An inside look into how Lata Data partners with Parke to build the analytics, forecasting models, and data infrastructure needed to understand demand, optimize product drops, and support data-driven inventory planning.
Overview
Parke is a rapidly growing fashion brand that operates on a drop-driven model, where new collections generate intense demand and frequently sell out within hours. As the brand scaled, the team faced increasingly complex questions around demand forecasting, inventory planning, and understanding the drivers behind product performance. Lata Data has worked closely with Parke to build the analytics systems needed to better understand demand patterns, evaluate product launches, and support data-driven decision making across inventory planning, product strategy, and marketing.
The Approach
Like many fast-growing brands operating in a drop model, Parke experienced explosive demand around new releases. However, the speed and volatility of these launches made it difficult to answer critical operational questions: - Which products, colors, and sizes were actually driving demand? - How quickly were products selling through after launch? - What quantities should be ordered for future releases? - How should size and color allocations be adjusted? Traditional analytics tools were not designed to capture the unique demand dynamics created by product drops, where sell-through can occur within minutes and demand patterns shift dramatically between releases. The Parke team needed a system that could transform raw Shopify sales data into clear insights about demand, inventory planning, and product performance. Lata Data partnered with Parke to build a comprehensive analytics framework designed specifically for drop-driven brands. This work focused on four key areas: 1. Post-Drop Performance Analysis After every product release, detailed performance analyses are conducted to understand how the drop unfolded. These analyses include: - SKU-level performance breakdowns - Colorway-level and size-level performance insights - Sell-through velocity analysis showing how quickly inventory moved over time - Identification of products that sold out prematurely - Estimation of revenue left on the table due to stockout This allows the team to identify which products, colors, and sizes are driving the strongest demand and which underperformed. 2. Demand Forecasting & Inventory Planning To support future product launches, custom forecasting models were developed to estimate demand at the product, color, and size level. These forecasting systems include: - Demand forecasting scripts analyzing historical sales data - Three-phase sell-down projection models - SKU-level velocity modeling - Size curve forecasting - Purchase order and inventory planning projections These tools help the Parke team make more informed decisions about: - How much inventory to produce - Which products to expand - How to allocate sizes and colorways across future releases 3. Data Infrastructure & Automation In addition to analytics models, Lata Data helped build the technical infrastructure required to capture and organize the brand’s data. These included: - Custom sales data reporting dashboards integrated with live Shopify order data - Custom influencer gifting management platform - Social media data pipelines to track Instagram and TikTok data and signals 4. Strategic Analytics Partnership What began as an initial data project quickly evolved into an ongoing analytics partnership. Lata Data now works closely with Parke on an ongoing basis to: - Analyze every product drop - Identify emerging demand trends - Refine inventory forecasting models - Support product and merchandising strategy This allows the Parke team to approach future launches with significantly greater visibility into the demand patterns behind their business.
The Result
Through the implementation of structured analytics and forecasting systems, Parke gained significantly deeper visibility into the performance of their product launches. The analytics framework built by Lata Data now enables the team to: - Understand demand patterns at the product, color, and size level - Identify sell-through velocity and revenue lost to stockouts - Make more informed purchase order decisions - Analyze influencer and marketing performance - Approach each collection drop with clearer data-driven insights As the brand continues to grow, these analytics systems provide the foundation for more informed decision making across product development, inventory planning, and growth strategy. Parke’s growth highlights a broader trend across modern consumer brands: product drops create demand patterns that traditional retail analytics tools were never designed to capture. By building analytics frameworks specifically for drop-driven brands, Lata Data helps teams transform the massive amount of data generated by each release into clear insights that guide future launches.