Maven Sales Group Blog

Artificial Intelligence vs. Machine Learning In Sales. What’s the difference?

6/4/18 11:41 AM / by David Fletcher

Artificial intelligence and machine learning are two of the biggest buzzwords and trends within the sales sector. While these two terms are often used interchangeably, they are in fact quite different. If sales associates want to maximize their efforts, then they need to ensure that they understand the key differences between artificial intelligence and machine learning, especially as they relate to big data and analytics.
What Is Artificial Intelligence (AI)? 
AI is the umbrella term for the variety of processes (including learning and decision making) that help make computers both faster and smarter. In fact, AI is an essential field within Computer Science. One of its integral components is big data. In order to continue to process and analyze information at faster speeds and larger quantities, AI systems need to have access to incredibly large fields of data.
One of the best components of AI is that it can be used across a wide variety of industries. For example, AI can scrutinize student study patterns to create personalized tutoring suggestions. It has also been used within robotics, speech therapy, transportation, medical, and marketing fields. For example, inbound marketing focuses on attracting customers via content that is engaging, relevant, and helpful. It focuses on establishing connections, growing relationships, and helping customers travel
through the sales funnel in a way that is both "human" and decidedly personal. Not only that, but inbound marketing is about delivering the right message to the right person at the right time and on the right communications platform.  So, where does AI fit in with inbound marketing?
AI provides the right data, intelligence, and tools, such as those offered by HubSpot, to deliver hyper-personalized content on a large scale. Through AI sales associates and marketers can make decisions based on carefully analyzed data points In fact, it's how Netflix, Pandora, Spotify, and Amazon are able to make the recommendations for what you should, watch, listen, or buy next. These powerful insights are all thanks to AI
What Is Machine Learning?
Machine learning falls under AI. It is a specific process whereby knowledge is discovered, data points are gathered, and algorithms are used. At its core the entire process follows these seven steps:
1Data is imported using a specific algorithm.
2Data is segmented into smaller subsections, including: training, validation, and test data.
3One model is built from the training data.
4The model is then validated against the gathered validation data.
5Finally, the model is adjusted to improve the accuracy of the initial algorithm.
6The final model is then used to make predictions about new (and upcoming) data sets.
7The cycle is repeated as the model and algorithm continue to be fine tuned through a series of tests and validations. 
The goal of machine learning is to help predict, optimize, and maximize efficiencies. It achieves these goals by sifting and learning from copious amounts of gathered data points. Once the model and algorithm have been validated, they can be deployed to help the sales teams effectively prioritize their leads. With this in mind, it's important to note that AI models don't need to be rebuilt. Unlike machine learning, AI models gather excessive levels of feedback to actively find better sources of data. As AI models find better sources of data, they automatically rebuild themselves, which is one of the biggest differences from its machine learning counterpart.
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How Can Artificial Intelligence And Machine Learning Be Used In Sales?
AI and machine learning can both be used to effectively enhance the sales journey for customers, while simultaneously improving the results of sales associates. In fact, AI can be used to more readily guide the sales journey, while machine learning can be used to fine-tune offers, processes, and the actions of the sales department. Additionally, these two powerful tools can be used to:
1Leverage Smarter Insights. -- AI delivers smarter sales intelligence. It does this by using big data analysis to search for, find, and predict the actions of similar leads. These insights are passed along to the sales associate, who can then turn a cold lead into a warm lead. AI can also be used to deliver the personal touch that customers expect from a brand. While AI is delivering smarter sales intelligence, it is also streamlining processes, optimizing and analyzing big data points, and increasing the effectiveness of entire sales organizations.
2Improve Sales Efficiencies. --In the old days, sales associates used to spend copious amounts of time completing mundane tasks. Now, thanks to AI, approximately 40 percent of these administrative type of mundane tasks can be effectively automated by AI technologies. For example, sales associates can say goodbye to manually entering CRM data. They can also reduce the amount of data entry errors, simply by using a proven AI technology. In fact, studies show that there is on average a 50 percent increase in leads when AI technologies are used to enhance sales efficiencies. The increase in leads, combined with additional free time, and smarter sales intelligence can all be combined to improve the bottom line; and it's all thanks to AI.
3Discover The Right Leads On The Right Platforms. -- Simply put, AI effectively answers the "who, what, where, when, and why" of finding new prospects. However, machine learning can also be leveraged to sift through the gathered data, so that you know exactly what messages to send, at what time, and on what platform. By working together, AI and machine learning tools can personalize these marketing messages, so that leads feel as if you are speaking directly to them. This personalization tactic is key, especially for large organizations who need to send out marketing messages on a large scale. Together, AI and machine learning work to segment your prospects into niche audiences who are more likely to positively respond to your marketing campaigns. As the audiences respond, machine learning and AI tools, such as HubSpot, can then share the insights with the sales team, so that the customer can more easily complete their buying journey.
The Bottom Line: AI And Machine Learning Are Both Important To Sales
Contrary to popular belief, AI and machine learning aren't here to take jobs away from hardworking sales associates. In fact, these two invaluable tools can and should be used to assist the entire sales process. No matter whether you are working within SaaS or the fashion industry, the customer's buying journey still hinges on your ability to establish a meaningful (and human) connection. Fortunately for the savvy sales associate, both AI and machine learning offer the specific tools and technologies needed to provide heightened insights, increased efficiencies, and empowered communications that enhance the customer's buying experience.

Topics: sales coaching, AI, Artificial Intelligence

David Fletcher

Written by David Fletcher

David Fletcher is the Co-Founder and Chairman of the Maven Sales Group, a HubSpot Sales Partner and sales enablement firm located in the Washington, DC area. David is also the Sr. Global VP of Sales for ClearSale, Maven's largest client, which is a fraud management and protection services company. David is a graduate of The George Washington University, graduating with dual majors in Business Management and Criminal Justice. After graduation, David stayed in the DC area as a sales professional before starting his own systems integration firm. Once his firm was acquired, David moved on to become the President of a marketing agency providing HubSpot Consulting and inbound sales strategies to B2B clients. David has a unique perspective on sales and marketing in which David doesn’t approach issues as a “sales problem” or a “marketing problem”, but as a “revenue problem”. As a seasoned sales and marketing professional, David has worked with the HubSpot product development teams in an effort to create a better user experience for HubSpot customers. David enjoys reading, golfing, fishing and the outdoors. He lives in Lake Shore, MD with his business partner & wife Shannon, and their 5 sons.

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