No sales team would pass up an opportunity to improve its overall productivity and profitability. Most also realize that big data and analytics are game changers. The question isnt whether to harness the power of big data and analytics. Its deciding what provides the most value to individual salespeople and the entire organization.
While the majority of today’s organizations may recognize the potential of big data, most struggle with how to properly apply the skills of data scientists:
Most businesses that do hire data scientists often lacks an idea how to effectively utilize their skills. Most data scientists are stuck in maintenance mode organizing and collating data, rather than actually analyzing it.
Below are several practical applications of big data that can be used to boost sales performance in an organization.
Real-time Performance Visibility and Optimization
Companies that consistently post record sales quarter after quarter have learned how to close the gap between CRM and the real-time performance of sales teams. One reason why is because big data gives management the visibility to more completely see whats going on with the entire sales team and their processes.
Sales platforms driven by big data give managers more information to work with when it comes to coaching their teams. The ability to see sales performance in real-time allows them to step in and give constructive feedback. Therefore patterns of underperformance dont continue.
According to a 2016 Corporate Executive Board study, it takes just three hours of one-on-one coaching per month for poorly performing sales personnel to increase their close rate by up to 70 percent. This also helps management identify and reward top performers more easily.
Success in sales happens most often when the decision-making process of the buyer and the sales process are closely aligned. One way to achieve this is by equipping sales professionals with pre-loaded conversations they can access in real-time from any location.
Based on a prospect’s overall profile, what products they are interested in, and where they are in the sales cycle, an algorithm can suggest insights and counters to common objections based on past data. This eliminates the need for salespeople to rely on gut instincts alone when meeting with prospects and trying to close deals.
Analyzing Big Data to Identify Opportunities
Locked within the troves of big data collected by the average business are insights that suggest emerging trends and new opportunities. Sales organizations should aim to implement algorithms that uncover the following benefits:
- Improved accuracy in sales forecasting
- Improved ability to identify opportunities for cross-selling
- Ability to separate customers into segments such as those looking to buy high-dollar items, long-term customers, and those that need the most convincing to close a deal
- Highlight ways to improve marketing efforts and better align sales and marketing
While it can take some trial and error to get the algorithms just right, a 2015 Strands Retail report indicates that sales teams can expect a return on investment of up to 20 percent.
Pipeline Analysis for Better Sales Performance
The quarterly business review (QBR) is an ideal time to review the strength of a salespersons pipeline. After three months of trying to close deals, it can be easy for sales reps to lose sight of the importance of a healthy pipeline. Some suggested topics to cover to make the best use of a QBR include:
- Whether the pipeline contains the right mix of prospects
- Whether deals forecasted for future quarters can be moved up
- Deciding how to move deals along that appear stuck in a certain stage of the sales process
- Whether the quota for the pipeline is realistic
- Realign the typical customer persona
Big data analysis helps ensure that the observations and recommendations made regarding the points above are backed by objective research rather than a manager’s intuition.
Discussing pipeline health doesnt have to wait until the QBR. Ideally, discussing it should be part of every one-on-one meeting between managers and sales reps.
Rethinking the Role of Skills of Sales Leadership
Although personality, business intuition, and an understanding of the “art of sales” will always be relevant for success in sales management, times are changing. With increasing recognizition of the value of big data in sales, an ever-growing number of sales leadership roles require a background in data science.
Understanding not just how to collect big data, but how to convert it into actionable insights to boost sales performance is now essential for leading sales organizations. VPs of Sales now must act as data scientists in order to effectively lead their teams in today’s business environment.
