4. The Voice of the Customer - Examples 2 and 3

In this section, we will explore two additional examples related to the Voice of the Customer pillar within Product Operations. These examples highlight how NPS surveys and deep dive analyses were implemented at VTEX to capture customer feedback and improve product development.

Example 2: NPS Survey

NPS (Net Promoter Score) is a widely used metric to measure customer satisfaction. It involves asking customers how likely they are to recommend a product on a scale of 1 to 10. Customers who give a score of 9 or 10 are considered promoters, while those who score 6 or below are classified as detractors. The goal for most SaaS companies is to maintain an NPS score of above 30, and an NPS score of above 40 is considered excellent.

At VTEX, there wasn’t a global NPS process in place, even though this metric is crucial for understanding customer satisfaction in a SaaS business. The Product Team is typically responsible for moving the NPS needle, but this required a more structured approach. Product Operations stepped in to help streamline the process.

The Problem

VTEX didn’t have a standardized, centralized process for running NPS surveys globally. The existing efforts were scattered and not aligned, which meant that the product team couldn’t effectively use NPS data to improve customer satisfaction.

The Solution: Consolidating the NPS Process

To address this, Product Operations consolidated the NPS survey process and launched it globally on a quarterly basis. The process included:

  1. Tools: VTEX used a combination of three different tools to launch the survey and collect the data.
  2. Automation: Initially, the Product Ops team manually analyzed the survey results. However, after the initial Beta test, a machine learning tool was introduced to automate the analysis of the thousands of comments received. This tool was trained to segment customer feedback and highlight trends for the product team.
  3. Dashboards: Product Ops also created dashboards to present the NPS results in a way that the entire company could easily access and understand.
  4. Tracking Usage: A key part of the process was tracking how the product team used the NPS data. The team ensured that the NPS results weren’t just published and forgotten; instead, they monitored whether the insights were being used to influence roadmap decisions and improve customer satisfaction.

In addition to analyzing the NPS results, Product Ops experimented with linking specific product features to the NPS feedback. For example, if customers mentioned issues with a specific checkout feature in the NPS survey, this feedback was tied directly to the product feature in the dashboard. The team then tracked whether improvements to that feature influenced NPS scores in future cycles. Although this test is complex, it’s particularly valuable for companies with fewer products or more controlled environments, as it allows for a direct correlation between product changes and customer satisfaction.

Example 3: Deep Dives into Segments or Challenges

The third example revolves around deep dives into specific customer segments or challenges faced by the product team. This approach differs from the more automated processes we’ve discussed and leans towards a more consultative, intelligence-driven method.

The Problem

The product team at VTEX faced the challenge of improving customer satisfaction across specific regions. However, satisfaction is influenced by multiple factors, and with 35 product managers, it was difficult for any one person to take ownership of the issue. Moreover, a surface-level analysis of customer feedback wasn’t enough to identify the real pain points or actionable solutions.

The Solution: Cross-Data Deep Dive

Product Operations experimented with conducting deep dives into key global challenges to offer a more comprehensive analysis for the product team. Here’s how the process worked:

  1. Data Funnel: The team started by analyzing NPS data and combined it with other data sources, such as support tickets, ideas submitted through the idea portal, and other customer feedback.
  2. Segmentation: The Product Ops team segmented the data to focus on specific regions and segments. They identified the most critical issues that, if addressed, would have the greatest impact on customer satisfaction.
  3. Presenting the Findings: The findings were compiled into a PowerPoint presentation and shared with multiple teams, including Sales, Product, and Engineering. This ensured that all relevant teams were aligned on the issues and potential solutions.

Bringing Teams Together

The deep dive approach was particularly valuable because it brought different teams—Sales, Product, and Engineering—together to work on a unified solution. By presenting the findings to the Sales team first, the Product Ops team was able to gather additional insights and ensure that everyone was on the same page. This collaborative approach helped eliminate the disconnect between different departments and created a shared understanding of the challenges at hand.

Lessons Learned from Deep Dives

Conclusion

Both the NPS survey consolidation and deep dive analyses were instrumental in helping VTEX better understand the Voice of the Customer. Through automated tools, clear dashboards, and collaborative deep dive sessions, the product team was able to make data-driven decisions, improve customer satisfaction, and better align their efforts with business goals. These processes illustrate the power of Product Operations in streamlining workflows and ensuring that the product roadmap is informed by customer feedback.