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3 Ways Analytics Can Supercharge the Sales Cycle

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    This article originally ran as part of DBA, a series on Mashable about running a business that features insights from leaders in entrepreneurship, venture capital and management.

    Over the last 10 years, marketing has experienced a technology revolution — CMOs target, attract, engage and create loyalty leveraging everything from marketing automation platforms to sophisticated big data and analytics solutions. The sales department, on the other hand, is just now starting to benefit from these advances to help salespeople meet and exceed their quotas.

    Salesforce, while a powerful platform, at its core is simply a database, and now a host of new companies is building applications on top of it to make the whole sales process — from tip to tail — much more effective. Why is this happening? Data and the insights it provides give sales the upper hand to better understand their prospects and provide more insight into the full sales cycle.

    Nowadays, most customers are incredibly well-informed about the products and services they are considering. They are making purchases later in the sales cycle, so when they finally talk to a salesperson, they’ve already done research, participated in an online customer community and maybe even tested the product in a free trial. In fact, Forrester Research found that 75 percent of the buying cycle is done before a customer has any interaction with a sales team.

    Salespeople need to be equally armed with information about a prospect and they need to be hyper-efficient with their time. They need to know how to engage prospects with the right information and then be able to predict when deals will close successfully.

    Here are three ways analytics can power your sales team:

    1. Find the right prospects

    Most sales organizations either have too many leads or too few, but how do you hone in on which leads are worth focusing on and which ones aren’t worth your time? The power duo combines pipeline data and customer insights. Sales teams can simply look at their existing customer and pipeline data to see which prospects are likely to be happy customers.

    Just as prospects are armed with more information before talking to a sales person, sales teams are also in a better position to know about your prospects’ needs and pain points by tapping into publicly available information via social profiles, websites and job postings. Sales teams can analyze this data to predict who they should engage with now, moving beyond just gathering data by turning that data into insights.

    2. Get personal

    Marketing teams create tons of information and collateral for salespeople to get more deals in the door, but how do salespeople find and know what works best for their customers? One prospect might be looking for a solution that helps the company scale fast, whereas another may prioritize pricing and customization options. Your salespeople shouldn’t approach these prospects with the same collateral because, put simply, they don’t have the same needs and pain points.

    Since salespeople enter the sales cycle later these days and engagement time with the prospect is limited, sales teams need to be equipped to provide the most relevant, targeted information based on the prospect’s specific needs. With predictive analytics technology, sales teams have data at their fingertips about what collateral works best based on a prospect’s need, so they can be more strategic in choosing resources to present the prospect.

    3. Know which deals will close and which are at risk

    CRM systems like Salesforce house customer account records in a database, so salespeople can easily access detailed information about every deal. But these systems can’t tell you the likelihood that a particular deal will close or which deals are at risk. In fact, most sales managers rely on a manually generated forecast from Excel and then apply a “gut feel” to predict the number of deals that will close.

    It’s no wonder that all VP of Sales have been stuck in a situation where suddenly 20 percent of their qualified pipeline vanishes in the last few days of the quarter as salespeople discreetly move deal close dates to the next quarter. Those sneaky salespeople leave VPs panicking when it’s time to deliver their quarterly metrics.

    Powerful predictive sales solutions that sit on top of CRM systems leave the guesswork out of pipeline predictions. They use machine learning to look at historical data and predict the likelihood that a deal will close. Then sales managers can steer salespeople to either ditch a deal or put more energy toward closing the deal — and better predict the outcome at the end of the quarter.

    Today, sales teams are kicking their strategies into high gear by leveraging sales intelligence to bring in higher revenue by tapping into insights about what prospects are looking for and what information will get them in the door. If you empower your sales team with the right resources and technologies, then next quarter could be your biggest one yet.

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