Most products are bound to evolve over time, but not every new addition translates into value for the user. 

New features may encourage growth in one customer segment while alienating another. This tension is common within the field of product management, and striking the right balance between innovation and simplicity is a crucial skill for product managers to learn.

To avoid adding unnecessary features to their products, PMs should take a multi-pronged approach. Firstly, the development of a solid product strategy can prevent individual stakeholders from exerting unearned influence on a product’s roadmap. Secondly, smart prioritization and development processes can ensure that product managers are focusing on the right inputs while taking the guesswork out of decision-making. Lastly, product managers can leverage different types of data at each point in the customer lifecycle to ensure that their efforts are serving customers effectively (and are primed to do so in the future).

We’ve turned to a group of experts to gather their insights on avoiding the pitfalls of unnecessary feature work:

Follow their advice to ensure products remain focused, user-centric, and effective as they grow.

Thanks to Kristen Poli for crafting this piece for GoPractice.

How do you ensure that you’re staying true to a product’s core value proposition and not deviating from its main goals?

Ensuring that a product adheres to its core values starts with defining a clear product strategy before development work begins. When planned features are mapped to critical customer problems and coupled with goals and benchmarks, product managers can confidently push back against extraneous feature requests that may arise during the development process.

It’s also important for PMs to understand their customers’ problems across multiple dimensions when citing them within a product strategy. Outlining the intended customer experience at each stage of product development can help prevent product managers from adding extraneous features.

In addition to defining a customer-focused product strategy, product leaders should establish a set of guiding principles to make managing potential trade-offs more efficient. By defining which characteristics of a product should be championed over others before development work begins, PMs can steer new features in the right direction without having to worry about being thrown off-course.

Cyrus Park (Senior Director of Product, Wistia)

Defining clear product principles

Like most product orgs, we have an overarching product strategy that details our strategic priorities and accompanying OKRs for the year. This is a must-have and helps us focus on the most important problems customers are facing. We have planning periods every four months where we focus on attacking specific parts of this.

In addition to that, we’ve developed a “Product Quality” framework, which can also be thought of as a clear definition of Wistia’s product principles. The genesis of this was realizing that if someone asks “what does a good quality product look like?” we can’t answer with “you know it when you see it”.

This framework allows us to have a shared understanding of what impacts quality the most at Wistia, and clearly defines areas where we never make trade-offs versus areas where we are willing to make trade-offs. For example, what do we care about more: secondary features or ease of use? Our Product Quality framework makes this answer clear.

Melissa Tanzosh (Principal Technical Product Manager, Amazon)

Maintaining a customer focus

During the strategy phase, it’s important to always work backwards from the customer for each milestone. I like to do this in a three part system by answering key questions, including: 

  • What is the customer’s experience today, and why is it a problem? 
  • What is the customer’s new experience with the product once it’s been launched? 
  • What would a customer say about how the product helps them? (ie. it’s faster, it solves a new need)

For every milestone or version of a product or feature, level set against these three things. You might find that a new feature or addition to a product doesn’t directly solve a problem, and that’s how you know you are deviating.

I also recommend that my team create product tenets prior to launch. Tenets aim to help teams make decisions ahead of time by thinking about their core values when faced with trade-offs. For example, a tenet could be that you are always biased towards customer trust versus innovation. Then, in the future, if a feature is having issues, you know you need to fix it before developing something new. With product tenets, the decision to rollback or patch is essentially made for you.

What strategies or frameworks do you use to evaluate feature requests and determine their relevance?

Product prioritization frameworks like KANO, RICE, and MoSCoW have the potential to help product managers evaluate feature requests and organize their backlogs quickly and effectively. However, these frameworks must be deployed in conjunction with other strategies to be effective. 

In addition to using prioritization frameworks wisely, it’s important for PMs to ensure that the feature requests they’re evaluating represent a set of proven and high-value customer problems.

One way to do this is to ensure that feedback collection processes are efficient, transparent, and capable of handling complexity. PMs must be able to account for the popularity of requests, the number and size of customers associated with each request, and whether or not requests map to organizational goals or product themes.

When using established frameworks to prioritize feature development, PMs should seek out methods that help quantify customers’ unmet needs. Opportunity Scoring can help PMs identify product or feature areas that customers are unsatisfied with but still regard as essential. 

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Cyrus Park (Senior Director of Product, Wistia)

Strategic feedback collection

I think the way a team goes about evaluating feature requests really starts with how they gather them. Said another way: your evaluation process is only as strong as the requests in your queue.

At Wistia, we recently started using Canny internally, which helps us capture, organize, and evaluate customer feedback. It’s integrated with tools Wistians are using every day (Intercom, Slack, etc.) to remove friction in submitting feedback on behalf of customers.

