Dashboard / Candidate
Aryan Kulkarni
Placed in Product Manager by best fit (no role stated; scored higher on this rubric) · 21_aryan_kulkarni.pdf
Private: squad_5@pg27.mesaschool.co · no phone found
Applied-role score
39/100#20 of 34 PM applicants
PM score
39/100SPM score
33/100Current status
AnalysedBelow shortlist (AI suggestion)
Your decision
1
Why they fit
- Problem -> Change -> Result 25%
The candidate provides clear examples of identifying problems, taking specific actions, and measuring the resulting outcomes. For instance, addressing return to origin (RTO) friction with prepaid nudges, OTP verification, and address validation resulted in an 18% reduction in RTOs, and introducing a loyalty program boosted repeat purchases by 35%.
2
Where they fall short
- Builds Repeatable Ways of Working −16 pts
There is indirect evidence of creating tools or integrations (such as a unified analytics dashboard), but there is no evidence that this or any other process, template, or operating framework was adopted or reused as a repeatable way of working by others.
- Carries Ambiguous Problems Through to Closure −16 pts
The CV lists cross-functional partnership and coordination of launches and vendor operations, but does not present a specific example of navigating an ambiguous, messy issue or escalation across functions through to post-resolution closure.
- Evidence-Led Decisions −12 pts
The CV mentions prioritizing the roadmap based on revenue impact and user data, as well as conducting A/B testing and localizing flows based on region-specific behavior. However, it lacks specific narrative details showing decisions actually being changed, stopped, or pivoted due to specific evidence.
| Criterion | Weight | Score | Weighted | AI reasoning | Evidence from CV |
|---|---|---|---|---|---|
| Problem -> Change -> Result | 25% | 4/5 | 20.0/25 | The candidate provides clear examples of identifying problems, taking specific actions, and measuring the resulting outcomes. For instance, addressing return to origin (RTO) friction with prepaid nudges, OTP verification, and address validation resulted in an 18% reduction in RTOs, and introducing a loyalty program boosted repeat purchases by 35%. |
|
| Evidence-Led Decisions | 20% | 2/5 | 8.0/20 | The CV mentions prioritizing the roadmap based on revenue impact and user data, as well as conducting A/B testing and localizing flows based on region-specific behavior. However, it lacks specific narrative details showing decisions actually being changed, stopped, or pivoted due to specific evidence. |
|
| Builds Repeatable Ways of Working | 20% | 1/5 | 4.0/20 | There is indirect evidence of creating tools or integrations (such as a unified analytics dashboard), but there is no evidence that this or any other process, template, or operating framework was adopted or reused as a repeatable way of working by others. |
|
| Carries Ambiguous Problems Through to Closure | 20% | 1/5 | 4.0/20 | The CV lists cross-functional partnership and coordination of launches and vendor operations, but does not present a specific example of navigating an ambiguous, messy issue or escalation across functions through to post-resolution closure. |
|
| Gets to the Source Before Designing the Fix | 15% | 1/5 | 3.0/15 | The candidate mentions a 'customer feedback loop' in their venture, but there is no specific evidence showing direct observation, user interviews, or firsthand discovery that specifically influenced or reshaped a product fix. |
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| Total | 100% | 39 | The candidate demonstrates solid execution in eCommerce and growth product management, showing strong evidence of problem-to-result delivery with measurable uplifts in conversion and retention. However, the CV provides minimal to no evidence regarding building repeatable ways of working for others, resolving ambiguous cross-functional issues, or conducting direct firsthand user research to shape product decisions. | ||
Scoring scale
- 0: No evidence in the CV
- 1: Indirect or participation-only evidence
- 2: Partial: some elements of the description, weak link to outcome
- 3: One clear example matching the description
- 4: Clear example with a visible result, candidate's own action linked to it
- 5: Repeated, strong examples fully matching the description, with results
Weighted contribution = score ÷ 5 × weight. Every quote is checked against the CV text; if none can be verified, the score is capped at 1.
