Don’t Report On Customer Sentiment, Predict It

Holly Felicetta, head of Kinetics℠ AI at NPSx, explains how to predict customer sentiment and improve performance on metrics that matter.

Depending on your industry, a “good” customer survey response rate could be somewhere between 5% and 15%.

The voice and experience of every customer is important – but if you’re relying on survey response alone, you won’t have sufficient insight to act on. Even if your response rate is above average for your industry, there’s no guarantee that you’re hearing from your most valuable customers.

Instead, what if you could:

Predict customer sentiment?
Identify the top drivers of influence for 100% of your customer base?
Anticipate how a customer will respond to a business change or event?
Target interventions for your most valuable customers?

That’s the level companies need to operate on to compete today. Meeting or exceeding customer expectations isn’t enough to win customer love anymore. In the third wave of customer experience (CX), brands need to predict individual customers’ needs and sentiments and move beyond survey feedback.

Believe it or not, most brands already possess the data they need to model customer sentiment – once they remove organizational roadblocks. To predict customer sentiment, companies need stronger alignment on CX, consistent access to data resources, and holistic journey management.

Organizational alignment around CX

To be clear, nobody wants their organization to deliver poor CX. But executives across the organization have their eyes on different targets, and most CX leaders can only articulate their success via CX metrics. Their impact gets lost or diluted in translation.

CX leaders need to build a stronger business case for their initiatives. They need to speak to the C-suite in terms of financial outcomes and other metrics that executives care about.

Say a CX team launches a program to reduce call hold times. As a result, they might see a lift in their NPS. That’s great – but it doesn’t tell the whole story. The CX team needs to connect their work to meaningful stats for the C-suite, like how shorter hold times lowered staffing and overhead costs, increased revenue or boosted retention.

Response rates and NPS rankings are not the end goal. CX leaders will garner more executive support when they communicate the material impacts of their programs in language that leaders care about.

Consistent access to data resources

Companies should be able to look at a string of customer data – demographics, purchase history, call logs, hold times, digital interactions, and more – and predict how an individual customer would react to an event.

Data to predict customer sentiment exists. Unfortunately, most CX teams don’t have consistent access to the resources they need to leverage it. Sometimes data teams are dedicated to a CX project, but not to the department overall. In other instances, data governance and cybersecurity policies are too restrictive for data to be useful — especially when external resources are required for analytics.

Organizations need to get more progressive about how they use and share data for CX. In other areas of the business, executives are expected to forecast demand, revenue, and other metrics – and they’re supported with data and capabilities to design appropriate strategic responses.

With the right data and skill support, CX leaders can build predictive models for CX. They can anticipate how a business change would affect sentiment and KPIs, such as product holdings, basket size, revenue, and customer value.

Data can be anonymized or coded to comply with GDPR and other safeguards for personally identifiable information. These are hurdles that brands should be willing to overcome, especially given the payoff that’s at stake.

Holistic journey management

Journey management should be end-to-end, cross-channel, and cross-functional to match the way customers see your business: as one entity.

Journey managers need to be accountable for the entire customer experience, from product selection and sales to servicing and financing. Someone needs to look at the holistic impact of decisions on customers, across every channel and event.

Likewise, journey managers need comprehensive data about each customer’s journey. They need a view that combines customer data with operational and financial data to accurately guide decision making. And they need support from executive-level leaders with the authority to act on customer intelligence.

With journey-wide data, CX leaders can pinpoint “make it or break it” events – even if customers don’t offer explicit feedback or respond to surveys.

Remember, most of your customers aren’t responding to surveys. They’re sending feedback by canceling orders or switching to a competitor. When CX teams have predictive insight, they can intervene at the most important moments to stop churn and delight customers.

Use data to get ahead on CX

Here’s the imperative: brands need to understand their customers better.

That’s the goal of data collection, whether it takes the form of a survey, order history, or any other customer record you keep. Companies need to leverage all forms of customer data, including transaction data across operational and financial systems, as a prerequisite for predictive capabilities.

Companies must understand and measure the experiences they’re delivering to all customers – not just the 5% or 15% that respond to surveys. They need to move beyond surveys and start using financial and operational data to predict and influence what’s ahead. That’s how CX can become a real growth advantage.