Building great products through feedback and psychology: Amritha Arun Babu Mysore (Product Leader, Amazon)

In an interview, Amritha Arun Babu, AI/ML Product Leader at Amazon, delves into the fundamental principles propelling product leadership at the e-commerce giant. From prioritizing user expectations to navigating the intricacies of data quality in AI development, Amritha shares invaluable insights and delves into future trends that will shape the product management landscape.

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Understanding the customer: A core principle at Amazon

Amritha Arun Babu Mysore, AI/ML Product Leader at Amazon, sheds light on the foundational principles that drive successful product leadership at the retail giant. For her, working backwards from the customer is not just a strategy; it’s embedded in Amazon’s DNA. “As a product manager, the customer is the key focus, and the product is always enriched if you work backwards from the customer,” she emphasises, “user interviews and surveys can create the foundations for making informed decisions,”

According to Amritha, diving deep into understanding the customer’s psyche is a crucial step in product development. “Understand their user journey, understand their pain points, understand why they are using a particular product in a specific way,” she suggests.

Leveraging insights and trends gathered from this understanding, she employs tools like user interviews and surveys to make informed decisions that directly impact product features.

Prioritising user expectations

Prioritising new features to build is a challenge for many product managers, Amritha commented looking back on her experiences with launching product features. She stresses the importance of aligning features with business goals. “Is this a feature we need to release now, or should we solve the existing issues for the customer and then start innovating once we have a baseline?”

Reflecting on her time as a salesforce product manager at Rubrik, Amritha explains that ensuring that the team aligns on the foundational principles is critical. Once that process is streamlined and communicated to all teams, it’s easier to balance tackling existing customer issues and innovating with new ideas.

Amritha believes that customer trust is a key asset to understanding the user. She suggests obtaining live and offline feedback, depending on the nature of the business: “Additionally, having an open line and regular communication system can establish a relationship with your customers” she says, “Take them on the journey and tell users how the product is changing based on their feedback.”

Data quality and responsible AI development

While AI promises to revolutionise industries through data-driven insights, much of the foundation for realising its potential lies in less glamorous backend infrastructure modernisation, as an ML Product Manager, Amritha explains, discussing AI in the wake of recent technological developments, “The fundamental ingredient for baking our AI cake is data – massive amounts of quality, perfectly measured data.”

Whether drawing real-time sensor feeds from industrial equipment, aggregating years of customer transactions, or accessing open public datasets, Amritha emphasises that “Clean data is the lifeblood of AI. Think of it like clean pipes for your AI cake. Clogged pipes with messy data mean the cake will be a disaster no matter how good your model is.” Common issues she observes are data trapped in legacy systems, incomplete data requiring heavy post-processing, and inconsistent taxonomies, making integration complex.

“My guide to business and engineering leaders is to first invest in streamlining their data architecture, governance, and ops before beginning prototype experiments. The returns downstream are 10x as product building is deeply related to understanding users. Clean data helps us truly understand users’ needs and behaviours. It’s like knowing your cake audience – chocolate or vanilla? Sprinkles or frosting? The better we understand them, the better our AI solutions can serve them.

Amritha contends this data supply-chain viewpoint is critical. “At the end of the day, our algorithms are only as strong as inputs the data team provides.”

Emerging trends: Sentiment analysis

Amritha predicts a significant shift towards understanding the sentiment behind user actions and creating trends. “When you rate a movie or product,” businesses will begin to understand better the ‘why’ which I think is missing today,”

Combining natural language processing with sentiment analysis is poised to play a pivotal role in shaping future products. At the moment, product managers create hypotheses based on their data. Amritha believes that understanding the sentiment behind the quantitative data will come to product managers much easier in the near future.

Frameworks and problem-solving

Amritha admits that a plethora of frameworks are available to product managers, but she emphasises the need to align them with specific problems. Drawing on her experience as a product manager at Wayfair, she provides an example involving the complexities of delivering furniture components. By focusing on foundational principles and sizing pain points, her team at the e-commerce company navigated the delicate balance between solving existing issues and innovating for the future.

She lists frameworks that she has used in previous and current roles:

Design thinking: This user-centred framework emphasises empathy, iterative prototyping, and testing to understand user needs and create solutions that truly resonate. It aligns with my approach of focusing on foundational principles and sizing pain points, ensuring solutions address real problems.

Lean startup: This framework champions rapid experimentation and learning through iterative cycles of build-measure-learn. It encourages focusing on minimum viable products (MVPs) to gather user feedback and refine solutions quickly, similar to my emphasis on navigating the delicate balance between solving existing issues and innovating.

User journey mapping: This framework visually maps users’ touchpoints with a product or service, highlighting pain points and opportunities for improvement. It complements my focus on understanding user needs and behaviours, providing a holistic view of the user experience.

Collaboration and stakeholder management

Throughout her time working at Amazon, Amritha has communicated with several stakeholders along the way. She says how building trust and human connection with internal teams are key when working with different skill sets and personalities. Amritha says, “You can then take people along the journey that solves the right problems for customers,”

She adds that addressing conflicting perspectives requires open communication and alignment on a shared vision, ensuring everyone is working towards solving the same problem.

Key lessons for aspiring product managers

Amritha’s parting advice for those entering the product field revolves around continuous customer feedback. “Get their continuous feedback so that you know if your product meets the expectation before you inject significant investment into a new feature”, she advises, “be transparent with these changes with your customers and build new features ethically to build trust.

Iteration based on customer feedback ensures ethical and transparent product development, a hallmark of successful product management.

The views and opinions expressed in this article are Amritha’s own and do not reflect the official policy or position of any institution, employer, or organization with which Amritha is or may have been affiliated.