Digital Marketing has become one of the most popular and effective techniques that businesses leverage to market their offerings as these techniques allow businesses to reach a wider audience and efficiently measure the performance of their Marketing efforts in a way that can be easily visualized and communicated to decision-makers. Since businesses are able to reach such a large audience, the number of leads they generate also grows exponentially.
But it is not possible for businesses to treat each Lead with the same priority since each Lead has a different level of interest. Hence, businesses felt the need to come up with a robust mechanism of assigning Lead Scores that can easily help them evaluate the quality of a Lead. This article will provide you with a comprehensive understanding of Lead Scores and the factors that need to be taken into account while developing a Lead Scoring Model.
Table of Contents
- Introduction to Lead Score
- Understanding the Need for Assigning Lead Scores
- Understanding the Key Attributes of a Lead Scoring Model
Introduction to Lead Score
Lead Score can be defined as a value assigned to each Lead that is generated by a business, usually in terms of numerical points or letters. Businesses usually assign Lead Scores taking into consideration multiple attributes. These attributes include the professional information the Leads might have submitted, how they’ve engaged with the brand, etc. The best methods to assign Lead Scores use Firmographic and Demographic attributes, such as Industry, Company Size, Job Title, etc., along with behavioral data such as Clicks, Web Visits, etc.
Businesses usually assign Lead Scores by implementing rankings using letters like A, B, C, D, numbers in ascending or descending order, or using terms like hot, warm, or cold.
The process of assigning Lead Scores helps the Marketing and Sales teams within a business prioritize potential customers, respond to them accordingly, and further increase the conversion rate of Leads into customers. The process of assigning Lead Scores is a shared Marketing and Sales methodology for ranking Leads to determine the chances of that Lead turning into a customer. The goal of assigning Lead Scores is to increase the combined efficiency, productivity, and conversion rate of Marketing and Sales teams within a business.
However, it is of paramount importance for businesses to understand that assigning Lead Scores can only help understand which Leads are ready to make the sale and which require further work. It is not a stand-alone Marketing technique, and the input of the Sales team is essential here. Businesses should also not ignore any Leads. Assigning Lead Scores should not be used to cherry-pick hot leads and ignore the rest. It should only be used as a mechanism to improve Sales and Marketing efficiency.
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Understanding the Need for Assigning Lead Scores
Businesses feel the need to assign Lead Scores because of the following reasons:
- Effective Marketing Campaigns: Assigning Lead Scores allows businesses to identify campaigns and channels that generate high-quality leads. This information can then be leveraged to build similar campaigns and advertise them across high-yield channels.
- Sales and Marketing Alignment: The lack of an effective mechanism to assign Lead Scores is the most significant contributor to misalignment between the Marketing and Sales teams. Having a clear set of rules in place for assigning Lead Scores can help businesses ensure that every Lead that is passed to Sales is qualified. This can strengthen the relationship between the departments, resulting in better Marketing and Sales alignment.
- Increased Revenue: Lead Scores can be leveraged by the Sales department to prioritize Leads and contact them accordingly. Reaching out to qualified Leads promptly can help businesses increase the amount of revenue significantly.
Understanding the Key Attributes of a Lead Scoring Model
The process of designing a framework to assign Lead Scores is not as easy as it sounds and varies significantly for every business and its products. Hence, a common tool or framework that can assign scores to all Leads might not be beneficial since the scoring should be done based on business requirements. However, most effective Lead Scoring frameworks take the following attributes into account:
1) Lead Score Threshold
A Lead Score Threshold refers to the point value at which the prospect is considered to be Sales-ready. Whenever the Lead Score reaches or exceeds this threshold value, it becomes a Marketing Qualified Lead (MQL) and is further passed on to Sales for them to finalize a deal. It is, however, essential to get the threshold value right. If it is too low and leads are qualified prematurely, the process for Sales will become much more complex since the Leads are not ready to be pursued yet. But if the value is too high, there is a high chance of losing the lead to a competitor since Sales took too long to respond.
