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Consumer Insights Analytics

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Project Context

As a modern research partner, MakerSights’ consumer insights drive success for retail brands like Adidas, HOKA, Ralph Lauren, North Face, and Timberland.

The three goals

Cut inefficiencies so teams could focus on high-value analysis, transition customers fully from 1.0 to 2.0, and lay the foundation for future capabilities — AI-powered analysis, advanced reporting, deeper enterprise features.

Company:
MakerSights
Year:
2024
Product type:
B2B Web App
My role:
Lead Product Designer
My UX team:
1 researcher & 1 freelance designer
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The Challenge

Our B2B users

Working in a B2B hybrid service–software model meant designing for two distinct user groups with very different goals:

  • Internal teams needed efficient tools to build and manage surveys under tight timelines.
  • B2B customers expected a smooth, intuitive experience that reflected their brand and instilled confidence in the research output.

Balancing these needs was critical. The challenge was to design solutions that served both audiences without compromising on either side.

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Navigation got in the way of insights

In 1.0, side navigation and filters dominated the screen, leaving less space for data. To help users quickly reach survey insights, we needed to restructure the results, separate insights from raw responses, and upgrade data visualization options.

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A time consuming and error prone workflow

Analysis often meant downloading CSVs, building pivot tables in Excel, and manually creating charts. This added 4–8 hours of work per project, draining time and keep our team away from higher value work.

Too much raw data, not enough insights

Even when results were accessible, users were overwhelmed by the volume and there was a gap to find relevant insights. We needed a way to surface meaningful insights faster, ideally leveraging AI for scale.

My Role

I was the lead designer on a team of three: Lena, a UX researcher, and Vasyl, a design system designer. Ten months total, with iterative delivery across two phases: first parity and efficiency, then new customer value.

Scope: Product strategy and feature prioritization, user research, interaction design, data visualization, design system work, and delivery.

Research: I advocated for user insights to prioritize the right features and ran impact/effort workshops with the team to keep focus on the highest-value work. Research from user sessions directly shaped which features shipped in which order. The incremental approach was a deliberate choice: early wins built momentum and created internal champions for 2.0 adoption before we'd finished everything.

Influence on scope: I pushed to organize the insights navigation around report formats, not data categories. That reframe wasn't obvious at the start — the team had assumed "better charts" was the primary need. Research showed navigation was the bigger barrier.

What we shipped

Flexible data visualizations

In 1.0, users could only analyze three question types with a single chart option, which limited how they explored their data. In 2.0, we expanded support to ten question types and five visualization styles, and added richer views for sentiment scores and line efficiencies.

Why it matters: This gave both internal teams and customers the flexibility to represent results in ways that matched their decision-making, moving beyond “one-size-fits-all” charts.

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Navigation that surfaces insights

The old layout buried insights under sidebars and tabs. In 2.0, we introduced a dedicated Survey Insights area that highlights key takeaways first, while restructuring navigation to mirror the report formats used by our retail customers.

Why it matters: Instead of hunting for meaning, users are guided directly to the insights they care about—building confidence in the tool and speeding up delivery.

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Introduced qualitative data summary with AI

Qualitative data is considered a “goldmine” for getting a “real read” on what people think about a product, colour, design, or topic. It is hard to collect and decipher at scale; reading through thousands of open ended responses to spot patterns. In 2.0, we introduced LLM-powered summarization to automatically surface themes across qualitative data.

Why it matters: What used to take hours of manual review can now be scanned in minutes, giving teams more time to interpret patterns and deliver richer insights.

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Streamlined analysis and comparison

Analysis in 1.0 often meant exporting to Excel and creating pivot tables by hand. In 2.0, we added aggregation, side-by-side comparison, and grouped filters directly into the platform.

Why it matters: Internal teams can now run comparisons across products and questions without leaving the tool, cutting down hours of repetitive work and making analysis accessible to non-technical users.

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Impact

Time saved in workflow

Before, our Customer Operations team spent 4–8 hours wrangling CSVs and pivot tables just to prepare a report. With the new results experience, they could analyze data and build decks in under an hour. This not only reduced frustration, but also freed them to focus on higher-value analysis instead of repetitive formatting—a big morale boost for a team under constant delivery pressure.

Customer satisfaction increased

For customers, the change was tangible: reports landed in their inbox 26% faster than before. That speed, paired with more intuitive visualizations, made insights easier to act on and drove a 12% boost in NPS. Faster, clearer results meant product teams could make decisions with more confidence—reducing the risk of delayed product launches or missed trends.

