Product Analytics : Is it a skill or a career?

Product Analytics is one of the core areas of interest for PMs. So lets deep dive...

In my latest episode of Product Talk with Malthi, I sat with Saurabh Agarwal who is Ex-SVP of Marketing at Lenskart and now is the founder of DAiOM, and helps brands grow profitable Omni channel growth with Tech , Ai and Growth Marketing.

In this discussion we deep dived into the world of Product Analytics – How is it different from Marketing Analytics. We spoke about Omnichannel strategies and how it impacts customer journeys. Best part is we spoke about a lot of examples – do catch them in the episode. In the end, Saurabh also shares some key insights as PMs should build their brands. A key insight is how product analytics are a key feature in many products.

As a special gesture, Saurabh is also hosting a Master Class on Omnichannel Strategies. Do scroll down to sign up for this session. Here are key insights from the discussion.

Catch up the full episode here:

Here are the highlights of the discussion

The Evolution of Product Analytics: A Skill or a Career?

• Traditionally, product analytics was considered a specialized career requiring deep expertise in data analysis, metrics tracking, and user behavior modeling.

• However, with advancements in AI, cloud computing, and self-service analytics tools like Amplitude and Mixpanel, data analysis has become significantly more accessible.

• Many product managers now use analytics tools as part of their day-to-day work, making it a skill rather than a dedicated career.

• The shift is similar to how Excel proficiency was once a career differentiator but later became a fundamental skill expected in most corporate jobs.

🤖 AI’s Disruptive Role in Product Management and Development

AI is reshaping two key areas:

• Marketing Content Generation: AI is being used to automate text, images, and even video content, reducing manual effort in branding and advertising.

• Product Development: AI-driven tools can now assist with coding, UX design, and even full product prototyping, reducing development time.

• He shared an example of winning an AI hackathon by building a fully functional weather app in 10 minutes without prior coding knowledge.

• The challenge for product teams is to go beyond just using AI for small efficiency gains and rethink entire workflows.

• AI adoption requires balancing speed and cost-effectiveness, as AI models come with high operational expenses.

📈 Measuring Product Success: More Features ≠ Better Product

• Many product managers measure success based on feature releases, leading to a “feature factory” mindset where adding new features is prioritized over improving user experience.

• Apple’s iPhone, with fewer features than some competitors, is a prime example of a product that succeeds due to superior UX and customer loyalty.

• Startups and traditional businesses need to redefine their KPIs, focusing on usability, adoption, and engagement instead of just backlog completion.

🏥 Healthcare & Wearables: How Product Analytics is Transforming Industries

• Wearable devices like smartwatches and fitness rings generate vast amounts of health data, enabling companies to improve user experiences.

• Interestingly, research suggests that one of the most-used smartwatch features is changing watch faces, rather than health-tracking metrics like step counts or heart rate.

• This underscores the importance of understanding real user behavior, rather than assuming the features designed for a product are the ones that will be used most.

• Analytics allows product managers to refine offerings based on data, ensuring better personalization and user retention.

🛍️ Omni-Channel Retail: CaratLane’s Success Story

• Omni-channel retail ensures a seamless shopping experience across digital and physical stores.

• CaratLane, a jewellery brand, has successfully merged online browsing with in-store experiences by:

  • Allowing customers to check local store inventory online.

  • Enabling reservations for specific designs before visiting a store.

  • Offering home try-on services for jewellery purchases.

• The complexity of merging digital and physical shopping requires advanced product management kills, highlighting how product analytics plays a critical role in optimizing user journeys.

📢 The Power of Personal Branding: LinkedIn as the New Résumé

• Traditional job-seeking methods (like applying through job portals) are becoming obsolete for mid-to-senior-level professionals.

• LinkedIn has emerged as the dominant platform for professional networking and job discovery.

• A compelling LinkedIn profile should go beyond listing experience—it should demonstrate thought leadership through posts, interactions, and personal insights.

🔍 Understanding Product vs. Marketing Analytics

• Product analytics and marketing analytics both fall under digital analytics, but they serve different functions:

  • Marketing analytics focuses on customer acquisition, ad performance, and engagement metrics.

  • Product analytics ensures smooth user journeys, tracking conversion rates, drop-off points, and feature adoption.

• He shared an anecdote where an e-commerce company miscalculated inventory demand based on product sales alone—failing to account for related product stock-outs.

  • This example highlights the importance of comprehensive data analysis, rather than making decisions based on isolated metrics.

Sign up for the masterclass here:

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