New Isn't Always Better Than Old
Knowledge Traction curates insights gained by startup builders during the early days of their entrepreneurial journey for others to learn from.
Building new features is exciting. Way more exciting than iterating on existing ones over and over again! However, one of the most under appreciated aspects of early stage company and product building is the opportunity cost of adding new features vs iterating on existing ones. Thus, make sure to carefully think through the ROI of adding a new “shiny object” before building it.
Today’s insight is from: Jeff Whitlock, the founder and CEO of PingPong, a YC-backed startup that enables better collaboration for startups in multiple time zones. On top, Jeff is also the co-founder of FounderPod, a community of founders helping founders, and he also writes on Medium.
When building your product, you always have a lot of ideas and get plenty of customer requests for new features. Most of them sound super exciting and leave plenty of room for imagination - could they be the missing piece that get you to product-market fit?
With that, it’s very tempting to pursue every “shiny new objects” instead of doing at least the 10th iteration on an existing feature that works but could be improved.
However, one of the most under appreciated aspects of early stage company and product building is the opportunity cost of adding new features vs iterating on existing ones. While adding new features is important, most of the time it’s less impactful vs improving exiting ones. Because for new features to actually move the needle, four things have to be true:
Your users want it
It functionally delivers on that want
Users can find / understand / try it
It fits into your users' mental model and usage patterns such that it can become part of habitual use
What startup builders also oftentimes underestimate is that new features take multiple iterations for just table stakes. You can validate a problem before building a product (user research, testing, analytics, etc.) but you won’t know if a new feature can deliver on all four criteria until you get it into your customers’ hands.
To add to the challenge, it’s hard to measure / quantify the ROI of a new feature vs doubling down on an existing one in startup land as there is typically very little data to support the decision making process (especially for new features).
When thinking about the potential ROI of new features, also consider that every time you add something new to your product, there’s not just the cost to build but also the cost to test, maintain, support and market it as well as the often underestimated cost of educating your users on what the new feature does / how to use it (email series, release notes, in-app walkthrough, support articles, etc.). The larger the surface area of your product becomes, the:
Less capacity you have to iterate on each feature
More people you need to manage and service your product / these features
Adding too many features too quickly can be a deadly sin for an early stage startup as a lot of time and money get wasted on features that aren’t core to the problem you’re solving. With too many features, you can run out of runway before you know it!
Instead, pay more attention to existing features that add proven value to your product. If you invested more into them, the ROI on time spent would oftentimes be much higher compared to new and unproven features. Thus, before you make a decision around what to prioritize, make sure stop and carefully think through:
“How confident are we that the new feature will have a bigger impact vs iterating / doubling down on what we already have / what our users are already doing?”
Jeff / PingPong’s template for “why are we building this”:
Before Jeff and PingPong make a feature related decision, they always ask:
“How will this increase our north star metric and what is the evidence?”: PingPong’s north star metric is maximizing time engaged. With existing features, they have a decent amount of data while for potential new features, impact on time engaged is mainly based on assumptions (i.e. there is little evidence). They make sure to challenge these assumptions very thoroughly before deciding.
“How does this fit in with our broader product vision?”: PingPong is a team messaging / collaboration app for remote asynchronous startups that aims to helps such startups to communicate in a rich, relevant and calm (non-distracting / asynchronous) way. For every potential feature, they ask themselves if that feature is another step in the right direction for this product vision.
“What are we really trying to do?”: For every potential feature, the PingPong team tries articulates the fundamental goal of it before making a decision. They learnt this the hard way - they e.g. once built a feature to get a video from PingPong into email with one click because some users had asked for it. Sharing videos via email goes against their north star metric and adds friction to the product. Needless to say that this feature no longer exists.
Thank you for sharing this insight Jeff!
🤝 - Share
Know an early stage entrepreneur that could find the insights covered in this newsletter helpful? They will appreciate you sharing it with them 🙏 !
📖 - Reads
Want to learn more on this topic? Jeff recommends reading:
Articles:
Why Your Startup Doesn't Invest Enough In It's Differentiators by Tomasz Tunguz
Part III of the Startup Playbook by Sam Altman
PMF Engine by Rahul Vohra, CEO of Superhuman
Feature Adoption Report by Suja Thomas from Pendo
His piece on How to put the minimum in MVP
Books
Hooked: How to Build Habit Forming Products by Nir Eyal
Competing Against Luck by Clayton Christensen
Super Thinking: The Big Book of Mental Models by Gabriel Weinberg
Risk Savvy: How to Make Good Decisions by Gerd Gigerenzer
Also check out these articles related to early stage company building:
👋 - Reminders
Share an insight: Have you gone through the earliest stages of venture-backed company building already and would like to share an insight? I’m all ears.
Share your startup: Are you in the earliest stages of building a capital efficient software startup in North America? Reach out to us - we at Darling Ventures lead / co-lead your first round of financing with checks up to $750K.