- 25.9% of marketers mentioned that one of their biggest challenges was understanding the quality of leads.
- Lead scoring models boost marketing efforts and help you better qualify to classify relevant leads to your business.
- Creating a custom lead scoring model can help your business to qualify leads better, as the model will be catered to your requirements.
In a scene of the movie “The Wolf of Wall Street,” Jordan Belfort, a successful stockbroker, addresses his sales team upon dealing with their failure and motivates them to sell more stocks.
One of the brokers in the team complains about the poor quality of leads.
Then, Belfort replies by promising to give the best leads to the top-performing sales reps of the week. This has created competition among the sales team, as all sales brokers will now hustle to be the best performer to get high-quality leads.
This movie scene typically indicates that having quality leads is important to get the conversion.
According to the 2021 Marketing Attribution and Reporting Analysis, 25.9% of marketers mentioned that one of the biggest challenges they faced was understanding lead quality.
25.9% is a considerable percentage for any business. However, if leads were scored, they could easily qualify the leads that are valuable and have a high conversion rate.
This blog covers top lead scoring models in the market and how a lead scoring model can help you identify and prioritize the best prospects for a business.
But before we explore the models, let’s look at the nitty-gritty of it.
What is a lead scoring model & how can it help you qualify better leads?
The lead scoring model basically means a framework to qualify leads based on specified criteria.
The criteria are dynamic and are decided based on factors such as;
- How much interest are prospects shown towards our product/services?
- Which industry your prospect belongs to? (For B2B businesses)
- Where does your prospect live?
- Do they have the relevant affordability budget?
- What are the varied time frame audiences you have?
And many more precise factors that are unique to your business.
Fundamentally, lead scoring models are based on certain criteria. Here are a few examples.
Now, every time a criterion is fulfilled, a few points are assigned to the lead. Let’s understand with an example, suppose you are selling an email marketing tool as your product.
And lead with a 70+ score is an SQLs for you.
Now, if any prospect performs the following action on your website, you score them for each step taken.
Visited your pricing page- 15 points
Downloaded a product knowledge eBook- 10 points
Signed for a product webinar: 20 points
Signed up for a free trial- 20 points
Opened your sales and marketing email- 10 points
So, a total of 75 scores is given to that lead and automatically qualifies as SQLs.
This means once a lead reaches the point threshold you set, it is considered qualified.
Also, lead scoring is not bound to just marketing. Sales teams also leverage them to evaluate sales-qualified leads.
5 most popular lead scoring models in the market
Let’s take a look at various models to score leads, and then you can decide on which model is the ideal fit for your organization:
Note: Pricing mentioned in the above table is subject to change.
1. Oracle Eloqua lead scoring model
The Eloqua lead scoring model by Oracle evaluates primarily two factors:
- Profile criteria: This criterion focuses on the demographic data of the lead, i.e., the job title, company information, value of the deal, and more. This is also known as explicit data of a lead. After evaluation, the lead is given a profile score of A, B, C, or D.
- Engagement criteria: This criterion focuses on the lead’s behavioral information, such as how long they spent on the website and how responsive they were to ads on social media. This is also known as the implicit data of a lead. After evaluation, the lead is given an engagement score of 1, 2, 3, or 4.
Post the score evaluation of profile and engagement, both of the scores are combined, and a score is assigned to the lead. With A1 being the most qualified & D4 being the least qualified.
2. Adobe Marketo lead scoring model
The Marketo lead scoring model also operates similarly to the Eloqua model. However, it also uses implicit and explicit information in lead scoring.
But, with Marketo, it assigns certain set points for each action taken by the lead.
In this model, Marketo assigns a score between 0 – 30 points for demographic attributes:
- 1 point for page visited or email opened
- 15 points for searching “Marketo Engage” on Google
As positive points are assigned to leads, there is also a concept called ‘negative scoring’.
Just like you add points to a lead score in positive scoring, in negative scoring, you remove set points from the score for performing undesirable actions.
So, in Marketo, – 50 points are assigned if one were to unsubscribe from email lists, – 10 points for an entry-level job title, and so on.
Ergo, here is how Marketo moves forward with a lead in the Sales Pipeline.
Leads with less than 65 points are classified as “prospects” for nurturing, while those with more than 65 points are classified as “sales-worthy leads” and further handed over to the sales team for conversion.
3. Lead Pilot
Lead Pilot, an inbound marketing tool, has built one of its own lead scoring model. It operates under the core premise that the greater a lead’s score, the more qualified it is. The scoring range is from 1 to 100.
Its algorithm considers multiple factors such as page visits, time spent on each page, actions taken, the lead’s engagement with content, and many more.
Moreover, it also allows the admin to assign stars to a lead and considers their input. These aspects are considered, and a score is assigned to the lead.
4. Juan Merodio lead scoring model
The lead scoring model by Merodio uses a scoring matrix that evaluates scores on two factors:
- PAIN Score: This score states the potency of a problem faced by the lead. And based on this, a score between 0 – 10 is assigned. 0 indicating the lead has no problem & 10 indicating the lead is facing an intense problem and requires a solution soon.
- FIT Score: This score signifies how close the lead is to your company’s ICP (ideal customer profile).
Post evaluating each score; a sum is generated. Wherefrom Merodio categorizes these leads into two ways;
- Cold leads
- Warm leads
- Hot leads
Or another is whether or not the lead is ready for more marketing or sales activity
- Marketing qualified leads(MQLs)
- Sale qualified leads(SQLs)
5. Madkudu Likelihood to Buy model (LTB)
Along with behavioral and intent data that are used in other lead models, Madkudu LTB model adds multiple efficiency protocols and lines to ensure high-quality lead qualification.
