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By combining the art of selling with predictive analytics you can contact leads when they’re ready to buy – with excellent results.  Here’s what you need to know.

Predictive selling combines your data and powerful analytics. It uses artificial intelligence to find patterns in data, creating forecasts about the future and helping to increase productivity.

Consider B2B sales, where a large amount of data that gets generated through everyday interactions and transactions, which further generates a trail of insights which if decoded correctly can help identify hidden buying signals and focus the efforts of a sales person effectively.

What is predictive sales?  It’s where the art of salesmanship combines with the power of predictive analytics.  By basing your sales decisions on data-driven insights, you can markedly improve the performance of your team.

Four Keys to Predictive Sales Success

How do you think about the data in your CRM?  As a list of names and email addresses, or as the heart of your company?  Remember, each entry in your CRM is all about finding and connecting with business opportunities. By using predictive analytics, you can transform the sales process into a focused, purposeful venture.

The key pillars of predictive selling are:

Key 1: Start Scoring Leads

A prospective lead list can grow exponentially in a short time. The trick is figuring out which leads are most likely to convert and giving them priority. This is where lead scoring comes to our rescue. These predictive models crunch a huge number of characteristics to come up with an individual score for each lead.

This score helps prioritize leads with the most conversion potential at any point in time. The key here is that this model changes as the prospect’s behavior changes.

Key 2: Know What Your Contacts Want

Knowing and understanding customer needs is at the center of every successful sale. This is true whether you’re dealing with individuals or businesses. However, learning and meeting the needs of a large number of customers at the same time is not an easy task.  And the proliferation of options isn’t making it any easier. So we’ve turned to product recommendation engines to give us the insight we need.

Building a good product recommendation system requires a deep understanding of customers, and the ability to map a complex set of products and services to customer needs. We also have to correctly predict customers’ future needs and use this knowledge to exceed their expectations.

The entire recommendation model is based on machine learning.  As the machine learns from the data, it builds associations that we would not be able to manually identify. These associations show us how to find the right products for each lead and have a much more productive conversation.

Key 3: Know the ‘Why’

Not only does the recommendation engine provide suggestions, it also shows why a particular product or service is being suggested. Maybe it’s because all your contacts’ competitors are buying the product. Or maybe the product would complement the client’s most recent purchase. Perhaps it is an upgraded model of a product they already have, or a complementary service.  This level of insight is a great way to make a positive impression.

This ‘Why’ will give each sales rep an edge over their competitors. Each time they interact with a prospect, they can provide a much more customized experience.

Key 4:  Know – Don’t Just Guess – Your Next Best Action

Before we contact a lead, wouldn’t it be awesome to know whether or not they are ready to buy? Predictive analytics helps companies focus on the right next step — the Next Best Action — for leads by analyzing customers’ needs at a given point of time. This makes every interaction with the customer a potentially productive one.

These strategies are not the result of a single model. Rather, they are a combination of many models, a decision engineering algorithm that also incorporates the specific business rules and policies of each organization. Once again, this will help reps get a more positive response when they contact leads.

Letting the Data Speak for Itself

Would knowing these keys be enough? The answer is definitely no. What every sales rep needs is all of these insights presented in an easy-to-use interactive weekly game plan.  They need a tool that makes the whole decision-making process simpler and more efficient.

The answer to a perfect sales pitch lies in combining the art of salesmanship with the innumerable insights your data has to share. Know your data and let it work its magic.

Authored by Titir Pal, Vice President at Absolutdata and Rajat Narang – Associate Director at Absolutdata