Marketing plans must combine efficiency and speed in order to supply your sales team with qualified leads. To meet this objective, your Lead Scoring must reveal the most relevant leads to facilitate engagement and help your sales teams transform your prospects into customers. It's a key part of any demand generation strategy and essential to marketing automation. What are the basic steps to efficiently build your Lead Scoring ‘algorithm’?
This post is the first of a series of 3 that will provide an overall view of Lead Scoring and help understand its key issues and phases.
What is a lead?
A lead is a prospect... Obviously.
A lead is an entity that exists within your information systems with which you want to achieve a sales objective. It’s composed of all of the relevant information to engage a business conversation on the initiative of either marketing or sales. Its data informs us on the entity’s nature and behaviour.
What does Lead Scoring mean?
Lead Scoring is a strategy that aims at dynamically qualifying prospects on a wide scale in order to activate the appropriate responses in terms of sales and marketing.
The 3 dimensions of Lead Scoring
First, here are a few basic reminders on Lead Scoring. According to SiriusDecisions, all prospect qualification data falls into 3 main categories:
- Demographic and corporate-related information
This is all of the information that individually defines each lead: the person’s contact information (name, position, title, e-mail, social profiles, etc.), information on the company (name, brand, Web site, revenue, business sector, number of employees, location, etc.) and, lastly, all of the archive data available in the company’s information systems (invoicing history, past marketing and sales actions, etc.)
- Behavioural data
This is composed of all of the interactions traced within your digital ecosystem and helps determine the prospect’s levels of interaction and interest. This data can show an individual level of interest as well as the company’s level when several people are involved in the same buying decision-making process. This information not only impacts a score but it also activates specific individualized marketing actions using marketing automation tools. The speed at which the level of interest increases is also a factor that helps define the notions of commercial momentum and indicates the right time to start sales follow-up.
BANT qualification (Budget, Authority, Need, Timeline)
The aim of this qualification is to determine whether the prospect has the necessary budget, the authority to decide, and has identified his need and established a timeline for making the decision.
Fit Scoring and Engagement Scoring
The Fitness Profile establishes the degree of fitness between a lead’s demographic and corporate-related data according to pre-established criteria. Fitness Engagement establishes the lead’s level of engagement according to the actions the lead has made in your digital eco-system or answers to various types of solicitation. These are the 2 main types of information that compose the lead scoring algorithm.
These scores are used to draw a map of your prospects and define the most appropriate marketing and/or sales scenarios.
Conclusion part one
Lead Scoring undeniably lays the foundation for a much finer analytical management of your leads and orients marketing actions with precise targets and objectives. In our upcoming posts, we will cover the key steps to building an efficient Lead Scoring strategy, we will discuss the traps to avoid and how to implement the strategy within your automated marketing and CRM tools.
Happy Modern Marketing !