As AI rapidly transforms the way businesses interact with their customers, traditional yardsticks for measuring customer experience success are in danger of becoming redundant.
Recent research by Metrigy found that AI is currently fully automating around 20 percent of customer interactions, altering the contact mix, and making it increasingly difficult for CX leaders to gauge efficiency through the old means of measurement.
“I think we’re just on the cusp of having to think about the metrics that we value, from a CX and contact center perspective, very differently,” Rebecca Wettemann, CEO & Principal Analyst at Valoir, tells CX Today.
That means we have to train people differently. That means we have to incentivize managers differently. That means we have to incentivize agents differently.
For example, Wettemann says incentivizing agents to make interactions as short as possible “doesn’t matter” in a future when an AI agent handles 80 percent of calls, which Gartner predicts will happen by 2029.
In most cases, organizations would prefer that they spend a little more time ensuring they’re giving the correct answer to the customer.
“I may want to incentivize them to take a few more seconds looking at what the AI agent is telling them and making an intelligent decision about whether they should relay that to the customer,” she adds.
Yet, it’s not only efficiency-based metrics that face the chop. Others like Net Promoter Scores (NPSs) and Customer Satisfaction (CSAT) rely on small customer sample sizes, with customers already fatigued by barrages of surveys.
Survey size isn’t the only issue. After all, while these measures might indicate there’s an issue, they offer little insight into what that problem may be.
As such, many customer experience leaders have grown tired of such metrics, with some claiming: “NPS is BS“. As Christopher Brooks, Global Customer Experience Specialist at Lexden CX, told CX Today:
NPS can account for one percent of a company’s profitability. There are 99 other factors. You and I never take a product out because we want to recommend it to a friend—that’s not our motive for doing it. Our motive, depending on what that product is, is very, very different.
However, part of the reason why metrics, like NPS, have stuck around is that nothing better has come along. Fortunately, the tides are turning, and three massive trends are converging, promising to change contact center reporting. With the rise of AI, that comes just at the right time.
Trend #1 – Contact Center Reporting Becomes More Prescriptive
Contact centers will soon utilize tools that don’t just surface insight but suggest possible actions to take, based on that insight. Indeed, these will pull together telemetry data to proactively recommend actions, improving customer, agent, and business outcomes.
Salesforce, for example, has already unveiled a “Customer Success Score”. The measurement highlights opportunities for value that businesses aren’t capturing.
Indeed, it focuses on the overall health of Salesforce implementation and how customer experience functions – like the contact center – consume available Salesforce resources. This kind of metric helps CX leaders pinpoint underused features, address adoption gaps before they cause friction, uncover upsell opportunities, and improve renewal rates.
Trend #2 – Contact Center Metrics Become More Predictive
Predictive metrics will also play a major role in the future. They’re already used in areas like contact center workforce management (WFM), but the use cases will expand considerably.
The introduction of GenAI has enabled new metrics like expected net promoter score (xNPS) to come to the fore.
xNPS is measured by AI that assumes the role of the customer and, based on the service interaction, produces the score a customer would likely leave on an NPS survey. This enables service teams to trigger recovery actions in the same interaction, improving resolution rates and preventing potential churn.
As such, customers don’t need to fill in surveys, and businesses get a healthier data supply on which they can take proactive action.
Trend #3 – Contact Center Dashboards Become More Interactive
Finally, the way performance data is presented is evolving. Conversational dashboards, powered by GenAI, will allow users to request specific insights in plain language and receive tailored visualizations.
AI agents may soon even spin up dashboards based on prompts, without the need for predefined parameters.
Ultimately, that’s the future, and it will save analysts hours of manual report-building, helping managers make faster, better-informed decisions, speeding up the cycle from insight to action.
The Key Takeaway
As AI takes over routine work, human interactions are becoming longer, more complex, and harder to score with the old yardsticks. New measures like predictive satisfaction scoring, success scores, and conversational dashboards will give CX leaders faster, more targeted insights, ensuring data drives action.
As a result, companies will make a positive shift from scoring how good they are at their own business to collecting feedback that drives specific actions.
