Customer experience analysts are often not shy to make bold predictions for the future. In recent years, one of the most eye-catching came from Forrester. It stated:
“CX becomes crucial for brands to survive, for them to avoid disintermediation, irrelevancy, blandness, and/or cluelessness about customer sentiment.”
While this rings true, many brands struggle in their survival bid, despite believing they are experience-driven. However, it is one thing to have designed a dusty customer journey map; it is another to make that operationally useful and actively engage in CX management.
Unfortunately, achieving this remains a struggle. The pandemic played its part, causing companies to rush transformation projects, leaving CX leaders languishing in a cycle of testing, learning, and embedding to enhance rushed implementations.
Yet, other longstanding issues persist. Perhaps the most prominent is silos. Indeed, a 2021 Dimension Data report revealed that 54 percent of organizations manage their customer experience operations in silos.
To sidestep “disintermediation, irrelevancy, blandness,” 2023 is the year to embrace cross-functional collaboration, connected goals, and an evolving c-suite mentality.
Fortunately, many emerging technologies can help here, unifying enterprises behind a customer experience strategy that is operationally useful to various functions.
Emerging CX Technologies to Prosper In 2023
In recent years, many emerging technologies have come to the fore with the advent of the cloud, easier API integrations, and deep marketplaces.
As this trend accelerates and cloud-native platforms become the norm, businesses will increase their interoperability efforts, allowing them to connect enterprise technologies.
In doing so, businesses can free up data, and its increased accessibility will allow departments to share insights and work towards the organization’s goal.
Such accessibility will also complement the growth of ERP, BI, and many AI technologies.
An excellent example of the latter is conversational AI. Gartner predicts that bots will automate six times more interactions than they currently do in 2026.
Indeed, as bots dip into more systems and piece together more information, they are beginning to automate much more than those simple, transactional customer queries.
As such, many CCaaS players are making conversational AI a core part of their contact center solutions, alongside robotic process automation (RPA) and conversational analytics.
Quanatiphi is one such solution provider, innovatively connecting the contact center to a conversational AI engine in an effort to drive “AI-first total experience transformation.”
This "total experience" concept will also gain momentum alongside the growth of AI as it takes away laborious, repetitive things away from employees’ workday and replace them with more meaningful, engaging work items.
As such, the agent experience requires much closer consideration, and productivity optimization technologies – including agent-assist – will likely surge.
A Futuristic Case Study
From the above, increased interoperability and conversational AI are two trends that will play a significant role in tomorrow's contact center.
Yet, their rise is already proving promising, as evident in many recent successful CX transformation initiatives, including one from the Illinois Department of Employment Security (IDES).
Like many organizations, it has struggled with surging contact volumes. However, in this case, the rise came from nowhere, with the pandemic pushing unemployment claims through the roof.
Luckily, the team at IDES responded quickly, working with Quantiphi to build a virtual agent – which leverages Google Dialogflow and integrates with a Cisco telephony system.
Moreover, the virtual agent learns from and uses data from various applications within the Google Cloud Platform and Google Sheets.
Within two weeks, it had supported 3.2 million customer queries, thanks to IDES and Quantiphi working together to train the Virtual Agent on 100+ custom intents.
The state of Illinois anticipates an estimated annual savings of $100M based on an initial analysis of the IDES’s virtual agent data.