Today, artificial intelligence is not an insidious invader, as it was represented earlier. Conversely, the integration of AI and related technologies is changing many spheres of our everyday life making it much easier.
In this article, we are going to discover one particular area that can benefit and seriously change with the help of AI. These are customer relationship management systems or CRMs.
Typical use cases for AI technologies in CRMs
There are 2 main scenarios how AI CRM systems can be utilized.
First, artificial intelligence acts as an advisor in the decision making process along with the data mining and machine learning. A system analyzes data to provide managers with predictions on sales, marketing, or customer service. It operates on the basis of pre-designed algorithms that include important data for analysis. The system itself can’t make decisions, only suggest the most suitable ones, e.g., it analyzes customers’ behaviour, purchase history, and their interests in social media to give sales specialists the clear view on the product that might be interesting.
Second, AI can become an autonomous unit and be responsible for a certain part of decisions. It can give recommendations on top of the results of machine learning. Usually, this use case is applicable for some routine actions that doesn’t require the final approval. For example, a chatbot can automate the customer service.
Regardless of the use case chosen, the CRMs will accurately solve business queries, such as in one of our solutions based on the Force.com platform. To improve marketing efficiency, SCAND has developed a Salesforce application—LeadControl—that aims to gather data about potential customers for its further processing. Therefore, the CRM system can generate cold calling leads to maximize marketing impact on the customers.
Machine learning and CRMs
Among a number of different AI-related technologies, machine learning is one of the most powerful additions to the existing CRM systems. It gives businesses an opportunity to change themselves from reactive to predictive customer services.
Initially, the system collects information about a wide range of things. Then, this data is analyzed and processed with the help of machine learning to create patterns and identify trends. For example, Microsoft Dynamics CRM machine learning is using the Azure cloud platform to build the model for automatic cross-sell product recommendations.
On top of that, the more information such machine learning CRM processes, the more precise and intelligent it becomes in its predictions. Based on SCAND’s experience, the results of machine learning assist in foreseeing:
- Consumer behavior that is hinged on the data about tastes and choices collected from many users (collaborative filtering).
- Demand for a certain product or service. That is about content-based filtering which is used to recommend the items a user might like according to his/her preferences.
Machine learning is only a part of AI-based technologies that is dramatically changing CRM systems. Modern CRMs being powered with artificial intelligence dictate the advanced level of business processes optimization and automation.
That should bring companies such benefits as cost savings, faster reaction to any kind of internal and external changes, and other positive shifts.
In case you are interested in CRM solution development, don’t hesitate to ask SCAND for a consultation.