with expert tips and actionable steps.
Identifying and prioritising high-value prospects is crucial for any sales team. This process, known as lead scoring, helps businesses focus their efforts on leads that are most likely to convert – maximising efficiency and revenue.
Stay with us as we delve into lead scoring, and offer expert tips on building, automating, and refining your lead scoring model.
B2B lead scoring definition and benefits
Lead scoring is a way of assessing the quality of your leads and examining their likely value to your business. It involves a systematic process of assigning a value to your leads, based on various attributes such as their behaviour, demographics, and firmographics.
These values help sales and marketing teams determine a lead’s potential to become a paying customer. Teams can then use this score to focus more on high-quality leads or disqualify others from further lead nurturing.
Lead scoring benefits
The primary benefits of lead scoring include:
- Increased sales efficiency: By prioritising high-value leads, sales teams can focus their efforts where it matters most.
- Improved marketing strategies: Marketing teams can tailor their campaigns to attract high-scoring leads.
- Better alignment between sales and marketing: Consistent criteria for evaluating leads ensure both teams are on the same page.
- Higher conversion rates: Focused efforts on high-potential leads typically result in higher conversion rates. Result!
Key attributes for effective lead scoring
So, how do you sort unqualified leads into ready-to-buy potential customers? To create a lead scoring model, you first need to decide on the factors and actions that matter, and that mark someone out as a good fit for your business.
Demographic factors
Demographic attributes refer to the characteristics of the individual lead, such as age, gender, job title, and income level. These factors can indicate whether a lead falls within your buyer personas.
Firmographic factors
Firmographic attributes are all about the characteristics of the lead’s company, such as industry, company size, and revenue. These factors help determine if the lead’s company fits your ideal customer profile.
Engagement data
Engagement attributes track the lead’s engagement with various touchpoints. This will include email opens, content downlaods, and interacting with your social posts. These factors indicate that they are engaged with your content and currently hold a level of interest.
Buyer intent data
Buyer intent data is a growing area of sales and marketing intel. It reveals previously hidden actions that show when a prospect is displaying purchase intent, like visiting your website repeatedly, or viewing key pages like pricing.
An 8 step B2B lead scoring model
So how do you actually implement all this in a real world scenario? We’ve outlined an eight step plan to take you through our lead scoring best practices, with actionable steps and key recommendations.
Step 1: Align sales and marketing teams
Every effective lead scoring method starts with close collaboration between sales and marketing teams. Establish regular meetings to discuss what makes a good lead, to share insights, to discuss demos, and quality from different channels. The idea is to ensure that both teams are aligned in their understanding and application of the lead scoring model.
Create a feedback loop where the sales team can share their experience on the quality of leads. If your CRM can record sales calls, get the marketing team to regularly watch a sample. This feedback is essential for refining and improving the lead scoring model’s accuracy.
Step 2: Define your criteria
Begin by identifying the key attributes that signify a high-quality lead. Collaborate with your sales and marketing teams to gather insights and establish a comprehensive list of criteria.
Real-world tip: Use surveys or direct feedback from your best customers to understand the attributes that led them to choose your product or service. This can help you refine your criteria further.
Step 3: Choose a scoring model
In order to implement a lead scoring model, you need to turn your defined criteria into point values, and then into actionable insights. Here’s how to effectively set up your process:
Choose a model
First, decide on the scoring model that suits your needs. You can opt for a simple linear model where each factor has equal value or a more complex model that assigns different values based on the importance of each attribute. For example, a lead’s job title might carry more weight than their geographic location.
Integrate data sources
Ensure your scoring model pulls data from all relevant sources. This includes website analytics, CRM systems, email marketing platforms, and any other tools that capture lead interactions. Integrating these sources allows for a comprehensive view of each lead’s engagement and potential value.
Step 4: Assign point values
Unless you are going for linear model, you’ll need to assign point values to each factor based on its importance. For instance, downloading a whitepaper might be worth more points than opening an email, as it indicates a higher level of interest.
