Pavan's Blog

Category: product

  • Leveraging AI/ML to Enhance User Activation and Engagements.

    Leveraging AI/ML to Enhance User Activation and Engagements.

    Innovative strategies are crucial for maintaining a competitive edge, particularly in user engagement and activation. This post outlines our integration of Artificial Intelligence (AI) and Machine Learning (ML) to significantly impact user experience and business outcomes for Mashkor. Our primary focus was on optimizing the experience for both first-time and existing users.

    Need

    Our journey was driven by a clear goal: to elevate activation rates for first-time users while simultaneously enhancing engagement for our existing users of the application. The challenge extended beyond introducing users to our platform; we aimed to ensure they discovered immediate value, encouraging ongoing engagement and improve a deeper connection with our services. To meet these objectives, we turned to the capabilities of ML and AI, focussing to create a seamless, efficient, and valuable user journey from their initial interaction.

    Initial Solutions

    Our strategy was executed in phases, acknowledging the intricate nature of user behavior and the diverse spectrum of their requirements.

    Phase One: Personalized Recommendations for First-Time and Existing Users

    The first phase of our initiative involved harnessing ML to tailor recommendations for both first-time and existing users, using a variety of input parameters to fine-tune these suggestions.

    For new users, we focused on their search terms and category interactions as a primary indicator of their immediate needs and interests. This allowed us to present a curated list of the most relevant stores, aiming to improve CTRs and, consequently, conversion rates. Google Vertex AI’s recommendation model was our tool of choice for this task, selected for its algorithms, compatibility with our tech stack and ability to scale efficiently.

    In addition to addressing the needs of new users, we also refined our approach for existing users by analyzing their past behaviors. This analysis and inputs included various parameters that enriched the personalization of their recommendations. Given their history with our platform, we anticipated that the model would yield faster and more accurate results for these users, enhancing their overall experience and satisfaction.

    We just initially decided to focus on batch recommendations and later evolve to real time recommendations.

    Phase Two: Refining the Model

    The second phase focused on refining our model to better achieve our goals of increasing activation for new users and bolstering engagement for returning ones. This stage involved iterative adjustments and enhancements, driven by continuous feedback and performance analysis. We also employed Generative AI in certain scenarios to create compelling copy, further personalizing the user experience.

    Challenges

    Adopting to ML came with its set of challenges. Initially, the limited amount of available data constrained our models’ predictive accuracy. Moreover, the success of these AI-driven solutions heavily depends on the quality of data, emphasizing the importance of sophisticated data collection and management strategies.

    Benefits

    Over time, the benefits of our AI integration became increasingly evident. For first-time users, the AI-powered recommendations facilitated a smoother discovery process, significantly improving their initial engagement with our platform. Existing users enjoyed enhanced personalization through the “Recommended for You” feature, which evolved to more accurately reflect their preferences and behavior patterns. These experiments helped us understand the impact of AI and ML on creating a user-centric, personalized experience. Integrating into our product was challenging, fun and rewarding.

  • Optimizing the Activation loop iteratively to improve the conversion for Mashkor App.

    Optimizing the Activation loop iteratively to improve the conversion for Mashkor App.

    Introduction

    • Wanted to share the story of working with Mashkor for the initial 8 months working here about how we worked to improve the activation loop, using two frameworks.
    • First, focussing with a user centric approach: Engage with users, understand pain points, iteratively develop the product, and refine based on feedback. And secondly implement the, Amazon’s working backwards culture and processes to execute.

    Outcomes and Stories of Specific User Groups –

    • House wives of Kuwait.
      • These users have shown tremendous appreciation for our services, finding immense value in the convenience we offer for their daily outdoor errands and shopping needs. Their feedback highlights how our app has become an integral part of their household management, enabling them to save time and focus on their families.
    • Busy office Workers.
      • This group values our app for the support it provides in managing their errands amidst hectic work schedules. They appreciate the efficiency and reliability of our services, allowing them to delegate tasks seamlessly and ensure their personal outdoor errands are handled promptly, even during their busy office hours and beyond.

    Goal: Improve conversion rate.

    • User Segmentation
      • Organic New Users: Individuals who download the app through word-of-mouth.
    • Pain Points Validation
      • Key findings from qualitative and quantitative analyses with user research and product discovery phase revealed four major areas for improvement:
        • Service discoverability was low; core services were not immediately apparent to users.
        • Discovering and storing locations was cumbersome for users.
        • The cart and checkout process was overly complex, involving additional steps that deterred completion.
    • Iterative Solution Phases
      • Phase 1: Enhancing User Onboarding and Service Discovery
        • Objective: Make service discovery straightforward from the onboarding stage.
        • Strategies Implemented:
          • Revamped onboarding experience to prominently highlight services on the home page.
          • Introduced WhatsApp OTP as an alternative to SMS for verification.
          • Conducted A/B testing to optimize service discovery placements and design.
        • Success Metrics:
          • Increased adoption of WhatsApp OTP.
          • Higher click-through rates (CTRs) for service discovery.
          • Reduced time to conversion.
      • Phase 2: Streamlining Location Discovery and Storage
        • Objective: Simplify the process for users to find and store locations.
        • Strategies Implemented:
          • Integrated Google Maps for a more intuitive location search experience.
          • Simplified the selection process for Google-identified locations, requiring minimal additional information.
        • Success Metrics:
          • 80% success rate in selecting top location searches.
          • 90% efficiency in storing addresses.
          • Reduced time needed to store addresses.
      • Phase 3: Simplifying Cart Addition and Checkout Process
        • Objective: Make adding items to the cart and checking out smoother and more intuitive.
        • Strategies Implemented:
          • Overhauled the cart UX to consolidate steps and improve guidance.
          • Introduced Apple Pay to cater to user preferences and regional adoption.
        • Success Metrics:
          • 40% reduction in time to checkout.