The LTB score is derived from the combination of all the actions of a prospect in the last 90 days, factoring in the decay.
Every event that the person takes is directly associated with two things. Firstly, the importance (weight) & secondly, a lifespan (decay).
This model functions in 3 parts:
Part 1: Weight calculation:
Any action taken by the prospect is calculated on the below-mentioned bases:
- Importance = Points assigned to the event on the day the event was taken.
- Lifespan (Decay) = Number of days the action has been taken & will contribute to the overall LTB score.
Part 2: Define segment thresholds:
Now, we need to establish the minimum raw or threshold score that is required for a user to be considered as having a likelihood to buy.(“very high,” “high,” “medium,” or “low”)
These segment thresholds are specific to your defined model. These scores can be adjusted to enhance the overall performance of the model.
Part 3: Score Normalization:
During this process, the LTB segment score that has been achieved is measured with a normalized score between 0 – 100. This prevents the over-addition of scores and gets you a final lead score. The normalization of the score is automatically done by Data Studio, ensuring your score lies within the scale from 0-100.
Why do you need to build a unique lead scoring model?
Lead score models are often designed to qualify specific types of leads based on certain set criteria.
And what works for someone might not be an ideal fit for another.
Therefore, it would be wise to create your unique model to score leads that consider the parameters you intend to use to qualify leads.
Having your own lead scoring model would bring a plethora of quality leads for your sales reps to convert.
But thinking, where would you find a smart solution for that?
Well, we’ve got you covered. Introducing, Salesmate Score!
Salesmate Score is a smart lead-scoring system to help you identify the ideal leads that you can deliver to your sales team. Here you can score leads based on the various actions and conditions.
There is no manual hustle; once the criteria are set up, you can automate your lead-scoring process and get high-value leads for sales.
Curious to know what more can you do with Salesmate Score?
- Leverage fields like country, job title, UTM source, event type, referrals URL and many more relevant ones to find the ideal leads.
- Create Automation Journeys to decrease or increase leads score.
- Enrich your lead profiles. For example, it automatically performs their social profile enrichment. And if any relevant social link is found, it will increase the lead score.
You will get to see the Salesmate Score next under each contact’s profile. This added a holistic experience to the users.
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As mentioned, lead scoring doesn’t fall under the “one fit for all” rule. So, you must know how to make a custom lead scoring model.
Our next segment is step-by-step learning on custom scoring model creation. So, let’s dive deep in.
How to create a lead scoring model that is unique?
Here is a 5-step process to create an optimum scoring model for winning a greater number of quality leads.
Step 1: Define a clear ICP
Defining your ideal customer profile at the initial level will help you to precisely evaluate who is your targeted audience base. Also, you will better understand their demographics on a more personal level.
Step 2: Determine triggers & thresholds
To evaluate which set of implicit and explicit criteria they will have to meet to be identified as MQLs and SQLs.
Step 3: Finalize on lead scoring software
Choose a lead scoring tool that doesn’t limit you to their lead scoring model or allows a flexible system. Get your dream lead scoring tool – read our expert recommendations now!
Step 4: Build a custom lead score model
Even though you pick the standard lead scoring model that matches your business needs. But you must check what qualifying criteria (e.g., profile and engagement) it offers.
Always look for models with maximum customization scope. But if you want to create an effective lead scoring system from scratch, Salesmate Score can get you one!
Step 5: Execute & improvise
Note that a lead score model that you built would only fit a certain goal/product and for a certain time frame. Improvisation based on recent customer data would be the right way to ensure optimum leads are qualified.
In a nutshell, good models for scoring leads help qualify & segment leads efficiently that match a business goal. Here are a few best practices to follow:
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Best practices for creating a coherent lead scoring system
For an effective lead generation startegy, you must consider the support of both your marketing and sales teams.
1. Build the model in collaboration
To create rational criteria for the model, if the marketing teams consult sales & customer success teams, then precise ICPs can be formed, the right thresholds can be set, and much more can be achieved.
Therefore, the collaboration of your sales and marketing teams brings you an effective lead scoring process.
2. Assign points on both profile & engagement
Utilizing both categories; lead profile and engagement activities to assign point values leads is a part of good lead scoring strategy. This way, it becomes easier to assess a lead who is the best fit for the company.
3. Different product, different model
Every product has its ideal audience. Basically, what worked for one product might not work for another. Therefore, create a new model catered to the target audience of the product, resulting in qualifying the product specific leads.
4. Test before launching
Test your models with demo customer profiles before integrating them with your sales pipeline. This will help mitigate the risk of not qualifying the right leads.
Lead scoring models contribute to generate a list of high-quality leads for your sales reps.
It assists in your business’s lead prioritization and helps you save time otherwise wasted on unqualified prospects.
Thus, even if you use one of the lead scoring models mentioned in this blog, ensure it’s modified according to your organization’s ideal customer profile.
If not, Salesmate can build one from scratch, catered specifically to your requirements.
Frequently asked questions
What is lead scoring?
Lead scoring is a method through which prospects are evaluated and scored with a scale representing their perceived value to your business.
What is predictive lead scoring?
Predictive lead scoring helps your score leads based on big data & machine learning algorithms. First, it evaluates your target prospects to discover relevant attributes to define your ideal customer profile. And then it automatically scores lead based on these attributes.
What is the difference between implicit and explicit scoring?
When you score leads based on their actions and behaviors like email opening, clicked links, webpage visits, social media engagement etc., it is said to as implicit scoring.
On the other hand, explicit scoring is based on the information directly shared by the lead, like email id, job title, industry type, company size, budget etc.