I design and build tools that make complex work feel simple.
UX Engineer ● Master in HCI ● 10+ years across Amazon, Microsoft and VMware
4Recent products, needfinding to production
0%Reduction in OPEX costs in 1Y after Metrics Hub
0%CSAT in first six months after launch of Inquiry Hub
0UMUX Score in first two month of Newsletter App
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Q3 Performance Review
The third quarter showed significant improvements across key metrics. Revenue exceeded targets by 12% while customer retention reached all-time highs.
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Executive Summary🔒
Customer reported intermittent service degradation affecting order processing in the EU-West region. Impact assessment indicates approximately 340 orders experienced delays exceeding the published SLA during a 72-hour window.
The customer was contacted within 4 hours of the initial report. An incident bridge was established and root cause investigation initiated immediately.
Customer Journey🔒
March 2, 09:14 UTC — First customer report via support channel. March 2, 13:40 — Case escalated to dedicated team. March 3, 08:00 — Customer outreach call completed. March 5 — Interim remediation deployed.
The 72-hour window needs cross-referencing with the monitoring timeline. I see a gap between detection and escalation.
AKA. Kumar4h ago
on Root Causes
RC-2 should reference the canary coverage gaps we identified in last quarter's review.
Resolved
JPJ. ParkJust now
on Executive Summary
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Ordering:DefaultPerformanceCustom
1Delivery Speed
2Customer Satisfaction
3Revenue Growth
4Order Defect Rate
5Seller Experience
6Inventory Health
Delivery Speed
Measures the percentage of packages delivered within the promised delivery window across all geographies and shipping tiers.
Why is this metric important?
Delivery speed directly impacts customer satisfaction, repeat purchase rates, and Prime membership retention. A 1pp improvement in on-time delivery correlates with a 0.3pp increase in 90-day repurchase rate.
Geo
Speed
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
US
Standard
94.2
94.5
94.8
95.1
95.3
95.0
95.4
95.7
95.9
96.1
96.3
96.5
Express
97.1
97.3
97.5
97.4
97.6
97.8
97.9
98.0
98.1
98.2
98.3
98.4
Same-Day
98.5
98.6
98.4
98.7
98.8
98.9
99.0
99.1
99.0
99.2
99.1
99.3
EU
Standard
91.8
92.1
92.4
92.6
92.9
93.1
93.3
93.5
93.7
93.9
94.0
94.2
Express
95.4
95.7
95.9
96.1
96.3
96.5
96.7
96.8
97.0
97.1
97.2
97.4
Same-Day
96.8
97.0
97.1
97.3
97.4
97.5
97.7
97.8
97.9
98.0
98.1
98.2
IN
Standard
88.1
88.5
88.9
89.2
89.6
89.8
90.1
90.4
90.7
91.0
91.3
91.5
Express
93.2
93.5
93.8
94.0
94.2
94.4
94.6
94.8
95.0
95.2
95.3
95.5
Same-Day
95.0
95.2
95.4
95.5
95.7
95.9
96.0
96.1
96.3
96.4
96.5
96.7
BR
Standard
85.3
85.7
86.0
86.4
86.8
87.1
87.4
87.7
88.0
88.3
88.5
88.8
Express
91.0
91.3
91.6
91.9
92.1
92.4
92.6
92.8
93.0
93.2
93.4
93.6
Same-Day
93.5
93.7
93.9
94.1
94.3
94.5
94.7
94.8
95.0
95.1
95.3
95.4
Describe the narrative performance for this month.
On-time delivery improved across all geos in 2024. US Standard rose from 94.2% to 96.5%, while Same-Day maintained 99%+ throughout. IN and BR showed strongest YoY gains, with BR Standard improving 3.5pp from 85.3% to 88.8%.
What are the planned actions based on this performance?
Expand same-day delivery in IN from 12 to 28 cities by Q2. Invest in last-mile partnerships in BR. Pilot predictive routing in EU to reduce Express miss rate below 3%.
Customer Satisfaction
Net Promoter Score (NPS) and Customer Satisfaction (CSAT) across product categories and customer segments.
