Today’s post is by Gilad Raichshtain, founder and CEO of Implisit, a Salesforce company.
If you’re a salesperson, you’re always trying to beat your quota. To do this, you need to answer several hard questions, such as: “Will my deal close?”; “Am I focusing my time on the right deals?”; and, “What else can I do to increase the likelihood to win this deal?”
Answering these questions takes selling with data science. And data science is no longer just about analyzing customer and prospect data from emails, phone calls, product usage, etc. Data science can now tap deeper by applying other technologies such as text mining and voice transcribing – and analyzing the content of your communications as well as the context for each activity. The results of these analyses are tailor-made insights that will help you close more deals and faster. And the beauty of it is that it’s all automatic, simple, and – in more and more cases – is reaching accuracy better than humans.
By now, you’re used to hearing about data science. And the smartest salespeople are already showing its promise with their results. These savvy salespeople are using customer data like athletes who study their health data and analyze every move they made during a game – helping them improve their techniques, create a plan for success, and, ultimately, win.
Here are some of the best ways salespeople are using data science to beat their competition.
1. Upgrade to a Smarter Inbox
Before selling with data science, smart emails used to mean simple auto-reply templates. Now, some salespeople are taking the meaning of smart emails to a whole new level by answering the question: “How can I get creative with the thousands of emails I send to prospects each month?"
With customer data, salespeople are eliminating blind auto-replies. Smart inboxes combine customer data with email history to suggest the right email for a potential customer based on the salesperson’s specific history with that customer and where that customer is in the sales lifecycle. Even if you get the same reply from two different customers, a smart inbox would recommend two personalized emails for you to send back based on your history with these customers. Plus, a smart inbox would auto-log these emails so you don’t have to manually do this.
Another capability of smart inboxes is insight into your calendar. For example, let’s say you send a colleague an email with three dates you are free for a meeting. Your colleague opens this email hours after you send it, and, in that time, you’ve booked up one of those dates. With a smart inbox, your email to your colleague would automatically reflect the changes on your calendar, so your colleague would see only your most up-to-date availability.
2. Predict Which Prospects Will Become Customers
Wouldn’t it be great if you could accurately predict the numbers for a winning lottery ticket? If you’re a salesperson, you often feel this way with customers, wishing you could predict the likelihood your email or phone call is the winning ticket to securing your prospect’s business. With data science, this is within reach.
Today, companies can analyze the history of leads that have converted into customers and build the DNA of a prospect most likely to become a customer. The historical analysis would take into account the number of employees at the prospect, their geography, their seniority level, and thousands of other features to determine the likelihood of closing a deal. This helps sales development reps understand which deals they should prioritize early in the sales process.
3. Get an Intelligent Sales Assistant
It’s great if you’re a salesperson who knows which leads to focus on, but how do you know the steps to take to convert these leads into customers? Enter the intelligent sales assistant. This is a sales rep’s guide through each stage of a company’s sales process and helps reps stay focused on important tasks so they can close deals quickly.
For example, a sales rep using an intelligent assistant that logs a call to a prospect may get a pop-up notification that reminds the rep to follow up with the customer in a week – along with detailed context around other actions that should take place to move the deal forward.
New technology has definitely made data science more useful and less intimidating for entire sales organizations. Now, teams of all sizes and industries can easily detect patterns, find correlations, and make predictions that help sales rep sell faster, sell smarter, and knock quotas out of the park.