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Published on
February 12, 2021

Why companies who want true VoC need to engage the power of AI

Michael Lawder

CX teams use ASAPP's generative AI to automate, boost agent productivity, & uncover insights.

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back to blog
Published on
February 12, 2021

Why companies who want true VoC need to engage the power of AI

Michael Lawder

The best businesses succeed by developing a holistic understanding of their customers. Most, if not all, consumer companies have a Voice of the Customer (VoC) program, intended to capture and analyze feedback, leveraging the insights to drive both strategic and operational improvements across the business. While the intent of these programs is critical to constant improvement, the tools that have been available to CX professionals fall short of delivering what they really need.

Surveys and samples only give a partial view

Many organizations build VoC programs solely on a “survey and score” foundation. When done right, surveys can play an important role in any VoC program. But due to their low average response rate and general bias, they provide organizations with a limited view of the overall customer experience and the quality of service that is being delivered by your organization.

An overreliance on surveys has other pitfalls, too. Relationship-based surveys, for example, evaluate general brand satisfaction, but often fail to provide clear feedback on the internal processes, people, and frontline events that contribute to customer experience. On the flip side, transaction-based surveys capture feedback in the moment, but tend to lose sight of what the overall relationship looks like from the customer’s point of view.

Other companies might record calls, then either listen to or transcribe a subset of these calls. This approach also limits analysis to a small sample of customer interactions.

Analyzing only a fraction of your calls fails to tell the whole story. Yet companies rely on this data to make important decisions about product, sales, and marketing initiatives as well as contact center operations.

What’s more, with both of these approaches, there can be a significant time lapse between capturing the data, gaining insight from that data, and putting that insight into action. The truth is that most of us in the customer experience world have never had a full view of the quality of service we are delivering to our customers, and the opportunities that exist to improve the way in which we serve our customers across the enterprise.

AI elevates VoC with new possibilities

Artificial intelligence fuels new options for gaining more comprehensive customer insight. And, for putting that insight into action. Forward thinking CX leaders are excited about mining this wealth of data and are heartened to learn that they won’t need an army of data scientists on staff to do it.

Highly accurate transcription is key

The best of these new solutions start with highly accurate real-time transcription of every call. Transcription is not the goal, but a means to an end. However the importance of the quality of transcription can’t be overstated, as this is the fuel for meaningful analysis. More on this here.

Michael Lawder
AI solutions that use machine learning models custom trained on a company’s lexicon are—not surprisingly—far more accurate than solutions using generic models trained on everyone’s data. Consequently, they can deliver far more value.

Michael Lawder

Getting this data in real time gives companies the opportunity to take action instantly instead of waiting weeks, months, or even longer to address customer needs. And having it for every call gives companies a much fuller customer perspective.

Rich actionable insights

The real value comes not in just getting the data, but in being able to put it to use in meaningful ways. Beyond accurately transcribing customer conversations, an AI-driven VoC program can:

  • Analyze sentiment and even predict CSAT and NPS scores
  • Capture customers problem statements
  • Classify intent at a useful level of detail
  • Spot correlations between things—for example: callbacks or sentiment by agent, intent, or length of call
  • Highlight trends and anomalies in customer conversations
  • Alert supervisors of coaching need by agent or topic
  • Automate summary notes, providing cleaner data for analysis and better records for future customer contact

For the first time, you can effectively measure the quality of service you are delivering for every product, every interaction, every agent.

Cultivating VoC of this depth can do more than help manage and optimize CX operations. It has the power to influence business as a whole. CX leaders become the ultimate advocate for the customer, able to synthesize customer wants and needs as they relate to every stage of the customer journey. This elevates their stature in the organization, as they become trusted sources for insights that inform key decisions and strategy aimed to build customer loyalty and grow revenue. If you’d like to hear how companies in your industry are using AI-driven speech intelligence solutions in their VOC programs, drop us a line at ask@asapp.com.

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About the speakers

Michael Lawder

Michael Lawder is Customer Experience Officer at ASAPP.

Why companies who want true VoC need to engage the power of AI

The best businesses succeed by developing a holistic understanding of their customers. Most, if not all, consumer companies have a Voice of the Customer (VoC) program, intended to capture and analyze feedback, leveraging the insights to drive both strategic and operational improvements across the business. While the intent of these programs is critical to constant improvement, the tools that have been available to CX professionals fall short of delivering what they really need.

Surveys and samples only give a partial view

Many organizations build VoC programs solely on a “survey and score” foundation. When done right, surveys can play an important role in any VoC program. But due to their low average response rate and general bias, they provide organizations with a limited view of the overall customer experience and the quality of service that is being delivered by your organization.

An overreliance on surveys has other pitfalls, too. Relationship-based surveys, for example, evaluate general brand satisfaction, but often fail to provide clear feedback on the internal processes, people, and frontline events that contribute to customer experience. On the flip side, transaction-based surveys capture feedback in the moment, but tend to lose sight of what the overall relationship looks like from the customer’s point of view.

Other companies might record calls, then either listen to or transcribe a subset of these calls. This approach also limits analysis to a small sample of customer interactions.

Analyzing only a fraction of your calls fails to tell the whole story. Yet companies rely on this data to make important decisions about product, sales, and marketing initiatives as well as contact center operations.

What’s more, with both of these approaches, there can be a significant time lapse between capturing the data, gaining insight from that data, and putting that insight into action. The truth is that most of us in the customer experience world have never had a full view of the quality of service we are delivering to our customers, and the opportunities that exist to improve the way in which we serve our customers across the enterprise.

AI elevates VoC with new possibilities

Artificial intelligence fuels new options for gaining more comprehensive customer insight. And, for putting that insight into action. Forward thinking CX leaders are excited about mining this wealth of data and are heartened to learn that they won’t need an army of data scientists on staff to do it.

Highly accurate transcription is key

The best of these new solutions start with highly accurate real-time transcription of every call. Transcription is not the goal, but a means to an end. However the importance of the quality of transcription can’t be overstated, as this is the fuel for meaningful analysis. More on this here.

Michael Lawder
AI solutions that use machine learning models custom trained on a company’s lexicon are—not surprisingly—far more accurate than solutions using generic models trained on everyone’s data. Consequently, they can deliver far more value.

Michael Lawder

Getting this data in real time gives companies the opportunity to take action instantly instead of waiting weeks, months, or even longer to address customer needs. And having it for every call gives companies a much fuller customer perspective.

Rich actionable insights

The real value comes not in just getting the data, but in being able to put it to use in meaningful ways. Beyond accurately transcribing customer conversations, an AI-driven VoC program can:

  • Analyze sentiment and even predict CSAT and NPS scores
  • Capture customers problem statements
  • Classify intent at a useful level of detail
  • Spot correlations between things—for example: callbacks or sentiment by agent, intent, or length of call
  • Highlight trends and anomalies in customer conversations
  • Alert supervisors of coaching need by agent or topic
  • Automate summary notes, providing cleaner data for analysis and better records for future customer contact

For the first time, you can effectively measure the quality of service you are delivering for every product, every interaction, every agent.

Cultivating VoC of this depth can do more than help manage and optimize CX operations. It has the power to influence business as a whole. CX leaders become the ultimate advocate for the customer, able to synthesize customer wants and needs as they relate to every stage of the customer journey. This elevates their stature in the organization, as they become trusted sources for insights that inform key decisions and strategy aimed to build customer loyalty and grow revenue. If you’d like to hear how companies in your industry are using AI-driven speech intelligence solutions in their VOC programs, drop us a line at ask@asapp.com.

Authors: 
Michael Lawder

Michael Lawder is Customer Experience Officer at ASAPP.

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