Why the modern retailer needs a modern data stack

A modern data stack, built on Fivetran and Google BigQuery, is fundamental to gaining the data visibility retailers need to deliver seamless personalized omnichannel experiences.
May 24, 2022

Modern retailers face the growing adoption of omnichannel shopping by consumers and the need to support increasingly complex and blended online/offline experiences such as buy online pick-up in-store (BOPIS), curbside pick-up or contactless payment.

Supply chain and inventory visibility has also become more critical as there are more delays and challenges with getting products. Personalization is now the expectation — and paramount to retaining customer loyalty.

To support all these areas of modern retailing requires fast access to trusted data from across systems, operations and vendors. Yet, the ability to monitor and analyze data from disparate sources, known as data visibility, is the #1 pain point for retailers' store operations, according to a recent IDC survey

A modern data stack, built on a unified platform comprised of modular cloud technologies — an automated data integration solution like Fivetran and a cloud-based data warehouse such as Google BigQuery — is the answer. When these capabilities are combined with a data transformation layer able to build, test and run SQL-based data models, retailers can not only process massive volumes of data reliably, they can finally gain the coordinated data visibility they need.

The power of a modern data stack

The power of the modern data stack is that it eliminates silos and increases visibility across all retail operations. This new level of visibility provides modern retailers with a multitude of benefits, such as a 360-degree view of the customer and enhanced personalization across the customer journey. Having full access to your data lets you derive insights faster and supports more precise decision-making.

Known today as Chubbies, the San Francisco-based clothier has gone from selling a few dozen pairs of shorts to distributing a clothing line in stores and across the globe online. The company’s marketing efforts have also moved from combing the beaches for customers to being able to analyze a blend of customer data from its martech data stack to better target customers more effectively. 

With data siloed in separate sources and all of its customer data analysis done in Excel, Chubbies was unable to paint a clear picture of users and customer behavior.

“We didn’t know the impact of Facebook advertising on customer service, or emails, on sales, for instance,” says Carlos Nido, senior manager of data and analytics at Chubbies. “People were looking at different sources for the same questions and would end up making different decisions.”

Chubbies adopted a modern data stack built on an automated data integration solution, Fivetran, to reliably centralize data in disparate data sources into Google BigQuery. This investment has accelerated decision-making across the business and eliminated massive amounts of engineering resources to build and maintain data pipelines. 

“Data with Fivetran has been a huge driving force for us,” adds Tom Montgomery, co-founder of Chubbies. “It has changed the way the acquisition team approaches using spend in order to acquire customers. If we launch a new channel we can measure its impact and compare it to baselines to ensure our spend is as efficient as possible.”

Global fast food chain automates data movement to drive greater visibility

When data is siloed or manually compiled, it's not only a time-consuming but error-prone process. For Nando’s, a rapidly expanding global takeaway chain famous, manual processes weren’t just a headache for the engineering team, they were impacting the business and marketing’s strategic capabilities as well.

“It was quite challenging, especially from a marketing point of view,” says Miquel Puig, technical lead on the Engineering team at Nando. “They need fast access to reports and dashboards to help them run successful campaigns and action the data and we just didn't have that flexibility.” 

On the engineering side, manual processes were also eating up far too much time. “Whole databases had to be replicated every day and it was very hard to model,” notes Puig. “Obviously, it was far from optimal. The team spent quite a lot of time building one of those pipelines and it went far from perfect.”

To resolve these challenges, Nando’s decided to implement a modern data stack. The goal was to have infrastructure that provided flexibility and visibility, giving the business a transparent view of data it knew it could trust. To achieve this goal, Nando’s moved their business data from SQL Server to Google Cloud Platform. The company chose BigQuery as the data warehouse at the center of their modern data stack and Fivetran as the data source connector. 

The biggest benefit from the modern data stack has been being able to see how the business is performing on a granular level, from the most profitable restaurants to what customers are ordering. The marketing team is also able to use data to activate campaigns much more quickly, whether in reaching platinum customers with special offers during the holidays or targeting gold customers with customized emails.

“We used to spend 80 percent of the time moving data over to build campaigns; that’s fallen to 20 percent. It means we can focus more on building engaging emails and making sure we have the data back from campaigns to analyze,” says Puig.

Gain data visibility without sacrificing security

According to IDC, data security concerns are one reason retailers have been holding back on automating data movement, despite recognizing that data visibility and data silos are barriers to successful operations. With data privacy laws like the GDPR and CCPA already in effect, and more regulations sure to come, a modern data stack must also maintain a high-level of security and privacy.

Fivetran allows retailers to automate, scale and secure data movement. Its data connectors are easy to integrate within minutes while Fivetran's Business Critical provides retailers the highest level of protection for sensitive data, enabling them to create a more secure, high-performing modern data stack that meets their internal and regulatory requirements. An automated data environment can also provide better data security, especially in relation to PII requirements. 

A modern data stack isn't just nice to have. It's fundamental for gaining the data visibility modern retailers need to deliver seamless personalized omnichannel experiences.

IDC Spotlight: Automated Data Movement for Today’s Modern Omnichannel Retailers


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