- Engagement and intent points: Assign more points to actions that indicate stronger intent, such as downloading a whitepaper, requesting a demo, or attending a webinar. For example, downloading a whitepaper might be worth 10 points, while opening an email might be worth two points.
- Demographic and firmographic points: Allocate points to demographic and firmographic factors that match your ideal customer profile. For instance, leads from companies with over 500 employees might get eight points, while C-level executives might get five points.
| Factor | Points | Explanation |
|---|---|---|
| Job title: C-suite or senior sales/marketing role | +5 | Prospect fits buyer persona |
| Company size: Over 500 | +8 | Fits the ideal customer profile |
| Downloaded a whitepaper | +10 | Indicates strong interest in your expertise |
| Attended a webinar | +15 | High engagement, shows commitment |
| Visited pricing page | +20 | Clear buying intent |
| Filled out a contact form | +40 | Ready to engage directly with your sales team |
| Unsubscribed from newsletter | -10 | Shows disinterest, decrease lead quality |
Real-world tip: Regularly review and adjust point values based on lead conversion data. If you notice that certain actions or attributes are more predictive of conversion, increase their point values accordingly.
Step 5: Incorporate negative scoring and score decay
Negative scoring is the practice of deducting points for behaviours that indicate a lack of interest or poor fit. For example, if a lead unsubscribes from your newsletter, their score should decrease.
Score decay is the gradual reduction of a prospect’s score over time if they do not engage with your brand. This ensures that your lead scores remain current and reflective of the prospect’s most recent behaviour.
Step 6: Set a lead-scoring threshold
Setting a threshold score helps you decide which leads are qualified and ready for the sales team’s follow-up. To determine an appropriate threshold, analyse the scores of leads that have successfully converted in the past and set your threshold slightly below this benchmark.
Review and adjust your threshold regularly based on performance data and any changes in your sales and marketing strategies. After all, testing performance and optimisation are the keys to a great sales strategy!
Step 7: Implement your model
Automate with software
Integrate your lead scoring model into your CRM or sales automation platform. CRM platforms like HubSpot and Salesforce offer built-in scoring functionalities. These tools can automatically update lead scores based on the interactions and data points you’ve defined, saving you time and ensuring accuracy.
Automating your B2B lead scoring processes offers several benefits:
- Efficiency: Automated systems can process large volumes of leads quickly and accurately.
- Consistency: Automation ensures that all leads are scored based on the same criteria.
- Scalability: Automated systems can easily scale with your business as leads grow.
Step 8: Test, learn and refine
Your lead scoring model should be subject to continuous improvement. Use data analytics to track performance. Analyse metrics such as conversion rates, lead-to-customer time, and lead quality at different score levels to identify areas for improvement.
Solicit feedback from both the sales and marketing teams regularly. Their insights on lead quality and scoring criteria are invaluable for refining the model. Use the data and the feedback to refine your criteria and scoring system regularly.
Common mistakes to avoid in lead scoring
Overcomplicating the model
Avoid making your lead scoring model too complex. A model with too many criteria can be difficult to manage and may lead to inconsistent scoring.
Ignoring negative scores and decay
Neglecting to incorporate negative scoring and score decay can result in inflated lead scores and a less accurate reflection of lead quality.
Lack of alignment
Ensure that your sales and marketing teams are aligned in their understanding and application of the lead scoring model. Misalignment can lead to confusion and reduced effectiveness.
A key component
Mastering lead scoring qualifies high-value prospects in order to maximise marketing and sales teams’ efficiency.
By understanding the key attributes, building a robust model, incorporating automation, and continuously refining your approach, you can ensure that your lead scoring strategy drives business success.
Remember, the ultimate goal is to focus your efforts on the leads that are most likely to convert, resulting in higher revenue and a more efficient sales process.
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