What is Lead Generation Validation Scoring? Everything You Need to Know!

Optimize your sales team and the quality of the data that you purchase. Better prioritize prospects and throw away low quality leads with IPQS lead generation validation.

Leads form the lifeline of any sales team. But not all leads are equal. So, how do you rank which leads are more lucrative than the others? By using lead generation scoring and lead data validation. So, here’s all you need to know about lead generation validation, scoring lead data, and how to determine if your business needs it.

What is lead generation validation? Lead Generation Validation is the process of verifying that user information collected by lead generation, such as names, phone numbers, email addresses, physical addresses, titles, and similar user data is accurate, current, and reachable. For example, if a user has an invalid email address and disconnected phone number, it would be very difficult to follow up with them.

Now that we know how to validate and verify lead data, we can explore the best way to prioritize leads.

What is lead generation scoring? Lead Generation Scoring is a methodology that allows businesses to rank their leads (prospective customers) in terms of value to the company. Leads are ranked in descending order where the highest rank is the most valuable prospect. This enables sales teams to convert sales more effectively and focus on quality lead data.

Why Do You Need Lead Generation Validation?

Lead Generation Validation

First and foremost, not all prospects represent the same value to the organization. For example, if you’re a B2B organization, you’ll value a C-level executive more than a middle-level manager. But the designation of the lead is not the only factor.

The engagement level of the lead ad how interested the lead is in your product also needs to be considered. So, if two leads have the same position then their engagement with your product allows you to distinguish between them.

The lead generation score allows you to understand when your lead might be ready for interaction and how willing they are to be converted. The more time quality leads spend with your content or products/services, the more likely they are to talk to your representatives. This is of course assuming that both leads have accurate data. Lead generation validation identifies lead data with low quality user information, such as disconnected phone numbers, invalid email addresses, incorrect mailing addresses, and even stolen user data. If you have experience with contacting leads, it is frequent to encounter a prospect that swears they never gave out their information or asked to be contacted by your company.

But is that all a lead scoring and validation system is good for? Not at all, here’s a list of benefits to help you understand better.

Benefits of Lead Validation Scoring

Research conducted by lenskold says that 68% of the best marketers in the world mention that validating lead generation data and prioritizing by lead scoring is a distinguishing factor in their success. But how exactly does it help? Here are some examples.

#1 Lesser Lost Opportunities

Studies have found that almost 70% of lost opportunities are down to poor follow up. One of the reasons your business might not have a good follow up engagement might be since the priorities are not set right. Lead scoring allows businesses to identify the right potentials and rank them accordingly. This allow you to lower your lost opportunities and throw out leads with invalid contact information.

#2 More Conversions

When your follows improve, your chances of conversions increase as well. Since the follow-up engagement is better and you're engaging the right people (more importantly), then they’re more likely to convert. As a result, ranked leads offer better conversions.

#3 Increased Productivity

Following up on leads takes up a major portion of the time for those responsible with conversions. It’s one of the most critical yet, time-consuming affairs. As a result, better management of the prospects allows businesses to save time and re-allocate their resources to other activities. By having a clear understanding of which leads to prioritize and which to follow up later, it allows managers to extract more productivity.

#4 Reduce Lead Generation Costs

Paying for junk leads with bogus user information is often considered a cost of doing business in this industry, however IPQS makes it easy to identify fraudulent leads so they can be replaced by your lead generation provider or simply refunded. Service providers that also prevent affiliate fraud can be useful for filtering low quality user data as many affiliate related lead generation programs can see fraud rates that exceed 45% of their budgets.

#5 Better Sync Between Marketing and Sales

Lead scoring systems are based on a wide variety of factors. These factors analyze the social presence, preferences, engagement, job profile and other factors to properly score the leads. By using a lead scoring system, marketers can understand which demographic profile is most attracted to their product and service and what appeals to them. This allows for better sync between the sales and marketing team and better alignment of product and marketing vision.

To better understand if your business needs lead scoring, ask yourself these questions:

a) Are We Generating Enough Leads for the Sales Team?

