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Part 3: Reporting and data analysis in VOC

Published on July 22, 2021 by Sanjay Malik

Unlocking organisational success with the Voice of the Customer programme (an 8-part series)

This is part 3 of 8 our comprehensive series of blogs on the Voice of Customer.

Stay tuned for more blogs.

In parts 1 and 2 of this series, we covered an overview of the VoC programme and why it is essential. This part focuses on how data gathered can be analysed and put to maximum efficient use.

Analysing VoC data

Data collected from VoC surveys can be qualitative, quantitative or both. Quantitative data helps make sense of an organisation’s standing. Organisations can analyse this data to define and track benchmarks, and understand progress over time or progress across different areas of the organisation. This is an obvious use of quantitative data, but it is also used to define number-based rules, e.g., an email alert mechanism can send out an email to an account executive as soon as a low score is received from a party in his account. Or a customer relationship leader could prioritise accounts for remedial action depending on their vulnerability scores.

Quantitative data also helps marketing teams create customer segments or buyer personas. Combining historical customer data with survey data and third-party data helps create more accurate customer profiles. Based on such profiles, organisations can make targeted pitches, considering ROI and lifetime value of customers. Enhanced capabilities of customer experience (CX) platforms enable data analysis in real time without any human intervention. When acknowledged and actioned upon, this helps retain customers and makes them feel valued.

On the other hand, qualitative data enables an organisation to examine “why” customers have given the particular feedback. Machine learning has enhanced analysis of this type of data, as it helps identify customer sentiment and segregates feedback by tone and business topic. These findings are divided into categories, themes, emerging issues and root causes that can then be reported and actioned upon. The process transforms unstructured text into structured data to be used to understand and predict customer behaviour, using multivariate or logistic regression, cluster analysis and other modelling techniques.

However, we need to keep in mind that feedback, particularly feedback other than event-specific responses, is the culmination of a number of factors that make up the entire customer experience. While the importance of each factor may vary by customer, organisations need to assess the feedback as a whole rather than each aspect independently. A well-thought-out approach is required to define all drivers of feedback (and for which organisations collect data) and then perform cross-segment and correlational analysis to extract and examine those insights that would not have been clear at first glance. It may show how different factors work together to influence an individual customer’s feedback, helping organisations build a more nuanced strategy to enhance the customer experience.

Reporting VoC data

Disseminating VoC information and insights is essential for the programme to be effective. Of course, the needs of an organisation’s various stakeholders would be different, e.g., C-suite executives would want a high-level view of key scores, and the main issues and situations of important customers, but a customer success manager would like to know it all. Individual contributors across service teams, people managers, customer experience teams, chief experience officers (CXOs) and operations analysts all have different objectives regarding reporting. Each party is focused on different sets of data relevant to them individually or to their specific team goals.

Thus, an organisation’s CX/VoC programme should support the following:

  • Role-based reporting with information security and client privacy controls in place

  • Real-time and automated data analysis capabilities

  • Flexibility to extract custom reports

  • Ability to replicate the organisational structure/reporting hierarchy for information consumption

  • Support cross-segment, demography-based and time period-based analysis

  • Statistical and text analytics-based reporting

  • Measuring employee engagement against CX/VoC initiatives

  • Data visualisation capabilities – in-built system or interface with visualisation tools such as Tableau or Power BI

While the above capabilities are related to feedback reporting, an effective CX programme would also consider including the ability to track and report action on and escalation of feedback. For example, while a considerable portion of feedback (mostly neutral and positive feedback) would not require action, the loop could be closed with an automatic but personalised reply. Other feedback (degrees of negative feedback) may require immediate acknowledgment and action, and often serves as a warning sign for the organisation to take corrective action or lose the customer for good.

Such reporting helps organisations on multiple fronts. Product teams obtain invaluable customer input about product features, usability, market fit, performance and expectations that help shape product agendas. Input is also consumed by other departments, including sales, marketing, legal and billing. However, the underlying objective remains the same – to listen to and act on customer feedback.

Another important aspect is talent. Organisations that put customers first work to hire and retain employees who are customer advocates and who keep customer-centricity on the agenda. Such leaders and strategies, popularly termed “customer success”, can elevate the customer experience to the next level when backed by capable data analysts and tech platforms, resulting in increased loyalty and business.

How Acuity Knowledge Partners can help

Acuity Knowledge Partners has been providing research and insight support to diverse stakeholders in the technology sector – tech corporates, tech advisory firms, and tech-focused investors – for nearly two decades. Equipped with a 360o view, we understand how customer data can be captured and analysed, and how the story emanating thereof can be leveraged to achieve better business outcomes. We help Fortune 500 technology corporations, mid-tier firms, and start-ups leverage customer feedback on people, products, and processes to remain flexible and better serve their customers.

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About the Author

Sanjay is a part of Strategy Research team at Acuity Knowledge Partners, with experience across domains such as financial services, fin-tech and consulting, besides working on bespoke projects in the strategy domain. He has worked on projects involving competitive intelligence, market entry & growth strategy, market sizing, industry profiles and benchmarking studies

He is responsible for project execution and delivery, besides working closely with client teams on research tasks and managing source references across projects. He has exposure and knowledge of proprietary databases such as FactSet, Hoovers, Nexis, Bloomberg, and Thomson

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