Lead Quality to Improve Conversion

Savvy sales and marketing professionals know that all prospects are not created equal. Lead quality varies widely based on a large number of factors. Understanding what those factors are can give organizations that work with leads and prospect a significant advantage over their competition.

A recent study looked at historical data, across millions of leads, and identified key attributes that impact lead quality. Each of the results included in this research suggest a number of actionable changes:

  1. the types of leads that should be pursued,
  2. the type of data that should be collected, and
  3. the best ways to manage different leads.

However, the potential value of this data can be maximized when the combined effect of these attributes is used to acquire leads, produce lead scores, and determine optimal prioritization, distribution, and nurturing strategies within a lead management solution.

Background

Lead scoring is quickly becoming an important aspect of lead management. There are many software applications and services out there that can help you score your leads, but there are also things you can do on your own to get started on this valuable process.

Lead scoring is simply the process of assigning scores to your leads according to the perceived and/or previously observed probability of them becoming customers. The first step to lead scoring is identifying which attributes or characteristics make a lead more or less likely to become a customer for your specific organization. In order to do this, it is crucial to truly know your customers.

Ideally, you also have access to historical customer data that can be analysed to help you validate your guesses. Customer data may also help you uncover attributes you may not have thought about. Analysing historical data on successful and unsuccessful leads won’t only help you verify that you’re looking at the right criteria, but it will also help you identify the actual effect of each characteristic on the probability of closing customers.

Once you have a good grasp of the criteria you’d like to use for your scoring model and the impact they have, you can begin assigning points to each of them to arrive at a final score for each lead. An important distinction you may want to make is between extrinsic and intrinsic criteria.

Extrinsic criteria include facts about your prospect, which are typically provided by the prospect or acquired through data appending services. These facts will likely tell you if a prospect possesses the characteristics that typically make leads more likely to become customers for you. Intrinsic characteristics are better indicators for the seriousness of your prospects and their readiness for your product or service. Intrinsic data is based on observed behavior or inferred from data that may not be directly provided by your prospects.

The combination of both intrinsic and extrinsic data will result in the most reliable lead scores. A reason to keep these scores separate might be to determine urgency based on the intrinsic factors and desired level of persistence based on extrinsic factors.

The lead scores you calculate and assign can be used to prioritize your leads, distribute them to the right groups or individuals, or to determine the type of follow up needed according to each lead’s score.

CRM software such as Maximizer which offers lead nurturing capabilities which can elevate Lead Quality to Improve Conversion. Contact ProAptivity today on 028 9073 5630 for your free consultation to understand how CRM can benefit your business.

Source: Leads360.

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