We also ensure every piece of feedback gets automatically shared in a company-wide Slack channel for visibility and learnings. Because all of our feedback lives in one place, we can see which requests are high volume, which are associated with the most MRR, which have been hot as of late, and what larger themes are showing up across them. We use that information in parallel with our strategy and data to make calls on what to action on.

On top of this, some teams also use prioritization frameworks like RICE (Reach, Impact, Confidence, Effort). I think those frameworks are helpful, but to be honest, in my experience, they’ve never been a game changer. Usually, frameworks like RICE show you what you’d expect, but make the decision easier to defend. Overall, they can be a bit of a time suck.

Jonathan Bartlett (Chief Product Officer, Exclaimer)

Opportunity scoring

There are some great frameworks out there, like RICE and Kano, but I believe Opportunity scoring is the most effective. It’s easy to get distracted by a thousand requests coming in from customers, but none of those customers are focused on how to grow your business.

They’re only focused on something that is going to help them, regardless of whether or not other customers will find it valuable. Opportunity scoring helps your team stay focused on what features are going to grow your business. Because poor retention has a negative effect on your company’s growth, issues that negatively affect your customers at scale will naturally find their way to the top in this model as well.

Can you share an example of a feature request that seemed valuable for your product initially, but upon deeper analysis, was deemed unnecessary?

According to our experts, it’s common for industry trends to influence an organization’s product roadmap. While competitive intelligence, market data, and industry reports can yield interesting and useful findings, a feature’s current (or predicted) popularity in the market is not always indicative of its success for a particular organization.

Product managers should take precautions to analyze the behaviors of their current customers – including the particular segments they’re targeting with a new feature – to ensure that products will have a significant user base before they’re launched. In addition, product managers should continue to reference their product principles when rolling out new features. If the user experience of a new product or feature conflicts with the principles of an organization, it should be overhauled or deprecated.

In any case, product managers should not be afraid to pause feature development or deprecate a feature once they receive confirmation that it’s not effectively solving a customer problem. Building products iteratively can help PMs de-risk their efforts, especially when approaching new markets or problem areas.

Cyrus Park (Senior Director of Product, Wistia)

Simplifying a complex user experience

Without getting into too much detail, Wistia does video creation in addition to hosting, sharing, analytics, and organization. We built a product called Studio to help users record or edit videos privately before they’re ready to publish–almost like a drafts section of your email or an unshared Google doc.

We had historical feedback on this from customers and knew others were doing it in the space, so we went for it. A few months in, the team started to realize that there was a problem. Not only was the problem that the feature was solving not as important as we thought (usage was low and stagnant) but more importantly, the feature was introducing a ton of complexity into our product, which normally wins for being easy to use and intuitive. It felt like we had taken a step back.

We learned about this trade-off, went back to interview customers, and decided to remove the feature to make sure we had the right balance of value. I was absolutely thrilled to see the team feeling confident and empowered to reverse a decision like this.

Melissa Tanzosh (Principal Technical Product Manager, Amazon)

Analyzing market momentum

In one of my previous roles, we were expanding our advertising product set to include video in addition to display. This was a huge customer request and was in line with company strategy and growth plans. Within the video product set, there were various paths we could take with respect to offering types and customer segments. Initially, streaming TV was deemed the most valuable because of the industry momentum and multi-year revenue uplift.

However, when we dove deep into customer segmentation, we found that the customer base actively allocating budget to streaming TV within other channels was not the same segment we were going after with this set of features. As a result, we deprioritized streaming TV and launched a feature set to support online video. We were able to follow up with streaming TV features later on.

In your experience, what are the common pitfalls or biases that can lead teams to add unnecessary features?

Many common pitfalls for product managers can be avoided by developing a well-defined product strategy. A documented strategy that contains clear problem statements and specific, measurable outcomes can help protect PMs from building unnecessary features.

While product strategies can be used proactively to ward off the addition of potentially low-impact features, product managers should exercise caution when asked to build custom features for specific customers or teams. It’s often possible for particularly vocal stakeholders to exert undue influence on a product roadmap – even if the solutions they’re proposing don’t support long-term business goals. Adept product managers should ensure that they’re not letting the loudest voices in the room have the greatest impact on their strategy and roadmap.  

It’s also important to check one’s own biases while developing new products and features. When spending weeks, months, or even years working on a particular product, it can be difficult to ignore signs that a feature isn’t performing well or solving a critical customer need. Gathering customer feedback and performance data regularly can help prevent personal bias from creeping in when managing a product’s lifecycle.

Cyrus Park (Senior Director of Product, Wistia)

Skipping goal setting

The most common pitfall I’ve seen is not having clear desired outcomes and goals before work even starts. Without knowing what your desired outcome is and how you’ll measure progress against it, there’s no way to know if features are performing well and why.

