Artificial intelligence can automate personalized responses and analyze CRM data in real time to better understand customers and their motivations, and thus facilitate decision-making based on trend analysis.
The possibilities offered by AI in CRM
The main advantage of AI is its ability to rapidly analyze a large mass of data in real time to derive trends, patterns and personalized responses.
- Research sales opportunities with existing customers. We’re asking AI to do what a good salesperson knows how to do: analyze customers’ products and services, determine complementary needs – in effect, automating what we call cross-selling or upselling. This is the simplest and most profitable function of AI, but it will never do it as well as a good salesperson.
- Sending personalized offers to customers by e-mail or on the website following analysis of their purchases and behavior. To visualize things better, if you watch a certain number of series on Netflix, they’ll offer you others in the style you like to build loyalty, and then try to cross-sell or upsell.
- Scoring and prioritizing the easiest to optimize and the most profitable prospects. This is the task of sales managers at the end of the year, and here it’s done automatically in the CRM.
- Analysis of customer sentiments by deciphering a large mass of comments about current products, new offers, new prices. Here again, it’s a task that humans can do, even more finely, but AI makes it possible to do it faster on a larger mass of information.
- Predicting consumer behavior based on trend analysis, we determine which segments will decrease, which will increase, and what offer should be made to them.
- Identify at-risk customers at risk of leaving in order to make loyalty offers to them
- Implementation of chatbots to automate responses to customer queries on the website. You’ve probably taken part in discussions on social networks or with customer service on certain sites, thinking you were talking to a human, but it was a machine. Virtual assistants save on the payroll costs of customer service, but a human is still needed at the end of the day. The main aim of the bots is to reduce the number of customer service agents.
How to integrate AI into CRM
There are four possibilities.
- CRMs already incorporating AI, such as Hubspot, are expensive and not always user-friendly, and are particularly suited to very large companies.
- CRM solutions that allow you to integrate AI yourself, such as Microsoft Dynamics, which integrates Microsoft Azure. This solution is also complex, as you need a strong AI team to do it yourself.
- CRM and a separate AI, with no integration, is probably the simplest solution for a medium-sized company, but it’s possible with ActionClient CRM, specialized for small businesses and the self-employed.
- CRM with “human intelligence” is still the best solution for small businesses. Indeed, AI does absolutely nothing new, it just processes a larger mass of data faster.
AI tools
We have identified a number of tools, and of course the market is evolving daily.
- Microsoft Azure ML: a set of AI model development tools hosted on the Azure cloud.
- Tensor Flow is a Google tool that is in fact an open library for deep learning.
- Keras: interface for testing models developed with Tensor Flow
- Py Torch: another open library for deep learning
- Scikit-learn: set of simple Python tools for data analysis
- IBM Watson: tools for analyzing and processing natural language and images
- Google Cloud AI platform: cloud platform offering tools for developing machine learning models
- Amazon Sage maker: an AWS (Amazon Web Service) service for hosting machine learning model development tools.
- NLTK: Python tools for natural language analysis and processing
- UiPath : tool for automating repetitive tasks.
- Rasa: platform for developing virtual assistants (chabots) Open CV: open library of computer vision image processing tools
Conclusion
A CRM must prioritize its primary function, which is to manage customers to improve customer service and increase sales.
AI can automate certain tasks and reduce the number of customer service agents, while the other function of AI is analysis – it can process more data, faster.
But don’t forget that a good CRM should focus even more on achieving good results than on analyzing failures. It’s always better to make profits than to analyze losses.
So choose a simple, efficient system. If you can add AI, that’s fine, but it should remain a complementary function, not the raison d’être of your system.
There are two types of company, those with the right results, and those with the right excuses based on analysis, only the former survive.
Jean-Pierre Mercier
