Viewst

Victoria Dubin's journey to founding Viewst reflects a non-traditional path. After earning her MS in Physics and Applied Mathematics, she spent 10 years in investment banking, progressing from analytics to trading and project management. Though she was an accomplished tennis player (competing from age 4 and earning money from coaching), she didn't transition to tech until later in her career. In 2020, at age 33, she launched her second startup, Viewst, targeting a massive market pain: enterprise marketing teams and big brands managing daily ad budgets of $25,000–$30,000 needed better tools to produce, test, and scale banner variations across channels.

Viewst began as a product-market exploration. Victoria and her team built a tool that combined ads production with project management and scaling capabilities. Rather than jumping straight to enterprise features, they used Appsumo as an initial testing ground to gather feedback from marketers and small businesses. While Appsumo users paid one-time lifetime deals (not the ideal enterprise motion), the platform provided invaluable feedback and user insights that shaped the product direction. The core insight emerged: enterprise marketing teams doing massive testing volumes needed an "simple and affordable tool" to manage variations, automate resizing, and streamline A/B testing workflows.

On the AI front, Victoria was pragmatic. Rather than chase the trend of AI-generated visuals—which weren't yet viable for high-quality banner work—she focused AI on practical, high-impact features: background removal and intelligent resizing across different ad formats. This showed disciplined prioritization.

The transition from individual Appsumo users to enterprise logos happened gradually. The first corporate customer signed in August (several months into the interview), marking a watershed moment. With 15 enterprise customers by the time of this interview, Victoria had cracked the logo acquisition playbook. Each customer signed annual contracts starting at $12,000 for five team members, with pricing scaling as teams added more members. The sweet spot turned out to be 7–10 person teams, with average contract values around $20,000 annually.

Notably, all growth to date had been organic—no paid marketing, no sales team. Victoria credited the product's fit with the market pain and word-of-mouth from satisfied customers managing massive testing workflows.

Viewst's traction tells a remarkable story: from $300 MRR one year prior to $15,000 MRR represented 50x growth. More precisely, the company grew 76% month-over-month over the preceding six months (though Victoria acknowledged the low base effect). The pricing model worked: starting at $12k annually for small teams and scaling naturally as customers added team members created predictable expansion revenue.

What didn't work was the first venture. Victoria shut down her prior startup after years of decline, later reflecting that she should have cut losses sooner. That painful experience shaped her decision-making: when numbers say something doesn't work, stop. She applied that discipline to Viewst, pivoting away from Appsumo once it became clear the enterprise opportunity lay elsewhere.

Victoria raised $1.5M on SAFEs at a $10M+ valuation cap, validating investor confidence despite the low MRR-to-valuation multiple (roughly 55x). She had also received a $20M acquisition offer, but declined it—partially cash, partially equity in the acquiring company. Her reasoning reflected founder determination: she loved the work, saw massive potential, had built a strong 11-person team (7 engineers), and wanted creative freedom after a decade in corporate banking.

With product-market fit confirmed, her next moves were disciplined: hire 2–3 more engineers, test marketing hypotheses (currently zero marketing budget), and potentially hire junior sales. She was inspired by Basecamp's lean approach and wanted to grow thoughtfully rather than explosively. The team composition—11 total with 7 engineers—reflected deep technical execution, and her vision was to invest the capital in go-to-market experiments while keeping the team lean and focused on product excellence.