PopSockets Turns to Unified Data to Power AI-Enabled Inventory Precision
Phone accessories brand PopSockets has invested in its data foundation, implementing a unified system that gets it ready for AI-enabled capabilities.
The company has historically relied on manual, time-intensive processes to track and analyze point-of-sale and inventory data, leaning on Excel spreadsheets to compile weekly reports from retailers and brokers.
It was a process that wasn't sustainable at scale, says Kyle Chu, senior manager of business intelligence and financial planning at PopSockets. It wasn't timely or granular enough to be actionable.
[Also: Kyle Chu was a member of CGT's inaugural class of Data Leadership Award winners]
To expedite timelines and improve decision-making, the company sought to consolidate this data and automate operations in 2024, moving away from "the cycle of downloading and stitching spreadsheets together" and toward real-time visibility.
To achieve this, PopSockets partnered with Crisp, with analytics integration support from Snowflake, to unify data sources from retail, e-commerce, marketing, ERP and finance.
"In order to gain real-time, store-level visibility, we needed a way to automate and streamline data ingestion, especially since our category moves so quickly and we strive to shift assortments with consumer trends," Chu tells CGT.
After a small learning curve that required navigating different data structures between retailers, the company harmonized its data intelligence and began seeing benefits.
Tightening Up Inventory Through Predictive Analytics
The company can now generate immediate inventory reports, connecting cross-functional teams through dashboards where they can identify trends and make data-informed merchandising decisions around assortment, replenishment and profitability.
This has resulted in daily store- and SKU-level data so PopSockets can understand what's happening inside individual stores, such as the impact of glass cases on sales.
"Some retailers place phone accessories behind glass for loss prevention, but our sales were being affected by this," says Chu. "With daily store-level data, we built custom store groupings, compared trends and had evidence to adjust how we approached those stores and recovered lost sales."
The company has tightened up its inventory management, getting in-stock rates in favorable shape, particularly with major retail partners. This has helped PopSockets to identify inventory inconsistencies and issues ahead of time before they impact shelf performance.
Having that daily access has changed how the company manages inventory, according to Chu. "Instead of reacting to stockouts after the fact, we can see issues forming in real time and get ahead of them. We sell thousands of SKUs, so having the ability to drill down into individual product performance is crucial."
As an example, the company was able to see a sudden spike at the store level for one of its sea turtle designs, quickly shifting inventory to keep the item in stock in high-demand locations and using the insights to develop designs for other products.
This is also reflected in PopSockets' experience with its MagSafe-compatible products — a large part of its assortment. Chu reports that combined sales of its MagSafe line have surpassed its classic adhesive grips, and "being able to measure that shift in real time gave us the confidence to invest more heavily in MagSafe accessories and adjust our roadmap to meet where consumer demand is heading."
Since the implementation, the company's in-stock rates increased to approximately 95% in its top stores and 96% to 97% in tier-one stores, helping recover sales it would have otherwise lost.
At Best Buy, PopSockets saw year-over-year sales growth of 44%. Additionally, by feeding SKU-level Amazon data into the platform, the company monitored trends more closely and improved advertising efficiency, leading to 12% YoY sales growth.
"We knew this would help us show up stronger for our retail partners. Being able to speak their language, with their own numbers, makes our conversations more productive and collaborative," says Chu, referencing strengthened relationships with retail partners such as Target.
Stepping Stones to Scalability
Chu encourages teams not to underestimate the value of speed-to-insight. And among the biggest benefits is getting the organization ready to start leveraging AI in more "meaningful ways across the business," says Chu.
"One of the biggest lessons for us was that data foundation matters more than anything else. Before you think about dashboards or AI or advanced forecasting, you need clean, connected data," he says.
The company has started with a few clear, high-impact use cases. And once it sees how the data pays off in those areas, it then expands into more complex, AI-enabled modeling and analysis.
Automating data pipelines early allowed PopSockets to shift its time toward analysis instead of manual reporting, which drove significant ROI and led to invaluable new efficiencies for a small BI team that can't afford long build cycles or heavy maintenance.
