Apoorva Narayanappa

Utilized deep-translator and Ollama to categorize approximately 60k English and Arabic user reviews.
Uncovered user experience insights that unlocked strategic menu engineering increasing average rating by 7%.
Identified a pain point in the user journey through product path flow analysis.
Collaborated with the product team to reduce average user SignUp/SignIn time by 53 seconds and sign-up drop off by 14%.
Partnered in a painted door test, resulting in a feature release that contributed to an increase in customer retention by 11%.
Conducted A/B experimentation with different pricing models and increased A2C by 6% and new user revenue by 2.5%.
Carried out factor analysis of declining AOV, quantifying the impact of product mix, price changes, and cannibalization.
Developed pricing simulations and recommendations that led to a 14% increase in AOV.
Initiated and built comprehensive views of variable costs by modeling KPIs such as FCR, ALC, Discounts, and Marketing Spends.
Increased overall Contribution Margin by 9% through bottom-line improvement strategies.
Streamlined adverts performance from Meta, Google, Snapchat, and TikTok.
Developed a consolidated performance dashboard including KPIs such as click rate, thumbs-stop rate, and video completion rate.
Empowered the content marketing team with adverts performance insights facilitating optimized strategies for brand awareness and customer acquisition.
Established scheduled data accuracy tests to uplift data governance and enable proactive data fixes.

Utilized deep-translator and Ollama to categorize ~60k (English + Arabic) user reviews, Uncovered user experience insights, Identified pain point in the user journey, Conducted A/B experimentation with pricing models, Carried out factor analysis of declining AOV, Initiated and built comprehensive views of variable costs, Streamlined adverts performance from multiple platforms, Established scheduled data accuracy tests

Led a data simulation to assess the feasibility of batching deliveries between LOBs.
Identified 27% potential for order batching, resulting in a reduction of First Mile cost by 5rs per order.
Resolved one of the order loss bottlenecks by conducting an end-to-end RCA analysis.
Uncovered Delivery Executive behavioral insights and implemented solutions that reduced O2A time by 26 seconds and actionable order loss by 1.2pp.
Performed stratified NPS analysis and correlated NPS scores with CX metrics such as complaints, resolution times, product history, and preferences.
Uncovered actionable insights, driving a approximately 3pp increase in quarterly NPS within a specific customer segment.
Developed a centralized customer 360 journey data source that enabled ease of advanced customer analysis.
Equipped CX agents with personalized insights to aid query resolution.
Supported churn prediction models.
Implemented key operational processes within the team such as creation and maintaining QC checklists.
Established comprehensive onboarding and offboarding procedures for effective project handovers.

Led a data simulation to assess the feasibility of batching deliveries between LOBs, Resolved order loss bottlenecks, Performed stratified NPS analysis, Developed a centralized customer 360 journey data source, Implemented key operational processes within the team

Implemented a robust tracking system to monitor builder and restorer performance on quality, cost, and timeliness for home claims management.
Developed an algorithm to automate estimated targets for vendors based on claim attributes.
Streamlined vendor performance and claim management, leading to a 12% increase in CSAT score.
Led a team of analysts and engineers to develop and implement solutions to optimize vendor contract renewals.
Analyzed each work item breakdown of SOW invoices submitted by vendors, uncovering overcharges and rate trends.
Uncovered a potential cost-saving of approximately 3 million USD through strategic vendor compliance comparison initiative.
Restructured data lineages and architectures.
Optimized DAG execution and reduced total runtime by 35 minutes, resulting in Snowflake cost savings.