How Customer Feedback Drives Better Scientific Software Development

Building software for research institutions requires balancing product vision with real-world needs. Academic publishers and funding agencies face unique challenges that standard software solutions rarely address effectively.

At Prophy, we've learned that the most valuable product improvements come from understanding why customers struggle with existing research workflows - not just what they say they want.

When User Feedback Signals Fundamental Problems

Sometimes customer feedback reveals when a feature needs complete reconstruction rather than incremental fixes. Our article search functionality consistently confused users who found the interface complex and difficult to navigate.

The feedback pattern indicated a core design problem. We had built a feature that was so complex it essentially served no one effectively. Rather than adding patches, we rebuilt the search system entirely from scratch.

Once our CTO spent three weeks exclusively focused on this rebuild - not managing the team, not answering client requests, just rebuilding search. The new version eliminated most user confusion, though we still maintain a list of potential improvements that could take months to implement.

Geographic Filtering: From Client Request to Universal Feature

Our client, a top-5 Belgium fund, asked if we could filter search results by country to identify collaborations for conflict-of-interest checking. When we explored their specific needs, they actually required regional filtering - not just Belgium, but specifically Flanders, the Dutch-speaking region.

This insight revealed broader implications. If Belgium needs regional filtering, other federative countries likely do too. Germany has multiple federal states. The US has state-level research priorities. Countries with federal structures often have region-specific funding bodies.

What started as a country filter request became regional filtering capability. The additional work to implement regions alongside countries was minimal - perhaps 20% more effort - but the market applicability expanded significantly.

Internal Workflow Pain Points Often Indicate Market Opportunities

Our most successful feature development came from solving internal problems. One of our engineers spent over a year writing manual scripts for proposal-to-reviewer allocations - a frustrating, time-intensive process.

Finding scripts from previous years, updating them after code changes, and validating results consumed enormous time and energy. The engineer developed his own solution: a custom language for describing constraints, an editor with autocompletion, and automated validation systems.

That internal tool became our Allocator product. The engineer went from being the only person who could handle allocations to enabling our customer success manager and even clients themselves to perform allocations independently.

Strategic Feature Prioritization Framework

Not every customer request merits immediate development. We evaluate based on implementation time:

Three days or less: Usually implemented immediately for existing customers. Quick implementations demonstrate responsiveness and often satisfy broader needs.

Three weeks to three months: Evaluated based on market applicability and strategic alignment.

Over three months: We wait for additional validation. If another customer requests something similar, we prioritize it. If not, it remains in the backlog.

This prevents expensive custom development while maintaining customer relationships.

Managing Interface Complexity Through Selective Enhancement

Some feedback requests would improve functionality for specific users while potentially degrading experience for others. Adding numerous filters to our Referee Finder could create overwhelming interface complexity - multiple screens of settings that make the tool harder to use.

The challenge is making complex features presentable and easy to use. Our previous search iteration failed because we didn't simplify it sufficiently. Complex features that work well typically evolve gradually rather than being designed comprehensively from the start.

Cross-Market Application Discovery

Sometimes customer feedback reveals unexpected use cases. Our Panel Composer was designed for grant funding panels, but journals began using it for editorial board management - same core functionality serving entirely different market needs.

When feedback suggests your tool addresses problems across multiple sectors, you've identified expansion opportunities beyond your original market assumptions.

Balancing Product Vision with Market Input

Effective product development requires both strategic direction and customer responsiveness. Core functionality should align with your original vision while remaining flexible enough to incorporate valuable market insights.

Our Referee Finder's core functionality still works as we envisioned years ago, but numerous small improvements came from customer feedback: additional filters, popup information displays, and specialized features like open access article identification.

The Power of Being Your Own User

The best product development happens when you're solving your own problems. We developed an ontology editor and author disambiguation tools primarily because we needed them ourselves. When you experience the pain points directly, you understand exactly what needs improvement.

Our Allocator tool succeeded because the engineer who built it was also its primary user. He understood every friction point and could immediately validate whether improvements actually worked.

Product Development Strategy for Research Software

For academic publishers and funding agencies, the key is identifying which customer feedback addresses systematic workflow problems versus individual preference requests.

When customer feedback consistently reveals friction points, you're likely seeing systematic issues worth addressing. When individual customers request very specific customizations, evaluate whether the broader research community would benefit from similar functionality.

The most effective research software evolves through this balance - maintaining product coherence while addressing real workflow challenges that research institutions face daily.

Customer feedback drives meaningful product improvements when properly evaluated through strategic filters. The goal is building software that serves the research community's actual needs, not just stated preferences.