Predictive Sales: Close more Deals with Advanced Analytics

Why do only 50% of deals forecasted to close, actually close? That’s because most sales organizations are still following the same old forecasting methods. And in today’s competitive world, it’s not just more leads that will help the Sales Leaders to increase the top line but the data about where they will find revenue, steps they need to take to achieve it and ways they can avoid risk! You don’t have to rely on your gut to leverage data for sales actions; Predictive Analytics can help you drive breakthrough results.

This doesn’t mean your existing data efforts are all in vain. Predictive Sales programs run on your existing data from CRM systems, Marketing Automation Systems and other external databases to make useful predictions about future events.

These insights decipher most doubts so as to why you should go for Predictive Sales solutions:

1. Forecasts help by identifying customers who are more likely to buy products. It depicts right leads to sales, and likely future sales, with high accuracy.
2. Sharpens Sales focus by attracting new customers, retaining valuable customers, optimizing buyer’s persona, predicting reactions, customer churn, credit scoring, customer ranking and lead scoring.
3. Helps Marketing to improve sales conversion rates by focusing on adding and modifying products, recommendations and market baskets.

SiriusDecisions found that 90% of users agree that predictive provides more value than traditional lead scoring approaches.

How to build a Predictive Sales Model?

Predictive Sales is the combination of data blending and advanced analytics to uncover hidden insights from the data, determine the significant variables, and improve sales forecasting. It gives a 360 degree view of customers and help Sales Reps to focus on those prospects that have a better chance of conversion. The following steps explains how to set up a Predictive Sales process:

1. Identification of Variables: The first step is to identify the variables which might affect your sales. These variables can come from CRM, Marketing Data, Financial Data, Social Data and other data sources. All of this data is then blended and cleansed using Alteryx data blending tools that allow you to restructure it to run a rules set on data.
2. Building a Data Model:This is a process that often involves training the model using multiple variables identified from the last step – to arrive on the best fit model based on the statistical analysis.
3. Validation and Refinement: The model is then evaluated for accuracy on the basis of how much percentage of past deals it can predict correctly. Based on the results, the model is recycled and refined to match the desired accuracy.
4. Scoring the Open Deals: The refined model is then used to score the open deals to determine their probability of winning.

Want to include Sales Predictions in your Business Process?

The good news is that at Grazitti Interactive – our Data Scientists can help you with building Predictive Sales models to help you drive maximum Sales revenue. Our solutions are built on Alteryx Platform– the global leader in Strategic Analytics, which are repeatable and customizable to the requirements. We extend predictive and prescriptive solutions using advanced analytics to increase win rates & reduced costs to help you win more business.

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