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Artificial Intelligence in Sales: What It Is, How to Use It and Companies to Demo
Blog Feature

By: Mike Kaput

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January 15th, 2019

Artificial Intelligence in Sales: What It Is, How to Use It and Companies to Demo

Artificial intelligence can help salespeople hit and exceed their quarterly numbers. This fact is often obscured by all the buzz around AI.


But make no mistake: AI has real applications to help you sell more—starting today.


Forward-thinking companies are catching on to that fact.


According to Salesforce’s latest State of Sales report, sales leaders expect their AI adoption to grow faster than any other technology. Salesforce also found that high-performing teams are 4.9X more likely to be using AI than underperforming ones.


Yet AI is not replacing salespeople. Quite the contrary, the vast majority of companies using AI or planning to over the next two years also plan to increase staff.


That’s because AI is creating practical value for sales teams by automating, augmenting and supercharging the way they work, with several real-world use cases and tools being used today.


But there’s so much hype around AI that salespeople often miss this fact. We don’t blame them. They’ve got numbers to hit, and too much commentary out there about AI is aspirational, not practical.


In this article, we’ll stick to the practical.


We’ll outline a working definition of AI for salespeople that includes just the bottom line, no fluff or technical jargon.


Then we’ll look at some top AI use cases for salespeople, so you’re armed with some ideas on how the technology can help teams better make their quotas.


Finally, we’ll overview some top companies that use AI to give salespeople superpowers, so you have a few tools to start looking into.


Happy hunting.

What Is AI for Sales?

Artificial intelligence is an umbrella term that covers several different technologies, like machine learning, computer vision, natural language processing, deep learning, and more.


At their core, though, all of these technologies help machines perform specific cognitive tasks as well as or better than humans.


For instance, AI-powered computer vision systems in self-driving cars are able to identify obstacles just like people do, allowing the machine to take the wheel.


Your favorite voice assistant, like Alexa or Siri, understands your words just like another person, then responds in kind—all using AI.


Amazon and Netflix use AI recommendation engines to offer up products and movies you might like, making assumptions about your preferences just like a fellow product or movie enthusiast might.


While there are a ton of complexities to different types of AI, all you really need to know right now is that “artificial intelligence” describes many different types of smart technologies. And many of these technologies can impact your sales career and performance in profound ways.


That’s because AI isn’t just automation, though it may include elements of intelligent automation. AI takes things a few steps further. These technologies analyze large datasets. They don’t just crunch numbers, though. They use advanced computer science techniques and superior computational firepower to extract insights from data. These insights can then be used to make predictions, recommendations, and decisions.


In the process, the most advanced AI systems actually learn to improve their predictions, recommendations, and decisions as they make more of them.


This last point holds the key to the true power of AI in sales:


Systems that use machine learning can be trained to achieve certain results, then turned loose on completely new data to achieve those results again and again, learning more and more about what works and what doesn’t each time.


This means sophisticated AI can analyze customer and prospect data, predict which prospects are most likely to close, recommend the most important sales actions to take, forecast results, optimize pricing, and much, much more.


Check out the Artificial Intelligence for Sales 101 Workshop at the Marketing AI Conference (MAICON), July 16, 2019 in Cleveland, OH.

Use Cases for AI in Sales

Thanks to this power to augment and improve sales performance, McKinsey analysts writing in Harvard Business Review estimate that AI can create $1.4 to $2.6 trillion of value in marketing and sales.


That’s because there are plenty of ways to use AI to hit your numbers faster or exceed them entirely, provided you have clean, organized data of the right type. Here are some of the top ones that sales pros might want to investigate further.

Predictive Forecasting

Artificial intelligence systems exist that can predict or forecast outcomes using historical data to inform future results. Common predictions that sales AI systems can make include:


  • Deals or prospects most likely to close.

  • Deals or prospects to target next.

  • New customers that may be interested in what you’re selling.


Now, the accuracy of those predictions depends on the system being used and the quality of the data. But the fact is that, with the right inputs in the past and present, AI is capable of showing you who is most likely to buy in the future.


Predictive forecasting can also create value for sales teams internally.


Using the same types of data analysis, AI can help sales managers forecast their team’s performance for the quarter well in advance, so they can take proactive steps based on the numbers.

Lead Scoring and Prioritization

Artificial intelligence can look dispassionately at large datasets from a number of sources and tell you which leads you should prioritize, based on the scores the AI has given them.


As noted by sales pro Victor Antonio in Harvard Business Review, human salespeople usually approach lead scoring and prioritization in an unscientific way:


“Often, this decision-making process is based on gut instinct and incomplete information. With AI, the algorithm can compile historical information about a client, along with social media postings and the salesperson’s customer interaction history (e.g., emails sent, voicemails left, text messages sent, etc.) and rank the opportunities or leads in the pipeline according to their chances of closing successfully.”


