It takes a community to build a much loved and consistently-used product. No matter what services you personally today, whether it’s Airbnb, Twitter, your phone...they’ve all gone through extensive market research and trial-and-error to arrive at the product that they did. This process is called product iteration, and it’s an on-going cycle of product development, feedback, measuring and learning, then developing again. At Metaranx, we often discuss how we started this company and what we thought it would be at that time. Metaranx evolved into a no code artificial intelligence (AI) platform by speaking with potential customers to create a product that made sense. Due to working with an iterative model software development life cycle for product development, we’re able to have rapid turnaround on our early product. Below, we explore how the Metaranx product changed over a few short months.
Our first idea for the platform
Our early stage idea was a software platform that had a series of marketing-focused artificial intelligence tools. As I was a content marketer at the time, with an expertise in content, SEO, keyword research, and other topics related to organic marketing, we believed we could automate these tasks. We knew from experience that organizations, especially small-to-medium businesses (SMBs) had a pain point with not being able to produce enough valuable content in a timely manner to compete in organic search. A lot of these SMB decision makers also did not understand what went into creating a successful content marketing strategy. We wanted to alleviate this burden through artificial intelligence at a low cost.
We did some target market and competitive landscape research. We discovered that SMBs spend the smallest amount on marketing efforts, and that it may be difficult to convince that market to spend on artificial intelligence tools. Further, we struggled to find companies that competed in this space - many were hyper-niche, offering their product as an application for specific use cases, such as through Wordpress or Shopify. After presenting our product to a few people in the tech industry, we discovered that we were late to the AI marketing technology game and we should explore other options.
Our pivot to the no code AI builder
During the process of building our martech company, we were also quietly building something we referred to as AIMS (Artificial Intelligence Management System) in the background. We thought it would be a great feature for our platform but after our research, decided to make it our full focus. The idea behind AIMS was to allow anyone to build AI applications without having to code. Lisen Kaci, our CTO, had noticed a lot of patterns, obstacles, and trends when building artificial intelligence tools. He wanted to streamline the process so that anyone could achieve their AI goals. Research told us that this was the future of not only artificial intelligence, but of no code and low code platforms. We felt that we were on the right track and decided to launch.
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Our product demo from March 2020
Speaking to users
We were able to speak to members of the no code community to get their feedback on our initial product. What we had built was still far too complicated and did not make artificial intelligence an easy-to-understand topic. One user pointed out on MakerStreams that they wanted to feel empowered when building on our platform. We knew we had to shift to a product that made building AI applications a process that wasn’t intimidating or overly-complex.
Our revamp of Metaranx’s console front-end
We went to work creating a more intuitive platform that clearly outlined your AI goals and pushed you through the process to achieve those goals. We built a data editor that simplifies creating labeled datasets, whether you’re a data scientist or a no code builder. We built a platform that made AI application building a breeze by only showing you items that are relevant to your exact AI goal - ideal for programmers or no code developers.
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Our product demo from May 2020
Where we go from here for product iteration
Once our closed beta is released, we will be reaching out to our sign ups to allow them to use our platform to create an AI application. We will then speak with our users to see if they feel our product allows them to achieve their AI goals with ease. We will be measuring how users interact with our product, where they get stuck, where we lose a user, and what our users love most. On our marketplace, we will see what items users need most so we can be sure to source more of those components. We will also be taking in information about features people may want our platform to offer. From there, we will modify the platform until we’re ready to launch our open beta later this year.
Product iteration is an on-going cycle of development and learning that never ends for any company. There are always ways to grow and improve your product, and you can’t do it without your community of users. Thanks to those willing to sit through demos, be beta testers, and discuss their experience with you, you’re able to learn valuable information that ensures you can launch the best possible product for your target market.