Risks & Mitigations

Early Growth

One of the key risks associated with our business model is that the app cannot facilitate connection if you have no friends on it. Early growth requires a different approach than simply making the app available in the app store. Whole groups of friends need to be made aware of the app and be motivated enough to download it. To address this risk, we will use a strategy similar to the one BeReal employed in its early days to facilitate its growth. We will sponsor university events and partner with student organisations to actively build a presence in student communities. This way, we aim to create dense pockets of adoption on individual campuses before expanding to others. Similar to how Facebook also initially grew, a strong university identity and word of mouth make it more likely that entire friend groups join together rather than isolated individuals.

Competition

A related risk is competition from the existing large social media platforms. In theory, Instagram or TikTok could observe our connection features and copy them into their own products. However, these platforms profit directly from the very behaviours we are trying to reduce. They don't necessarily have any reason to implement these features, as it would directly compete against their business model. Big platforms may implement superficial measures to promote connection, but they will never implement the connection-first design of the Mannequin platform.

Revenue Model

Another risk is related to our revenue model. We expect around 15% of users to subscribe to our premium subscription service Mannequin+. If there is not enough value to this premium subscription, our initial revenue forecasting will not be met. To mitigate this, we are in constant contact with our target demographic and are continuously designing unique features that elevate the Mannequin experience for those willing to make such a purchase.

Content Moderation

Finally, content moderation and data protection are risks we take seriously. However, we also greatly prioritise privacy. To ensure that our privacy demands are met even when it comes to moderation, we will run a locally hosted AI model on a dedicated server that automatically flags potentially harmful content. This means sensitive data is not processed by third-party services or even accessed by Mannequin. Users whose content is flagged will have the right to appeal, and only at that point will a human reviewer evaluate the relevant post. Users will also be able to report content directly. This approach allows us to stay fully in line with GDPR and the privacy promise we give as part of our platform.

For a more detailed overview of our business model and financials, you can download our pitch deck.