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Machine Learning in Sales: 6 Ways ML Optimizes An SDR’s Workflow

Sales is a charismatic profession and it definitely requires the human touch. It’s all about building trust and relationships—the kinds of things we do instinctively and implicitly. So, why would you need machine learning to help out with sales? 

While there is not—and never will be—a substitute for the human element in sales, machine learning can empower your sales representatives in some surprising ways. It takes out the drudgery, optimizes your sales pipeline, makes the whole job a lot easier, and allows your sales representatives to do what they do best: connect with customers, and sell your product.

If you want to know how machine learning can be used in sales, read on. We’ll tell you six practical ways that machine learning in sales can make your representatives’ lives easier.

 

What is machine learning?

Machine learning is an important branch of AI. It involves the use of carefully curated data, for example from a PySpark dataframe filter, to continuously “teach” an AI.

The AI will use data and algorithms to observe and gain progressive insights on a given topic. Netflix’s recommendations AI is a good example. It “learns” your preferences by studying your watching data. At the same time, it learns from the wider pool of Netflix users the kinds of programs people with your watching history prefer. It then uses that data to present you with recommendations. These grow and change on a continuous basis, based on your own behavior on the platform.

   

There are many models of machine learning. The most sophisticated use “neural nets” to imitate human learning processes, but even a “basic” machine-learning AI can come up with some very impressive insights.

As well as giving you great Netflix and Amazon recommendations, machine learning can help your sales reps in several practical ways. Here’s how:

 

1. Save time and increase job satisfaction with automation

Sales is a very time-consuming job. As well as the customer-facing stuff, there’s a lot of prep and study involved. Plenty of salespeople work long hours and take their work into the weekends.

For many, sales is a vocation. They don’t mind the long hours and stressful workload because they love what they do. They love the thrill of clinching a deal and enjoy connecting with customers. However, a lot of the sales process is pretty mundane. The dynamic, creative, charismatic stuff is contrasted with research, data entry, scheduling, emailing, etc.

Machine learning can automate a lot of this mundane stuff, giving your representatives time and headspace to put their focus where it counts: on the customers. For example, you can use machine learning to automate aspects of the customer journey. Automations can send crucial emails like welcome emails, cart abandonment emails and delivery notifications. What’s more, automated AIs can do this kind of repetitive, mundane work constantly, quickly and accurately. 

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Automating workflows and routine tasks can free up a massive amount of time for your human sales team. At the same time, taking away the drudgery allows your sales reps to focus on the more fulfilling stuff. This gives a massive boost to job satisfaction.

 

2. Bring insights quickly, easily, and accurately

Understanding your customer is crucial for sales. To properly understand your customer, you need to study them. In the age of e-commerce, this means data analysis. Every customer touchpoint yields valuable data from social media interactions to purchase orders.

There are plenty of insights to be gleaned from this data, but combing through, organizing and analyzing the data is a full-time job. For humans, this level of data analysis is a slog. But an AI thrives on data. Data is the sea that AIs live in; they live and breathe data. 

Data science is a subset of AI and machine learning, but this subset has a huge part to play for sales professionals. An AI can gather, organize and analyze millions of data points in seconds. It can then feed its analysis back to your salespeople in the form of actionable insights.

Take lead generation, for example. Finding new leads is a huge part of any salesperson’s job. And a huge part of that huge job is market research. Salespeople slog through bytes and bytes of market data every day in order to get insights about their customers: where they hang out, what they want, what they need, what they’re likely to respond to. It’s a lot. And it takes time.

However, there’s nothing easier than market research for a machine-learning algorithm. Just plug them into the data and wait for the insights to roll in.

AIs can process millions of bytes of data in a very short amount of time. They can provide insights with a volume and degree of accuracy that would simply be impossible for a human. And, thanks to machine learning, they will get better at understanding your customers the more data they parse.

So, not only will you take a burdensome task off your sales representatives’ shoulders, but you’ll also optimize your entire market research process.

 

3. Optimize every process

Sales is an intuitive process. It requires an innate understanding of human nature, and an ability to intuit, empathize and connect. An algorithm can’t do these things. But what it can do is reduce the margin of error. When you’re working with human emotions, there’s a lot of doubt. And we overcome that doubt in very human ways. 

Take superstition, for example. Ask any salesperson, and they will tell you that they have superstitions about their job. Maybe they wear a “lucky” necklace when making an important sale. Maybe they have a set routine that they follow at all costs. 

It’s pretty harmless but based on incorrect correlations and assumptions. And that mechanism carries over into everything a human salesperson does. A machine-learning algorithm doesn’t have those constraints. It deals in real, incontrovertible market data. The insights that data can yield will help you to cut the crud. When you automate, machine learning can arm your salespeople with firm facts. 

This allows you to optimize every process at the source before any human doubt, error or extras can creep in. 

4. Provide the right data at the right time

Research is a time-consuming process. Machine learning, however, can slash research time from hours to seconds. For example, rather than trawling through old records to pull up a customer’s information, your salesperson can simply click a button, and the algorithm will tell them everything they need to know.

Depending on how you integrate your algorithm and/or what platform you go with, you can give your sales representatives absolutely everything they need to know, in one place, with a single click.

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5. Take the pain out of pricing

The modern consumer shops around. They have access to every competitor in your market at their fingertips through the internet. This makes pricing a major headache for companies.

You don’t want to take prices so low that you can’t meet your costs, devalue your product, or both. But you also don’t want to price yourself out of the market. Keeping yourself in the pricing sweet spot involves a lot of market scrutiny—a huge job.

Machine learning, however, can constantly monitor that demand-supply curve and cross-reference it with average competitor prices. It can then advise you about your business’s best possible pricing strategy.

It can also arm your salespeople with the information they need to make informed pricing decisions. For example, it can recommend discounts, offers and loss-leaders where appropriate.

6. Look into the future

Forecasting is one of the dark arts of sales. Experienced salespeople are very good at predicting market trends. Based on their knowledge of market forces, their experience of trends, and what they see and hear from customers daily, they can come up with great market predictions. That being said, forecasting takes a lot of time. And it’s far from an exact science.

When you bring machine learning into the mix, you take the labor out of forecasting. Using present data and past trends, your algorithm can predict things like demand, pricing, CLV and even customer trends with high accuracy.

Most importantly, they can do this very quickly and on a continuous basis. This takes the pressure off your representatives, enabling them to focus their time and energy on your customers.

 

Optimize your time with machine learning

The bottom line here is that machine learning can give your sales representatives their time back. Machine learning isn’t designed to replace human sales representatives. Far from it! It’s designed to enable them. Machine learning removes the pressure from your human salespeople by taking on mundane tasks like curating email journeys and data analysis. This gives them the time and to focus on what they do best: connect with customers


This article is part of the Crunchbase Community Contributor Series. The author is an expert in their field and we are honored to feature and promote their contribution on the Crunchbase blog.

Please note that the author is not employed by Crunchbase and the opinions expressed in this article do not necessarily reflect official views or opinions of Crunchbase, Inc.


  • Originally published August 5, 2022