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Mike Lieberman, CEO and Chief Revenue ScientistThu, Dec 21, 2017 5 min read

Your Ultimate Guide to Machine Learning and Sales

{}If you have yet to embrace the rise of artificial intelligence (AI), you are quickly losing your competitive edge. There is more consumer data out there than ever before, just waiting to be captured. While some are still worried that AI means the death of the sales professional, top organizations have already taken the leap and consider AI a vital part of the sales process.

Technology is making our machines smarter and better optimized. Using artificial intelligence, sales tasks are automated, leads are qualified with hard data, and sales managers get real-time analyses of their forecasts and rep performance.

AI has its pros and cons, but one thing’s for sure: Machine learning will change how the world does business and how companies interact with consumers.

What Is Machine Learning?

Artificial intelligence is the broad term for machines performing processes on their own and learning from their decisions and data input. Machine learning is the application of AI to develop computer programs that can recognize patterns in data and learn for themselves how, when, and where to take their next action or make their next prediction.

Every time the machine receives a new tidbit of data, it updates its system and optimizes its recommendations. Think about every time you watch a new show on Netflix. You have given its algorithm juicy new data on your interests and watching habits, making it easier for Netflix to recommend and tailor the site to your preferences.

In the sales world, this allows sales teams to be more data-driven and proactive. AI acts as a guide, picking up on prospects’ signals and actions, and facilitating the buyer’s journey. Many businesses already track and collect customer data. With machine learning, this data is used effectively by allowing a system to make decisions and implement processes based on gathered information.

How Will Machine Learning Change Sales?

Efficient Prospect Targeting

You would be surprised how much information your organization has on the buying patterns of your customers. While it might take a salesperson hours to pore over data or read every CRM report, machine learning software can analyze data in a split second. It can identify patterns, recognize exactly where a prospect is in the sales cycle, and decide when they are a fully qualified lead.

Once it knows what a converted lead looks like, it can accurately perform lead scoring and only pass along qualified options to a salesperson to close the deal. There is no more wasted time on leads that are unlikely to convert.

Improved Lead Nurturing

According to a Harvard Business Review, 85 percent of a customer’s interactions with an organization will happen without human interaction by 2020. Even today, a significant part of the buying process is completed without ever talking to a salesperson.

Communication with customers and the experience of buying have changed. Today, chatbots can answer initial simple questions about pricing, services, product features, and points of contact. Using the feedback from these conversations, bots can either continue to nurture these leads or pass them onto a sales rep.

With all the collected data, businesses can predict effective sales tactics, which activities will push the deal in the right direction, how long it will take, and how they can upsell the prospect. This crucial data lets salespeople know exactly what they should be doing and when in order to have the highest chances of success.

Tailored Sales Coaching

Machine learning can also help sales managers guide their coaching and training initiatives. A strong sales team is built by constantly improving the skill level of every salesperson and recommitting to best practices and tactics.

AI can help generate a training plan and point out where your team has weaknesses. It can analyze the processes of your all-stars and also enable reps to focus on training by doing many of the tedious tasks for them.

Accurate Forecasting

With the addition of AI, sales managers can rely on accurate forecast predictions narrowed down to the sales rep. This can help them build healthy pipelines, analyze the team’s performance, and reduce costs. With this detailed type of analysis, sales leaders can discover the underlying reasons for certain sales trends and find tangible solutions to fix issues.

AI will never replace the personal interaction or the trust that comes with a human salesperson, but it can provide value both to the customer and to the sales organization. By guiding the sales process based on hard data and automating tasks that many salespeople resist completing, sales teams can focus on their top priority—closing the deal.


Mike Lieberman, CEO and Chief Revenue Scientist

Mike is the CEO and Chief Revenue Scientist at Square 2. He is passionate about helping people turn their ordinary businesses into businesses people talk about. For more than 25 years, Mike has been working hand-in-hand with CEOs and marketing and sales executives to help them create strategic revenue growth plans, compelling marketing strategies and remarkable sales processes that shorten the sales cycle and increase close rates.