Challenge
Forecasting Demand With Seasonal Constraints Amid Rapid Growth
Yasaman Bakhtiar and Leah Marcus co-founded Good Girl Snacks after noticing that Gen Z women were obsessed with pickles — but saw no brands speaking directly to them. So the duo built a bold, social-first brand that transformed a grocery staple into a cultural moment.
By 2025, the company had turned its online momentum into retail placements and set a goal to 10x sales. But their operations weren’t designed to support that level of growth. “We had a scrappy system that worked early on, but it wouldn’t support where we were going,” Yasaman explains.
Given the nature of the product, planning has always been complex. To uphold clean-eating values, Good Girl Snacks exclusively sources organic cucumbers. The product’s strict seasonal availability meant Yasaman, who manages sales and marketing, needed to forecast nearly a year’s worth of demand in advance, while balancing growth rates that could change from month to month.
To keep up, Yasaman and Head of Operations Aashika Jikaria built a highly manual inventory in Google Sheets. It ensured they had eyes on every input, but also required constant actuals and inventory updates across multiple tabs. And without a standardized way to incorporate historical performance data, forecasting was dependent on subjective predictions.
Even with this level of manual oversight, demand was difficult to predict. Viral social media moments could drive sudden spikes in sales, making forecasting less reliable. Even purposeful growth — such as adding retailers, channels, and products — introduced new variables.
Ultimately, without confident projections, they risked locking up valuable cash in excess inventory, missed sales, and strained relationships with retailers. Given their lean three-person team, scaling efficiently — without adding headcount — was the only viable path forward.
After a $3 million fundraise, Yasaman went searching for a sophisticated, AI-driven solution that could flexibly adapt to their business. The platform needed to be intuitive and easily integrated into their busy daily workflow.
Having used Moselle at a previous food and beverage company, Aashika introduced the platform to Yasaman, who quickly realized Moselle’s simple interface and AI-powered forecasting were exactly what Good Girl Snacks needed to scale.
“Forecasting in spreadsheets alone took us as far as it could, but we knew we were ready for more. We wanted to leverage AI to make sure our previous learnings were powering our future product launches.”
Solution
A Bespoke Planning Partner Built for Reactive CPG Growth
Onboarding was fast and intuitive, with Shopify and key channels integrated on day one. Within weeks, Yasaman and Aashika had a clear view of inventory, demand, and purchase orders across 11 sales channels.
Today, Moselle fits naturally into the team’s existing processes, pairing the familiarity of Google Sheets with AI-informed forecasting and insights.
At the core of their workflow is Mo, Moselle’s AI layer. Mo generates dynamic reports on demand and inventory performance across channels, which Yasaman and Aashika use in weekly S&OP calls to make real-time decisions.
They also use Mo to quickly turn new retail assumptions — like door count and sales velocity — into inventory and demand forecasts. Because their data is automatically updated, when a SKU trends on social or a wholesale reorder comes in, they can immediately see the downstream impact across demand, inventory, and cash.
The system continuously learns from actual performance to improve future predictions, with no manual input required from Yasaman or Aashika. Over time, this has made forecasts consistently more reliable. “We’re now confident we can match supply to demand throughout the year, even with a seasonal product like pickles where production windows are extremely limited,” Yasaman says.
By leaning into tooling purpose‑built for food and beverage supply chains, Yasaman and her lean team now do more with less. They’re confidently expanding into new channels like TikTok Shop and Amazon and launching new SKUs without adding headcount or putting cash flow and sales at risk.
The Moselle team itself has been a key part of the value, remaining accessible via Slack and responsive within the hour. This built‑in support has been instrumental in high‑stakes moments, from refining board‑ready metrics to preparing investor‑grade fundraising materials.
After trading manual firefighting for a scalable operational engine, Good Girl Snacks finally has the right foundation to support its next stage of growth.
“Mo doesn’t replace what we’re doing — it enhances it. We’re able to use our own systems with Moselle to move faster and make better decisions.”
Results
Good Girl Snacks Gains Real-Time Visibility Across 11 Sales Channels
With Moselle, Good Girl Snacks has the visibility and flexibility to respond quickly to demand shifts, plan confidently around seasonal production windows, and support rapid growth without adding operational complexity.
Since adopting Moselle:
- 63% higher forecast accuracy in 4 months
- 11 sales channels integrated into one dashboard
- 10x growth goal supported without expanding core team
- 90% of produced inventory sold through
Looking ahead, Good Girl Snacks plans to integrate more of its tech stack — including its EDI — with Moselle, as well as onboard their fractional finance team.
“Scaling in food and beverage can be incredibly hard. Moselle gives us the infrastructure to grow our brand without needing a huge team.”
Want to see how Moselle can unlock planning automation for your business? → Let's chat.
