Precavida | caique

How I set up and ran a health tech startup accelerated by MIT and Techstars

CONTEXT

Precavida is a health tech marketplace with a personalized navigator that connects patients and healthcare services. During its incubation in MIT delta v, Precavida had the opportunity to prove its concept, and as a Techstars 2020 class member, our mission was to run its business model in an MVE (Minimum Viable Experience) fashion and find the product-marketing fit.

IN THIS CASE

Customer Behavior Analysis & Journey Mapping

Rapid Prototyping & Validation

Roadmap Planning, and Implementation

CHALENGES

1) To build a cheap functional product that delivers value for the patients, as well as validate the business hypothesis, generating consistent learnings to base the pilot roadmap

2) The COVID-19 outbreak, which challenged us to pivot the business operation model about to start the MVE, from in presence to telehealth

3) Attract investors by evidencing a relevant product-market fit, based on real achievements during the MVE phase

MY ROLE

• As the product leader, my role was to design the main customers' profiles and the journeys the product would serve, defining during this process the conversion funnels that we'd validate

• As a second step, create a very lean, fast, and cheap digital product structure to support the operations, and the customer experience delivery

• Finally, to compile useful learnings, and experiences, gathering enough information to design an action plan for national traction

DIRECTLY RESPONDED TO

LAÍS FONSECA

CEO

WHAT WE DID

Designed two main customer journeys to experiment

• Even though the service concept in a mature stage could have many ways to deliver the value proposition, in the current stage was fundamental to consider only what we believed was the core of the business. Those services were "consultation booking for doctors" and "lab exams quotation and booking"

Developed the digital product without code, but with lots of experience, and API integrations

• The purpose here was to have a digital product flexible enough to support every test that we considered relevant, spending more time designing the experience instead of the code. A codeless product also means to be able to make rapid changes over the operation, avoiding concerns about extensive development, QA processes, or bug fixes.

• At the same time, we integrated third-party platforms in order to automate some tasks (notifications, e.g.), and speed up the product release. This was fundamental to focus on customer experience and operational process planning.

Pivoted the model to respond to the COVID-19 outbreak and made sure to have a tuneful back-office operations

• The Coronavirus outbreak came about one week before our release date. The patient consultations planned to happen in person would have to be online, and the doctors would have to be trained, both in a short period of time. So, we made it first integrating a video call platform, which was chosen based on two factors: easy for the patient to attend the consultation, and effortless to implement.

• In the back-office, we hired a young nurse, very familiar with the digital environment and healthcare procedures. Her mission was to take care of the doctor's side, which was pretty different from the original format, considering that nobody was used to telemedicine. This way we prevented doctor's insecurity, dropouts, and ensured their engagement.

Tagged the funnels and analyzed the learnings

• From the acquisition channels to the patient aftercare, we tagged the whole path through the funnels. This was not just to measure the KPIs, but as well as to understand how the customers were using the product, the value proposition perception, and to get evidence that (in)validates our hypothesis. The team's daily talk about operation findings, customer behaviors, and metrics was key to map relevant learnings.

OUTCOMES

Validated hypothesis

Running the service with real customers made us able to validate the minimum viable experience, as well as to model the communication hooks of acquisition, engagement, and conversion. In the same way, we have found out the references of fundamental metrics like CAC, CTR, and conversion rates related to our public, geographic region, and services offered.

Product architecture

To define how a product has to behave is something tough. Although, when a multidisciplinary team really experiments the whole customer flow with real clients, even using a "manual" version of the product, the product vision becomes much more clear. This was one of the biggest outcomes: a concrete roadmap of the product architecture design and its needs to get the targets.