Bridging the Product & Research hole – Part I: Demystifying Product for Researchers

February 04, 2025 Published by Henrik Lindström

About the creator: Henrik Lindström is a Principal Product Manager, at present serving because the Product Lead for the Personalization Tech Research workforce. He started his Spotify profession as a software program engineer in 2011 however rapidly transitioned into product administration. Over the years, Henrik has taken on a wide range of management roles, together with a number of years on the helm of the Spotify Search workforce, the place he performed a key position in shaping consumer experiences and driving innovation.

Developing modern merchandise play a necessary a part of Spotify’s success. This is true for a lot of corporations within the tech business, and because the time period R&D signifies, it’s about combining Research and Development or Product groups. There are many success tales of how Research has been transferred into product. To point out just a few latest ones from Spotify, we’ve got leveraged graph based mostly fashions to propel audiobook and podcast suggestions, auto-generated podcast chapters, and contextualized suggestions utilizing fine-tuned LLMs. However, speaking to of us in numerous organisations, discovering an efficient set-up for the right way to work throughout analysis and product groups stays a standard problem.

Last yr I began a brand new chapter as Product Lead for the Personalization Tech Research workforce. We are organized as a central workforce of Research Scientists, aligning with a variety of product groups to drive impression. In my earlier position I used to be product lead for a type of groups. Having expertise from “both sides” offers me a singular perspective on the right way to strengthen collaboration between product and analysis to realize even higher outcomes.

This is the primary of two weblog posts the place I’ll discover this matter, beginning with demystifying Product improvement for Research Scientists. I’m additionally arguing that researchers ought to deal with their analysis as a product with product groups as their clients.   

Product and Science Mindsets: More Similar than You Think

At its core, a product mindset has sturdy similarities to a scientific one. In reality, Product Management and improvement seen via a scientific lens – a standard analogy for the position – is about steady experimentation and speculation testing. Both contain a shared give attention to fixing complicated issues, and decreasing uncertainty. In addition, each require a basis of curiosity, and grit to drive impactful outcomes. However, key distinctions exist by way of how these mindsets are utilized:

• Focus: Researchers typically go deep into the “how” of an issue, looking for to know its elementary nature. Product groups, whereas valuing this understanding, prioritize the “why” and “what” – e.g. what answer will finest meet consumer wants and enterprise targets?
• Outcomes: Researchers attempt for options which can be technically sound and modern. Product groups search options which can be fascinating by shoppers and viable for the enterprise.
• Delivery: Research can culminate in expertise switch, sharing information and findings someday feeding into the longer term roadmap. Product improvement focuses on delivering merchandise that clients can use and profit from, the place expertise is certainly one of many elements.

Similarities and variations between a Product and Research mindset

To bridge the variations that do exist, I’ll subsequent give a primer on two frameworks for product technique and improvement: Good technique/Bad technique, and the way to consider Risk in Product discovery. I select these two as a result of they’re generally identified and used within the product group, and thus function good entry factors. That stated, there are various strategies and frameworks, and what works finest will rely on the workforce and state of affairs. 

Product Strategy: Getting to the Why

In the realm of product technique, Richard Rumelt’s e book Good Strategy / Bad Strategy is taken into account a canonical textual content, extensively adopted inside the product group. Rumelt introduces the idea of the “kernel of a strategy”, which consists of three key components: (1) a prognosis, (2) a guiding coverage, and (3) coherent motion. The prognosis serves as an issue assertion, clearly defining the character of the problem at hand. The guiding coverage acts as a speculation, outlining the method to handle the problem. Finally, coherent motion encompasses a set of options designed to execute the guiding coverage successfully. Just as in analysis there isn’t a actual system, however Rumelt identifies these as important components of a “good strategy”.

What does this imply for analysis? Understanding the “kernel” of what Product is making an attempt to realize, will assist make certain the analysis is addressing the underlying drawback, and make it simpler for Product to see the connection to “their” technique.

Product Discovery: Unpacking the What

Another core side of Product Development is to articulate what product will assist drive the technique. This is known as product discovery, and it’s about exploring and defining numerous options. I cannot go into ideation strategies, and confer with design sprints and thoughtful execution nearly as good locations to start out. Once we’ve got just a few potential options, how would possibly we derisk constructing the “wrong thing”, or later understand it can’t be scaled? In his e book Inspired, Marty Cagan articulates key kinds of dangers that any new product being ideated and developed on ought to contemplate, ensuring to sort out the largest dangers up entrance: 

• Value Risk: Will clients discover the product beneficial sufficient to purchase or use?
• Usability Risk: Can customers simply perceive and work together with the product?
• Feasibility Risk: Can the product be constructed with obtainable sources and expertise?
• Business Viability Risk: Does the product align with the corporate’s total enterprise technique and targets?

Tech Research at Spotify typically performs a essential position derisking feasibility, contributing with experience round present expertise and researching novel options. But what if we utilized the size of Value and Usability Risk to the analysis itself?

Looking via the lens of the Product workforce being the client, we will reformulate the dangers as follows:

• Value Risk: Will clients Product groups discover the product analysis beneficial sufficient to purchase or use?
• Usability Risk: Can customers Product groups simply perceive and work together with the product analysis?
• Feasibility Risk: As talked about, that is already on the core of what analysis at Spotify does.
• Business Viability Risk: The enterprise threat stays the identical.

In this sense, analysis is a product with Product groups as clients and customers. Treating it as such would possibly assist enhance the possibilities of getting the PMs consideration, and finally to convey the analysis to profit the customers, creators, and the enterprise.

Key ways for Researcher-Product Collaboration

Finally, I’m leaving with six ideas that may assist researchers enhance their collaboration with Product builders. These are based mostly on my private expertise from a few years of getting labored throughout  analysis and product improvement.

• Start with the Why: Clearly articulate the issue the analysis addresses and why it issues to the enterprise.
• Connect to Existing Problems: Align the analysis with the challenges the product workforce is at present dealing with.
• Speak their Language: Use terminology and metrics that resonate with the Product groups.
• Reduce Complexity: Present findings in a transparent, concise, and actionable method.
• Timing is Key: Be aware of the product workforce’s priorities and timelines.
• Show, don’t Tell: Demonstrate the potential impression of the analysis via prototypes or demos.

Research continues to play an integral position within the success of Spotify, positively impacting customers, creators, and the enterprise. This is barely doable via sturdy relationships and efficient collaboration between Research and Product. We are continually studying and evolving how to do that nicely. In this weblog publish, I explored a further step on this course of – by embracing a product mindset, Research Scientists can develop into more practical collaborators and enhance the impression of their work. Remember, analysis is a product too!

Thanks for studying, and keep tuned for half II, demystifying Research for Product groups.