4
Evidence
Verified CV quotes used (PM rubric)
- “Launched prepaid nudges, OTP verifications, and address validation flows, reducing RTOs by 18%.” · Problem -> Change -> Result
- “Designed and launched loyalty program within the app, boosting repeat purchases by 35%.” · Problem -> Change -> Result
- “Relaunched US storefront with new PDPs, driving a 22% uplift in conversion rates.” · Problem -> Change -> Result
- “Partnered with business, design, and engineering to prioritize roadmap based on revenue impact and user data.” · Evidence-Led Decisions
- “Localized content and checkout flows based on region-specific behavior and payment preferences.” · Evidence-Led Decisions
- “Implemented VWO-led A/B tests on home, cart, and PDP, improving conversion rates by up to 28%.” · Evidence-Led Decisions
- “Integrated Appsflyer, Firebase, and Shopify APIs to create a unified analytics dashboard for performance tracking.” · Builds Repeatable Ways of Working
- “Partnered with business, design, and engineering to prioritize roadmap based on revenue impact and user data.” · Carries Ambiguous Problems Through to Closure
- “Managed third-party tech/vendor coordination for product updates and CRM integrations.” · Carries Ambiguous Problems Through to Closure
- “Achieved 35% repeat rate and <7% return rate by focusing on quality and customer feedback loop.” · Gets to the Source Before Designing the Fix
Outcomes stated in the CV
- Scaled GNC India app from 0 to ₹3 Cr/month in revenue in 6 months
- Increased GNC mobile app revenue contribution to 35%
- Boosted repeat purchases by 35% via a newly designed and launched loyalty program in GNC app
- Improved conversion rates by up to 28% via VWO-led A/B testing on GNC
- Drove a 22% conversion rate uplift by relaunching the BetterAlt US storefront
- Improved BetterAlt global site speed by 40%
- Reduced RTOs by 18% via prepaid nudges, OTP verifications, and address validation flows
- Grew GlossUp to 1500+ paying customers in 3 months with a 35% repeat rate and <7% return rate
Anonymised CV (exactly what the AI saw)
SUMMARY CORE SKILLS Pune / Mumbai Product Manager – Growth & eCommerce Product Manager with 2.5+ years of experience building and scaling D2C and eCommerce products across mobile and web. Led the GNC India app from 0 to ₹3 Cr/month in 6 months, driving 20–35% conversion uplifts through A/B testing, UX optimization, and retention-led features. Strong execution across Shopify, mobile apps, analytics, and cross-functional teams, with hands-on experience launching products from scratch in both enterprise and startup environments. Product Strategy & Roadmapping eCommerce Platform Management (Shopify, VWO) Conversion Rate Optimization (CRO) Mobile App Development & Feature Ownership A/B Testing & Data-Driven Decision Making User Journey Optimization & Retention Strategy Cross-Functional Team Collaboration Analytics & Performance Tracking (GA4, Appsflyer, Firebase) Linkedin - PROFESSIONAL EXPERIENCE Guardian Group (GNC, BetterAlt, Bellavita, Bevzilla, Springwel) | Oct 2022 – Present Associate Product Manager - BetterAlt Jan 2025 – Present Owned product roadmap for BetterAlt’s multi-country Shopify stores (India, US, UK); improved global site speed by 40%. Localized content and checkout flows based on region-specific behavior and payment preferences. Relaunched US storefront with new PDPs, driving a 22% uplift in conversion rates. Partnered with business, design, and engineering to prioritize roadmap based on revenue impact and user data. Launched prepaid nudges, OTP verifications, and address validation flows, reducing RTOs by 18%. Associate Product Manager - GNC Oct 2023 – Jan 2025 Led development of GNC India mobile app from scratch; scaled from 0 to ₹3 Cr/month in revenue within 6 months. Increased app's revenue contribution to 35% by optimizing user journeys and integrating one-click checkout. Designed and launched loyalty program within the app, boosting repeat purchases by 35%. Implemented VWO-led A/B tests on home, cart, and PDP, improving conversion rates by up to 28%. Integrated Appsflyer, Firebase, and Shopify APIs to create a unified analytics dashboard for performance tracking.[CANDIDATE] [EMAIL REDACTED] +91 90492 1738490492 17384 ENTREPRENEURIAL VENTURESFounder, GlossUp – Press-On Nail Brand Oct 2024 – Jan 2025 | Pune Launched D2C press-on nail brand with 1500+ paying customers in 3 months. Built Shopify store, handled end-to-end product packaging, fulfillment, and influencer seeding. Achieved 35% repeat rate and <7% return rate by focusing on quality and customer feedback loop. Leveraged Instagram Reels and TikTok-style content to drive organic growth.Event Organizer – Ticketed College Events Feb 2023 – Apr 2023 | Gurgaon Generated ₹2L+ in revenue through BookMyShow ticketing and vendor sponsorships. Managed logistics, venue operations, and team of 10+ volunteers. Earlier Roles: Product Associate (Oct 2022 – Oct 2023) Supported product operations across Bellavita, Bevzilla, and Springwel. Coordinated launches of promotional campaigns and website refreshes in sync with marketing. Managed third-party tech/vendor coordination for product updates and CRM integrations.Product Management – Great Learning (2024) Conversion Rate Optimization – Udemy (2024) Digital Marketing – Google (2023) Fortinet Network Security - Level 1 (2023) CERTIFICATIONS EDUCATIONB.Sc Cyber Security 2020 – 2023 K. R. Mangalam University
Redacted: name ×4, email ×1
5
Interview brief
Briefs are written when you shortlist a candidate.
6
Email draft
An offer or rejection draft is prepared once you make a decision. Nothing is ever sent without your approval.
Audit trail (3)
- 9/29/2026, 11:36:12 AMsystemanalysis completed{"PM_score":39,"SPM_score":33}
- 9/29/2026, 11:36:12 AMsystemrole assigned best fit{"role":"PM","PM_score":39,"SPM_score":33}
- 9/29/2026, 11:29:32 AMsystemcv ingested{"file":"21_aryan_kulkarni.pdf","role":"AUTO","redactions":{"name":4,"email":1},"name_detected":true}