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If you want to buy something special, go to a specialist. This advice is as true for e-commerce as it is for brick and mortar stores. That’s why, for those who know what they’re looking for, niche shops are the place to go: they offer a better selection of products, better customer service, and a more pleasant customer experience than general stores. And this is exactly what Niceshops excels at.
Niceshops is an e-commerce retailer that operates around 40 different shop portals. Each Niceshops store focuses on a specific product niche, from electric bikes to 3D printing or cosmetic products. A team of more than 500 people is bringing these shops to life.
“Every Niceshops employee brings a different set of core skills to the table, and we want to leverage those skills as much as possible,” says Christoph Schreiner, CEO, Niceshops. “Our shops can only thrive if we let our people do what they do best and enable our employees to make their own decisions. But to make those decisions, they need the right data at their fingertips.”
Building self-service data models with Google Cloud
To empower employees with the right data tools, Niceshops had to overcome its data silo problems. “As an e-commerce company with more than 40 shops, we had a lot of isolated data sources, such as sales histories, financial reports or performance marketing data,” says Marina Tosic, Team Lead Data Analytics, Niceshops. “We needed to unify these data sources in a single warehouse to create a holistic overview.”
Niceshops decided to develop its new data platform in-house, using Google Cloud solutions. “We’ve long been working with Google products in other departments, mainly Google Workspace and Google Ads,” says Tosic. “We selected Google Cloud because of our strong track record of collaboration, combined with the fact that Google Cloud is one of the leading innovators when it comes to cloud-based data warehousing.”
The Niceshops team decided to generate actionable insights by combining the data warehouse capabilities of BigQuery with the analytics features of Looker, explains Tosic: “We began by importing data from two main sources, our e-commerce backend data and performance marketing data, to BigQuery. Then we created cross-department analytical insights using Looker.” With its new, centralised data platform, Niceshops was able to create self-service models on top of different data sources, giving employees better access to historical sales and marketing data. But that was just the beginning.
Expanding the data platform with DoiT
The Niceshops employees loved the new self-service data opportunities and wanted more – more data, more data sources and more ways to use that data. To better leverage the Google Cloud tool stack and expand its data platform, Niceshops enlisted support from DoiT.
“We knew exactly what we wanted to achieve, but Google Cloud offers so many possibilities that the most straightforward way to get there isn’t always clear,” says Rafael Dovjak, Data Engineer, Niceshops. “DoiT became our trusted guide through these technologies, helping us to navigate the Google Cloud landscape in order to create the best tech stack for our needs.”
Tapping into DoiT’s knowledge to build new data pipelines
With managed services and support from DoiT, Niceshops began expanding its data platform, creating more advanced data engineering and analytics pipelines. New data sources included competitors’ price monitoring solutions, marketing insights and financial reports. The Niceshops team also built new pipelines in-house to replace its legacy third-party ingestion tools. With enterprise level support around the clock, constant assessment of Niceshops’ solutions and processes against best practices, and continuous automated cost monitoring optimization, DoiT helped the team make the most of their Google Cloud setup.
“Building data pipelines has multiple components to it, from orchestration to scheduling and monitoring,” says Dovjak. “In a training session, DoiT shared useful tips and best practices with us, helping us to develop new pipelines on our own quickly.”
Speeding up development with first-class support
Whenever the Niceshops team ran into issues they couldn’t resolve in-house, DoiT was the first point of contact. The support tickets that were submitted via the DoiT Console were usually resolved on the same day, enabling Niceshops to speed up the development process.
“Whenever we had an issue, DoiT basically already had the answer ready because they had experienced the exact same issue with other customers several times before,” says Tosic.
Stefan Gajanovic, Data Engineer, Niceshops, adds: “Working with DoiT keeps us on the right track, and ensures that we’re not doing the wrong thing or using tools that aren’t scalable or not meant for a particular use case. That’s especially important with the Google Cloud toolkit, which grows and changes every day.”
Identifying and cutting the costs of ML models and data ingestion
Turning data into analytics comes with a price tag. Visibility is the first step towards cost reduction, but in a complex cloud environment, it’s not always easy to see where specific costs occur. DoiT helped the Niceshops team gain visibility into their cloud spend and identify inefficiencies.
“With DoiT’s help, we were able to set up a monitoring framework that gives us a daily overview of our costs. This helped us detect and avoid cost peaks and improve our queries,“ says Gajanovic. “We’re estimating that we can lower our data ingestion expenses by 50%, thanks to support from DoiT.”
The DoiT team also helped Niceshops adopt the best practices for using BigQuery Machine Learning (ML) models in Looker. “We discovered in-house that our BigQuery ML models were not configured in Looker correctly; they were executing continuously instead of monthly, which was driving up our BQ consumption significantly” says Tosic. “DoiT’s Looker experts helped us troubleshoot these issues and adapt our development processes, which helped us reduce our cloud spend by 30%.”
Making data-based decisions is the new normal
Data silos are now a thing of the past at Niceshops. The online retailer has become a truly data-driven company, thanks to the holistic overview of its business metrics enabled by the new data platform. DoiT’s support helped Niceshops to greatly expand this platform, making a wide range of data accessible to a large number of employees.
“With just a few clicks, our employees can get detailed insights into many aspects of our operations, and the market as a whole and leverage these insights to make better business decisions,” says Tosic. “DoiT helped us get to this point so much faster – and avoid many pitfalls along the way.”
“It’s amazing what our data and analytics team created in the past two years,” adds Schreiner. “And no doubt, our data platform wouldn’t be as good as it is now without DoiT.”
Getting more bang for the marketing buck
Marketing is a key area where Niceshops’ new data platform makes a big difference. The platform helps the team to identify the shopping patterns of different customer segments, which informs new ad campaigns and improves customer communication. And marketing calculations that used to take a week because they were done manually in spreadsheets, now only take half an hour. “Basically, we’re spending less and achieving better results,” says Schreiner.
Niceshops wants to further expand its data platform to improve existing use cases and develop new ones. Besides customer analytics, the team is working on an AI-based recommendation system and demand forecasting models. Because the product catalogues of the company’s many shops are enormous, those are challenging use cases, and the Niceshops team can count on ongoing support from DoiT to deploy and scale them faster.
“Google Cloud opens up so many possibilities that it can be almost overwhelming,” says Tosic. “That’s why it’s so important to have a technology partner that helps you make the most of the technology. For us, that’s DoiT.”
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