AI Needs Context for Great CX. Customer Journeys are the Solution
The end of 2024 is upon us. In our home market, the December period is a time for end of year holidays. Business shuts down and we head towards the coast or mountains to enjoy a break and welcome the new year.
This year will be remembered as a year of massive developments in AI. In particular, LLMs and generative AI have stood out as incredible new technologies that truly have become mainstream.
With the developments of AI, and reflecting on the very poor experiences that customers have had with Chatbots, it begs the question, why haven’t we seen dramatically better implementations of AI to service and guide customers?
I recently listened to a Podcast from the Chief Customer Officer of Verizon , Brian Higgins and a key discussion point was how Verizon is using AI to empower agents to be able to service customers. As the agent is interacting with the customer, content is presented that is relevant to the query. With the growing range of solutions and offerings within Verizon, it makes sense to help augment human agents with content that is relevant to the context of the situation. The situation still relies on an agent to apply reason and logic to interact with the end customer. The reason for this is that the agent deals with the context of the situation while the LLM deals with finding relevant content.
If you do a deep dive into AI and the latest developments, you will hear a lot about agentic AI. The basic application of AI makes use of a framework called RAG (Retrieval Augmented Generation). When combining agents with AI, the agent takes the power of generative AI a step further, because instead of just assisting you, agents can work alongside you or even on your behalf. Agents can do a range of things, from responding to questions to more complicated or multistep assignments. What sets them apart from a personal assistant is that they can be tailored to have a particular expertise. We can use the AI agent approach within the journey context.
The title of this newsletter is “AI Needs Context for Great CX. Journey is the Solution.” I would like to explain why I believe a journey centric approach is the perfect construct for customer engagement:
As we know, any interaction between two humans relies on the knowledge that exists between the two individuals. Individuals with a strong “relationship” really means that they have shared knowledge of past interactions. There is a mutual understanding and the conversion is effective because of a shared context that has been built up over time. Contrast that with a typical interaction with a Website chatbot. These chatbots (even with the latest generative AI) are “dumb”. They are perceived to be dumb because they have no context of the person that they are interacting with (the goldfish analogy comes to mind, on the basis that a goldfish supposedly has a 3 second memory).
There exits a unique opportunity to combine the following components to dramatically improve customer engagement:
The solution is illustrated below:
Explaining the above concepts:
o The long-term history is everything we know about the customer that has been collected over time. This can include past interactions, products, demographics, patterns of interaction
o The company’s organisational information is as a source that will be served up to assist the customer. This can include the processes, products, rules and marketing material of the organisation.
o The most recent data collected must be prioritised in providing context as it has the highest relevance. This includes the specific questions, products and details of the most recent
o The interaction style and tone of the organisation is used to overlay the brand tone to be use when interacting with the customer. This is combined with the objectives of the interaction.
Journey is the perfect container to achieve the above as it has some unique capabilities:
The process for engaging customers plays out as follows:
The result is content that is context aware, highly personalised, timed appropriately and delivered through the interaction channel of choice.
We have already seen that simple rules based content leads to dramatically better results when driving customers along the customer journey. The augmentation of the generative AI capabilities will lead to even better results and ultimately better goal achievement.
As mentioned at the start of this newsletter, we are headed towards our summer holiday. That means less AI, more human interaction, more interaction with the physical world, while not missing the opportunity to both reflect on the year behind us and dream about what we plan achieve in the year ahead. The year has been a very exciting one for the inQuba team. We have achieved significant progress in the application of our Journey Management Concepts. We plan to accelerate these development into next year.
I trust that you have enjoyed the input, perspectives and experiences in driving Customer Journey management. Please share your perspectives – it would be great to hear from you.
Have a brilliant week ahead and as always enjoy the journey
Trent
great discussion. it feels like SMEs actually have a chance to leapfrog larger enterprises in this space. They typically have less formality and consequently siloed mentality to overcome and now with the simplicity of extending the leading UCaaS platforms like Zoom or Teams and extending them with omnichannel out-the-box at super low cost, means they sit on a an absolute goldmine of unstructured data that they can point AI at and grab insights instantly. Could this be one of those moments where a technology actually smashes through the human's intransigence to just do stuff? Steve Job's was good at that - iPhone anyone?
Hi Trent, you offer up an excellent question: "Why haven’t we seen dramatically better implementations of AI to service and guide customers?" Part of the problem is that CX and Operational leaders look at the terms Journey Management or Journey Orchestration and dismiss the state of art tech possibilities as they misguidedly believe they already have such capabilities. But the biggest factor is that no single Enterprise stakeholder 'owns' inbound customer contact. Telephony is the remit of the contact centre; conversational AI owned by digital teams; Socials are never relinquished by marketing. Siloism reigns supreme. Thus, the biggest block to success for any AI powered triage and orchestration offering is the silo mentality where leaders only own part of the customer contact. The tech vendor rhetoric of 'meet the customer in their channel of choice' hasn't helped. A few companies are starting to break down the silos from an Exec board level and applying the novel mindset of, "Meet the customer in their channel of choice, but triage /orchestrate it to our preferred place for resolution " Intent-level intelligence is the first step and all stakeholders need to decide upon their preferred place of resolution for every intent