The ProtoCanvas
A Pre-Product Tool to Expose Lean Assumptions
TL;DR… Use the ProtoCanvas to capture your product concept — quickly communicate the idea and indicate necessary steps to validation.
The Lean methodologies are great theoretical ideas, but tactical application is sometimes hard to come by. Over time, I’ve built a document that helps to capture and reference the initial information you’ll need to clarify the earliest stages of your product concept and map out the experiments you’ll be running for viability (steps I’m referring to as the ‘proto-product process’). Organically, the document took the form of a ‘canvas’.
Canvas defined… The canvas concept, (popularized by Osterwalder’s Business Model Canvas) creates a framework for the disparate information needed to organize a concept. It acts both as a checklist and a visual communication tool as you solicit feedback on your ideas.*
If you’re not familiar with the collection of methodologies referred to as Lean, don’t worry. The canvas guides us through a version of the process that my teams and clients have found effective without foundational knowledge (it helps). The high-level concept here is:
Assumption → Hypothesis to form your Customer Development Research + Experiments
The ProtoCanvas
Breaking it Down
User Goals — Also called ‘User Needs’. Captured here is a goal, need or desire that can be satiated by a customer through use of your product. The word ‘need’ implies that you’re solving a specific problem, the first step to identifying the value of your product.
We’ve found that Mental Frameworking can help to keep teams on-track and aligned with the vision behind the product. The broadest example of this is ‘we’re [successful company] for [problem/field]’ (aka “Uber for Cats” or “a better version of the Swarm ‘events’ tab”) This is also the space to quickly capture identified competitors or organizations that are doing something similar in a different field.
Assumptions are the key element of the ProtoCanvas. As you begin to brainstorm assumptions, you’re able to think objectively about your idea and the steps you’ll be writing into your hypothesis. (Ex. “Users have a problem getting cats” or “Users find more value in human curation”)
Hypotheses — Testing hypotheses is critical to product validation. Hypotheses are generally written as ‘We believe people like [customer type] have a need for (or problem doing) [need/action/behavior]’. The hard questions come after this;
What would indicate that the product is providing this solution?
What makes us think people will value it?
What is the simplest way to prove it?
Writing good hypotheses can be harder than you’d think. The point of the ProtoCanvas is to help clarify the information you’re looking to load into a hypothesis and understand how it will be measured.
The Measurement section of the canvas defines how we view success, our baseline, and how this data will be captured.
Output: Experiments, Clarity
The idea here is to turn to the ProtoCanvas as a tool to quickly jot down ideas in progress that need to be quickly communicated and understood by you and your team. The output of the canvas should be a clear understanding of what the product is and isn’t, who you’re solving problems for, what you actually don’t know as a fact and the experiments that you can use to prove yourself right or wrong.
You’ll notice there’s no place on the document to list experiments. This is because experiments can be anything from a question to a prototype, to a concierge system. These concepts are significantly more complex than a canvas could accommodate.
Download & Usage
The ProtoCanvas has been created as a Google Draw document for ease of use and real-time collaboration. See the canvas here and either ‘Make a copy…’ or ‘Download as…’ (both under ‘File’). You can also see an example of a completed ProtoCanvas here.
I’ve used this document for a number of consulting clients and all of my projects at Thirty Labs. I’m always improving the ProtoCanvas and I’d love your feedback.
The ProtoCanvas is licensed CC Attribution-ShareAlike 4.0 International
Thanks to Andrew Abshere and Jenn Ku for feedback
