Products vs. Features
Advice from Product Experts on How to Tell the Difference
In my last post about navigating the idea-to-product journey, I emphasized the importance of thinking in terms of products, not just features. This sparked some follow-up questions about how to actually distinguish between the two.
I decided to call on the help of some Product Experts in my circle to help shed some light and advice on how to think about this space – a special thanks to Mat (VP Product @ Google, former Microsoft), Neena (AI PM @ Meta, former Google & Microsoft), Nino (CPO @ Northstar Travel Group, former Google), Emily (VP Product @ Ahara, former Microsoft), Marily (AI PM @ Google, former Meta), and Cassie (PM @ Weights @ Biases) for sharing their thoughts with me for this post.
The Value of an Idea: A Quick Reality Check
Before we dive into their insights, I want to address the elephant in the room: not all ideas are created equal. In fact, most ideas are probably… not great. And that's okay! The key is to be brutally honest with yourself about an idea's potential before investing significant time and resources. As Mat put it:
“It comes down to defining hypotheses and finding out the quickest possible way to test them…most hypotheses fail, that's a good thing. Fail quickly…Do whatever is cheaper/faster to tell you if the hypothesis holds signal, which is RARE. Most ideas are bad, that's a fact of life.”
The goal is to validate (or invalidate) your assumptions as quickly and cheaply as possible. Remember, failing fast is a feature, not a bug. It allows you to iterate, pivot, and ultimately increase your chances of landing on a truly great product.
And failure can strike for reasons beyond the initial idea itself. Sometimes, the real challenge lies in building a sustainable business around the product. Emily brought up that a true product not only solves a user's problem but does so in a way that allows the company to keep solving that problem sustainably by “making revenues to afford the R&D of the next iteration.” This is especially crucial for companies pioneering new technologies, but even established products can grow stale. Ensuring you have a path to profitability while still investing and iterating on the next big thing is essential.
Now, with that crucial reality check out of the way, let's dive into what differentiates a feature from a product, drawing on insights from my expert network and my own experiences in the world of generative AI.
Scope: The Breadth of the Solution
One way to differentiate between a feature and a product is to consider the scope of the idea. A product tackles a broader user problem with a more comprehensive solution, while a feature addresses a smaller, more specific need within that broader context. As Nino puts it:
“In order to be a product, I think a solution needs to solve a complete user problem from end-to-end.
For example, when we worked on Speech at Google, we provided Speech recognition for nearly every product at Google. Most of these were FEATURES. Things like captions on YouTube, Voice Search on Android and Voice Typing in Gboard.
But sometimes those features can be so powerful that they evolve into a full product, like the Recorder App for Pixel. The main feature was high quality speech recognition (along with advanced features such as speaker diarization) but those combined together with the right UX proved to be a very powerful tool, especially for specific users such as Journalists or teachers. That became a PRODUCT.”
Recently I also wrote about two ideas I had where I thought Generative AI could help improve a user experience. Let’s walk through each in the framework of whether they’re a feature or a product:
AI-Powered Document Titles: Imagine never having to come up with a file name again. You write a document, and the system intelligently suggests a title based on the content. This feature could be incredibly useful and save users time and effort. But is it a product? Not quite. It enhances an existing product experience (like Google Docs or any other document creation tool), but it doesn't have a standalone value proposition.
Personalized TV Show Recaps: We've all been there—returning to a TV series after a break, only to find ourselves lost in the narrative. A feature that summarizes previously watched episodes, providing a personalized recap, could be a welcome addition to streaming platforms like Netflix or Hulu. But again, this is a feature, not a product. It improves the user experience within an existing platform, but it wouldn't exist independently.
Total Addressable Market (TAM): Is It Big Enough?
Even if you have a seemingly complete, end-to-end user journey for your idea, another crucial factor to consider is the Total Addressable Market (TAM). Sometimes, even with a well-defined offering, the potential market might simply not be large enough to justify the business value of creating and sustaining that product as a standalone entity.
The good news is that a limited TAM today doesn't mean your idea is destined for the graveyard of good intentions. Sometimes, it can serve as a launchpad, a strategic first step towards capturing a much larger market down the road.
Tesla's Roadster wasn't just a high-end electric car for the wealthy few; it was a proof of concept, a way to refine technology and manufacturing processes that would later power their mass-market Model Y. Amazon didn't become a global behemoth by staying a humble online bookstore forever. Even GoPro started with surf-ready cameras that led them to conquering the world of everyday adventures.
The key here is to think ahead to what that larger vision could be — what is your North Star? While your initial product doesn’t need to achieve it completely at first, you should at least be making sure that that larger vision exists.
Target Users: Expanding Your Reach
Another telltale sign of a product is its potential to reach a new market segment. Does your idea open up your existing product to a whole new audience? If so, that's a strong indicator you're dealing with a product, not just a feature. As Neena puts it, "new products are where they’re disrupting a category, an industry, or workflow."
Take Adobe's foray into generative AI as an example. As someone aptly described at a recent dinner I attended, his grandmother, who would have never used Photoshop, could now effortlessly create personalized graphics thanks to the user-friendly capabilities of generative AI. This expansion into a new user demographic signals a distinct product offering. That said, I also really enjoyed Nino’s perspective on this particular example:
“Looking at it from a generative AI perspective, you can see this with image editing tools such as DALL-E or Midjourney. These are incredibly ground breaking technologies, but my experience is often frustrating, because the images are so hard to edit. it is not a full solution, but a very powerful start to a finish. To be a full-fledged product, either one of two things must happen:
[1] Adobe will become the leader here, and image generation will be a FEATURE of their already industry leading product, OR [2] OpenAI/Midjourney/Etc need to add editing capabilities to their products to fully disrupt Adobe.
Current state is likely untenable where users go to one tool for one feature but need to go to another tool to finish the job. This is especially true when both tools require a subscription and are not free.”
A Quick Litmus Test: Is Your Idea a Product or a Feature in Disguise?
Here's a few more quick questions that might help you assess the potential of your idea and whether or not it’s better off as a feature or a product:
Does your idea have a standalone revenue model? Could you price it independently and have it make sense to customers?
Can you explain the value proposition in one concise sentence? Products tend to have clear, easily digestible value propositions; features often require lengthy explanations.
Does it solve an end-to-end user problem in a sustainable way? Can your product continue to solve the user problem, generating enough revenue to afford the R&D of the next iteration?
Does it feel right? Does your idea naturally complement your existing product strategy (1 to 1), or does it feel like a forced fit? Products often define entirely new strategic directions (0 to 1), while features should enhance what's already there.
I find this quick chart helpful as a side-by-side comparison of the key characteristics we discussed above:
The Power of Features, the Potential of Products
Remember, features are essential building blocks, but they rely on a larger product for their context and value. Products, on the other hand, stand on their own, offering a complete solution to a user's needs. In the ever-evolving landscape of generative AI, it's more important than ever to think deeply about what constitutes a product vs. a feature. By focusing on long-term vision, user experience, and differentiation, we can build products that not only capitalize on the power of AI but also stand the test of time.
I’ll leave you with something Mat said that I thought was great advice: “Satya used to say ‘No regrets investment‘ Which investment will make you have no regrets, even if the idea was bad?”