One of the most common tripwires in the lead generation game is:
Wasting resources on leads that’ll never convert.
Luckily, you can use lead scoring to identify and pursue qualified leads in your sales cycle.
In this article, we’ll cover seven top-tier lead scoring best practices to identify who’s a tough sell or a hot lead 🔥.
We’ll also highlight a one-of-a-kind tool that helps you make the most of your customer base.
But before we start with our best practices, let’s explore the basics of lead scoring.
What is Lead Scoring?
Lead scoring determines which leads are most likely to purchase your offering.
It assigns scores to each inbound lead based on their activity and demographics.
Lower lead scores indicate a prospect should be nurtured further through marketing, deprioritized, or disqualified.
The higher the score, the closer a prospect is to becoming a qualified lead. These are prospects who are familiar with your product and ready to purchase.
At that point, sales can swoop in and close the deal.
The two main ways to do lead scoring are:
- Manual lead scoring: Making manual calculations to see which actions significantly affect your conversion rates. You can then design a scoring system accordingly.
- Predictive lead scoring: Uses machine learning to create and optimize a lead scoring system.
Predictive lead scoring is by far the easier and more effective method.
Here and some benefits of predictive lead scoring over manual lead scoring:
- A predictive tool can incorporate more data from more sources than humans can manually.
- It allows for complexities that identify the best leads instead of just sorting out the unqualified leads.
- You don’t have to worry about creating the perfect system, testing it, and troubleshooting it, which takes time and labor. A predictive scoring tool does it all for you and continually adapts itself to stay current.
But what data is used for lead scoring?
Well, that depends on the lead scoring model you choose.
A Brief Guide to Lead Scoring Models:
A lead scoring model is a system by which you evaluate and score your leads. Your scoring model should fit your unique business model and objectives, but that doesn’t mean you have to reinvent the wheel.
Your scoring model can use explicit scoring — assign points related to who your prospect is — and/or implicit scoring — assign points related to how a prospect behaves.
Below are a few data point types you can use to create your lead scoring models:
Explicit scoring data point types
- 👥 Demographic data: You can qualify leads if they match a certain persona. Incorporate this if you have a niche target demographic.
- 🏢 Company information: In B2B lead scoring, you may be able to qualify leads according to the type, size, industry, or location of businesses.
Implicit scoring data point types
- 🧑💻 Product usage signals: You can tell a lot from how prospects use your product — the number of features they use, how regularly they use it, etc. This in-app behavior data helps identify hot leads for free to paid conversions or account upgrades.
- 🖱️ Website interaction: Certain behavior on your website can hint at an intent to purchase or not (e.g., Number of visits, visiting the pricing page, filling in a form, requesting a demo, etc.).
- 📲 Social media engagement: It’s usually a good sign when potential customers interact with your social media content often, such as through likes, shares, positive comments, etc.
- 📧 Email activity: Promising leads may also show signs of interest in your email lead nurturing campaigns.
Note: You can leverage more than one of these data types in your lead scoring system.
So, are you ready to learn how to optimize your lead scoring process?
Great! Then let’s get into some best practices for your lead scoring strategy.
Seven Game-Changing Lead Scoring Best Practices
Below are seven pieces of advice to incorporate when designing your lead scoring system:
1. Target your Buyer Personas
Not everyone who sees your digital marketing material or visits your website will want or need your product.
One way to identify unqualified leads is to compare them to your ideal customer persona. A buyer persona is a fictionalized idea of a group of customers you wish to target. You can assign higher lead scores to those closely matching your buyer personas.
This can be based on information like their:
- Job title
- Decision-making power
For example, if your ideal customer is an executive at a manufacturing enterprise, you shouldn’t pursue a lead who’s a young engineering student.
At least, not just yet.
2. Tailor your Lead Scoring Criteria
How do you know which data types should inform the lead scoring criteria for your company?
Here are some tips:
- Examine your existing customers who’ve been through the sales process and note shared characteristics you could score positively.
- Speak to your sales team about trends they’ve noticed in leads that convert or drop off.
- Study those leads that didn’t convert and try to identify why based on their characteristics or actions. This is helpful for understanding when to assign a low or negative score.
3. Establish a Threshold Score
People generally don’t like to be contacted by sales before they’re ready to make a purchase.
A score threshold is a point value that indicates when a Marketing Qualified Lead may be ready to buy. It’s up to you to decide on a suitable threshold score based on your data.
Only when leads meet this threshold should you start pursuing them.
4. Assign Weight to Positive Actions
Here’s where we get to the most crucial part of any lead scoring strategy — the scoring 😜.
Sometimes a lead's behavior indicates they might be interested in purchasing.
And sometimes, their firmographic or demographic data indicates they would greatly benefit from using your product.
It’s your job to figure out scoring criteria for different actions and traits.
To do this, you can study your buyer journey and look for promising signifiers. Assign a higher point value to those more likely to result in a conversion.
Let’s look at an example:
Viewed your pricing page (10 points)
Clicked on a call to action (5 points)
Toggled between monthly and annual pricing (40 points)
Filled out a form to receive a content asset (5 points)
Matches your ideal buyer persona (30 points)
Is from North America (10 points)
Invited a team member (30 points)
Viewed your pricing page (10 points)
Total lead score = 110 👌
Total lead score = 30 😔
In this example, lead A has a higher lead score and may be a hot lead. Depending on your threshold, it could be time to refer them to a sales rep. Lead B, on the other hand, is far from where you’d want them to be.
5. Factor in Negative Points and Decay
Now, what if an inbound lead unsubscribes from your mailing list or doesn’t engage for several months? 🤔
Naturally, that should warrant a negative score.
