In some of my previous blogs, I’ve talked about how the Artificial Intelligence/Machine Learning (AI/ML) revolution is taking the Customer Communications Management (CCM) / Customer Experience Management (CXM) industry by storm and how it promises to be one of the most disruptive elements in the market’s history. Aspire is currently conducting an extensive study that will help our clients incorporate this exciting and disruptive technology into their business strategies. We’ve completed a survey of enterprises across the globe and we’re now conducting supplementary interviews and working on our analysis. A first cursory review showed that European enterprises look to have a higher readiness for AI in CCM/CXM than the U.S., and that a larger share of European businesses prefer to buy technology whereas U.S. organizations prefer to build things themselves.
(On that note, if you’re an enterprise executive active in the CCM/CXM space and you’re willing to share your insights and discuss how your organization is leveraging AI/ML, please drop me a personal message. Our team would love to talk to you. As a “thank you”, we’ll send you a free copy of the enterprise report once we’ve completed our research.)
So far, we’ve found that “generative AI” in particular is rapidly evolving and that it has developing widespread implications – both for the practitioners looking for ways to achieve “more for less” as well as for technology vendors on the hunt for technological innovations. Generative AI (Gen-AI) applies AI techniques to autonomously generate personalized and contextually relevant customer communications, elevating the overall customer experience.
We currently see three major areas in CCM-CXM where gen-AI is making an impact:
1. Content intelligence (CI) describes organizational efforts to improve a communication’s tone, clarity, and readability to make it easier to understand and more likely to accomplish its designed purpose. In past studies, we’ve noted the importance of recent developments in this space and identified a number of key drivers including the desire to ensure regulatory compliance and improve customer experience and satisfaction. Interestingly, again in this study, businesses continue to place content intelligence use cases near the top of their list when identifying preferred areas for AI investment. Companies like Messagepoint have invested in content intelligence for many years now, supporting all major CI use-cases, and were quick to implement OpenAI/ChatGPT integration into their products. Smart Communications and other vendors have implemented AI capabilities that can grasp the complexities of grammar and readability. OpenText recently launched Aviator, an AI-agnostic integration framework providing content intelligence capabilities based on various AI engines, most notably Google’s Vertex AI / PaLM. Written content is crucially important in CCM so it’s no surprise that this receives so much attention.
2. Communication creation and approval is another major area where AI can make a big difference. The ability to code forms, communication templates, journey steps, or other areas based on text-prompts while specifying tone-of-voice is an incredibly powerful use of this new technology. At its latest Summit (Spring 2023), Adobe showed a live demo of an AI engine creating and altering images through text prompts and then drafting an email to accompany them. Several vendors have privately briefed us on their development of AI code CCM templates. Integrators like Tata Consultancy Services and service providers like O’Neil Digital Solutions have demonstrate these technologies as well. Many vendors, including Quadient with their InspireXpress or SmartComms with Migration Studio have developed migration tools that can migrate existing communications templates to their systems.
We expect communications creation and approval to be a major area of AI investment as businesses work to secure the ability to automatically improve messages and interactions or find the best approver for a given use case. Companies like Isis Papyrus have been pitching this kind of functionality for quite a while, but generative AI has the potential to apply even deeper cognitive understanding. Of course, CCM always sits at the end of a business process, so AI will also have tremendous benefits there (through fraud detection, or billing accuracy in AR/AP for example). Although this typically sits outside of CCM, some CCM vendors, like Quadient and MHC Automation, are actively evolving in this direction, typically by going more downmarket (SMB or mid-market). From a tech vendor perspective, generative AI can be a real accelerator for SMB growth.
3. Front office interactions (to go from customer experience to total experience): AI technology has advanced to a stage where we can expect an increase in fully automated front office interactions. Traditionally, enterprises in the regulated B2C space have been very wary of this prospect, but a recent healthcare study found that 79% of patients prefer ChatGPT’s responses to those given by a human doctor. Respondents reported that the AI engine had a better “bedside manner” than its human counterpart. It was found to be more empathetic and reassuring than a human doctor.
Furthermore, Aspire’s research continues to show that CX leaders want to provide more consistent and personalized experiences across all channels, including bi-directional ones. CCM traditionally has been all about outbound interactions, but as these outbound communications shift to digital channels, AI complements can capture user input within the touchpoint and follow-up with an automated personalized message. Data collection is not the challenge – many technologies exist for that purpose – but marrying collection to a CCM engine at scale and driving meaningful orchestration and interaction is easier said than done. We believe AI will have a significant impact in the area we call Interaction Experience Management (IXM), but I’ll write about this in more detail in another blog. Vendors like Precisely, SmartComms, and Adobe are active in this space, companies like Crawford who demonstrated front-office translation / NLP capabilities, as well as vendors who come from it from a low-code angle such as Elixir, NewGen or In10se Technologies.
Our research will present more up-to-date perspectives on AI use cases, where AI will be implemented first, and the obstacles businesses will need to overcome to embrace it.
If you’d like to learn more about this study, please visit this link to register your interest.