Made By Gather Improves On-Shelf Availability With Real-Time Data Boost
Kitchenware company Made By Gather, which produces such brands as Bella and Drew Barrymore's Beautiful, has evolved its data foundation, eliminating fragmented processes in exchange for consolidated insight streams.
In 2024, the company sought a replacement for time-intensive, manual data-pulling efforts. At that point, Made By Gather was stitching together insights from individual retailer portals and manually parsing through them in Excel files.
"The process was slow and required constant upkeep just to keep reports usable," Emma Todd, data operations manager at Made By Gather, tells CGT.
Additionally, the data was often outdated by the time the company had the analytics in hand, she says. This created reporting inconsistencies, broken pipelines from retail portal changes and costly operational missteps.
Because retail partners deliver data in different formats, each having its own structure and naming conventions, Made By Gather was having trouble keeping data aggregation consistent.
"We couldn’t realistically keep up with ongoing changes like schema drift without dedicating significant internal resources," says Todd.
Addressing Data Complexity
The company sought out a tech solution that could easily integrate into the Snowflake platform it was already working with. It partnered with Crisp for the effort, automating data consolidation with insights pulled from retail partners such as Target, Amazon, Costco and others.
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Adoption came naturally, she says. There was immediate buy-in from the team, especially the company's CMO, who sees immense value in clean insights. Today, more than 35 team members are using the analytics, and clean data practices are embedded into the culture of the organization.
"Knowing how complex retail data automation can be, it was impressive to receive data in such an accurate, analytics-ready state, which allowed us to move quickly into deeper analytics and machine learning use cases," says Todd.
The Benefits of Consolidated Insights
In the two years since the implementation, Made By Gather has seen significant results, including improved forecasting and replenishment. At Amazon, for example, the company has maintained a 95% in-stock rate.
Additionally, it can more proactively identify risks and opportunities at the SKU and store levels in near real-time, rather than reacting after performance has changed, improving on-shelf availability rates.
"It has also supported faster product innovation, allowing teams to bring new products to market with greater confidence in demand planning and performance expectations," says Todd. Its Bella Fits-Anywhere line at Target saw 1,450% year-over-year growth last year, for example.
Todd says the company also expanded its distribution, partnering with companies like Costco and Best Buy. This has driven revenue growth as Made By Gather continues launching new products across multiple household categories.
Overall, Todd can now focus more on strategic analysis and advanced data modeling in her role.
"Across supply chain, sales, marketing, finance and other teams, data is readily available. No more chasing reports or reconciling inconsistencies," she says.
For those in similar shoes, Todd suggests prioritizing a scalable data foundation early on.
"The cost of manual work compounds quickly as the business grows," she says. "Invest early in clean, automated data; it pays dividends across every function as you scale and keeps you competitive and informed with your retail partners."