In this case, AI can bring a level of logic and standardization to the process that humans just can’t match.

Expert Recommendations

Beyond prediction and prioritization, some AI systems may actually recommend sales actions, going so far as to tell sales teams which actions the system thinks make the most sense, based on your goals and insights from the data.


These recommendations may include advice on how to price a deal, who to target next, or which customers to target first with upsells or cross-sells.


The result is targeted guidance on what actions to take, so salespeople can free up bandwidth to close deals, rather than deliberating about what to do next.

Performance and Productivity Enhancement

AI can also automate or augment your work to take away some of the drudgery that distracts you from higher-value tasks.


AI can help with everything from managing your calendar to scheduling meetings to assessing a sales team’s pipeline by automatically doing these things for you or making them dramatically easier by using your historical usage data to make decisions. This use case is very similar to how some consumer calendar and productivity apps work, recommending recurring events or to-dos dynamically thanks to AI.

AI Companies with Sales Applications

Now that you know what AI can do, you might be wondering what solutions out there actually do it.


One of the top players in AI for sales is (not unexpectedly) Salesforce. The company’s AI is called “Einstein,” and it shows up in many places throughout Salesforce’s Customer Success Platform.


Einstein automatically prioritizes leads for your sales reps. It evaluates the likelihood of deals to close. And it empowers developers to bake AI into their Salesforce apps.


Salesforce Einstein is a prime example of how many players in the AI for sales space are existing companies. Big existing players, at least the savvy ones, are incorporating AI into existing platforms by hiring AI talent or buying AI companies. In fact, Salesforce has acquired four different AI startups since 2015 to power Einstein, according to CB Insights.


Another example of existing companies embracing AI is InsideSales.com.


Since 2004, InsideSales.com has provided sales automation software that boosts productivity and performance. Recently, the company has gone all-in on artificial intelligence, baking the technology into its platform.


The result?


The company’s AI predicts which deals or accounts are most likely to close, leading InsideSales.com to claim the system can boost customer revenue by 30% in 90 days.


One of the company’s strengths is its enormous dataset. The company analyzes trillions of data points related to sales transactions to make its recommendations. Its AI also looks at your CRM data and external data that may influence deals, like stock market moves or merger and acquisition activity.


The AI that powers the solution will even prescribe steps for sales teams to take to convert prospects.


Conversica is another major player in the space, with $87 million in funding. The company provides an automated AI sales assistant that engages your leads in conversation. The AI assistant conducts conversations with leads, further qualifying them before they talk to a rep.


This type of intelligent automation provides a number of benefits. Human reps are freed up to actually sell to people who are interested in a product or service, rather than wasting a lot of time talking to people who aren’t qualified. Every lead gets a follow-up, since the AI assistant can scale easily.


It’s a perfect example of how machine and humans can collaborate in sales to unlock even more value.


And let’s not forget the startups.


One example is Node, an AI startup backed by Mark Cuban that he calls a “cold call killer.” The platform relies on machine learning and natural language processing to proactively recommend new customers to sales teams. Based on the results, the platform learns over time to more accurately improve its recommendations.


These are just a sampling of the companies out there working on sales and marketing solutions. At the Marketing AI Institute, we’re tracking 1,100+ sales and marketing companies with more than $5.2 billion in funding. Subscribe to our blog to keep up with the latest profiles we do on sales AI vendors.


In the meantime, where do sales pros go from here?

What Do You Do Next?

You have a better understanding of AI’s potential, its use cases, and some examples of actual companies that use AI in sales.


What’s next?


This article and our blog are great places to start.


But reading isn’t enough.


Remember that Salesforce State of Sales study? High-performing sales organizations are 4.9 times more likely to be using AI than low-performing ones.


It’s absolutely critical that salespeople go from theory to practice as fast as possible if they want to develop a competitive advantage with AI and not get left behind or made obsolete when the competition starts using AI.


If you choose to take action, I hope you’ll join us in Cleveland, Ohio, July 16 - 18, 2019 for the inaugural Marketing Artificial Intelligence Conference (MAICON).


MAICON brings together top authors, entrepreneurs, AI researchers and executives to share case studies, strategies, and technologies that make AI approachable and actionable for marketers and salespeople.


In addition to relevant speakers and main tracks, the event also has a dedicated workshop for sales professionals.


Click below to learn more.

Get free access to the Ultimate Beginner's Guide to AI in Marketing: https://www.marketingaiinstitute.com/beginners-guide-access

About Mike Kaput

Mike Kaput is the Director of Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs. Full bio.

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