Stryber’s approach // #1 Research vs. Signal Based Ideation

Stryber’s Venture Building Framework: How our signal-based approach complements research based ideation

When startups fail, it is most likely because they built a product that no one wants.

Venture studios systematically create startups, many of which succeed in the market. To achieve this, they develop and adopt ideation methods to ensure that they are creating the right products, the right value propositions for end customers.

Over the years, various approaches to systematic ideation have been developed, each with its own characteristics. At Stryber, a key differentiator is our market-driven and signal-based approach, which we complement with other ideation methods to derive a full picture.

In this article, we would like to give a brief overview of how to build startups that people actually need by introducing three major categories of ideation methods:

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Problem-driven Ideation

Also called bottom-up ideation. Here are some popular methods:

• Human-centered design: This method is centered around discovering customer pain points through interviews and observing customers in their daily lives. Following that, coming up with solutions to those discovered pain points.
• Brainstorming: The venture team discusses together to generate creative ideas to solve a problem
• Sticky note ideation: This is to brainstorming, as Scrum is to Agile. It is a codified way of brainstorming, using the help of sticky notes to tangibly see, imagine, and organize thoughts and generate even better ideas.
• Design sprint: Design sprint is a highly codified method, in which a team completes the following in a single week - finding problems to be solved, creating a prototype, and testing the solution with customers. This method is a reverse of human-centered design, because it starts with designing potential solutions first before talking with customers.  

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Market-driven Ideation

Also called top-down ideation.

• Research study: In this method, ideation is done by gathering and analyzing large amounts of quantitative and qualitative data from literature, interviews, and focus groups. This can be quite time consuming and expensive, but it is a good fit for incremental innovations.
• Signal-based Ideation: In this method, the venture team goes through a database of market signals - startups that have shown traction in other geographies. Traction data gives confidence that 4 things are true: 1) that there are customers with the pain point, 2) the solution solves the pain point, 3) the solution can be built, and 4) the market size and unit economics work. Stryber has seen great results from startups derived from this ideation method, and has recently augmented this with AI.

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Other Ideation methods:

• Founder-led Ideation: In this method, a founder is brought in with an idea for a venture. The founder champions the project and does the necessary pivots to implement and improve the idea. This method relies on serendipity as the ideas generated are dependent on the founders brought in.

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Stryber’s signal-based ideation process creates a list of emerging proven business models with a strong chance of success when adapted to a new locale. This was essentially the playbook of Grab and Gojek in Southeast Asia - they took the signal from Uber, which showed a lot of emerging traction at the time, and adapted the ride-hailing model to become regional unicorns.

The signal ideation process can be thought of as a funnel, starting from a database of startup signals which is filtered through multiple stages to obtain the best signals and ideas.

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Signal-based ideation is not as straightforward as copy-pasting value propositions and business models, however, for 3 reasons:

1. Signals with higher traction are more likely to succeed, but quantifying traction can be challenging. There are many data points that can be used to do so, which might result in different signal selections.
2. Each geography and market is different: demographics, income levels, and cultural considerations are among the many factors that complicate the selection process.
3. There are many signals - over 3 million of them. In order to choose the right one, one has to traverse a large amount of data, classify and categorize them, and make the right selections.

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At Stryber, we solve these problems with three solutions - of which AI is the latest addition.

The first is the Stryber score and the momentum score. These are complex measures (our secret sauce) to assess existing startups’ signals of success which help to derive first insights for potential new business models for our clients. 

The second are strategic filters combined with market research, user and expert interviews. We look at a variety of factors in evaluating a signal’s value proposition specific to a particular investor’s agenda - e.g. strategic relevance, speed to market, relevance in target geography, etc. This gives us a deeper understanding as we go further into the idea funnel.

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The last one is the most exciting, and one that we will dive deep in upcoming articles. At Stryber, we have been developing a proprietary AI system that helps us categorise startups based on their value propositions and business models. This gives us ‘market maps’, which help us to precisely choose which groups of startup signals to evaluate. As an example, if we want to look for ideas to solve problems around home affordability, we can directly zoom into those AI categories and find the relevant startups very quickly.

In the next articles of this series, we will explore further how our AI-powered signal-based ideation can help your organization to find the best startups and ventures to build. Stay tuned!