sahana srivatsan

linkedin

cv

01 / overview

02 / priorities

03 / process

UX CASE STUDY — 01

email report modernization:
re-establishing trust between users and their data

email report modernization:
re-establishing trust between users and their data

ROLE

Lead designer

DURATION

August 2025- ongoing

DISCIPLINES

Data visualization

Information architecture

AI

Quantitative user research

40% +

of weekly active customers use this report

55.5%

of user feedback indicated a need to be able to benchmark their campaigns

+10-15%

targeted lift in report weekly active usage

role

I led an end-to-end redesign grounded in voice-of-customer data building out features testing whether closing those gaps with explainable AI insights would build the confidence marketers needed to trust their own numbers.

01 - overview

problem

More than 40% of weekly active customers used the email report, but data was spread across seven tabs different tabs. Marketers had to piece together metrics to understand whether a campaign performed well, while inconsistent experiences across tabs made the data hard to trust. We used a survey to address understand exactly what customers wanted the most: 55.5% of the feedback asked for better metrics, insights, or comparisons.

FROM
FROM

Data is dispersed amongst seven siloed tabs, some which had inconsistent data

TO
TO

Four clearer destinations bring related data together

FROM
FROM

Data is dispersed amongst seven siloed tabs, some which had inconsistent data

TO
TO

Four clearer destinations bring related data together

FROM
FROM

Data is dispersed amongst seven siloed tabs, some which had inconsistent data

TO
TO

Four clearer destinations bring related data together

02 — research priorities

Customer feedback gave us a clear priority order: actionable metrics, insights, and comparative reporting were the features requested most.

Metrics, insights & comparisons

55.5%

Inbox placement (“what’s actually landing”)

14.0%

Data accuracy & consistency

11.6%

Engagement depth / non-opener re-engagement

8.5%

Sharing, export & reuse

4.3%

Deliverability visibility

3.7%

Platform reliability & reporting functionality

2.4%

VALIDATED WITH 500+ CUSTOMERS

A broader survey reinforced the same hierarchy, surfacing device-level reporting, segment and location drill downs, explainable metrics, time-based link analytics, and reliable sharing, export, and print alongside comparative benchmarking.

03 — process

hypothesis

I hypothesized that a report organized around customers’ most common questions would help marketers understand performance without having to export their data to a spreadsheet.

This approach translated to:

• Lead with comparisons: show performance against past sends, top campaigns, and benchmarks.


• Flatten the report: bring the most useful answers together instead of separating them across tabs.


• Show the evidence behind AI insights: pair a summary with the numbers a customer can inspect.

• Lead with comparisons: show performance against past sends, top campaigns, and benchmarks.

• Flatten the report: bring the most useful answers together instead of separating them across tab & getting rid of unmodernized data


• Show the evidence behind AI insights: pair a summary with the numbers customer could trust themselves

04 — design

01

Comparisons & benchmarking

Show performance against sends, top campaigns, and benchmarks

02

Flatten the report

Bring the most useful information together instead of siloing it against seven tabs and get rid of unmodernized data

From

To

03

Show the evidence behind the AI insights

Pair the summary with numbers and insights the customer can contextualize

04

Report redesign

05 — validation

early customer feedback

early customer feedback

Early testing on the redesign surfaced four consistent themes:


  • Leading with comparisons landed well — customers called it a fast "pulse check" against their own past performance and industry averages

  • The flatter IA reduced friction — testers no longer had to hunt across "seven different things to click on"

  • AI summaries need receipts — customers were skeptical of insights without visible data behind them

  • Data ecosystem over data silos — heat maps and link-performance breakdowns were specifically valued

Early testing on the redesign surfaced four consistent themes:


• Leading with comparisons landed well: customers described it as a fast “pulse check” against their own past performance, their best campaigns, and industry averages.


• The flatter IA reduced friction: users said they no longer needed to hunt across “seven different things to click on” and the new layout let them see everything relevant to a campaign in one place.


• AI summaries need receipts customers were explicitly skeptical of qualitative AI insights without the numbers behind them which made us think more critically of how to substantiate our AI insights with real data. Even then, customers would ask us where did AI come up with certain numbers.


• Data ecosystem over data silos heat maps and link-performance breakdowns were specifically called out as valuable for understanding engagement, validating the shift away from siloed tab-by-tab views

05 — outcome

Shipping in phases. targeting a +10–15% increase in Email/SMS/A-B report WAU, and a 15% increase in post-report actions within 48 hours of viewing a report.

Shipping in phases. Targeting a +10–15% increase in Email/SMS/A-B report weekly active use, and a 15% increase in post-report actions within 48 hours of viewing a report.

next project: custom report builder

have a question about this project, or similar reporting problems on your plate?

have a question about this project, or similar reporting problems on your plate?

let's chat

let's chat

2026 sahana srivatsan

brooklyn, nyc

8:03:31 PM

brooklyn, nyc

8:03:31 PM