Apply AI in CRM to Magnify Customer Experience

CRM Solutions, CRM software, Customer Experience, AI in CRM

Businesses are intensely meditating on the term 'customer experience'. What makes 'customer experience' crucial?

Retaining customers is the primary goal of businesses.

The law of business jungle states that higher the retention rates, greater the chances of survival.

The ability of your business to deliver delightful customer experience at every interaction, be it via a marketing campaign, contact center call, notification etc. makes or breaks customer loyalty. A great business reads the data and takes intelligent decisions to magnify customer experience.

AI helps to simplify complex dashboards and gives out ideas to exponentially optimize marketing and service. Delightful customer journeys, the crux of customer experience are being developed by AI powering units like Natural Language Processing (NLP), product suggestions, deep learning etc.

So how can you apply AI in CRM to significantly improve customer experiences? Read on. 

1. Put AI tools at the core of CX strategy
Add a dash of AI while fine tuning  CX strategies. It can include dismantling tedious customer service silos and straightening them out with the help of intelligent bots. Activate self-service tools in the form of chatbots, VPAs (Virtual Private Assistants) etc. Once done, define and measure CX metrics to track progress and deviations.

A leading auto finance company used intelligent 'underwriting bots' to automate and streamline loan processes. It now approves loan applications in under three minutes.

2. Employ predictive lead scoring
Manual lead scoring is time-consuming and tedious. In other words, maximum slog for minimal results.

Predictive lead scoring takes in customer data and predicts the next best action to be taken by the customer by identifying patterns and trends. This proves priceless while developing targeted marketing campaigns and messaging.

Taking the help of machine learning to study leads will help to based on interaction and other sales data will help teams understand which leads are more inclined to convert. For example, if the Director of a prospect company calls for presentations twice a month, he may be more inclined towards your product/service.

predictive scoring vs manual scoring
3. Embrace engagement scoring
Applying AI in campaigns will allow you to predict customer behavior in terms of campaign engagement. For instance, you will get answers to some of the pressing campaign questions like

a. How many customers are likely to subscribe?
b. How many customers are likely to unsubscribe?
c. How many prospects are likely to buy?

By getting relevant scoring, you can simplify and automate customer segmentation in your cross-sell modeler. This will empower you to analyze patterns and create more successful campaigns.

Virtual Customer Assistants statistics 2018
4. Offer personalized product recommendations
Using intelligent automation in CRM solutions, you can unveil customer preferences, behavior and the next best actions. This information, derived from frequency analysis, can then be used to automatically recommend relevant products or services that are highly likely to convert. Similar to Amazon.

Machine learning acts as the Christmas tree where you can put all sorts of customizations. It augments your marketing capabilities with in-depth customer data mining based on engagement data. This allows you to run the right campaigns to the right target audience at the right time to deliver the right experience. 

The age of AI in CRM software brings together real-time insights, trends and patterns empowering your business to magnify customer experiences.