Customer Support has long been a cost center positioned towards the end of the customer journey, or only when a customer has a problem. But let's look at the potential of Customer Support instead as a business value generator and a driver of customer experience.
The conversations with customers are hidden assets which are not fully exploited. We need to turn the spotlight on Value$/Conversation. The advancement of speech analytics in AI, natural language processing, knowledge graph ontologies, as well as large and small language models provide us the ability to understand the rich nuggets of what customers think, feel, and say about our brand, products, processes, and services and actionize on these to deliver superior experiences to them.
By harnessing value from the most atomic unit, which is a single conversation, and scaling these to the millions of contacts, we can find patterns to make Customer Support the star at center stage. It can become the lead provocateur of proactive cross-sell and up-sell, revenue growth, customer surprise and delight, and even real-time product updates to create real Customer Success.
I am guiding my clients toward this new view of Customer Support that connects more closely with sales, marketing, and product engineering. This connection is self-reinforcing, as we capture more data, we can improve experience and product usage, generating more data in a feedback loop. This new view of Customer Support is particularly salient in today’s market, as AI has accelerated everyone's expectations for higher quality experiences, and as modern tools allow for new types of engagements.
Many enterprises are already likeminded in this belief, so the question is not about WHAT the Customer Support role should be or WHY that role is critical to business value. The question is HOW we can navigate across technology platforms, data silos, disparate channels and ways-of-working to achieve and accelerate business value and to leverage scale, physical, human and geographic assets, volumes of data, and existing brand equities to listen to, predict and satisfy the needs and demands of product and service users.
The quick chart below shows a high level flow of how we can build fast lanes through complex legacy systems and processes to accelerate the transformation of Customer Support, from cost center to driver of Customer Success, through hyper-personalization with real-time and predictive product optimization and experiences. I consider this a AI driven User Generated Customer Success (UGCS), which will close the loop for the entire product and experience lifecycle.
Let me know in the comments below if you would like to have a conversation on fast lanes, UGCS and/or HOW to move forward to reframe and revalue your Customer Support functions.
Related Posts
