Over the last 10 years, marketing has experienced a technology revolution. CMOs target, attract, engage and create loyalty by leveraging everything from marketing automation platforms to sophisticated big data and analytics solutions.
The sales department, on the other hand, is now starting to benefit from these advances to help salespeople meet and exceed their quotas.
Salesforce, while a powerful platform, is, at its core, simply a database. Now, a host of new companies are 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 — gives 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 make 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 tested the product in a free trial.
In fact, Forrester Research found that buyers might be 67% to 90% through their sales experience before they contact a vendor.
Salespeople need to be equally armed with information about a prospect, and they need to be hyper-efficient with their time. They should also know how to engage prospects with the right information and 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 home in on which leads are worth focusing on and which ones aren't worth your time?
The best answer 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 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, ensuring that they move beyond gathering data and are able to turn it 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?
While one prospect might be looking for a solution that helps the company scale fast, another may be prioritizing 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 today enter the sales cycle later (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 which resources to use 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 VPs of Sales have been stuck in a situation where, suddenly, 20% 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 it, giving themselves the ability to 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 and 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 the next quarter could be your biggest one yet.
By Stacey Bishop