I’ve seen teams ship an initial feature targeting a primary customer problem, assume that the feature has solved that problem, and then move on to adding additional features before knowing if the core problem was solved.

Another bias I’ve seen is that, as product people, we naturally fall in love with our features. We spend so much time obsessing over them–it’s natural. However, we need to be the biggest critics of our work, because without doing so, we run the risk of investing more resources into something that’s not working, disengaging with customer feedback, and holding back the business.

Melissa Tanzosh (Principal Technical Product Manager, Amazon)

Listening to the “squeaky wheel”

One common pitfall is to listen to the “squeakiest wheel”: whether that be a sales team or a customer. Just because they’re asking for a feature doesn’t mean it will be used or have long-term benefits for the company. I strongly urge all teams to evaluate every request against what problem is trying to be solved, and all the possible ways that problem can be solved. You would be surprised how often a new feature is not actually needed.

Jonathan Bartlett (Chief Product Officer, Exclaimer)

Prioritizing large customers

Customer size is a common bias that results in teams over-prioritizing features. Building a feature for that large customer won’t necessarily increase your business with them or increase acquisition. You need to be very honest with yourself about the opportunity and risk of churn a specific customer presents, and do your best to resist these situations.

In addition, be on the lookout for solutions being pushed as opposed to underlying needs being discussed. These represent common pitfalls, where you can get pulled into building a custom feature that won’t benefit your business growth.

What role does data play in your decision-making process when considering new features?

Successful PMs use data to help them make decisions during each stage of product development. Leveraging performance, revenue, and customer data can help product managers make smart hypotheses about the features they’re building. These datasets can also be used to generate benchmarks, which are necessary to measure the success of a particular product or feature.

Data can also be used differently depending on which stage a product currently occupies within its lifecycle. Product managers in growth roles who are responsible for optimizing an existing product can lean on performance and usage data more heavily than product managers who are building products or features from scratch.

New or aspiring product managers should also be aware that data won’t—and shouldn’t—make strategic decisions for them. It’s important for PMs to use data as a tool to make better decisions while acknowledging that a ‘perfect’ dataset may be unavailable. In some situations, waiting for more robust data may impede a product manager’s ability to build features iteratively and learn more about their customers and the market while they do so.

Cyrus Park (Senior Director of Product, Wistia)

Using data and iterative development

The short answer is that we use data to make decisions of all sizes. The longer answer is that data alone is rarely enough to make product decisions for us, and often we don’t have the exact data that we want.

While we should always be striving to fill gaps in our datasets and be transparent when we don’t know something we should, our job as PMs is to make decisions with the information we have on a given day.

So, our team aims to be decisive: we de-risk blind spots by building quickly and iteratively. This way, we can learn fast, and if we fail, we can do so as early as possible.

I also think the value of data changes depending on how mature a product is and what kind of problem space you’re focused on. If you’re working on a more mature product or are in the growth space, it’s more likely that you’re optimizing a product. In those situations, data will be extremely critical to your day-to-day decision-making through things like A/B testing. If you’re going from 0-1 with a product, your current data set is likely limited. In a green space, it’s more likely that you’re thinking about how to build out datasets and new learnings through iterative development.

Melissa Tanzosh (Principal Technical Product Manager, Amazon)

Weaving data with strategy

Data is critical – we use customer segmentation data, usage data, performance data, and revenue data to make all decisions. To ensure we are always data-first, we ask all product managers to include data in their product strategy documents and presentations before development begins. We also hypothesize usage and performance post-launch, so we can benchmark ourselves against goals.


Preventing the addition of unnecessary features requires constant vigilance on behalf of product management teams. In order to ensure that new features consistently provide value to users, product managers can develop strategies that are customer-centric, experience-oriented, and rooted in organizational product principles. Product strategies that include a clear vision for the customers’ experience as well as goals and benchmarks can help product managers remain accountable to their customers, even when challenged by stakeholders.

In addition to creating well-defined product strategies, PMs can focus on creating and maintaining processes that encourage customer-centricity at each stage of the product life cycle. PMs who routinely gather customer data and feedback and scope out new opportunities with diligence will excel in consistently providing value to users. As a part of this process, PMs can leverage opportunity scoring frameworks, market sizing techniques, and incremental development models.

In addition to leveraging smart protocols and building solid product strategies, PMs must work to check their own biases when adding new features to a product. While new PMs may be tempted to overinvest in product areas because of their previous experiences, seasoned PMs know that measuring a product’s performance is their most critical tool, and deprecating certain features may serve users best (even if the process is painful).

Illustration by Anna Golde for GoPractice