Ayush Kumar

Ayush Kumar

Toronto, ON, Canada
Member since July 12, 2019
Ayush is a growth product manager helping companies create user-focused experiences that solve customer needs to deliver business impact. A "no excuse" guy, he's directly owned orders and revenue metrics and brings a mix of human psychology, data analytics, and business sense into his work. Ayush has contributed an incremental $4.6 million (9.2% of top-line) via projects across the business lifecycle: acquisition, engagement, and monetization.
Ayush is now available for hire
Project Highlights
  • Agile Product Management
  • Business Requirements
  • Product Growth
  • Product Owner
  • Product Roadmaps
  • Requirements & Specifications
  • User Story Mapping
  • Wireframing
  • Associate Director — Product Management
    2019 - PRESENT
    • Ideated on how technology can be leveraged to scale already existing products to drive social impacts being delivered.
    • Formulated a scalable product strategy along with a cross-functional team of sales, brand partnerships, product marketing, and business.
    • Brainstormed solutions for how might we help consumers and companies do good and generate revenue at the same time, at scale.
  • Senior Product Manager
    2015 - 2019
    People Interactive Pvt. Ltd.
    • Solved a top user problem in matchmaking where users received no responses from matches—this resulted in an 81% lift in responses.
    • Boosted user retention by 3.5% by building a chatbot on WhatsApp which increased engagement and retention.
    • Improved order conversion by 12% by redesigning the payment flow on web and mobile apps (iOS and Android).
    • Developed a machine-learning-based discounting strategy model thereby increasing the order-and-revenue market share by 13% and 8%.
    • Strengthened the acquisition funnel (visit to profile ratio) by 4.6% via the removal of friction points during user registration.
    • Implemented a self-learning AI-based predictive dialer and achieved 92% lift in telesales team’s productivity (600 strong).
    • Oversaw a product segment worth $50 million and contributed an incremental $4.6 million (9.2% of top-line) through projects across the business lifecycle: acquisition, engagement, and monetization.
    • Handled project management to deliver sprint tasks and ship products/features within the agreed upon time frame.
    • Worked closely with the design and user experience team, to create low-fidelity wireframes, and conduct user research and usability testing.
  • Testing and Development Engineer
    2011 - 2013
    TVS Motor Company
    • Helped to launch new two-wheelers (Phoenix, Jupiter) by researching and developing the chassis, frame, tires, and other parts.
    • Improved the product quality and included best product features by bench-marking competitor products.
    • Developed processes by researching on new testing methods to gauge vehicle-handling performance.
Project History
  • Increased Mutual Matches | Driving Online Dating User Joy
    Generated an 81% increase in mutual matches via design thinking, ideating and shipping an MVP, and measuring impact on KPIs

    Male users didn’t receive responses from their sent invitations so they didn’t experience the joy of dating which led to drop-offs. This reflected in key user metrics: low male retention, low order conversion, and low customer satisfaction (CSAT) scores.

    We followed a design-thinking process and conducted in-depth qualitative user interviews. This unveiled an interesting finding: female users were serious, thoughtful, and deliberated a lot before tapping the "accept" button. Our question was how could we "casualize" their response behavior?

    "Casualizing" took us to the dating space where a user can say yes (swipe right) and no (swipe left) to a profile. We envisioned an MVP, to be done only on the Android app (the maximum user engagement platform). We planned to use the existing APIs (using service-oriented architecture, SOA) and integrated them on a new UI with a Tinder-like swipe functionality (implemented via an existing component from the Android native library). I then sent it production within two sprints (ten working days) and achieved ground-breaking success.

    • Saw an 81% lift in responses.
    • Increased order conversion by 5.3%.
    • Jumped 4.8% in CSAT score.

  • Machine Learning-based Discounting Algorithm
    Increased revenue realization (top line) by 1.5% using differential discounting based on demography and activity parameters.

    Conducted data & business analysis to arrive at the insight - users usually have varied reasons for using the platform. Hence, rather than offering flat rates/discounts, we could base discounts on user intent, i.e. a more serious user gets a lower discount and vice versa.

    We needed to figure out the demographics and activity parameters that defined intent. For instance - an older female, living away from her home town who was also logging-in frequently would have higher intent (in the Indian context).

    We created a machine learning algorithm along with the data science team considering numerous such parameters, which was then integrated with the existing discounting platform (keeping all existing logics uninterrupted). Finally, we tested it with a small cohort of users, which reduced and increased discounts for users based on the algorithm. We only tested it on new users, because existing ones already have a preconceived notion towards a price point, and this could bias our results.

    Saw a 1.3% lift in revenue (a highly significant impact, which is generally achieved by multiple projects combined).

  • Artificially Intelligent (AI) Predictive Dialer for the Telesales Team
    Created a predictive dialer to automate manual, redundant, and monotonous tasks—causing a 92% increase in team productivity.

    We were only reaching a 35% connectivity with consumers through telecalls. This was caused because of the disposal of nonconnected calls and scheduling them for later.

    We implemented an AI predictive dialer that will direct only connected calls to the team. Working with the data science and engineering team, I also created a requirements document along with all the use cases. We then developed an algorithm that learned based on various user demographics and activity parameters.

    Control Metrics:
    • Ensure an agent is free before the call to ensure a good customer experience.
    • A customer shouldn’t receive more than "x" number of calls in a day and should be called within the official time limits unless otherwise specified.
    • Dialer will learn the answering patterns of users based on their demography and activity.
    Other Work:
    • Built reports and dashboards so that leads could monitor productivity and efficiency.
    • Launched it as an A/B test with a few advisors and compared them against similar performing advisors in the other set.

    • Increased telesales team productivity by 92%.
    • Reduced the sales team size by half and added skills for cross-department usefulness.

  • Optimization of Payment Funnel
    Increased the activation ratio by 3.7% via a new mode of payment; also led vendor identification and API integration.

    The internet banking payment mode had a lower activation ratio. The primary reason was the bank’s site's UX. The bank login page loaded in a web view on mobile devices, rather than having a mobile-friendly UI. This reflected in key user metrics: low activation ratio and order conversion.

    We studied user behavior focusing on why users used net banking rather than credit/debit cards. We researched best practices followed for net banking by other merchants.

    Net banking was primarily used by parents who perceived a security risk with credit card usage, and best practices indicated the use of a vendor which converts a bank’s login pages into mobile-friendly pages. This placed net banking in a lower rank compared to other better performing modes of payments. However, a small user segment was ready to use UPI (unified payments interface) as an alternative to net banking.

    I spearheaded the integration of a new mode of payment: UPI with minimal handshakes and an intuitive UX. I also led the integration of JUSPAY to make bank pages mobile-friendly and ensured database security.

    • Increased activation ratio by 9.2%.
    • Improved order conversion by 3.7%.

  • Master's degree in Marketing
    2013 - 2015
    Institute of Management Technology, Ghaziabad - Ghaziabad, India
  • Bachelor's degree in Metallurgical and Materials Engineering
    2007 - 2011
    National Institute of Technology Karnataka, Surathkal - Mangalore, India
  • Product Innovation for Product Managers
    JULY 2019 - PRESENT
  • Certified Scrum Master
    JULY 2019 - PRESENT
  • Growth Hacking Foundations
    APRIL 2019 - PRESENT

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