Customer Research Insights:
Customer Research Insights:
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The Messy Middle Between Creating and Posting
Benjamin’s interviews revealed a common frustration: finishing a design doesn’t mean the work is done. One participant described the tedious routine of exporting a Canva file, sending it to their phone, uploading it again, and only then posting. Jen’s interviewee shared the same issue — creative tools and social platforms rarely work together seamlessly.
Takeaway: The challenge isn’t creativity itself but the constant switching between tools. People want one connected space where they can create and share without friction.
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Getting Started and Making It Feel Personal
Eugene’s participants often said the hardest part was simply getting started. One mentioned struggling to “find something worth doing,” while others described AI results that looked polished but lacked substance. Armita’s group found similar patterns — users often have an idea in mind but no clear way to shape it across tools like Pinterest, Figma, and Canva.
Takeaway: Users don’t just want faster tools; they want help turning half-formed ideas into something that feels authentic and personal, not generic or templated.
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How People Think About AI: Trust and Control
Most of Armita’s interviewees said AI graphics “don’t work half the time” or feel too mechanical. Eugene’s group described a similar sense of detachment when AI took over too much of the process. One person compared it to outsourcing art: “The concept might be mine, but the soul isn’t.”
Takeaway: Creators want AI to assist, not replace them. The ideal tool enhances human intuition and creativity rather than automating it away.
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Time, Frustration, and the Will to Keep Going
Across Eugene’s and Armita’s interviews, slow workflows repeatedly surfaced as motivation killers. An interviewee said it can take “eight to ten tries” before he’s satisfied with a design, while Romy mentioned that under pressure, she’d rather modify an old layout than start from scratch.
Takeaway: Speed and flow matter. When the process feels fast and forgiving, people stay motivated and produce better results.
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Taste Still Matters
In Armita’s and Rushank’s conversations, one theme kept resurfacing: automation can’t replace taste. As one participant said, “Taste is your edge.” Even as AI tools become more advanced, users still value having a distinct, human touch. Many noted that current outputs feel too similar—clean but bland.
Takeaway: The opportunity isn’t to replace human taste but to enhance it. The best systems will adapt to each person’s creative style and strengthen what makes their work unique.
Link to interview transcripts/notes:
Benjamin’s Interviews: Interview 1, Interview 2
Eugene’s Interviews: Interview 1, Interview 2
Jen’s Interviews: Interview 1, Interview 2
Rushank’s Interview: Interview 1, Interview 2
Armita’s Interview: Interview 1, Interview 2
Competitive Analysis:
Canva: Canva is a key direct competitor of SnapEdit, offering a value proposition closely aligned with what SnapEdit promises: accessible, high-quality creativity for non-designers. The platform offers a freemium business model split into three categories: a variety of features for free access, a monthly subscription option, and an enterprise plan with customized pricing for businesses. What particularly stands out is the workflow integration and consumer lock-in strategy employed by Canva: the platform starts out simple, but offers advanced features, collaboration opportunities, and AI tools. This creates a competitive moat for Canva: by capturing the entire user journey, it eliminates the need for switching to alternative platforms. This creates high entry barriers for companies like SnapEdit, whose value proposition may capture a niche aspect of Canva’s broader ecosystem. Another key strength is Canva’s cross-device continuity, allowing users to access it both through mobile and desktop syncing (SnapEdit lacks the latter). The wide audience of users Canva has also provided it with data advantages that can help significantly improve its AI model’s effectiveness over time.
Adobe Express: The platform uses a freemium model, offering a free version with certain features, a pro plan, and a firefly pro feature for people who want advanced capabilities in AI image creation. Adobe represents a tradeoff between image quality and complexity, and this pricing model aids with this. Specifically, users can determine their specific needs, and based on that, decide the financial and time investment they plan to place into the platform. By doing this, Adobe captures a broader market than if it were to solely focus on one customer segment. Furthermore, Adobe benefits from trust, brand credibility, and reputation. When considering top design/editing tools, it is one of the first thoughts people have. This contrasts to a company like SnapEdit, that needs to establish a name for itself to build customer loyalty long-term. Adobe’s approach also highlights the need for SnapEdit to differentiate itself not solely through ease, but through a functionality or unique value proposition that Adobe doesn’t otherwise offer.
Midjourney: Midjourney offers a tiered subscription model, charging $10 for the most basic functionality and up to $120/month for more advanced features, with usage tied to GPU hours and generation modes. The platform collapses the act of “editing” into “prompting,” helping users create high-quality images within seconds. Yet, the trade-off is control; while the results are often of a high caliber, they are not always editable or brand-consistent. This can introduce frictions to the experience, hindering users from attaining the images they need. This creates a wedge for SnapEdit to position itself as the post-generation editing layer, where AI is used to automate workflows while still retaining autonomy for the user. Another key aspect of Midjourney’s approach is its integration into Discord. This has helped transcend image generation from an individual to a social activity, helping to create strategic network effects. At the same time, Midjourney is merely focused on the image generation aspect rather than broader workflow integration, creating yet another opportunity for SnapEdit to differentiate.
DALL-E: The business model is split between ChatGPT subscriptions and per-image API pricing for developers. DALL-E’s moat is derived from its distribution channels; image generation is already embedded into environments where users return to daily, such as ChatGPT and partner applications. This lowers perceived switching costs for users, and reinforces dependency on the host platform by offering this added functionality. At the same time, this breadth of integration can lead to generic outputs rather than specialized results tailored toward the user’s specific use cases. Furthermore, some creatives may intentionally want to diversify their platform use to not increase dependencies on a single tool. SnapEdit could effectively compete with DALL-E by promising an independent platform. At the same time, similar to other well-known tools, DALL-E benefits from brand credibility and signaling power, and the low switching costs/frictions to adoption make it a highly viable tool.
