A growing number of businesses are eager to invest in predictive data analytics to accelerate their CX strategies. But there still is a question: How can companies make customer data actionable to transition from a reactive to a proactive CX approach? Discover some insights in this article that will help you use AI CRM insights to grow your business and accelerate your CX efforts.
Turn Intent Data into Proactive Action
Data alone is not enough to give you context to what customers want and need. Once you make data actionable, you can use it proactively. Only after you have actionable information can you deliver it to the right team members who can use it to improve their odds of closing deals and recover from unexpected scenarios.
Modern AI CRM solutions that are elevated with AI capabilities help companies to conduct customer behavior analysis and structure that data into appropriate responses that can automatically execute or propose next-step actions to the consumer of the information, namely your team members.
One perfect example of leveraging CRM systems is running analytics on invoice information in your ERP tool to help predict and offer your sales and marketing teams actionable insights. That information can be used to spot purchase patterns or make recommendations using AI paired with analytics. This practice of anticipating your customers’ needs and deepening connections while optimizing the customer journey reflected in their purchasing behavior is a perfect example of proactively using AI and analytics.
Use Intent Data to Personalize Customer Interactions
In dynamic business spaces such as the environment we are currently witnessing, all stakeholders and teams across an organization need to leverage customer insights and use those to accelerate revenue growth. Turning data such as purchase behaviors into actionable insights takes more than just storing the data. It takes a lot of processing, which is more effective in the presence of artificial intelligence and predictive analytics.
Such data can be used by marketing, sales, and support teams to automatically execute tasks that can accelerate revenue growth and customer satisfaction. The earlier example of analyzing purchasing patterns also shows if the company is losing market share or if its customers are shifting purchases from one product to another. Customer-facing teams can extract all these details from invoicing and CRM data for actionable intelligence on responding and providing the best experience unique to their customers.
Connect Intent Data to Engagement Scoring
Lead scoring is critical for effective sales and marketing strategies, but its unpredictable nature leaves room for improvement. AI eliminates uncertainty from the lead scoring process and replaces it with accurate and up-to-date data based on the measurable activities that drive lead conversion. When AI is used for lead scoring, the system looks at similarities of historical conversions. At the same time, the Ideal Customer Profile created identifies similar leads to a company’s past and current customer bases.
More than this, by using customer interaction data from sales, marketing, and customer service, your company can create a very accurate “engagement score.” Measuring this engagement score over time can offer your business insights on aspects such as whether or not your customer engagements are increasing or improving, so you can double down and do more, or if they are on the decline, you can pivot and re-adapt your strategies.
This data feeds a company’s business process engines to support proactive actions to service customers. The results of doing so are avoiding loss of revenue, increasing share of wallet with customers, and taking advantage of new revenue opportunities quicker.
Predict Intent with Sentiment Analysis
AI tools are becoming more and more accurate in identifying customer sentiment and helping your teams respond with empathy to all customer inquiries. No matter the channel your teams engage with customers, they need to be able to respond empathetically in real time. Sentiment analysis powered by AI elevates your CRM functions, such as sales, marketing, and service interactions, by revealing each customer’s and prospect’s emotional state and intent – which immediately enhances the customer conversation.
AI tools that enhance sentiment analysis leverage a combination of Natural Language Processing (NLP) and AI that reveals to your teams the best following action for empathic customer engagement, whether this means escalating to a supervisor, presenting a save-the-sale offer, or taking an opportunity to upsell/cross-sell. Besides, your teams can accurately evaluate the overall CX and journey effectiveness by leveraging sentiment analysis. In the long run, this will allow you to continuously improve and adapt your strategy to meet and exceed customer expectations.
It’s All About Data Quality
We’ve said on all occasions that data quality matters. Poor data can point to the wrong customer identity next steps and damage your market positioning. The best way to ensure you truly know your customers is by using clean data sets and employing good data hygiene, governance practices, and ongoing data maintenance across your organization. This is becoming increasingly important when you consider AI and ChatGPT are used against your data for information automation. Thus, having a foundation of good data and good practices for curating, maintaining, and cleaning your data is critical. If you have sloppy data, wrong data, or miscoded data, all this automation will do is enhance and exacerbate those mistakes. And the speed of automation means errors can go wrong faster, which means new checks and balances will be required to keep pace.
One thing marketing and sales teams have in common is abundant data from their CRM platform. With advancements in applying predictive analytics and buyer intent data to CRM, marketers and sellers can transition from a reactive to a proactive CX approach that fuels business growth.
If you’re interested in learning more about the topic, make sure to get in touch with us. Or, if you want to get insights across all verticals on CRM use and deployment trends, read our 2024 State of CRM Report!
This blog post is based on an article initially published on Martech Cube.