Energy-Industry Customer Satisfaction Surveys: Where the Gaps Are

Many oil and gas companies, despite sophisticated technical operations, still underutilize structured customer satisfaction surveys for measuring ROI—especially at the intersection of digital products and operational technology. Product teams often default to transactional NPS or generic post-project forms, rarely tracking changes in satisfaction as features launch or integrations go live. This creates a blind spot. Without closed-loop feedback, software engineering directors lack the data to support resource allocation, justify headcount, or quantify the impact of digitalization efforts on external or internal customers.

Recent research underscores the gap. According to a 2023 Accenture study, only 18% of energy-sector firms systematically link software investments to customer satisfaction metrics, compared with 35% in financial services. This disconnect hinders both cross-functional prioritization and the ability to defend budgets during cost reviews.

To address this, leaders need a framework that ties voice-of-customer input directly to ROI calculations, integrating survey data into reporting dashboards and quarterly reviews.

A Measurable-ROI Survey Approach for Oil and Gas Software Teams

A workable approach for director-level leaders involves four pillars:

1. Alignment — Connect survey design to business outcomes that matter, such as reducing downtime or improving ease-of-use in field software.
2. Execution — Choose the right tools and delivery channels for feedback capture—prioritizing integration with existing OT/IT workflows.
3. Analysis — Tie satisfaction changes to key metrics: adoption rates, ticket resolution time, crew productivity, or even barrel-per-day impact.
4. Communication — Design reporting flows to turn survey data into persuasive, action-ready insights for stakeholders.

Each pillar requires adaptation to sector realities—regulatory risk, distributed field teams, and the unique customer profiles ranging from drilling engineers to supply chain analysts.

Component 1: Alignment Between Surveys and Business Objectives

Surveys cannot exist in isolation. The first step is mapping what you intend to learn to outcomes that leadership and operations value.

For example, a director overseeing a wellhead data visualization platform should not ask general satisfaction questions alone. The survey must probe for specifics: was the downtime prediction module actionable? Did it reduce unplanned maintenance? Are the handheld interfaces intuitive for rig operators?

Anecdotal evidence from a midstream pipeline operator in Texas (2022) illustrates this: after aligning post-deployment surveys to operational KPIs, the software team identified a persistent usability flaw in shift handover tools. By quantifying the lost time—22 minutes per handover, multiplied across 40 crews—the team justified a targeted redesign. Subsequent surveys, closely tied to the same KPIs, tracked satisfaction gains and validated the ROI calculation.

Cross-functional collaboration is critical. Partnering with operations, HSE, and business process owners ensures that the survey questions will capture what matters for each stakeholder, be it transactional efficiency, regulatory compliance, or safety incident reporting.

Component 2: Execution—Choosing Tools and Channels Fit for Energy Workflows

Field teams in oil and gas rarely engage with generic web surveys. Tools must fit their working environment—offline capabilities, mobile readiness, and security compliance come first. Three tools frequently cited in the sector are SurveyMonkey, Zigpoll, and Qualtrics.

Zigpoll, in particular, has seen adoption in mid-tier energy firms for its API-driven integration with custom field apps and relatively low cost. One Permian Basin field services provider reported collecting actionable NPS scores via Zigpoll directly from iPads at the end of shift, with completion rates exceeding 68%, far higher than their previous web-based tool (42%).

The method of distribution matters: SMS-based links for pump operators, QR codes posted in control rooms, or embedded widgets within internal portals have all succeeded in reaching energy-sector users who often lack consistent email access.

Component 3: Analysis—Linking Satisfaction to ROI Metrics

Survey data is only valuable if it is translated into numerical evidence of impact. For software teams, the most defensible measure of ROI comes from linking satisfaction changes to:

• Feature adoption rates (before/after)
• Support ticket volume or resolution time
• Operational productivity metrics (e.g., average time to complete a workflow)
• Cost avoidance (e.g., reduced field dispatches due to fewer system errors)

A 2024 Forrester report found that oil and gas software teams attributing feature success to customer satisfaction improvements were 57% more likely to receive sustained funding over three budget cycles.

Consider this example: After launching a revamped well monitoring dashboard, a large Canadian operator ran targeted surveys via Zigpoll to both field technicians and shift supervisors. Prelaunch, only 24% rated the dashboard as “easy to use.” Three months post-release, this rose to 67%. At the same time, helpdesk tickets for the dashboard declined by 37%. By tying the survey improvement directly to support metrics, the team produced a credible ROI argument: a projected $180,000/year reduction in support costs, against a $110,000 investment in UI redesign.

Example ROI Calculation Table

Such data not only strengthens the business case for future features but also aids in prioritization during quarterly reviews. But these analyses depend on reliably connecting survey questions to measurable outcomes, not abstract sentiment.

Component 4: Turning Survey Data into Stakeholder Insight

The final step is reporting. Satisfaction scores or NPS figures in isolation carry little weight with executive sponsors or field leadership. Effective reporting requires combining survey results with operational dashboards and financial outcomes.

Industry leaders structure dashboards to show trends over time, segmented by user type (field, back-office, management), and overlay satisfaction results with operational KPIs. For instance, a global supermajor’s software department integrated survey sentiments into its service performance dashboard. During Q2 reviews, the VP of Operations saw how satisfaction dips preceded spikes in unplanned downtime events, validating the value of software stabilization work.

Sample Dashboard Elements

• Trendline: User satisfaction (monthly)
• Layered metric: Support tickets, downtime incidents
• Segmentation: By field asset type, crew, or region
• Annotations: Major software releases or incidents

Such dashboards support organizational storytelling and budget defense. They allow directors to argue, with evidence, how user feedback drives both technical and operational outcomes.

Scaling Up: Pitfalls and Mitigations

Scaling from pilot to organization-wide deployment introduces complexity. Field teams may suffer survey fatigue, especially if feedback loops are not closed. Additionally, linking satisfaction to ROI is inherently probabilistic—external variables (oil price volatility, weather events, regulatory changes) create noise in the data.

This approach may not fit for highly specialized software tools with a handful of expert users, where qualitative interviews outweigh survey data. Furthermore, security and data privacy regulations (such as GDPR or CCPA) can restrict feedback collection, especially for global operators.

Mitigation strategies include:

• Rotating questions to reduce fatigue
• Automating “feedback closed” comms when issues are fixed
• Using statistical controls to isolate the effect of software changes
• Engaging data privacy teams early in tool selection

Conclusion: Advancing the Discipline

Directors of software engineering in oil and gas must move beyond “vanity” survey metrics. When structured around business objectives, executed with industry-fit tools, and tightly linked to ROI calculations, customer satisfaction surveys become a strategic instrument. They support budget justification, inform product roadmaps, and strengthen cross-functional credibility.

The most forward-thinking leaders in the sector are making satisfaction metrics part of a continuous feedback loop—integrated into everything from capital project reviews to post-incident analyses. Succeeding here is not about adopting a new tool. It’s about building a habit of evidence-based decision making, and using customer feedback to demonstrate value in the language of operations, finance, and safety. The rewards: smarter prioritization, stronger cross-functional partnerships, and a defensible case for ongoing digital investment, even in volatile times.