RFID-based Grow Management Platform
Led the product design and development for an RFID grow management system for the cannabis space—from concept to MVP and pilots.
This was a complicated project due to the newness of government requirements and regulations in the cannabis space, and the general lack of technological sophistication of most commercial growers at the time.
Working with the company's CEO, I helped his team build and manage a development backlog, refine feature prioritization, interview clients, and oversaw the development project for more than a year.
The project was technically tricky in that it covered a vast array of technologies: cloud backend and web application, a native mobile app with RFID reader integration, fixed infrastructure RFID readers, and on-site middleware. In addition to the wide variety of technologies in play, the system needed to meet various government (and sovereign nation) reporting and auditing requirements, most of which were not well defined as we were developing the system.
MomCo App
Led product management and development activities through 7 quarters of >30% user growth and $300,000 in seed funding raised.
The MomCo app was a mobile app (native iOS and Android apps) that used geolocation services to help moms find other moms with similarly aged children near. The app also promoted company hosted playdates and other events around the US, private mom groups, and a host of other features.
The app was featured on the Today show and attracted more than 50,000 moms to the platform. The engagement and adoption that the app was able to generate attracted $300,000 in seed funding during my tenure with the company.
With the ability to get moms (a highly valuable demographic) to attend events and provide feedback on products and services that were available to try at these events, we started work on developing features to allow the app to be used as a virtual consumer panel. We did this so we could sell access to selected collections of moms to brands that wanted to sell to that demographic. This was an exciting expansion opportunity for the platform.
eCommerce Data Analytics Platform
Led the product design and development for eCommerce analytics tools—enabling client YoY revenue growth >400%.
The client is an online retailer looking to optimize the allocation of their capital across hundreds of thousands of products that they could potentially sell. Adding another level of complexity, the client was also selling established products on Amazon, which meant there was dynamic competition, pricing pressure, and other factors present that made demand and price forecasting particularly tricky.
Working with the client, we devised an ideal workflow that would enable maximum efficiency and automation. The workflow would use algorithms to identify potential products from Amazon's 450 million item product catalog that might be good performers for the client to sell.
The algorithms would add brands to a sales pipeline tool where workers would process the leads and attempt to establish relationships with the manufacturers and obtain pricing information (and other logistic information). The workers would then submit that data to another software solution that would perform an in-depth financial analysis of each product, including leveraging several machine learning algorithms, to identify the optimal inventory investment mix that the business could act upon. This efficiency allowed the company to scan hundreds of thousands of products.
Accounting Analysis and Reporting Platform
Led product development for a full-service accounting firm to bring an analysis and reporting SaaS platform to market.
The client was interested in building a SaaS product to replace in-house financial analysis and reporting spreadsheets and other AIS tools they used with a more automated and integrated web solution that could also be sold to other firms.
The client being a full-service accounting firm had no in-house technical resources or any experience bringing technical products to market. For this project, I worked with the client as if I were an in-house CTO.
In my role as fractional CTO, I worked with the client to capture and refine their product vision and requirements, decomposed those product requirements in to user stories, and defined the technology stack and system architecture for the project. Once this up-front work was completed, I managed a vendor selection process to qualify on- and off-shore development firms and guided the client through the partner decision making process. Once the development firm was selected, I worked with them constantly throughout the project to both manage the agile development process with them, serving as the product owner, but also in managing user acceptance testing and other responsibilities of the client, while transparently communicating project status, issues, and so forth to the client.
Voice Analytics Data Product Management
Delivered a comprehensive MVP package for a new voice analytics product: market research, strategic definition of what the MVP should be, economic analysis of the proposed MVP, evaluation process for technology partners, and detailed user stories.
For this project, I worked on defining what the MVP of a voice analytics product should look like.
I presented an in-depth analysis of the marketplace, from the perspective of who the players are, what business models are in play, what technology relationships exist, and what each competitor's offering looks like.
I worked with several existing and potential customers of the clients to identify their pain points, concept test potential product features and business models, and really try to understand how these technologies could create value in their organizations.
With this information, I developed an MVP concept, including which features should (or should not) be a part of the MVP (and what a feature roadmap might look like—similar to a PRD), as well as a few business model options and how each of the models might perform (considering various development cost scenarios combined with different operational cost and pricing models).
After receiving buy-in from the client's stakeholders, I worked through the MVP definition and created user stories to break down and describe each of the MVP's features, and technical evaluation and selection criteria for the technology partners that I had previously identified.