Keith Dawson's Analyst Perspectives

Contact centers have long collected feedback from customers, usually through short surveys. It is very common for an agent or an automated system to ask for an assessment of the interaction that just occurred, hoping to get the customer's candid, instant view of whether they were satisfied. For the most part, what's learned in those short engagements is very narrow. It can be used for a customer satisfaction snapshot, and it can be used to find out if a particular agent is running into trouble. That is useful, but extremely limited in scope. Some organizations are beginning to look beyond that simple use case, and beyond the basic tools used to collect data. Surveys are reactive – they tell you whether what has already happened was good or bad. Worse, they don't define “good” and “bad.” They merely ask the customer for a status report, without room for nuance or interpretation. Today’s voice of the customer or customer feedback programs are able to look at the question much more broadly through deeper analysis of more data points that don't necessarily originate with a customer response. In other words, hearing the customer's voice means taking into account what they are doing and saying, how they do and say it and what you can interpret from signals provided by individuals and groups. Sources for broader VoC feedback include social media, customer communities and even analysis of how people interact with websites and mobile apps. We believe that through 2027, automated analytics technologies will become better at determining customer intent and sentiment than customers' own reporting through surveys. It is still the case that most contact centers consider feedback or VoC to be a very limited project. Gathering short-form survey results tells you if something has gone wrong in a small way, and can potentially help flag problems that are localized to a particular agent, all once a case or interaction is resolved. But there is so much latent potential in VoC that it is quickly becoming a tool for leading-edge practitioners to work with marketing or product teams to maximize broader insights: How are people using a website, for example, and how does that relate to their tendency to call a center? How have new product debuts or business changes impacted sentiment within the customer base – not just their need for service, but their intent to buy and stay customers? To move beyond surveys and have a wider impact, organizations have to use recorded calls (transcribed), text sources from non-voice interactions and related customer histories and buying patterns. One has to apply advanced analytics to the problem of inferring what customers are really experiencing and how they feel about it, from signals embedded in what they say, what they don't say, tone of voice, apparent emotion and other subtle indicators that can be pulled out of large data sets. The value of this research doesn't always flow to the contact center, which is only able to use feedback to intervene when something goes wrong. Instead, it's valuable to teams that design and orchestrate longer periods of the customer journey or life cycle. In our recent Value Index on Customer Experience Management systems, we looked at the variety of tools that fall under the VoC or customer feedback umbrella. We found vendors that focus on contact center operations still have a fairly limited set of tools for capturing and interpreting feedback, primarily focusing on surveys and snap answers. Contact center vendors can sometimes provide the transcription of recordings into text, and can sometimes perform sentiment analysis on the output. At the moment, the contact center buying audience has not demanded much more functionality than the ability to capture and transcribe. Interpretation and pivoting to act on broad trends isn't part of the standard contact center operational process. CXM vendors that come from outside the contact center space are stepping into that gap with full-blown analytics that focus on getting that deeper inference about customer intent, and maximizing it for boosting sales conversions, for example, or identifying prospects and targeting them with personalized offers or incentives. The more marketing-focused a CXM product is, the more likely it is to facilitate using VoC research to maximize positive outcomes, rather than tally up negative ones. One key driver of the expansion of customer feedback usage is the growing adoption of artificial intelligence and machine learning technologies. As advanced AI is built into CX platforms – especially contact center products – more organizations are able to search data for more meaning in what customers are saying. The next step in the evolution of the process is going to be helping those organizations understand what is being learned, and designing processes that act on the new knowledge. And indeed, the challenges to creating an expanded VoC program can be steep. For example, there may be issues integrating those different feedback channels to consolidate the data. And it will likely require analysts and planners to acquire specific technical expertise and resources for the task. These are cross-departmental challenges that are difficult to address just from within the contact center. They require collaboration between marketers, sales teams, service teams and potentially, with a coordinating authority (possible a chief customer or chief experience officer). However, the rewards for taking on this kind of ambitious project will be found in revenue impacts and higher metrics for loyalty, longevity and satisfaction. These are measures that affect the health and growth of the entire organization, not just the service department. That helps knit together the activities of departments that aren't used to pulling together for a common goal. The next 24 months will likely see many more organizations exploring how to better use the data generated by contact centers. Across the industry, vendors are dramatically expanding the analytic capabilities of CX and contact center platforms, often thanks to the addition of AI. This will galvanize many service teams to look anew at how they measure and respond to customer feedback. For many firms, feedback analysis will be the gateway to more complete customer life cycle management across the organization. For more information on contact centers and customer experience, visit our Customer Experience expertise area. Regards, Keith Dawson

Keith Dawson's Analyst Perspectives

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