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How Artificial Intelligence Will Revolutionize the Sales Industry


Buttice, C. (2017, 9 27). Retrieved from How Artificial Intelligence Will Revolutionize the Sales Industry:

Takeaway: AI is already assisting businesses in sales, but is poised to become an even more important player in the world of sales and customer service

Artificial intelligence (AI) is becoming a major player in the sales scenario, before, during and after the sale is done. From scavenging through big data that no human could ever analyze, to fully automating the process through intelligent, machine-learning bots, AI is already critical to bolstering a brand's marketing efforts.

Often called the “AI revolution,” the introduction of computer-based solutions to automate the sales process is still taking its first steps. However, we’re not so far from a world where self-managing scripted systems are going to be a substitute human intelligence altogether. Just take a look at how well Google Translate is now able to understand human languages, or how targeted ads keep haunting our searches like there’s a hidden “someone” out there who really knows our tastes.

Artificial intelligence is definitely bound to change the sales industry in the future, but it is already impacting it in very significant ways. (Want to learn more about AI? Then check out How Should I Start Learning About AI?)


Artificial Neural Networks (ANNs)

Artificial neural networks (ANNs) are the synthetic reproduction of a mammal brain: a large network of interconnected processors that operate in parallel. Just like a much more simplified version of human neurons, these computing units processinformation, learn from experience and identify patterns. Although they lack the flexibility and ability to adapt like biologic interfaces, ANNs may take previously solved examples to build a system which is able to make new decisions.

One of the traditional uses of ANNs is to analyze historical data collected in spreadsheets to make rather accurate predictions and sales forecasts. After a short “training period” during which the neural network learns using historical problem data in which the outcomes are known, the AI is able to recognize patterns and provide solutions and estimates.

Thanks to this ability, they can be used to efficiently allocate marketing resources and optimize a company's advertising efforts. By interpreting a plethora of parameters such as marketing costs and gross profits, ANNs can be used to predict next period's sales with a relatively narrow margin of error.

Deep Learning Algorithms

Shortly after we search online for any one of our interests, tons of ads for closely related products start appearing everywhere. Deep learning algorithms already started scanning through the big data to forever change the world of automated ads. Google’s search engine always included a certain degree of machine automation in the form of algorithms, but it is only recently that deep learning ones have been introduced.

Driven by highly advanced neural nets, they constantly analyze information ranging from spoken smartphone commands to social network photos and statuses, and, obviously, search engine queries. They possess their own “intelligence,” and since they’re much faster and can act on a much larger scale than humans, they are already able to outperform us in this task. Their training process never ends, but in these last few years they've been able to learn so much about our behaviors that they can now predict almost every step of the average user.

Machine-Learning Bots and Sales Automation Platforms

All bots are programmed to find the quickest, most effective way to achieve a goal – in this case, automate the sales process. Machine-learning bots go beyond that, and, in time, learn to optimize their process by gathering data and info from customers. But the biggest challenge that every AI must face is to collect the data required to train the algorithms. And while for giants that deal with practically endless amounts of user data, like Google and Facebook, this might not be an issue, for smaller companies it definitely is.

However, just like Tesla beat Google in the self-driving car race (pun intended), some ambitious and resourceful new enterprises like Growbots showed that the even start-ups might have the strength to compete at the same level. With a 10 percent growthmonth over month, this relatively new business is changing the outbound sales scenario with a fully automated platform that is able to analyze millions of websites every day to extract data about companies and people alike.

AI-controlled bots can easily reach millions of customers, find the right ones to contact, write follow-up emails and automate the entire sales sequence. By minimizing their marketing expenses with these smart solutions, even small and medium-sized businesses (SMBs) can now compete with the big players and their enormous budgets. Salesforce integration and smart deduplication functions allow less-than-huge companies to reduce their workload by up to 90 percent, and save precious resources as well as employees' time.

Assisting Humans with Customer Experience

User engagement and customer experience are critical aspects of the post-sale process. Existing clients are more valuable than new ones because of their loyalty and referrals. However, both when assisting customers or securing new prospects, almost half of salespeople cannot understand customers' pain and problems. They lack the confidence to uncover their issues, leading to fumbles and misunderstandings that ultimately cause them to spoil the relationship with the client.

To achieve a smarter lead generation process, AI can simply assist humans in many ways. AI may analyze all data points of a selling process to identify the weak spots and create a comprehensive, more efficient prescriptive sales approach. It may dig into all available customer data to determine the right time or day to call a certain prospect, as well as that person's interests, wants and needs, in order to assist the sales force teams. A well-established process will bolster sellers’ confidence and increase their chances of closing a deal.

Machine-learning engines might help human customer service agents by determining who would serve that customer best. In addition, AI-assisted speech recognition may help spot keywords that trigger vital service enhancements, such as alerting a manager to assist the call when the word “supervisor” is mentioned. (Learn more about speech recognition in How Natural Language Processing Can Improve Business Insights.)

According to recent research, 70 percent of people claim that they would be willing to pay more for a brand if their customer service reputation is good enough. It's no surprise then that, according to recent forecasts, within five years, AI will manage 85 percent of customer relations.


Improved marketing automation is leading to greater scaling, better outcomes and reduced costs. Impractical tasks are already being handled by self-sufficient machines, and newer AIs support the human workforce every day by facilitating their operations.

Although in the future a few employees are bound to lose their jobs to robots, the AI-augmented sales process might help our society become a little more fair and equal. In fact, Even SMBs that cannot afford to hire hundreds of employees could then compete with the larger corporations.

However, the ultimate beneficiaries of this alleged revolution are undoubtedly going to be customers, who will enjoy a much smoother and more finely tailored buying experience

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