Difference Between Traditional and Predictive Lead Scoring

How do you distinguish between a qualified lead from an unqualified one? That's the question most marketers ask. For a sales and marketing team to succeed, they must know the key factors that makes a lead a qualified lead. So that the right content can be sent through the right channel that makes most send to these qualified leads. Once this process is in place, it will help your sales team make the most of their time by providing them means to prioritize leads. This is where lead scoring comes in. Lead scoring aims to simplify the way businesses identify the best leads for their salespeople to connect with through the use of a strategic scoring system.

There are two types of lead scoring i.e. The traditional leand scoring and the predictive lead scoring. Following are the basic differences between the two.

Traditional Lead scoring:
Traditional Lead scoring is a tool to identify  which qualified leads should be sent to sales team. To figure out a qualified lead, a marketer need to consider a series of qualifying factors that aim to indicate whether or not a lead makes sense to their business.

The first part of lead scoring is identifying parameters that are a must to qualify. The more parameters a lead qualifies on, the better is the lead. And then the second part of lead scoring is to assign a value to how important or unimportant these parameters are. As you add and deduct values based on the information you collect about a lead, you will find that some have a higher score than others. Those are your most qualified leads based on the information you laid out and should be prioritized by your sales team.

Predictive Lead Scoring:
Predictive lead scoring is a tool that uses an algorithm to predic who in your database is qualified or un-qualified. The information taken into consideration to predict this, difeers from provider to provider.Parameters considered are behavioral data, social information, demographics, and media written about your company. The best part about predictive lead scoring is that you don't have to figureout which properties shold be included or how much value is to be assigned to each parameter. The lead scoring algorith considers what information is common amongst your customer and what information was common in leads that did not close. After analyzing this information, the lead scoring algorith then comes up with a formula that will automatically bucket leads for you to be identified as most qualified.

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