This is a guest post by Applico Product Manager Raffi Holzer.
If you're in tech, you're familiar with the term "Minimal Viable Product" (MVP). Meant to validate assumptions and maximize learning through minimal effort, an MVP can be as simple as an ad campaign and a pre-order sign up list to gauge demand. However, the most useful MVPs are prototype businesses where the primary value proposition is actually delivered to customers in a non-scalable way. So instead of software completely automating the core transaction, there are manual processes in place for the moment. The idea here is to avoid building expensive software to automate an interaction that lacks demand and interest.
Zappos founder Nick Swinmurn is perhaps the most famous practitioner of this form of MVP. He launched Zappos without a logistics infrastructure or automated backend (the tech stuff that goes on in the background to make digital businesses work). While these processes are necessary at Zappos' current scale, at the beginning, all Nick had to do was prove that there was demand for a better shoe shopping experience. To determine that, he put up a site with pictures of shoes and allowed people to place orders. He then went out to shoe stores, purchased shoes, and filled those orders manually. A classic MVP performance!
At Applico, we do this type of prototyping for platform businesses through Platform Modeling. The idea is to take existing commercially available and easy to use 3rd-party technology tools to fashion a working model to test out the idea's business viability.
Let's say you want to create a marketplace platform for graduation gowns; the platform would connect alumni looking to rent their gowns to graduating seniors and collect 20% of the total transaction for facilitating the exchange. The platform model functionality would look something like this for its producers (gown owners) and consumers (renters):
- list gown
- manage the rental availability of gowns
- receive payment
- search for a gown by school, location, and price
- message owner to request rental
It's fundamentally possible to test the viability of this marketplace with light resources. If assumptions about the market are correct, Platform Modeling is a cost-effective validation before investing time and resources into building scalable software that delivers automation for your marketplace.
The actual development of a marketplace business (connecting the software pieces together into a working whole) can be done in under 48 hours as long as you understand your platform type and the landscape of 3rd party services. To be clear, this approach we're outlining here involves no custom software development and will most likely be limited to web, not mobile.
Got a Platform Type?
We recently completed an engagement with a service marketplace business, so let's work with service marketplaces as an example. A service marketplace facilitates an exchange between a service provider and recipient, think Uber, Airbnb, Handy, etc. To build a working marketplace, we needed to understand the core activities that take place on this type of platform. For the purposes of this guide, let's say our service marketplace allowed a consumer to request a service from a producer.
We determined there were five basic activities a service marketplace needs to execute in order to prove the market viability (does my marketplace solve a problem?) of its concept. For the consumer/producer, respectively:
- view/post service,
- book/accept appointment,
- and send/receive payment,
and for the platform itself:
- and marketing.
Understanding the Landscape
For each of the activities listed above, there is an associated bucket of software tools that can be used to support it. The landscape of these tools is depicted in the image above. Briefly though, the corresponding tool required to build a digital marketplace are:
- Front-end builders
- Booking and scheduling tools
- Payment tools
- Automated marketing tools
- Analytics engines
Building your Prototype
By taking a tool from each bucket and integrating them appropriately, you can put together a prototype service marketplace pretty quickly. The only thing you need to remember is that as a prototype, this marketplace will necessarily be limited. The single biggest limitation is that not everything can be automated; there are going to be manual processes involved.
For the service marketplace we worked on, we started with a front-end web builder. We built a beautiful site where customers would be able to log on and view the various services and service providers. We created a quick text-based logo, uploaded it and a couple of images, and we were off to the races. 20 work hours elapsed for this process.
We then did our homework on booking and scheduling tools. We needed a service that would be compatible with our front-end website tool and would allow multiple service providers to update their availability and accept appointments. Finding the right service took a little while but plugging it in was a snap. We then linked the scheduler to our email and calendar so we'd receive notifications of bookings and we were on to the next step. This process took 20 work hours.
Connecting a payment tool was a breeze. We tested the payment functionality by paying ourselves to ensure everything was working properly. We spent 4 work hours on this task.
Now we needed to get the word out through marketing. We designed a few ads and defined our target strategy. We also rounded up as many emails as we could to combine a direct mail campaign with our social media ad buy. With a few hundred dollars in advertising and some good design work, we had requests rolling in. The execution took 4 work hours.
When it came to analytics, our main goal was to calculate the percentage of people who saw our ads and followed through to book our service. This data helped inform our understanding of the idea's market viability. For our purposes, all the metrics were tracked by our marketing and front-end tools. However, if you need to measure a KPI that isn't tracked by those tools, there are plenty of other available options. The key is to prioritize what metrics matter and track those effectively. From there, it's a matter of experimenting quickly to see what moves the needle forward.
Like with all other 3rd party services, analytics engines are a breeze to set up. Throwing in a few extra hours when analytics is needed and you are still near 48 work hours to set up a working prototype service marketplace. After you've successfully tested your idea, the next step is achieving product-market fit, which will require custom mobile app software development.