Customer feedback (VoC) is generated daily through surveys, social media, and in-store inquiries. However, many sales and marketing professionals find that they collect this feedback but are not fully utilizing it. This article explains the basic concepts of VoC analysis, practical steps, and key points for its application in the sales environment of consumer goods manufacturers.
What is VoC (Voice of Customer) analysis?
VoC stands for "Voice of Customer," and refers to the voice of the customer. It is used as a general term for various opinions, requests, and complaints expressed by customers, such as free-response answers in surveys, inquiries to call centers, and posts on social media and review sites.
Benefits of using VOC analysis
VoC analysis refers to a series of methods for systematically collecting customer feedback and using it to improve products and services and to inform sales proposals.
A key feature of this approach is that it handles both quantitative data such as satisfaction scores and NPS, and qualitative data such as free-response texts and review essays. Its value lies in being able to understand both the facts—"what is happening and to what extent"—and the background—"why it is happening."
The background behind the growing attention to VOC analysis
With the rise of social media, customer complaints and reviews now spread faster than companies can even grasp them. Early detection and response to negative feedback are essential for protecting brand image.
Furthermore, with the growing emphasis on a customer-centric management style that continuously refines services, the shift from decision-making based solely on intuition and experience to data-driven decision-making based on genuine customer feedback is another reason why attention to VoC analysis is increasing.
Three Benefits of Conducting Voice of the Customer Analysis
1. Deeper understanding of customers
The words customers actually use can sometimes reveal hidden needs and frustrations that differ from what the company has anticipated.
By carefully gathering individual customer feedback, also known as "N1 voices," we can understand specific reasons for purchase and non-purchase that cannot be seen from averages or aggregated data alone.
2. Leads to improved customer satisfaction and lifetime value (LTV).
By identifying customer dissatisfaction and requests early on and using that information to implement improvements, you can expect to see an increase in customer satisfaction and repeat business.
Especially with consumer goods and other products that are purchased frequently, resolving minor dissatisfactions can directly lead to an increase in LTV (Customer Lifetime Value).
3. Provides hints for product development and sales expansion.
POS data alone can tell you "what sold," but it doesn't tell you "why it didn't sell."
By using Voice of the Customer (Voice of the Customer) analysis to identify the reasons why a purchase was not made and the reactions at the point of sale, it becomes possible to conduct factor analysis in combination with POS data, thereby improving the accuracy of future product development and sales promotion strategies.
How to Conduct a VOC Analysis | 4 Steps
VoC analysis collection channels
Surveys, reviews, and social media
Common channels for collecting Voice of the Customer (VoC) include customer surveys, call center inquiry history, and reviews and word-of-mouth on e-commerce sites and social media.
By gathering feedback from diverse channels, it becomes easier to capture balanced opinions that are not biased towards any particular customer segment.
Channels unique to consumer goods manufacturers: Field round reports and sales reports.
For consumer goods manufacturers, an often overlooked but crucial source of Voice of the Consumer (VoC) is the "actual customer experience."
The reactions of sales floors gathered by field representatives and supervisors during their store visits, the notes from negotiations with buyers, and the raw customer feedback recorded in sales reports are all valuable primary information, yet they tend to get buried and forgotten due to their inconsistent formats such as Excel, Word, and PDF.
The ability to structure and process this kind of feedback from the field is crucial to the quality of VoC analysis for consumer goods manufacturers.
Of these four steps, steps ② and ③, "structuring" and "gaining insights," require the most effort and are also the parts that tend to rely on individual expertise. How efficiently these steps can be made will determine whether VoC analysis can be established as a sustainable practice.
Common challenges in VoC analysis and key points for using AI.
The field reports are inconsistent and cannot be analyzed.
Manually reading daily reports and round reports, which vary in format from store to store and area to area, and compiling trends is a very time-consuming process. Inconsistencies in the points of focus among different personnel also contribute to a decrease in the accuracy of the analysis.
It is difficult to translate qualitative data into quantitative decision-making.
Qualitative data such as free-response texts and comments are often not directly useful for meetings or management decisions, and in many cases, they are left untouched because "it's unclear how to utilize them."
[Efficiency through AI] What you can do with Omatome Ninja
Omatome Ninja is an AI sales report analysis tool for consumer goods manufacturers that solves these problems. It reads field reports (round reports and daily reports) in different formats such as Excel, Word, and PDF, and the AI automatically extracts the reasons why products sold and why they didn't, providing end-to-end support from start to finish, including document creation.
In addition to generating proposal stories based on the authentic voices (N1) of individual stores and individual customers, it enables factor analysis from both qualitative and numerical perspectives by combining this with POS data. It provides end-to-end support for the entire process of visualizing on-site execution capabilities, transforming voices into insights, and converting winning patterns into proposals.
How to choose a VoC analysis tool
Differences between SFA/CRM, BI tools, and AI-powered meeting minutes management tools.
When considering a VoC analysis tool, it's crucial to be mindful of its role in relation to existing SFA/CRM, BI tools, and AI-powered meeting minute management systems. Each tool has its own strengths and a common limitation: they struggle to delve into the "why" behind customer feedback.
| Tool Type | Things I'm good at | Values that are often lacking in VOC analysis |
|---|---|---|
| SFA/CRM | Management of sales activities and negotiation history | A function to formulate hypotheses for proposals based on feedback from the field. |
| BI tools | Visualization of sales and POS data | Analysis of the factors behind why something sold or didn't sell. |
| AI for meeting minutes and transcription | Transcription of conversations and reports | The power of analysis to transform text into insights |
| Summary Ninja Retail Insight | AI analysis of on-site reports and POS data, and automated proposal generation. | We provide visualization, analysis, and proposals in a seamless, end-to-end service. |
Rather than replacing single-function tools, the key to a smooth implementation is to combine dedicated VoC analysis tools, positioning them to complement each other's shortcomings in areas such as "hypothesis formulation," "factor analysis," and "insight transformation."
Frequently Asked Questions about VOC Analysis
The main objective is to enable data-driven decision-making based on genuine customer feedback, rather than decision-making that relies on intuition or experience.
This term is used to refer to a variety of opinions, requests, and complaints expressed by customers, such as those in free-response sections of surveys, inquiries to call centers, and posts on social media and review sites.
Marketing methods based on this concept are also called "VoC marketing," and at its core is "VoC analysis," which is explained in this article.
If you want to use VoC analysis as a practical tool, try Omatome Ninja.
VoC analysis is a method for systematically collecting customer feedback and utilizing it in business activities. Especially for consumer goods manufacturers, the raw voices gathered by field representatives and supervisors on a daily basis, rather than just call centers or surveys, become unique VoC that other companies cannot imitate.
The key to making VoC analysis successful lies in being able to structure disparate field reports and combine them with POS data to decipher "why it sold"—all in a seamless, end-to-end process. Start by trying the free demo of Omatome Ninja to see how you can leverage the VoC data lying dormant in your own company.
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