If there aren’t enough leads for your sales team to follow-up, then your problem first lies with generating initial leads. Lead scoring isn’t your immediate concern. You should dedicate resources to first generating enough leads.

b) Does the Sales Team Follow up Each and Every Lead?

Sales teams thrive on a good level of leads. This is consistent across almost all industries. At this point, it means that you’re generating enough leads if your sales team is struggling to keep up with each lead follow up. But the quality of lead follow-up might then be a concern. This would be a good time to implement a lead scoring system that allows you to identify high-value and low-value leads. However, sometimes irregular follow-up or no follow-ups can also be a reason for leads going cold.

c) Do You Have Enough Data to Implement Lead Validation Scoring?

You need at least two types of data when implementing lead scoring - explicit and implicit. Explicit is demographic info while implicit is behavioral. While explicit is more easily available, implicit data only comes when the leads spent a minimum amount of time on your application or website. As a result, without substantial data supporting the lead scoring models, it’s of no use.

Now, that you know how it benefits you, let’s take a look at how it works.

Instantly score lead data and perform lead generation validation to ensure leads that you purchase or collect have high quality data and will result in a positive ROI.

How Is Lead Validation Scoring Conducted?

As we mentioned previously, lead scoring models use a wide variety of factors including lead validation. These factors can be divided into two categories - explicit and implicit. Explicit data is the information provided by the lead directly or that which is explicitly available. Examples of this data are the job profile, industry, company size, geographic location, etc.

Implicit data refers to the information gathered during observation and by indirect means. For example, behavioral data, social media preferences, e-mail opens and website visits are seen as implicit data. By analyzing these data, the lead scoring model looks to understand the willingness of the lead to interact with the brand. The model also helps to analyze which stage of the buying cycle the lead is in.

For example, is the lead browsing for solutions casually, looking for an immediate fix or has the lead already decided to purchase your product. By gaining a comprehensive understanding of the lead’s status-quo, it allows marketers to pitch their solutions accordingly.

Now, there are various methodologies used to create a lead scoring model. Here are some of them discussed below:

Key Methodologies

Lamb or Spam

This type of methodology is generally employed by small and micro businesses who are yet to decide on a specific ideal customer profile (ICP). The lamb, also known as spam, model works by sorting out the duds or low-quality leads and identifying the high-quality leads.

The quality of the leads is usually identified by the domain of the email address. For example, if you are focussed on business to business (b2b) leads, an email address that has a personal mail provider such as Gmail, Yahoo or Bing is classified as a low-value lead. Whereas a custom domain name is seen as a high-value lead. Of course, verifying an email address is valid in the first place is the best way to begin the scoring process, through lead generation validation.


The rule-based lead scoring system uses various factors to identify the potential value of a lead. It will use company metrics as well as behavioral attributes to set ‘point values’ for each factor. Before marking points, a threshold is set to determine low-value and high-value lead. Based on the points accumulated, the rank list is prepared.

Predictive Lead Validation Scoring

Predictive lead scoring looks to make a detailed analysis based on the historical data of the leads, accumulated from third-party sources. It is the only methodology which deals with machine learning and uses historical data to predict future outcomes. The basis of this analysis are variously internal and external factors

The information gathered from the sales, marketing, and product teams are treated as internal data in which information gathered from third-party sources are treated as external data.

This kind of scoring is also used to sort, identify and qualify leads. Since the model uses behavioral and statistical analysis, product and marketing teams can identify markers to better align their product and marketing strategy for the target customer.

Small but incremental changes in product, allows the company to become customer-centric and build a product philosophy that can outlive trends.

For example, Apple prides itself on creating technological masterpieces that are intuitive and beautiful. It understands the points which appeal most to its customer base and accordingly creates its product line. As a result, a simple understanding allows it to create an entire product philosophy that is not seasonal.

Predictive scoring is more beneficial for SaaS companies, as they tend to have a customer lifetime value. Since SaaS companies have a huge database of customer behavior data, the predictive model can make a more accurate analysis to aid the business. It’ll allow the business to target high-value leads and fast track them through the sales funnel.

