In case you need more convincing, here are 4 reasons to use AI in VoC programs

Ashley Sava

August 27, 2020

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The customer's unadulterated perspective is the value AI in VoC programs deliver, with the most worthy ones providing data to guide strategy. AI gives your voice of the customer programs the edge they need to make measurable change.

An NTT study found that 44 percent of enterprises now operate structured VoC programs to drive CX improvement and innovation. As businesses continue to attempt to close the gap on a customer’s expectations for a product or service and what they actually experience, an accurate overview of the customer’s opinions, critiques and desires is essential. The most thorough VoC programs are able to sort through customer interactions to provide organizations customer intelligence and insights that anyone inside the enterprise can interpret. 

Here are four reasons you should use AI in VoC programs:

Effectively work through sales strategies 

Are you curious about how upsells, cross-sells, promotions and campaigns are impacting customer loyalty? If not, you should be. The pandemic has altered the course of the buyer journey and nailing down best practices on new behaviors and habits takes time. Using AI in your VoC programs lets you measure which promotions and cross-sell are beneficial, track campaign success, evaluate sales pitches and gauge customer loyalty levels. If behaviors change (as they often do) you won’t be stuck in a rut wondering whether or not you’re keeping up with preferences. 

Stop churn in its tracks

Why are some customers churning faster than others? Why is there a sudden spike in churn after a new product upgrade? Stop wondering and let AI’s machine learning algorithms help you determine which factors are influencing your customer’s decision to pull the plug. According to statistics from Small Business Trends, 65 percent of an organization’s business comes from existing customers. Leveraging AI to forecast behaviors can help businesses unbury once hidden indicators of future churn. Using platforms like Tethr, organizations can collect raw data on interactions with customers and transcribe it into a searchable format, while collecting powerful insights to help leaders immediately zero-in on the best opportunities for driving transformation. These insights can uncover reasons for customer dissatisfaction, compliance risks, problem agents, and areas of customer effort.

Never miss a touchpoint

AI gives you access to expand speech analytics’ range to include call center conversations, chats and operational data from every customer touchpoint. Customers are engaging with your business on your website, through social media profiles, on your blog, through chats, via email and over the phone. Whether they’re speaking to someone in your call center or interacting digitally, there is so much you can learn about the customer experience as a whole if you listen to all the ways a customer communicates with your business. Inside every channel, instances of customer effort, frustration, confusion and feedback are prevalent. By drawing insights from all of these areas, identifying problems with things like digital platforms or the product experience is a given. Your customers have already provided all of the insights you need and have given you feedback along their journey—you just have to collect it. Using listening enterprise platforms like Tethr, organizations can gather intelligence from conversations and derive actionable insights in a timely manner.

Improve the performance of your call center reps

Machine learning algorithms have given us the opportunity to extract near real-time agent-based performance data. The Tethr Effort Index (TEI), the market’s first machine learning-based, predictive effort score, tracks customer effort at a conversation-level, and immediately drills down into high-effort interactions that spark disloyalty and churn. The TEI score is automatically assigned by the Tethr platform at the completion of every customer interaction, allowing managers to instantly understand the effort level of an interaction so improvement to the customer experience can commence.

Why use AI in VoC programs?

In addition to TEI, Tethr now offers the Agent Impact Score (AIS), a TEI derivative that gives managers the ability to measure the quality of agent performance and track how different agents are handling difficult customer situations.

Want to learn more about the value of AI in VoC programs? Sign up for a demo of Tethr to start moving VoC to the center of your enterprise today.

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