Businesses should be able to determine the threshold value by analyzing the historical data and try to understand which characteristics resulted in the Lead getting marked as qualified. For example, if a Lead requesting a product demo is the top indicator for eventual conversion into a sale, the Lead Score Threshold should be set such that any Lead that requests a demo should be given enough points for it to immediately become an MQL.
Once businesses set a threshold, they can set up their Customer Relationship Management (CRM) system to automatically notify them when a Lead reaches the threshold value.
2) Explicit Scoring
With Explicit Scoring in place, businesses can assign points to every Lead based on specific qualities, such as Firmographic or Demographic details. The explicit characters that are usually taken into account by most businesses include Job Title, Level of Seniority, Industry, Company Size, Company Revenue, Geographic Location, etc. Businesses can also give leads a chance to voluntarily provide all information they need for Explicit Scoring. For example, businesses can ask their website visitors to fill out a questionnaire to download exclusive content, sign up for a free product trial, etc.
3) Implicit Scoring
Implicit Scoring refers to the points that businesses award to a Lead based on their behavior, such as website visits, free trial sign-up/product demos, Social Media interactions, contact requests, newsletter subscriptions, content downloads, etc. Implicit Scoring should ideally contribute more to a Lead’s overall score as compared to Explicit Scoring. This is because a Lead can only be scored once for characteristics such as Job Title, Company Size, etc., but will be scored every time that they perform Explicit actions such as visiting the website, downloading content, opening Promotional Email, etc.
4) Negative Scoring
It is important to understand that not every interaction a Lead has with a business is a step forward in the Buyer’s Journey and all Lead Score models need to take that into consideration. A Negative Lead Score can be used to remove points based on actions or characteristics that indicate a reduced or complete lack of interest.
These include unsubscribing from the Email list, the Lead visiting the careers page implying that they are interested in becoming an employee and not a customer, a job title like a student, or working in an industry that has nothing to do with the product or service being offered, suggesting that they are interested in the content for purely academic reasons, etc. Negative Lead Scores are essential to avoid deceptively high Lead Scores.
There might also be situations in which a lead has a healthy score, but their actions show they’re increasingly losing interest. With Negative Scoring, the Sales team can take suitable actions to get them interested in the product or brand again or pursue other High-quality Leads if the current Lead shows clear disinterest.
It is important for the Sales and Marketing teams within a business to work together to understand all the red flags that could indicate a Lead isn’t likely to convert. A Negative Lead Score can then be assigned accordingly based on the severity of the action.
5) Score Degradation
Score Degradation helps businesses take into account stagnant Leads and take suitable actions for them. Ideally, if a Lead hasn’t interacted with the brand over a significant period of time, it would make sense to lower its Lead Score. For example, businesses usually lower a Lead Score if the Lead stopped opening their Promotional emails or downloaded a piece of content but never interacted with the website again.
Score Degradation helps businesses pick out poor Low-intent Leads and focus on more valuable, High-quality Leads, just like the Negative Lead Score. To leverage Score Degradation, businesses need to understand which actions should warrant point degradations. A common strategy that numerous businesses implement is reversing the point system they use for Implicit Scoring. For example, if a Lead is given 10 points for subscribing to a Newsletter, they lose 10 points for unsubscribing.
All Lead Scoring Models should account for at least the above-stated factors. However, it is essential to understand that this model needs to be refined regularly to improve it. It is not possible to develop a single model and expect it to generate accurate results forever.
Businesses should regularly update their scoring methods based on recent customer data to keep their Lead Scoring model as accurate as possible. For example, if a large number of Leads are getting qualified but only a few are being converted to customers by the Sales department, it is likely that the Lead Scoring threshold is too low. Hence, changes need to be made accordingly to fix that issue.
This article provided you with an in-depth understanding of what Lead Scores are, why they’re essential, along with a list of the key attributes that should ideally be included while creating a Lead Scoring framework for your business.
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