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NewYM Export Enhancement

Designing a faster, more intuitive export experience for Revenue Management Analysts

Overview

Product: NewYM
Users: Revenue Management Analysts
Feature: Data Export (Excel)
Goal: Make exported data easier to read, verify, and share.

Role: UX/Product Design (Research, Problem Definition, Solution Design, Dev Collaboration)

Time: June 2024 (3 months)

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Revenue Management Analysts rely heavily on exporting data from NewYM to Excel in order to analyze trends and share insights with internal stakeholders. However, the existing export format was difficult to interpret and required significant manual effort to validate and organize.

 

I led an enhancement that redesigned how chart data exports into Excel so that the structure mirrors the layout users see in NewYM.

 

Impact:

  • Reduced time spent finding and validating exported data by ~80%

  • Improved analyst workflow efficiency

  • Made exported data easier to share with stakeholders

The Problem

​​Users frequently export chart data from NewYM screens to conduct deeper analysis in Excel.

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However, the exported file had major usability issues.

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The key pain points:

  • Disorganized Structure
    The exported data appeared in a format that did not match the layout of the NewYM interface.
     

  • Difficult to Navigate
    Users had to search through rows and columns to locate the data they needed.
     

  • Time-Consuming Validation
    Analysts frequently had to double-check that the numbers in Excel matched the values on the NewYM screen.
     

  • Manual Cleanup
    Many users would reorganize or reformat the spreadsheet themselves before using it.

 

Because of this, analysts would often spend several minutes just locating the correct data, slowing down their workflow.

 

This created friction in a process that users perform many times throughout the day.

Understanding The Users

The primary users were the Revenue Management Analysts who depend on data exports to:

  • Perform deeper analysis outside of the platform

  • Validate metrics shown in NewYM

  • Share data with internal stakeholders (Field Leaders, Group Leaders, etc.)

  • Build reports and presentations

 

Because Excel remains a core tool in their workflow, exporting platform data is a critical step in their analysis process.

Research & Discovery

My approach was to address this issue by working closely with the users and developers to understand how exports were being used and how it was currently functioning.

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User Research:

I conducted interviews to learn:

  • How often they export data

  • What information users look for first in exported files

  • Where confusion occurs in the spreadsheet

  • How users verify the numbers match the platform

  • How/why data was being uploaded and organized in Excel

 

A key insight quickly emerged:

The problem wasn’t the data itself.

The problem was the structure.

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Users rely heavily on the visual structure of the charts within NewYM when interpreting data.

 

When the exported spreadsheet didn’t follow that same structure, users had to mentally translate between two completely different formats.

 

This created unnecessary cognitive effort and slowed down their work.

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The Opportunity:

Design an export format that mirrors the structure and labeling of the NewYM interface so users can immediately understand the data.

The Solution

I partnered with developers to redesign how the exported chart data should be structured in Excel.

 

The solution was simple but powerful:

Mirror the Interface Layout in NewYM

 

Key Improvements:

  • Interface-Aligned Structure
    The exported spreadsheet now reflects the same layout and hierarchy as the NewYM chart.
     

  • Clear Data Labels
    Labels now match those used within the product interface, reducing confusion.
     

  • Logical Organization
    Rows and columns are structured in a way that makes the data easy to scan and interpret.
     

  • Immediate Usability
    Users can open the export and immediately find the information they need without reorganizing the spreadsheet.

 

This makes the transition from screen to spreadsheet intuitive.

 

Users no longer need to interpret or hunt for data.

The Before & After

Note: Due to a non-disclosure agreement, specific product screens and internal data from NewYM cannot be shown. The visuals in this case study have been simplified or recreated to illustrate the design process while protecting proprietary information.

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Example of Before:​

Column A: Metric 1
Column B: Metric 7
Column C: Metric 3
Column D: Metric 2
Column E: Metric 9

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Example of After:

Booking Curve Data

Date        | Actual Bookings | Forecast | Variance
---------------------------------------------------
Jan 1       | 120                           | 115            | +5
Jan 2       | 130                           | 128            | +2
Jan 3       | 118                           | 120            | -2

The Impact

The redesign significantly improved efficiency for analysts who rely on exports for daily analysis.

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Results:

  • 80% reduction in time spent locating and validating exported data

  • Faster analysis workflows

  • Reduced frustration for users

  • Improved confidence in exported data

  • Easier sharing with stakeholders and leadership

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What was previously a manual cleanup step became a usable export instantly.

Takeaways

  • Consistency reduces cognitive load
    When data appears in a familiar structure, users can interpret it much faster.

 

  • Small workflow improvements can have big impact
    Even though this was a relatively contained feature, it dramatically improved a daily workflow.

 

  • Understanding real user behavior is critical
    The right solution came from observing how analysts actually worked with exported data.

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