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CRM and Artificial Intelligence: Today & Tomorrow

CRM Expert and IT Architect


While the cloud technologies and artificial intelligence (AI) keeps winning the business world, our CRM consultants give a closer look at what changes it can bring to the CRM market. But first, here's what the numbers tell about the AI use in CRM today.

B2B CRM and AI

AI plus CRM: 7 stats you don't want to miss

As cloud-based CRM is growing in popularity (with 62% of CRM software predicted to move to cloud by 2018, Forbes), machine learning and artificial intelligence technologies keep entering sales people's daily routines with products like Einstein or Dynamics 365. According to the Economist Intelligence Unit report, 75% of the executives surveyed plan to introduce AI in their companies till 2020. 26% of them hope that this will help to improve customer service, while 17% expect to get an increase in sales.

Application of AI in CRM is supposed to keep growing with the advancement of tools offered by incumbents. Already in 2015, 25% of leaders in customer service relied on the best-next-action functionality of a kind, and 74% of marketers used predictive intelligence to craft content for a better customer experience (Salesforce). Looking at the tomorrow of machine-enabled communication, Gartner goes further and claims that, by 2020, 85% of customer interactions won't require human service reps as machines will be able to collect customer data across channels and manage human-like interaction with clients.

While machine dominance in the (historically human) CRM area can seem too brave a prediction at first sight, successful cases like Marston's show that AI is soon going to disrupt the CRM space.

Why AI for CRM booms in B2B

With ample data generated by customers in B2C (for example, via social networks), the growth of AI-powered CRM is reasonable. But what can the B2B sector expect from the new technology? The main change that AI brings to CRM in B2B is that software seizes to only consume and provide information at user request. Instead, it pulls relevant data when it's most appropriate (for example, in the form of actionable cards in Dynamics 365).

Such an upside-down approach turns an AI-enabled CRM into a company's assistant that effectively solves common sales challenges such as the following.

Challenge #1. Target efforts at the leads who will convert

Perhaps, every sales person has at least once lost a lead after hard nurturing. This time could have been spent more wisely if they could predict the outcome in advance. Machine learning allows analyzing leads' behavior in CRM so as to automatically rank them by the probability to convert and even identifying if the contact person has the authority to close the deal. This way, a company can manage their resources better, by allocating more time for and assigning more experienced team members to stronger leads, as well as by prioritizing tasks for all sales agents to let them focus on high-quality leads first.

Challenge #2. Win them back before they flee

When there are competitors around, even a slowdown in customers' responses can be an alarming sign. Yet, it's hardly possible for sales people to monitor every customer's account. However, AI-enabled CRM can analyze a customer's mood and deliver alerts right to sales people's fingertips. By drawing on patterns in purchase history and email answers, the software can help to spot relationships at risk and suggest how to revive them.

Challenge #3. Optimize sales people's daily performance

Customer satisfaction depends on how prompt and relevant sales people's answers are. AI can speed up sales agents' daily routines with recommendations of the next best action. For example, by spotting a question in the customer's email, the software can suggest marketing materials from the knowledge base (relevant case studies or presentations). By analyzing customer behavior (content openings, purchase history, browsing history), a CRM can learn what information the customer needs, or what the cross-selling and up-selling opportunities are. As a result, machine learning not only makes sales people more effective in tasks but substantially improves customer experience.

The future of AI and CRM

Today, incumbent vendors Microsoft, Salesforce, SAP, Oracle invest heavily in AI capabilities of their CRM offerings. As the new features can considerably improve customer experience and optimize sales people's work, it's likely that in a few years down the line many companies will turn to CRM customization to bring AI to their dialog with customers. Yet, for now, it's questionable whether machines will be able to perform 85% of the tasks human reps do today. What do you think about it? Feel free to comment below. 

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