Artificial intelligence (AI) is revolutionizing customer relationship management (CRM) by making sense of unstructured data—information that doesn’t fit neatly into databases. Sources like customer emails, call transcripts, social media posts, chat logs, and product reviews are brimming with insights that can transform customer experiences and help drive business growth. What if the key to transforming customer experiences lies buried in the data you’ve already collected but haven’t yet explored? Here’s how AI and unstructured CRM data can help organizations unlock growth potential, and how applying the Rumsfeld Matrix—a decision-making framework dividing “knowns” and “unknowns” into four categories—can guide the process of leveraging these insights.
Enhanced Customer Understanding
Unstructured data can reveal valuable details about customer preferences, frustrations, and expectations. AI tools can analyze diverse sources, such as customer emails, call transcripts, and social media posts, to identify patterns that organizations can use to refine their strategies.
For instance, AI might study product reviews to detect common pain points or sift through call recordings and emails to uncover recurring support issues. The result? Businesses gain a clearer picture of what their customers value, enabling them to tailor offerings accordingly.
- Known Knowns: AI analyzes unstructured data to understand customer sentiments and preferences
- Known Unknowns: The exact impact of these insights on customer satisfaction and loyalty
- Unknown Knowns: Existing data patterns that haven’t been fully leveraged
- Unknown Unknowns: New insights from future data analysis
Improved Customer Journeys
Understanding the customer journey requires inspecting interactions across multiple touchpoints. AI examines data from sources like chat transcripts, support tickets, and call recordings to create a 360-degree view of the customer experience.
For example, an AI system might detect that customers often call after receiving a particular email campaign, indicating confusion or interest that could be addressed proactively. By studying the interplay between these touchpoints, businesses can smooth friction areas and help improve overall satisfaction.
- Known Knowns: AI maps customer interactions across channels to improve journeys
- Known Unknowns: Potential gaps in understanding the emotional impact of touchpoints
- Unknown Knowns: Insights buried in underutilized CRM data
- Unknown Unknowns: Innovative approaches to enriching journey analytics
Customer Sentiment Analysis
AI tools excel at gauging customer sentiment from unstructured data sources. Whether it’s reviews, social media posts, or call recordings, these tools can identify shifts in tone and sentiment that might indicate satisfaction—or dissatisfaction.
For instance, exploring support chat logs and call center transcripts can reveal rising frustration about delayed delivery times. Armed with this insight, businesses can act quickly to mitigate negative sentiment before it escalates.
- Known Knowns: AI detects sentiment trends in unstructured data
- Known Unknowns: Challenges in accurately interpreting cultural or contextual nuances
- Unknown Knowns: Hidden sentiment drivers within historical data
- Unknown Unknowns: New sentiment patterns or triggers that may emerge
Predictive Analytics for Proactive Strategies
AI leverages unstructured data to predict customer behavior. Call transcripts, combined with email and social media data, can help organizations identify trends that indicate churn risk or opportunities for upselling.
For example, a technology company used AI to probe both social media mentions and support call data, discovering that customers discussing competitors were at a higher risk of switching providers. This insight allowed the company to intervene with targeted retention campaigns.
- Known Knowns: AI predicts customer behavior based on historical trends
- Known Unknowns: The consistency of these predictions across diverse demographics
- Unknown Knowns: Predictive models with untapped potential for refinement
- Unknown Unknowns: Emerging behaviors and market conditions
Automation & Efficiency
Unstructured data often requires significant time and effort to analyze manually. AI automates these processes, extracting practical insights faster and more accurately.
For instance, AI can process hundreds of customer call transcripts alongside chat logs and emails, categorizing them by issue type and priority. This can significantly reduce workload for human agents and enable faster response times, improving operational efficiency.
- Known Knowns: AI automates unstructured data analysis
- Known Unknowns: The extent to which AI can handle more complex tasks
- Unknown Knowns: Automation features within existing systems that are underused
- Unknown Unknowns: Novel automation possibilities as AI advances
Enhanced Data Integration
Integrating unstructured data with structured CRM data can give organizations a holistic view of customer interactions. AI can help bridge the gap between unstructured and structured data, combining call recordings, purchase histories, and social media interactions, to deliver key insights and a unified customer profile.
For instance, a retail company might use AI to merge call center feedback with loyalty program data, detecting that long-time customers value personalized thank-you notes after purchases. This insight helps refine loyalty strategies for better engagement.
- Known Knowns: AI integrates diverse data into an encompassing customer profile
- Known Unknowns: Challenges in harmonizing inconsistent data sources
- Unknown Knowns: Integration opportunities not fully explored
- Unknown Unknowns: Innovative techniques for deeper integration
Real-Time Insights for Agile Decision Making
AI processes unstructured data in real time, enabling businesses to act on emerging trends. Social media monitoring allows companies to track prospective customer sentiment dynamically, while summaries of recent call center conversations can identify urgent issues.
Imagine detecting a surge of complaints about a new product. With AI, an organization can respond quickly, adjusting marketing messages or issuing clarifications to address customer concerns.
- Known Knowns: AI delivers real-time insights to aid decision making
- Known Unknowns: The reliability of these insights in high-stakes scenarios
- Unknown Knowns: Latent insights from real-time data streams
- Unknown Unknowns: Future opportunities for real-time AI innovation
Use Cases
Here are examples of how organizations have leveraged AI and unstructured CRM data:
- A retail company identified rising complaints in call center transcripts about delivery times. By addressing logistical bottlenecks, it improved customer satisfaction and loyalty.
- An e-commerce platform used social media data to detect negative sentiment about a confusing promotion, enabling it to clarify terms and rebuild trust with customers.
- A technology company combined email and call data to identify common troubleshooting issues, streamlining its self-service portal for improved user experience.
- An entertainment service analyzed chat transcripts and user reviews to enhance recommendation algorithms, lifting engagement and retention.
How Forvis Mazars Can Help
AI tools can effectively harness the power of unstructured data. When combined with other CRM data, AI can revolutionize how organizations interact with customers and prospective customers. By drawing insights from call transcripts, social media posts, emails, and other sources, companies can understand their customers better, streamline operations, and forecast future behaviors. Applying frameworks like the Rumsfeld Matrix can provide a strategic approach to leveraging AI technology, helping organizations identify opportunities, mitigate risks, and remain agile in a competitive landscape. Start by identifying the unstructured data sources already at your disposal. Next, explore resources that can help you integrate AI and unstructured CRM data to uncover insights. For future-forward organizations, the potential of modern CRM lies in leveraging the unknowns for a competitive edge.
To help you get started on your AI in CRM journey, Business Technology Services at Forvis Mazars has dedicated resources. Our technology consultants are experienced in implementation, design, upgrades, and ongoing support services for Microsoft Dynamics 365 and Salesforce CRM applications. Connect with us today to learn more or request a personalized demo.