Paper Planes SAAS Product
Paper Planes delivers advanced machine learning intelligence to streamline and maximize everyday retail management.
The Challenge
Retailers struggle to keep up with rapidly changing inventory, future demand, and consumer targeting. The legalized cannabis industry faces its unique challenges in needing to destroy expired products, adapt to constantly changing inventory availability, pair the correct product to the proper customer, and compete with black market sales. After a retailer's initial peek in sales from a recently opened store or a newly legalized state, sales quickly begin to decline, and mass amounts of inventory are being destroyed or sold at a loss from not understanding consumer demand.
Goals & Approach
The goal is to integrate advanced machine learning technologies seamlessly into everyday management, replacing lengthy reports, analyses, and inventory updates with prioritized recommended actions. This AI data intelligence would replace hours of work with one-click actions so retailers can focus less on repetitive, time-consuming tasks and more on growing the business. Leading this product build, I split the project into multiple phases: discovery, branding, product design, funding, MVP build, and pilot launch.
Discovery Phase
Competitive analysis
When researching direct competitors in the industry, we created a SWOT analysis for each and expanded into all cannabis technology sectors to understand the full scope of the supply chain and its flaws.
Product-market fit
Our detailed competitive discovery led us to find the specific technology gaps in the market where we can build a helpful solution. We call it "finding the spot no one is standing in."
Industry interviews
We also conducted comprehensive interviews with retail owners, managers, and employees to fully understand their current challenges, how to integrate improvements into existing workflows, and how to optimize employee operations.
Discovery overview
Overall, we spent about a year researching competitors, identifying industry gaps, and completing interviews. This approach was essential for understanding market demand and features needed before product design or pursuing funding.
Brand Development
A solid brand was crucial in developing this product to show visual consistency, competitor differentiation, and a unified voice & tone. I began developing a logo iconmark that can stand alone and visually represent the brand in a clever, identifiable symbol. I then continued building the brand's focus on being boldly visionary and always human-first, from content creation to product design. These brand characteristics become the foundation for creating all design assets, including website landing pages, email campaigns, social media campaigns, presentations, and overall product design.
Brand Design Phase
Logo concept
"Paper planes" is slang that refers to a rolled cannabis joint. I wanted to avoid literal cannabis leaf visuals and add personality that touches cannabis culture. I created a logo concept that visualizes a paper plane, with the center subtly being a rolled joint.
Brand concept
The mission is to humanize cannabis in data and life. The vision is to create the best human-centric intelligence for the cannabis supply chain. I developed an innovative, empowering, friendly brand voice with a human, inclusive, and approachable tone.
Website design
I executed the Paper Planes website, strategizing product storytelling, designing unique supporting illustrations, and using humourous, approachable brand content. I also implemented accessibility standards across the website for improved useability for all.
Launch assets
In preparation for the product launch, I developed additional marketing assets, including brand guidelines, social media templates, a marketing website design system, email campaign templates, sales collateral, and branded company gifts (investor giveaways).
The Solution
We developed Paper Planes, a SAAS platform with AI-driven suggested actions for daily retail management. As I led the product design and collaborated with chief officers to seek funding and present prototype demos, we successfully built our data intelligence product, providing predictive actions, consumer segmenting, and a user-centered interface design. Transform data into action.
Product Design Phase
Data architecture
With the CTO and lead engineer, we architected the technology stack, API layer, data models, and normalization across multiple data sources. Understanding how the infrastructure works for our machine learning engine was crucial.
User experience
I built the complete product design, from sketches to high-fidelity wireframes. The UX design went through multiple iterations with feedback from stakeholders and subject matter experts to ensure usability and quality assurance.
Figma prototypes
I created extensively detailed prototypes and design systems to showcase the product for demos and clients. They also serve as dev documentation, including animations, universal components, and variants for all user types.
Industry feedback
With a completed product design, we needed to seek feedback from multiple industry leaders and retail owners to point out edge cases and capture missed needs. This feedback helped to perfect the feature designs before the build.
Results & Impact
Collaborating with stakeholders, we funded our pre-seed round to build the full MVP product. With our engineering team and data experts, our joint effort launched a private MVP pilot with limited clients to train the machine learning model and analyze the amount of time/money saved when using the product. Early results and feedback have shown quicker decision-making and immediate identification of first-out products.
Funding Phase
During this phase, we presented our concept and prototype to various potential investors to fund the MVP build and validate the industry's need for this product. I focused on prototype presentations to show product value and collaborated with chief officers to run sales pitches. We successfully funded our pre-seed round to build a solid machine-learning foundation and complete a proof of concept.
Product Build Phase
Transitioning the product design requirements to engineering included a detailed walkthrough of the prototype, exported assets, and written documentation. Each feature requirement included the user story/goal, feature description, calculation/validation needs, and a visual or link to the prototype screen. I also introduced a detailed design system for engineers to build a universal component scheme for scalability and consistency.
MVP Pilot Launch
Like building any product, there were unforeseen complexities in the engineering, which led to a scope adjustment for the MVP. We worked closely with our development team to prioritize needed features and confirm what is possible within our timeline, budget, and limitations. Finally, we launched a private MVP pilot and onboarded limited clients to test our product, train our machine learning engine, and receive real-time feedback from users in the industry.
Future Steps
We have made incredible progress in building a solution to improve the retail sales experience, but products and user demands are constantly evolving. The private pilot will run for a year to understand how retailers use the product, what they like/don't like, and what additional features are needed. In future iterations, our priority will always be the user experience and making the product as intuitive and inclusive as possible.
Reflection
With Paper Planes, I have learned that knowledge is power and failure is a part of the process. A lengthy discovery and design phase was a lot of work, but it gave us the knowledge to identify market gaps and outline the feature sets needed. This led to insightful approaches to UI design, data-driven decision-making, and smooth requirements handoff to engineers. However, it is essential to remember that products constantly evolve, and failure is a part of the process. Research and knowledge can set you up for better approaches, but it's important to allow for failure and to know what fails to learn and act on a better solution. Learn constantly and design fearlessly.