Strategic goal aligned

At a business level, the project moved MakerSights closer to its vision of being a modern research partner. More powerful analytics tools meant we weren’t just delivering raw data—we were helping brands see the “why” behind consumer choices. This elevated our credibility in sales conversations and positioned us to grow deeper partnerships with enterprise clients.

How we tackled it

Understanding core user needs

Our Customer Operations team—the main users of Survey Results—struggled with clunky workflows and had to build client decks manually. Without deeply understanding their process, we risked designing solutions that missed the mark.

I embedded with the team by joining their weekly standups, shadowing their projects, and reviewing hundreds of their final Insight Report decks. This gave me visibility into both their workflow bottlenecks and the customer-facing expectations.

By grounding product priorities in their day-to-day reality, I was able to advocate for features that directly reduced their pain and aligned better with what customers needed to see in reports.

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Prioritizing features incrementally

The scope was too large to solve all at once, and our small team risked spreading efforts thin. If we didn’t deliver value quickly, adoption of 2.0 would stall.

I worked with the product triad to break the work into epics—starting with productizing 1.0 flows so we had continuity, then layering in new analysis features once the foundation was stable. I facilitated prioritization workshops to help the team weigh impact vs. effort, ensuring focus stayed on what mattered most.

This incremental approach allowed us to ship meaningful improvements early, maintain momentum, and build trust with internal users—who in turn became champions for adopting the 2.0 results experience.

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The iterative designs

Introduce collapsible sidebars
To maximize the data view’s real estate, we made the navigation and filter sidebars collapsible. Given that most surveys include at least 15 products, we also introduced a full-screen mode, ensuring all products are visible without being cut off in a smaller view.

Users could now scan entire surveys without distraction, reducing scrolling and improving efficiency when comparing many products at once.

Compare toggle in the sidebar
Comparing data across products or questions required multiple manual steps and was confusing for users.

I explored several comparison layouts and, together with our UX researcher, tested usability, chart comprehension, and navigation. The solution—a clear Compare toggle in the sidebar—proved discoverable and effective.

Users could now easily compare across all questions at once, improving clarity and reducing reliance on external Excel pivot tables.

Prioritize displaying ranked product images
From my regular conversations with the Customer Operations team, I learned that customers value product visuals more than constant chart-based representations. By the time this feature was prioritized, I had already gathered key insights on what was needed for its design. I advocated for giving users control over the size of product tiles, allowing them to customize their view in the Insight Report.

Insights become more visual without losing the data, helping merchandising teams make decisions faster.

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Platform rebrand updates

While we were redesigning, the company went through a marketing rebrand, which risked creating inconsistency between software and customer-facing materials.

I led the rebrand updates for the product, partnering with marketing and engineers to align both 1.0 and 2.0 platforms with the new identity. This included creating a unified, accessible color palette, updating the typescale, and refining design system components—especially data visualization elements.

This ensured the platform reflected our new brand identity, reinforced credibility in front of enterprise clients, and created consistency across both 1.0 and 2.0 during the transition.

Takeaways

Design impact goes beyond software

I learned that improving the customer experience meant looking beyond the interface. By mapping the Customer Operations team’s workflow and service journey, I was able to refine not only the software but also the reports they deliver. By connecting software and service touchpoints, I learned that design has the most impact when it bridges the full end-to-end experience.

Connect the holistic experience

Working across both 1.0 and 2.0 systems meant designing with systemic thinking. I spent time understanding both platforms deeply so I could connect Results, Creator, and Taker flows without introducing new gaps. This allowed users to transition smoothly, even while we phased out old systems. It reinforced for me that good design isn’t just about new features—it’s about stitching together a coherent experience through change.

The design team of one

Being the only full-time designer on a growing product was challenging. With limited UX resources, I had to flex between craft, product thinking, and facilitation. I enrolled in a Product Strategy for Designers course, practiced workshop facilitation (even when sessions didn’t go as planned), and deepened my understanding of engineering so I could present trade-offs clearly. It was a stretching experience that taught me that influence comes as much from clarity and collaboration as it does from design craft.

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About Me

Senior Product Designer with a business and marketing background. Driving vision through validated insights, fast collaboration, and prototyping with care.

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Milan, Italy
ly.vu.connect@gmail.com
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