Defining product market fit potential

In taking an application focused approach to product market fit, we’re able to narrow down to just a selection of market verticals from those we initially identified.

Not exactly easy to use, but very illustrative of the uniqueness of a viable, appealing application for Zensors technology.

Building off of the market vertical criteria

While the criteria that we identified continues to be helpful as we make progress evaluating the market verticals we identified, it became very apparent that while the criteria that makes a market attractive for Zensors is useful, further breaking down the criteria that covers the application aspect would be critical to helping us narrow in on specific use cases.

Attractive applications for Zensors

The strengths of Zensors are the flexibility with which it can actually start gathering data and facilitating insights coupled with out of the box computer vision aspects that find a natural for areas that are looking for ways to automate or increase process efficiency. Below we’ve formalized the key qualities that comprise an attractive application:

1. Application for periodic sampling
2. Tolerance for error
3. Financial advantage
4. Low level privacy concerns
5. Little crowd training needed
6. Physical conditions appropriate for camera placement

Periodic sampling

At it’s core, Zensors enables users to send a frame sampling off to be analyzed by the crowd. Applications that depend on real time, low latency feedback are not a great fit. This removes use cases involving most security applications, urgent or emergency scenarios, or extremely dynamic video feeds.

Tolerance for error

Even with perfect data, there’s still a chance for error. Accordingly, any application that requires a very narrow margin of error or no error at all, is not a fit. Again for emergencies or urgent situations, this applies. For a business that cannot support a margin of error would also be a less than desirable fit.

Financial advantage

There are a couple of aspects of the financial advantage needed in order for Zensors to be adopted. In the business criteria, we started to get at the need for a budget and funds with which to operate a Zensors system. Beyond that, Zensors needs to represent gained efficiency either through direct cost savings or indirectly, likely through resource burn. Without a financial benefit, adoption is highly unlikely.

Low-level privacy concerns

With any kind of data, privacy is always a concern. With Zensors, there are essentially two levels of concerns that we’ve grouped together — there’s the concern over what the user is going to do with these insights (are they using this system for ulterior motives or to monitor specific people) and there’s also the concern over who has access to the video feeds themselves related to the crowd work. The crowd could potentially be contracted or be employed directly by the user or customer, but the motivations of the user in the first place are a component to watch for.

Little crowd training needed

Even with a private crowd (instead of a public one), there would still need to be some instruction for all people in the loop to follow. That said, if the type of data is especially involved or the visuals are particularly nuanced, it’s unlikely that Zensors would be a fit.

Physical conditions appropriate for camera placement

Just like it says on the tin, the ability for visual data to be collected in order for Zensors to provide a mechanism with which to process it is also very important. A user might have all of the above worked out, but if the type of data being collected doesn’t lend itself to a camera being placed to do it, there’s not much Zensors can do.

What’s next

With all of this, we’ll be better positioned to narrate our process of validation and elimination of market verticals and use cases. In the next few posts, we’ll share out research updates and finally get into how all of this is shaping our design process.