The technologies that bring the most value to companies, where leaders expect to see gains, and an increase in investment are among the trends Gartner identified talking with customer service leaders worldwide for their piece, 4 Key Tech Trends in Customer Service to Watch.
Those predictions were made from a survey of customer service and support leaders from around the world. But how are these predictions holding up a year later, and do they relate to what we, and others, are seeing?
1. Enabling Customer Service Representatives Brings the Most Value
Gartner predicted that, while AI, internet of things (IoT), and VR technologies were capturing attention, tools that enable customer service representatives (CSRs) actually brought the most value and would continue to do so. Specifically, Gartner referenced their ability to increase flexibility, manage a hybrid workforce, and meet customer expectations.
Many products in this space now tout their ability to offer agent assistance while including some of the other tools Gartner referenced - including AI in particular. This shows that the market still feels enabling reps is important a year later.
Many of those platforms use AI though, so it’s not necessarily a standalone solution, and the use of AI meets many of those demands. While helping CSRs brings value, the ability to do that while also unlocking other capabilities with technology such as AI is a place many see value. According to CCW Digital’s March 2022 Market Study, leaders’ highest priority is business metrics such as revenue and profit, which all of these technologies tie into. This reflects what we’ve seen, where businesses ultimately want technology that can achieve multiple things to improve business metrics.
2. You Need to Understand Your Customers
Digital self-service channels and predictive customer analytics would become the most valuable capabilities within the next two years, according to Gartner. A year in, and the value is evident.
According to Talkdesk, 60% of companies are using or actively investing into AI for self service. Even among those that aren’t investing in it yet, many of the companies we have spoken to are interested in both capabilities. In fact, we’re currently working with one company that is enabling self service for voice first for some of their simplest yet highest volume reasons for calling - order tracking.
The potential cost savings for companies in these areas can be substantial. Even more impactful to revenue, customers expect a smooth experience, and are inclined to leave a brand if they don’t get it.
3. Leaders Expect Data and Analytics to Become the Most Valuable
Customer service and support leaders told Gartner that they expected data and analytics to be the most valuable tool in two years. A year into that, and it’s hard to disagree - data and analytics are the most valuable tool for most parts of any business.
In the case of customer service, we have heard the same from many leaders that we’ve spoken to, with examples of how it could have saved money based off patterns in interactions to wanting to see real-time analytics
We’re unlocking that data not just by analyzing interactions in real-time for intent and sentiment, but we also capture all of the data from interactions and process insights from that data. This idea continues to resonate with businesses that are collecting data, but don’t have the full picture of their customers and their journeys.
4. Large Investments in AI and Chatbots Are Coming
Gartner predicted that more companies were about to invest in the likes of AI for customer service. In fact, leaders Gartner surveyed predicted this is where value would increase the most in the future. And while investment has dropped slightly since last year - according to Talkdesk, 69% were using or investing in AI for self service last year compared to the 60% this year - it is still being heavily invested in.
There are some bigger picture reasons for the drop, but many businesses have struggled to implement AI for customer service and stepped back from doing so. Some commonly cited causes for this include technical troubles up front, not having the skill sets on staff to maintain it, or not realizing immediate value.
Using AI and chatbots can be complicated because it’s not the right choice for every potential use case, and the groundwork needs to be done to ensure adoption. However, investment is still widespread, and as it becomes more commonplace, customers will expect it - and potentially demand it - reflecting the prediction that it will gain the most value.
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If you’re interested in learning more about how we’re helping companies leverage AI for customer service, you can read more about our Unified Conversational Customer Service Platform.
