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Mind the Product

Innovation

Sunday Rewind: Show your true innovative colours by Julia Shalet

Customer

How behavioral economics can improve product strategy

B2B product management

Artificial Intelligence (AI) & Machine Learning (ML)

Building Product Teams

Business Strategy

Data Driven Product Management

Digital Transformation

Diversity and Inclusion

Minimum Viable Product

OKRs

Prioritisation

Product Design

Product Research

Product Development Process

Product Ethics

Product Discovery

Product Leadership

Product Management Career

Product Strategy

Stakeholder Management

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Join us at #mtpcon London in 2025 – mark your calendars

Connecting fans to creators at Spotify (Dariusz Dziuk, Product Lead, Spotify)

Why teams often struggle with OKRs: A conversation with Jeff Gothelf

Deep dive: Crafting your product vision and mission

5 ways to invent and simplify as an AI/ML product manager

Lorian is product professional and independent researcher immersed in Stockholm's tech scene, with expertise spanning lifestyle and entertainment technology, internet and consumer tech, B2B/B2C hardware, and internal tools. This diverse experience allows her to bring a nuanced perspective to each project. Passionate about the intersection of technology and society, she also conducts research exploring how technology shapes everyday life, with a special focus on internet and mobile phone studies. Her published work highlights their commitment to understanding the broader impact of our digital interactions.

Lorian Leong

<p>When developing products, customer insight is vital to understanding the critical question: where are we going? Insights can help us better to understand our product and how it fits into the everyday lives of users — users who live in an age of abundance, where every product competes for a minute of attention. But insights too fall into our cultural condition of excess.</p>
<p>From focus groups to customer service feedback to analytics to surveys to personal experience, product teams swim in an ocean of information coming from various functional teams. But synthesising information into insight is an art form and an exercise in restraint. Information can only tell us so much &#8211; finding the relevant information and contextualising it given certain complexities and nuances to turn it into insights is a challenge.</p>
<p>As a product manager, navigating the deep waters of information overload requires an acute awareness of politics, an understanding of methodology, and solid communication skills. And all that is doubly true when it comes to sharing your insights and using them to inspire action across the business.</p>
<h2>Alter the Egos</h2>
<p>It would be naïve to assume functional teams don’t have their own agendas for product innovation. When knowledge is power, information retrieval is the road to a coronation. For product managers standing at the intersection of business, technology, and user experience, it’s a screaming match from functional teams fighting to be heard. Be they user researchers, data analysts, market researchers, or customer service agents, every team is fighting to legitimise their job role (and livelihood).</p>
<p>The best way to manage the cacophony is to acknowledge the benefits of each team’s research in a weighted and measured manner. This makes them feel like their work is valued and recognised. But in order to do this, an understanding of what their research and insights offer is imperative.</p>
<h2>Size Up Your Sources</h2>
<p>Functional teams can use a myriad of research methodologies, but some are more common than others. All methodologies are used to measure and glean specific types of insights and have limitations.</p>
<p><strong>User Experience</strong> teams often use user interviews to test and explore. A common practice for testing is to test with five ‘average’ users, as results are said to yield diminishing returns beyond this. But usability is not the same as user research. User interviews are also common practice among User Experience teams to understand market behaviour. While usability may be more easy to extrapolate, insights gained from small user interviews are not necessarily applicable to the greater population. What can be extracted from small interview groups is a range of viewpoints and in-depth information.</p>
<p><strong>Marketing</strong> teams, on the other hand, often rely on surveys and other forms of quantitative data that offer different insights on users. But these methodologies generally test pre-defined concepts and lack the depth and range of opinions offered by users. Sometimes, marketing can conflate survey insights with user-generated opinions.</p>
<p><strong>Data analysts</strong> investigate volumes of data from user tracking within products (e.g. apps). This data offers highly detailed information (and in large scale) about user behaviour. But the motivations and intentions are not always clear. Generally, what the data shows is what the users did, not why they did it.</p>
<p><strong>Customer feedback</strong> is equally important, getting unprompted, unmediated opinions about your product. While the sample population can be skewed towards vocal minorities and problem users — often seen with aberrant requests, frequently reported problems can show early indications of problems or desires.</p>
<p>When a product manager has a good understanding of research, it becomes easier to communicate the value of insights brought for by each team. An awareness of the design and implementation of methodology is beneficial in evaluating weight of findings.</p>
<h2>Retracing Steps</h2>
<p>Insights are yielded by combining the information from user experience, marketing teams, data analysts, and customer feedback (among other sources). Together, they cobble together an almost complete picture. For example, when launching a new feature, using insights across multiple teams can help measure its success in the pre- and post-launch phases.</p>
<p>Different teams will have different measures for what “success” looks like, and by acting as a bridge between them you can not only work to unify them towards a coherent view of product success, but also get their buy-in as you work towards your product vision. It’s crucial to remember that Information and insights you’ll gain are cyclical, and should feed back into the ongoing product development process to not only inform your next steps, but to reframe your understanding of your users’ and keep everyone aligned.</p>
<h3>Pre-Launch</h3>
<ul>
<li>Gather user research and understand your users’ needs. Baseline questions can be gathered from previous customer feedback, market research surveys, or conducting a few pilot interviews to see what opinions are expressed</li>
<li>Work with development and prototyping, and test through usability research to see whether the solution and feature created solves the identified need</li>
</ul>
<h3>Post-Launch</h3>
<ul>
<li>Through data analytics, track the usage of the launched app</li>
<li>Corroborate data against marketing teams to see if increased usage was only due to heavy promotion of the new feature</li>
<li>Check customer feedback to see if there are bugs and other issues, or if there are only rave reviews (&amp; be naturally suspicious of seemingly perfect reviews!)</li>
<li>Cross-reference user tracking data against the opinions expressed in user research</li>
<li>Survey a subset of users on their satisfaction and use of the product and feature at an appropriate time post-launch (timeframe dependent on the product)</li>
</ul>
<p>When users behave contrary to the intended design, it is useful to re-evaluate the collected information to see where there may be a miscommunication, misunderstanding, or misinterpretation between users and product teams.</p>
<h2>Selective Show and Tell</h2>
<p>You don’t need to drown others in data to show them your ocean of information — a map of the key islands of insight will suffice. While good teams will involve product managers in the process of user research or provide raw data, in silo-ed corporate environments that is a privilege, and not a right. Product managers must learn to synthesise information in its given shape and form, and present it in meaningful and relevant ways back to their teams and to their stakeholders.</p>
<ul>
<li><strong>Cite carefully</strong> – An understanding of methodology allows product managers to use the right information in the right contexts. Telling a market launch coordinator the opinions of a few users as representative of the entire market, for example, could decrease your authority.</li>
<li><strong>Confess limitations</strong> – A good way to increase your influence is to address the limitations of research. Critical reflexivity shows understanding of bias and adds credibility.</li>
<li><strong>Credit generously</strong> – When product decisions are made based on insights, apply credit to as many teams as possible. While one domain may have had a stronger influence on a product decision, acknowledgement will minimise the perceived need to play team politics.</li>
</ul>

core/freeform

How to lead data-centric product teams: Jon Mora (Chief AI Officer, Zefr)

How to be a better data-driven product manager

User insights for product decisions by Cris Valerio

Data scaling for startups by Crystal Widjaja

Make Better Product Decisions by Using Quantitative and Qualitative Data, by Brian Tran

The Challenge of Managing – and Communicating – Customer Insights

Lorian Leong

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