January 13, 2017
It’s safe to say that 2016 was the year of artificial intelligence. And while 2016 has come and gone, 2017 isn’t going to stray from the AI path we’re on right now. This technology has penetrated nearly every conceivable sector, from finance and education to operations and service, and in a particularly interesting way, to sales.
How AI Can Improve The Sales Culture
Depending on the report you read, somewhere between 50-70 percent of sales people don’t make their yearly quotas. That number is staggeringly high and suggests that there is an enormous amount of room in the average sales department for improving those outcomes.
Part of the problem is that, while most sales teams already have all the data to close those deals faster stashed in their CRM, obtaining the intel can be rather challenging. In fact, according to research conducted by Attivio, only 23 percent of companies encourage the use of big data to make sales easier. Additionally, 37 percent of respondents mentioned that it may take a day or more to access the sources for the analytics and dig through all the data silos.
Hiring data scientists to do the digging for you seems like the obvious decision in this case. However, 66 percent of the same survey respondents mentioned that hiring a professional is extremely challenging. For startups, the cost of having an in-house employee may be rather high as well.
That’s exactly where artificial intelligence could play a great role. Earlier this year, Salesforce has created some hype after announcing their new AI-powered CRM add-on, nicknamed Einstein, that would deliver better insights to the sales, marketing and customer support teams. The app will also deliver smart recommendations and predictions based on the advanced machine learning algorithms.
Salesforce, however, isn’t the only sales platform harnessing the power of artificial intelligence. Base CRM has recently launched another tool called Apollo, which also acts as a smart big data advisor and automatically delivers better insights about your customer base.
People.ai has taken another approach and built a productivity platform for sales managers, which delivers actionable insights on how to improve the teams performance, highlight what strategies are working, and advise on what to ditch.
In addition, SaaS Co. has just received $800,000 in Seed funding to continue developing the first AI-driven sales assistant named LISA.
The Most Anticipated AI Integrations for CRMs
As Tom Dietterich, a professor and director of Intelligent Systems at Oregon State University, previously stated:
“Instead of AI systems replacing people in the workplace, each of us would have an AI assistant that we would train in our lives and the two of us, together, would be employed … This is where we can see super-human performance coming from the combination of the human and the computer.”
That’s exactly the case with sales. We shouldn’t expect artificial intelligence to fully replace the human sales teams. But this technology can definitely leverage the efficiency and business decisions in multiple ways. It can be used to capture and refine data from external sources. For instance, IoT gadgets or on-premises iBeacons. In that case, we can obtain real-time details of customer buying behaviour.
By sourcing and analyzing the data coming from different sales channels (emails, calls, social media), the AI algorithms could provide the optimal personalized propositions for customers and compose the best marketing emails. In addition, personalization can be taken on a whole new level as well as razor sharp audience segmenting and smarter targeting.
Artificial intelligence algorithms could even retrieve the best opportunities to improve customer satisfaction and deploy automatic up-sell and cross-sell strategies.
The Word of Caution About Using AI in Sales
While artificial intelligence can definitely help us optimize and organize piled data more effectively, it’s still not a magic pill for all your problems. AI-powered systems will have to be trained to make accurate predictions based on your historic data. But what if past insight are incomplete or incorrect?
Another important question we should be asking is how to establish trust between humans and AI-powered solutions. As Patrick Mankins noted:
“Before self-driving cars can really take off, people will probably have to trust their cars to make complex, sometimes moral, decisions on their behalf, much like when another person is driving.”
If we want a future where customer support and sales assistants get replaced by smart chatbots, we’ll have to work on building solutions that sound convincing, confident and can build up empathy. Right now, chatbots still need to learn that. But we are sure to have some great advances in this filed in 2017.
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