Additionally, scores should start to decay after a long period of no engagement. So, establish time frames for your lead scoring system that suit the length of your sales cycle.
Here are some more examples of factors or actions that could warrant negative scoring:
- They don’t match your buyer persona.
- Your emails bounce.
- They visited your Careers page (indicates interest in a job, not your product).
- They’re from a competitor company.
Keep in mind: Negative scoring doesn’t disqualify your leads from being retargeted through digital marketing. It just prevents your sales team from wasting time and resources contacting unqualified leads for the moment.
6. Utilize Automation
You can use a lead scoring tool (e.g., Hubspot lead scoring) to help you automate the lead scoring process.
Of course, you’ll still need an idea of your target persona and scoring criteria.
But a lead scoring tool can:
- Calculate lead scores at scale.
- Automatically route a sales qualified lead to a sales rep when they hit the threshold.
- Automatically qualify or disqualify leads for certain actions (e.g., Requesting a demo = automatic lead qualification. Listing their occupation as “student” for an enterprise service = automatic disqualification).
You could also employ a predictive scoring tool, which can assign scores automatically with AI. The benefit of predictive lead scoring over manual lead scoring is that it improves its lead qualification algorithms over time.
7. Reevaluate your Lead Scoring System Regularly
Manual lead scoring shouldn’t be a “set it and forget it” process. You should regularly fine-tune your lead scoring model based on your performance data and growth metrics.
Here are a few growth metrics that can track the success of your lead scoring system:
- Conversion rate: A low conversion rate indicates that your lead scoring model misunderstands customer readiness and needs tweaking.
- MQL (Marketing Qualified Lead) to SQL (Sales Qualified Lead) conversion rate: If this percentage is low, it could mean prospects aren’t adequately qualified when sales steps in, or your threshold is too low.
- Net Promoter Score (NPS): Listening to customer opinions can help you understand what is and isn’t working in the lead nurturing process.
Important reminder: You don’t need to manually update a predictive lead scoring system. Predictive lead scoring tools use machine learning to adjust their algorithms automatically — no number crunching for you! 🔢
So, is lead scoring really worth doing?
Is Lead Scoring Right for Your SaaS Company?
Lead scoring can be time-consuming and challenging if you’re taking it on manually.
Plus, it’s not always worth it for every business. For example, if you’re a new startup, you may not have enough leads to construct an accurate scoring model. In this case, it would be better to focus on lead generation first.
Or, what if you’re a product-based SaaS company and you want to study product usage data to find more opportunities for upsells and cross-sells?
You may find that you’ve got lots of leads and good conversion rates, but you’re struggling to maintain a consistent, engaged user base — leading to a high churn rate.
If only there was a tool that could help you build a better pipeline, improve your win rate, and boost expansion 💭…
Wait, there is — it’s called Toplyne!
Get the Most Out of Your Lead Scoring Efforts with Toplyne
Effective lead scoring is about identifying the leads your sales team should focus on to drive conversions.
On the other hand, Toplyne is a unique headless sales AI that slots right into your existing CRM and GTM tools. It helps you discover qualified leads in your sales pipeline to improve both conversion and expansion.
How does Toplyne do this?
Toplyne leverages product usage signals for your free and paid users from your existing product analytics apps (Mixpanel, Amplitude, Segment). It then segments users based on their engagement so you can target them for conversion, retention, and expansion opportunities.
And best of all, it helps you experiment with various sales-assist strategies rapidly and at scale by providing highly-specific user data to your GTM tools!
To name a few:
➡️ Build a pipeline of product-qualified leads (PQLs).
📈 Improve your freemium conversion rates.
💸 Motivate paying users to upgrade.
🤩 Encourage a faster time-to-value and sustained engagement.
🛑 Prevent customer churn and encourage reactivation.
Here’s how it works:
- Create monetization playbooks to identify conversion and expansion opportunities.
- You can choose to target either individual users or accounts (groups of users in an organization)
- Toplyne segments your users into cold, warm, and hot leads, and you can choose which to target for different actions.
- You can then further segment and filter the target group and even set up control groups.
- Toplyne can then sync the data from your monetization playbooks with your GTM apps to execute highly-targeted outreach, and provide top-notch analysis of the results.
It can do all of this without any change management since it integrates seamlessly with tools like Hubspot, Salesforce, and Pipedrive.
At the end of the day, Toplyne helps match you up with customers who are a good fit, love your product, and want to commit 😍.
It uses evidence from users’ actions while using the free trial, freemium version, or even paid version. For example:
- Frequent product usage.
- Using multiple features.
- Trying premium features.
- Inviting team members.
- Viewing the pricing page multiple times or for a long period.
Then Toplyne enables you to reach out to these hot leads with the right messaging at the right time. For example:
- In-app nudges when they need help understanding features.
- Chatbot messages when they’ve reached a paywall.
- Calls to action to upgrade to a paid plan when their free trial is coming to an end.
This results in more conversions, less churn, and improved revenue expansion!
Score Your Leads and Delight Your User Base with Toplyne
Lead scoring can be a great way to understand which leads to focus on.
It can save your sales team a lot of time and resources from chasing leads that won’t ever convert.
As a result, effective lead scoring can help boost your conversion rates and growth metrics.
But do you want to turbocharge your product-led growth alongside your lead scoring efforts?
Toplyne can help you put the pedal to the metal! 🏎️💨
Toplyne empowers you to find undiscovered PQLs and identify how best to target them.
This way, you can say goodbye to churn and missed opportunities. Instead, welcome in higher revenue from premium conversions and upsells.
Sign up for Toplyne for free today to discover how to transform your sales process, turning promising leads into long-time supporters.