The DriveSales™ | Most effective and efficient lead scoring guide for B2B companies and businesses!
Lead scoring is a system of assigning values, often in the form of numerical points, to rank prospective leads based on their probabilities to convert into customers considering a variety of insights ranging from sales-centric activities like price scouting, low-level engagement such as reading through a blog, and mid-level engagement like reviewing products and solutions. The basic premise of lead scoring is to assign a rating of different prospects based on their behavioural or demographic patterns and prioritizing the higher scores as better candidates for sales teams to pursue.
Lead scoring estimations are critical in achieving accurate and actionable sales forecasting.
It is used to determine the sales readiness of leads and move them through different stages of the sales process.
1) Lead Scoring Setup
· Create Ideal Customer Profile (ICP): An ideal customer profile (ICP) is a fictional profile of a customer that has all of the qualities that would make them a perfect match for the products or services a business has to offer. ICP helps marketing and sales teams to have a clear and cohesive vision from the very beginning. It is essential in understanding defining factors for lead qualification. Data is collected about customers from various sources and touchpoints (e.g., sales, website, chat, etc.) using a mix of primary and third-party data.
· Splitting into Data Attributes: Here, the ICP is further segregated into different attributes based on their profile and behavioural attributes such as industry size, company size, revenue, etc.
· Connect Data Attributes to Lead Scoring Rules: Create lead scoring rules based on all the attributes selected in the previous step.
· Assign Points based on Weightage: Leads can either be given positive points or negative points. Positive points are awarded for positive attributes or behaviours such as if a lead is from a targeted demographic. Similarly, points are deducted for negative attributes or behaviours such as unsubscribing from important mailing subscriptions or removing payment information).
· Determine the Sales-Ready Lead Score: Define a pre-determined score that must be attained for a lead to be qualified as Sales Ready by going over the scores of existing customers. Validate the model based on current/past leads data and refine the model accordingly adding/deleting the attributes which determine the sales readiness most significantly. For instance, a lead with a 70/100 score converted into a customer or there is a need to nurture it further to 95 before it gets converted.
2) Lead Scoring Data Points:
· Explicit data score, which is provided by the prospect through web forms when a lead enters the system and/or collected through third parties. This includes data such as company size, industry, role, and specific product/service interests. The two primary contributors to this score are as follows:
· Individual Data: This data consists of information about the first point of contact who is evaluating the product/service on behalf of their company. This data from this preliminary stage of lead qualification includes organizational role and seniority which further helps in identifying leads with decision-making capabilities.
· Company Data: Another crucial data point for initial vetting, this data consists of firmographic information like industry, the number of employees, geographic area, revenue, etc. This data helps in filtering out leads who match the target business profile and segregate leads based on ticket size.
· Implicit “behaviour” data is based on online activity and sometimes referred to as digital body language. Examples include the depth of a website visit (including page visits and recency), registering for webinars, resources downloaded like e-books, white papers, or case studies, watching product demo videos, subscriptions to free trials, completion of lead generation forms, on-page searches, etc.
I. This data point unleashes the true potential of Lead Scoring’s leverage. As leads interact with the content at multiple touch-points, their lead scores keep changing dynamically. Apart from helping understand a lead’s intent for initial qualification, behavioural data also helps in categorizing leads based on the different stages of the buying process for better targeting and serving personalized content.
II. Social Engagement metrics is a new entrant used for Lead Scores which predicts lead relevancy based on analysing a person’s presence and activities on social networks.
III. Other Engagement metrics such as Email engagement data (measures promotional or nurturing email open rates), Sales/CRM Data, demographic data, and techno-graphic data as per the requirement.
Key benefits of an effective Lead Scoring Model: An effective Lead Scoring model positively impacts the revenues due to:
· Increase in sales efficiency and effectiveness.
· Strengthened relationships and cohesiveness between marketing and sales teams by establishing a common language with which marketing and sales leaders can discuss the quality and quantity of leads generated.
· Allowing a business to customize a prospect’s experience based on his or her buying stage and interest level.
· Improving the quality and readiness of leads that are delivered to sales organizations for follow up.
· Quantifying the types of leads or lead attributes which matter the most for marketing teams, which helps marketing more effectively to target its inbound and outbound programs and deliver more high-quality leads to sales.
According to Aberdeen Group’s survey titled “Lead Scoring and Prioritization: The Path to Higher Conversion”, it was found that 80% of top-performing companies are more likely to use lead scoring as part of their lead qualification process, thus, illustrating the potential impact of lead scoring on revenue performance.
With the rise of digital selling, a growing need for qualifying leads has come forward for businesses of all sizes primarily because with ever-increasing accessibility, more people now interact with businesses and thus the ratio of potential customers has fallen significantly. Prospective customers go through an extended buying process fueling the need for an efficient lead scoring process.
The evolution of lead scoring parallels the evolution of the buying behaviour of B2B customers. In the past, buyers interacted with sales teams early in the product research process. Consequently, sales teams exerted more influence over a longer portion of the buying cycle. Now, buyers start their information-gathering long before they first contact the prospective seller through a plethora of touch-points. Buyers are turning to the web to download whitepapers, case studies, reading company reviews, and reaching out via social media to gauge the opinions and experiences of other users.
Lead scoring is data-intrinsic relying heavily on the accuracy and depth of data and continuous data enrichment for an efficient and effective lead scoring strategy.
Now, as an effective SALESPERSON! We can do three things from here.
1. Not ignoring the opportunity and blaming the situation for revenue loss.
2. Taking necessary notes and revisiting your sales strategy with a growth mindset.
3. Reach out to The DriveSales™ in case you need any specialized help.
To conclude, what you believe also provides some idea of your development as a consultative salesperson. For more, please be connected to team The DriveSales™ as these are the foundations for our culture and ways of working!