We’ve spoken to numerous enterprises and print service providers and there is no doubt that Customer Communications Management (CCM) stands at a pivotal crossroads. We know that today's customers expect better interactions across all touchpoints; however, when it comes to regulated communications, most organizations struggle to deliver on what customers expect. Companies are having to deal with economic pressures, changing customer expectations and regulatory shifts. Artificial Intelligence (AI) can no longer just be a buzzword. It offers a way to deliver value at scale on these essential communications.
Having spent years helping organizations shift from legacy documents to dynamic, customer-centric versions, one thing is clear: AI is changing the game. We strongly feel that it’s not about replacing what works; rather, it’s about enhancing current processes, communications and documents with smarter tools and better data that add value to the customer.
Generative AI (GenAI) is a transformative technology for CCM strategies. With 70% of CX leaders planning to integrate GenAI into most of their touchpoints in the next two years, according to Zendesk Research, the question is no longer if but how to apply the technology effectively.
The Business Case for GenAI in CCM
Before diving into implementation strategies within CCM, let's understand why GenAI matters for customer communications, according to a recent survey by Deloitte on the State of GenAI:
- Improved Efficiency and Productivity: 56% of organizations cite this as the top benefit they hope to achieve with GenAI.
- Cost Reduction: 35% of companies expect GenAI to help lower operational costs.
- Enhanced Customer Relationships: 23% believe GenAI will improve relationships with customers.
- Revenue Growth: 25% anticipate increased revenue through more effective communications.
Most importantly, GenAI helps bridge the widening gap between customer expectations and what companies currently deliver.
Six Strategic Applications of GenAI in CCM
1. Data Management
AI really shines when it can work with good data, and on the other side of the coin, it helps make data better. From resolving duplicate records and filling in missing fields to enriching customer profiles from various data sources, AI can play a critical role in maintaining data hygiene. Some instances include:
- Automating data cleaning and standardization: Identifying and correcting or flagging inconsistencies across databases
- Extracting insights from unstructured data: Converting free-text fields into structured, actionable information
- Ensuring data security and compliance: Identifying potential vulnerabilities in data storage and transmission
2. Content Rationalization
Many organizations have hundreds and even thousands of templates without any consistency across those templates. We’ve seen clients struggle with this issue that more often than not, leads to fractured experiences for customers. Maintaining these variations is costly. Having a clear picture of the extent of the issue is a daunting task. This is where GenAI can help:
- Identify duplicate or similar content: Finding redundancies across communication templates
- Standardize messaging and terminology: Ensuring consistent language use
- Improve readability: Adjusting content to appropriate comprehension levels
- Analyze sentiment: Ensuring communications convey the intended emotional tone
3. Hyper-Personalization
True personalization goes beyond dropping in a first name or referencing a recent transaction. With AI, we can achieve hyper-personalization that adapts in real time to a customer’s needs, preferences and context. GenAI enables true hyper-personalization by:
- Creating customer-specific content: Generating unique messaging based on individual preferences and behaviors
- Microsegmentation: Drawing on a variety of data sets, create sub-sections of customers to personalize and tailor content
- Dynamically adjusting tone and style: Matching communication style to customer preferences
4. Next-Best-Message Optimization
Rather than static content in regulated communications, GenAI can determine the optimal message for each customer by:
- Recommending next-best actions: From payment nudges to suggesting relevant products or services based on customer history
- Optimizing send timing: Determining when customers are most receptive to communications like billing where payment is required or collections notices
5. Customer Analytics
If data is the fuel, analytics is the engine, and AI makes it smarter. By analyzing trends across customer interactions, AI can identify who is likely to respond to actions that need to be taken, who may be confused by certain documents, and who is at risk of disengaging altogether. GenAI transforms how organizations understand customer behavior by:
- Predicting customer needs: Anticipating requirements before customers explicitly express them
- Detecting dissatisfaction signals: Identifying early warning signs of potential issues
6. AI-Driven Conversational Interfaces
Traditional chatbots follow rigid decision trees. AI powered bots can be incorporated in various channels (and documents) to help respond to common customer queries, automate follow-ups, and even trigger proactive outreach based on customer behavior. GenAI-powered conversational interfaces can:
- Maintain context across interactions: Remembering previous conversations for continuity
- Generate human-like responses: Creating natural, conversational replies
- Learn from interactions: Continuously improving based on customer conversations
Getting Started with AI in CCM
We often get asked: “Where do I begin?” The answer depends on your current state and strategic goals, but here are a few universal principles we recommend:
- Start with a clear use case: Whether it’s optimizing email performance or reducing template volume, define the problem before applying AI.
- Ensure your data is ready: Clean, connected data is essential. Without it, AI models will underperform.
- Think about people and process: AI tools amplify productivity. Make sure your teams understand how to use insights and act on recommendations.
- Measure outcomes: Track improvements in engagement, conversion and operational efficiency. Use these wins to expand AI’s role over time.
- Incorporate privacy and security protocols: Ensure that applications comply with relevant regulations and you have robust data protection measures in place
- Think about bias and accuracy: Audit outputs for potential bias in language and establish a rigorous validation process, along with human oversight.
Conclusion: The Future of CCM Ss AI-Enhanced, Not AI-Replaced
AI won’t magically solve all your CCM challenges. However, when it’s applied thoughtfully, it has the potential to transform how you engage with customers, making interactions more intelligent, responsive, and more valuable.
From predictive insights to dynamic content and smarter workflows, the future of CCM is digital AND intelligent. Don’t think about replacing your current approach, rather think about evolving it with a little help from AI.
Mia Papanicalou helps companies go paperless for transactional customer communications and works to improve those touchpoints through customized strategy and advisory services.She is a regular speaker and blogger on digital customer communication, digital maturity and improving the customer experience.
Elizabeth Stephen is an expert in CCM and helping clients utilize digital communications to meet their CX goals. As a true specialist in transactional communications, Liz has the ability to help companies make the needed microchanges that will immediately impact the customer experience, while putting the steps in place to make long-term changes.
