Artificial Intelligence (AI)
in CRM…CRM of the
Artificial Intelligence, for years, has been the symbol of what the future will bring…whether it be robots in the workplace or smart appliances in your home. Well, the future is now.
AI is commonly described as intelligence displayed by machines, as opposed to “natural intelligence,” which is displayed by humans and other animals.
The long-range plan by numerous technology vendors is to evolve AI to include machine learning, reasoning, knowledge, planning, voice/speech recognition, text analysis, perception, and the ability to move and manipulate objects.
AI technologies are becoming more important in the world of business applications each year. And with more integration, data sets, and machine learning capabilities, the technology should continuously get more advanced.
When you couple the massive data explosion that is currently happening with the “Internet of things,” we’re putting a plethora of personal data out there to be mined. The need for AI technologies is being required more and more to sort it all out.
Past and present trends have been to move away from legacy CRMs that historically were mostly on-premises and operated as Excel replacements and static data-entry systems. There’s been a shift towards deploying more cloud-based CRM systems that act as digital assistants, rather than basic data input tools.
Software as a service, mobile and social are all becoming more prominent. With all the available information across many devices and platforms, companies had to have a way to integrate this “big data” into their cloud-based CRM in a way that produces results that are more predictive in nature. AI for CRM, powered by machine-based learning, is optimized for these large data sets.
AI and machine learning are still in their infancy stage when used with a CRM. However, in the next few years, businesses will/should be able to deliver more predictive and personalized customer experiences across sales, service, marketing, and commerce resulting in accelerated sales cycles, improved lead generation/qualification, personalized marketing campaigns, and lower costs of support calls.
AI-enabled CRM software will be able to:
- Analyze customer records & business data the system collects from sales, e-commerce activity, emails, IoT-generated data & social media, etc., and provide automated insights.
For example, you will be able to:
- Identify target businesses and provide companies’ previous purchase patterns, informing you whether your solution is complementary or redundant. The predictive analytics will provide better sentiment/intent analysis, product recommendations, and upselling. This intelligence will also increase customer retention.
- Assist sales reps in focusing on the most promising leads based on engagement data analysis & advanced lead-scoring tools. Also, recommend when to trigger email campaigns using machine learning algorithms and customer response history.
- Help determine the best person to contact to win the opportunity. Over time, the system will be able to teach itself to do an even better job of targeting potential customers and decision-makers by identifying which personal or professional attributes hold the most weight. As the software evolves, it will effectively create a system of continuous improvement for sales and marketing teams.
- By enhancing and automating the routine-based parts of the business process, sales teams can focus on better serving the more complicated and human-demanding needs of customers.
- Use Chatbots/assistants that:
- Can automatically reach out to anyone interested in the company, such as by downloading a whitepaper or requesting information from the website.
- The assistant processes customer replies determines feedback and potential questions, and issues a response. The assistant passes off the lead to a human salesperson when the time is right.
- In conjunction with AI algorithms, companies can efficiently identify and resolve customer issues/problems through natural conversation. These assistants free up customer support rep time for more critical and complicated tasks.