Fashion and collection-based retail is a tough business where having the smallest advantage can make all the difference. Nextail goes a step further. Discover how it built its merchandising optimization platform on Snowflake’s Data Cloud to accelerate time to decision by eight times.
For retailers, quickly making the right merchandising decisions at the right time can make all the difference to their revenues and brand reputations. It’s why peak times—such as Black Friday, the December holidays, and seasonal transitions—can often change a brand’s fortunes on a dime.
Nextail understands this better than most. Its AI-driven merchandising optimization platform is designed to give retailers the right answers to their most pressing questions based on blended real-time and historical data. And when combined with its AI models, retailers can access intelligent insights that grow with their own operations.
“Retail is very high pressure; you need to make tough decisions, and if you get them wrong, you risk the impression you don’t understand your business,” said Carlos Seguin-Lozano, Product Marketing Director at Nextail. “Many retailers are sat on the right data but often struggle to find the right tool to leverage that data at scale. Our platform establishes data relationships to identify hidden patterns, exposing new merchandising opportunities that positively impact balance sheets.”
But as customer demand for processing higher data volumes increased, Nextail needed to expand its capabilities to offer the necessary scale and performance. Nextail also wanted to demonstrate its platform’s value, and build trust with its customers. So, it also needed a way to perform faster proof of concepts.
“We needed a way to ingest data at scale and from multiple data sources—everything came down to scalability,” explained Seguin-Lozano. “We also wanted to simplify our data science environment—reducing complexity and freeing our data scientists to focus on more impactful activities.”
Millions of products with countless variables—analyzed in a matter of minutes
“We keep a keen eye on the tech market and regularly evaluate our own systems, so we were already aware of Snowflake’s Data Cloud and its capabilities,” said Seguin-Lozano. “We created a proof of concept that tasked Snowflake’s platform with processing and analyzing 1 million products, each with their own attributes. We immediately achieved a 90% processing time improvement, down from 12 hours to just minutes—enabling us to simulate countless scenarios instantly and make informed assortment, buying, and distribution decisions. It was an eye opener—we knew we were on to something special.”
An early member of the Powered by Snowflake program, Nextail initially benefited from access to valuable resources that helped the company plan and build its platform on Snowflake’s Data Cloud. The program also helps Nextail go to market as a Snowflake partner, marketing its platform to thousands of Snowflake’s current and prospective retail customers.
To migrate its existing platform to Snowflake’s Data Cloud, Nextail split its data environment into different modules mirroring the merchandising journey, lifting and shifting each one in a way that allows for comparison and elasticity. The company has already automated countless business rules and constraints for its customers’ data, helping remove manual labor and the risk of human error.
From JSON and XML data format support to JDBC driver connectors, Nextail now has a flexible platform and a range of capabilities at its disposal. For example, the company uses Snowflake’s Time Travel function to quickly interrogate invaluable historical data. “Being able to look back in time at data is critical for us,” said Seguin-Lozano. “Fast access to time-stamped data supports our vision and cuts down complex siloes. Getting insights of this depth would have been too difficult to achieve without Snowflake.”
Fast data integration for quicker customer impacts
With each of Nextail’s customers sitting on significant data volumes, fast processing—no matter the scale—is critical to the platform’s success. And as Seguin-Lozano explained, it also fosters trust in its customers that their most valuable asset is being treated appropriately: “Loading large data sets into a platform can be a painful process. Snowflake’s Data Cloud now handles all the complexity, including SQL optimization. It means we can show our value much quicker—in days rather than months. And with data quality, our data integrations are seamless, and require very few IT resources. And for our customers that use Snowflake, we share data in real time between Snowflake instances without the need for any integration.”
Seguin-Lozano added: “Snowflake brings operational efficiencies to our data science teams, meaning our teams have more time to focus on greater value added tasks, increasing our agility to answer customer needs and our impact on their business.”
Part of Nextail’s data quality checks involves mapping its customer data using dbt integrated with Snowflake to demonstrate exactly what the company intends to do with customers’ data. It means that Nextail can now complete the process of transforming and analyzing three years of customer data x8 faster than with its previous infrastructure—giving customers quick access to insights.
Nextail also benefits from wide-ranging integrations with other leading vendors, such as Domo for business intelligence and Dagster for process orchestration. “We believe we can now handle any amount of data, and are able to offer our customers near infinite scalability.,” said Seguin-Lozano. “We’re onboarding much larger customers than ever before and giving them a better experience that wouldn’t have otherwise been possible.”
The future’s bright. The future’s AI.
From cost optimization and warehouse capacity to in-store assistance, Nextail wants to embed AI across every aspect of merchandising. And as a Powered by Snowflake partner, the company’s platform is set to be a strategic asset for many Snowflake customers.
“The more data that’s fed into our platform, the more accurate its insights,” said Seguin-Lozano. “With Snowflake, we can enrich our models with new internal and external data at speed, benefiting our customer’s merchandising and product decisions straight away. The combination of Snowflake, our AI models, and other components on the platform mean that operations that used to take months now take just days.”