Features That Sing and Ones that Whisper

A product might earn sales with features that sing, but it won’t retain users and grow virally without ones that whisper, and it might…

A product might earn sales with features that sing, but it won’t retain users and grow virally without ones that whisper, and it might retain users with ones that whisper, but it won’t attract net-new markets or generate excitement without the ones that sing.

For simplicity, let’s call features that sing the ones that capture audience attention and are sexy, and the ones that whisper are important but may go unnoticed when everything is ‘working.’

For Apple Airpods, the features that sing are the great design and fit in the ear, the charging case that frees the user from wires, and the incredible sound quality in a tiny product. For the original iPhone, it was the ability to really browse a web page in a first-class way. By contrast, a feature that whispers is the Airpod’s lightning-quick pairing and unpairing with your phone. For the original iPhone, it was the amazing sensitivity of the screen to your touch. Probably neither of these latter features caused you to buy directly, but when you use the Airpods multiple times a day and they always ‘just work’ and then you try a competitor and spend an hour re-pairing, the value is clear. And with that first iPhone, typing on it became realistic, nagging at you that it might one day replace your computer. With feature combinations like these, you speak the product’s praises, others hear you, so they buy too, they fall in love with the combined experience, the product grows virally, and all is good in the world of product.

In short, a great product must have both types of features to be world-class.

Let’s dive deeper on an example from my work. Part of working on platforms that empower data scientists is the challenge of getting those data scientists, who are accustomed to using their own specialized setup to try something new. Many industries have this same challenge. When we began building features for data scientists, we knew they would appreciate easily integrating with tools that give them special powers, like easy traceability of a machine learning model or the ability to quickly containerize and scale a model for a massive user base without having to really understand the infrastructure. These are features that sing for the data scientist.

Crucially, however, all these features did was get people excited, but they weren’t very productive for user adoption or creating real behavior change or producing results for a customer problem. When we dived in with a representative set of users, we quickly learned that we had gotten a bit too excited and skipped right past some of the core features that whisper. For example, what happens when the data scientist is working with billions or trillions of high-velocity records instead of a volume that can be interrogated on a local laptop setup? How can a user access all these great features from their existing, comfortable developer environment instead of requiring them to use one of our own creation? What’s the fastest way to understand what data is available to them, and how can we limit or restrict roles to prevent misuse or costly mistakes that could taint the environment for that data scientist or other users? Each of these is a potential feature that whispers, and what it’s saying is “you’ve got to make this easy for me” and “it must solve a problem I actually have today, not just one that would be cool.” If the user gets stuck easily, your innovation isn’t an innovation at all, it’s just a poorly executed idea.

The trouble is, each of these styles of innovation tends to resonate differently with different sets of personalities, so a great product requires both types of people on the team, that is the ones who love singing and the ones who love whispering. The balance between them is more art than science and depends on the level of market penetration and where and how the business wants to grow, but I can say from many experiences in both extremes, the extremes are not where you want to be to make something amazing.