How to Setup a Lead Generation Validation Scoring Model?

Wondering if you could set up a lead scoring model. Sure, you can. With the help of a well-planned blueprint, you’ll be able to set up for a lead scoring model or at least hire the experts who can.

Identifying the Right Scoring Criteria

After lead data validation has been completed, the first step to setting up a successful lead scoring model is identifying the characteristics and markers for a qualified lead. A qualified lead (also known as a ‘marketing qualified lead’ or MQL) is a potential customer who has already been vetted for on-boarding and is on the way to be a genuine customer. The difference between a high-value lead and a qualified lead is the purchase intent.

Once you identify the characteristics of a MQL, you can set points for each of those factors and apply a weighting. So, when these characteristics pop up for a new lead, the scoring system will automatically calculate the likelihood of conversion and provide the sales team a distinct direction.

The demographics of a MQL should be first identified. This will allow you to customize your lead capture forms to ensure that the right information is captured.

For example, your MQL is a C-level executive of a medium to large enterprise in the IT and ITeS industry. So the lead capture form should at least allow visitors to fill up their job title, company size, and industry, so on and so forth.

Next, you might want to identify the behavioral markers of a MQL.

  • How many times does an ideal lead visit your website in a day?
  • How many pages does he visit in one session?
  • What is the amount of time they spend on the site?

You would also need to sort the interest shown by leads in your products. Some leads will express interest in a demo, some will view a particular product page for a particular amount of time, while others might enter the sales funnel but exit mid-way. Each behavior will allow you to understand the kind of lead you’re generating - or not generating!

Setting Point Values

Once you have set the markers and identifiers for the ideal lead, it’s time to set ‘point values’. The point values will signify the importance of each factor. For example, a visitor requesting a demo will receive more ‘weight’ than one spending two minutes on a product page.

Similarly, a senior-level executive will receive more importance than an entry-level executive, since the decision-maker in a company is more likely to be in senior management.

If the range of variances is limited then you can create a 1-10 scale. But if the variance range is wide, you can increase the scale up to 100. Depending on the past data of your MQL, the weighting and variance can be decided.

Determining the Ideal Lead Score

The objective of scoring a lead is in two parts -

  • It stops your sales team from antagonizing and potentially alienating leads who aren’t ready to engage with the brand. Likewise, follow-ups with leads who aren’t real customers can antagonize sales teams and turn any chances you had of converting into a negative.
  • It allows you to maximize your sales team’s productivity by focussing on those leads which are most likely to bear results and are ready to engage with your brand.

After setting the point values for the markers, it’s time to decide on a benchmark point value. The benchmark point value will allow you to set the bar for what you can identify as a MQL. You can also set benchmarks for other lead classifications.

As the scoring system gathers more data, you’ll be able to learn more about your leads.

Why Should You Implement Lead Generation Validation Scoring?

Lead Generation Scoring can seem like an over-analytical way of using data when we know people don’t always fit the data. It could also be seen as a way of superseding your sales teams ‘sales instincts’. But in truth, it’s an additional tool in your armory that can help your sales teams target their sales pitch more effectively. Validating user data will also provide instant results by filtering low quality leads that your sales team may be spending hours hopelessly trying to contact. If you are collecting leads through your own funnels, it's ideal to install lead generation validation directly in your capture form, so that when users enter inaccurate information, an error can alert them to try again with correct information. This approach is typically very effective at solving invalid lead data.

If you implement effective Lead Gen Scoring, your sales team is more likely to convert leads and be more efficient with their sales time. This can produce marked improvements, and easily offset the cost of any implementation of such a system.

Some Final Thoughts on Lead Generation Validation

Lead generation validation scoring can be an effective and cost-efficient tool for your business and we hope this article has demonstrated that. But no two businesses are the same, so for your business, it will need professional assistance to implement successfully from experienced professionals. These solutions are typically very easy to deploy, with same day setup. So, if you’re ready to discuss this further then start by contacting IPQS or giving us a call today and help us create a more successful sales team for your company!

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