    Conclusive Insights

    • Following these three phases and further optimizations led to 40% incremental improvement for conversion rate of.
    • The systematic framework emphasized understanding goals, breaking down problems, prioritizing impactful solutions, and iterating based on feedback.
    • This approach not only achieved the immediate objectives but also set a foundation for ongoing improvement and user satisfaction.

  • Unlocking Success with MVPs: Enhancing Customer Experience

    Wanted to share some learnings about MVP’s. In our fast-paced world of product and growth, especially for domain in our which is highly operation-driven business, the mantra was clear to test out ideas soon –
    MVPs (Minimum Viable Products) should make customers’ lives faster, easier, and less expensive


    Here’s a breakdown of how MVPs achieve these goals and why it matters, always tested using this framework:


    Faster:

    – Time-Saving Solutions: MVPs address specific pain points or tasks, enabling customers to accomplish their goals more efficiently.

    – Reduced Learning Curve: By prioritizing simplicity and ease of use, MVPs empower customers to quickly grasp and utilize the product’s core features.

    – Immediate Value: MVPs deliver immediate benefits, allowing customers to see results sooner rather than waiting for a fully developed product.


    Easier:

    – Simplified Solutions: MVPs eliminate unnecessary complexity, providing customers with a seamless and user-friendly experience.

    – Focused Features: By concentrating on essential functionality, MVPs alleviate decision fatigue and enable customers to focus on what truly matters.

    – Problem-Specific: MVPs target specific pain points, offering tailored solutions that address customers’ unique needs.


    Less Expensive:

    – Affordability: With lower price points, MVPs make valuable solutions accessible to a broader audience, driving adoption and market penetration.

    – Reduced Resource Costs: By streamlining features, MVPs require fewer resources from customers, minimizing time, effort, and financial investment.

    – Value for Investment: Customers perceive MVPs as cost-effective solutions that deliver tangible value without unnecessary frills, maximizing ROI.

    In conclusion, prioritizing customer-centric MVP development is key to unlocking success in product innovation. By making customers’ lives faster, easier, and less expensive, MVPs not only meet user expectations but also drive sustainable growth and market differentiation.

    We encourage our folks to test your MVPs quickly by leveraging user feedback loops and iteration cycles. Incorporate insights from real-world usage to refine and enhance your product rapidly.

    Feel free to share any insights, or any comments if any MVP’s got your surprised breakthroughs! 😉

    hashtag#Product hashtag#CustomerExperience hashtag#MVPStrategy

  • 🌱The Evolution to Product – Growth function.

    🌱The Evolution to Product – Growth function.


    Having received numerous inquiries from my network about the nuances between Growth Product leaders and traditional Product leaders, I thought to shed light on this topic from all the work I have been doing and how its differentiated from my previous approach.
    The role of Growth Product function is at the crossroads of product development and business expansion. Here’s a glimpse into how this evolution has unfolded:

    → Beyond Product Development:
    While traditional Product Managers function focus on building and enhancing products, Growth Product Managers extend their scope to driving user acquisition, retention, and revenue growth. It’s about the entire product lifecycle, from ideation to sustained success.

    → Data-Driven Growth Strategies:
    Growth Product managers are proficient in leveraging data to identify growth opportunities. Analytics-driven insights fuel strategic decision-making, enabling them to optimize user journeys and maximize conversion rates.

    → Experimentation and Iteration:
    Embracing a culture of experimentation, Growth Product Managers constantly iterate on strategies. A/B testing, user feedback loops, and rapid experimentation are key tools in their arsenal to uncover what truly drives growth.

    → User-Centric Growth:
    Just as with Product Managers, understanding the user remains paramount. However, for Growth Product Managers, it goes beyond delivering a great product – it’s about crafting experiences that drive user engagement and conversion.

    → Collaboration with Marketing & Sales:
    Growth Product leaders work closely with marketing & sales counterparts to align product launches, campaigns, and user acquisition strategies, ensuring a cohesive approach.

    → Optimizing User Acquisition and retention channels:
    Identifying and optimizing the most effective user acquisition and retention channels is a key responsibility. Growth Product leaders analyze performance metrics to allocate resources where they deliver the highest impact.

    → Monetization Strategies:
    Revenue growth is a central focus. Growth Product Managers play a pivotal role in devising and implementing monetization strategies, ensuring sustainable business growth while delivering value to users.

    → Metrics-Driven Accountability:
    Growth Product Managers are held accountable for specific growth metrics. They establish clear KPIs, track performance rigorously, and pivot strategies based on real-time insights to achieve and exceed growth targets.

    By seamlessly blending product expertise with a growth mindset this function can navigate the intersection of innovation and business expansion.
    Feel free to share your comments about, the evolutions you have from your roles as compared to your previous way of working. Sharing more resources in the first comments.

    hashtag#productgrowth hashtag#productstrategy hashtag#growthstrategy hashtag#businessinnovation