Why is this metric important?
NPS is the strongest leading indicator of long-term customer lifetime value and organic growth through word-of-mouth.
Segment
Measure
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Prime
NPS
72
73
73
74
74
75
75
76
76
77
77
78
CSAT
4.5
4.5
4.5
4.6
4.6
4.6
4.6
4.7
4.7
4.7
4.7
4.8
Non-Prime
NPS
58
58
59
59
60
60
61
61
62
62
63
63
CSAT
4.1
4.1
4.1
4.2
4.2
4.2
4.2
4.3
4.3
4.3
4.3
4.4
Describe the narrative performance for this month.
Prime NPS improved steadily from 72 to 78 (+6pts). Non-Prime grew 5pts to 63. CSAT reached 4.8 for Prime members in December, highest on record.
Revenue Growth
Year-over-year revenue growth by business line and geography, normalized for currency fluctuations.
Why is this metric important?
Revenue growth at scale indicates market share expansion and the effectiveness of new product launches and geographic investments.
Geo
Line
Q1
Q2
Q3
Q4
YoY
US
1P Retail
+8.2%
+9.1%
+10.3%
+11.7%
+9.8%
3P Marketplace
+14.5%
+15.2%
+16.0%
+17.3%
+15.8%
Intl
1P Retail
+5.1%
+6.3%
+7.8%
+8.4%
+6.9%
3P Marketplace
+18.2%
+19.7%
+21.1%
+22.5%
+20.4%
Describe the narrative performance for this month.
Intl 3P Marketplace led growth at +22.5% in Q4, accelerating each quarter. US 1P Retail improved from +8.2% to +11.7%, driven by grocery and pharmacy expansion.
Comments
VPV. Patel2h ago
Can we add a Q3 vs Q4 delta column to the delivery speed table?
MKM. Kim1h ago
BR narrative approved. Numbers look solid.
JLJ. Liu3h ago
Non-Prime NPS still lags. Should we flag this for the retention team?
SRS. Rao45m ago
Intl 3P growth is impressive. Let’s make sure we call out the FX normalization methodology.
VPV. Patel30m ago
Agreed. Also add a footnote on the grocery/pharmacy contribution to US 1P.
A zero-dependency Web Audio library that adds subtle, synthesized sound feedback to native HTML form elements. No audio files — just real-time synthesis. Five sound profiles, DTMF phone tones, pitch-mapped sliders, per-element opt-out.
A CSS 3D boxel engine that composes interactive scenes entirely from DOM divs. Textures, boolean operations, edge fusion that culls 90% of internal faces, per-face styling, and orbit controls. Zero dependencies.
Prioritized customer enquiries were too complex to spec on paper. I built a strategic prototype that validated the interaction model and convinced stakeholders to fund the build.
Email rendering is broken by design. Outlook uses Word's engine, Gmail strips your styles. I built an authoring platform on MJML that guarantees consistent rendering.
Monthly metric decks for the C-suite and Board required dozens of people and weeks of coordination. When someone left, their metrics vanished. I designed the platform that replaced it.
Researchers can collect endlessly, but turning that pile into an original idea is where they get stuck. An 8-month capstone with Prof. Niki Kittur at CMU.
Most AI tools bolt a chatbot onto the side of your workflow and call it done.
I'm interested in the alternate question: how do you weave AI into the actual surface where people work — their document, their dashboard, their review process — so it helps without interrupting? That's the design problem I've spent the last three years on at Amazon, building four products used by C-suite, Board, and VP-level leadership.
Before Amazon, I studied HCI at Carnegie Mellon with Niki Kittur, researching how people synthesize scattered information into new knowledge. That research directly shaped how I think about AI-assisted authoring today. Before that, I shipped enterprise platforms at Microsoft and VMware for four years — timekeeping, cloud migration, accessibility consulting, and infrastructure modernization.
What stays constant: I find the real problem through observation and data — not just stated briefs — design multiple solutions, discard most of them, and ship the one that fits the resourcing, scope, and timeline while solving the actual pain point. Research through production. That's the job.
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Open to design engineering, AI product, and research collaborations.
