About GreenJinn
GreenJinn is a cashback platform that offers users personalized promotions through a mobile app, allowing them to buy full-price items, snap receipts, and receive cashback. In addition to serving consumers, GreenJinn provides FMCG brands with valuable customer insights, helping them drive product adoption and convert advertising into in-store sales opportunities. As a company, GreenJinn is committed to simplifying processes, continually improving, and maintaining a customer-centric focus.
How GreenJinn Took the Strain Off Their Core Tech Team and Achieved a 200% ROI With Datalore
Trapped in the insights loop
As GreenJinn scaled, its tech and engineering team became overwhelmed with data extraction requests from non-technical teams, including operations, insights, sales, and marketing. These teams relied on the tech department for all their data needs, creating a bottleneck that slowed down operations and disrupted product development.
“If you’d asked me a few months ago, I would have said we were absolutely stuck. We were in a constant struggle to satisfy insights requests. The tech team was tied up with low-value tasks, like extracting data and making endless revisions, which prevented us from focusing on high-priority product development.”
— Daniel Sonny Agliardi, Tech Lead at GreenJinn
The insights loop was a repetitive cycle. The operations and insights team would submit data requests, but often, the initial requests were incomplete, leading to multiple follow-ups and delays. This inefficiency meant that the tech team was spending up to 11 hours per week on data extraction tasks, rather than focusing on core development work.
“We identified our reliance on the tech team for data extraction as the root cause of inefficiencies. The constant need for follow-ups and clarifications made it impossible for us to deliver insights in a timely manner.”
— Marco Patrini, Operations & Insights Lead at GreenJinn
GreenJinn’s small tech team struggled with technical debt and outdated dashboards, adding further strain on the system. This led to delays, miscommunication, and ultimately slowed decision-making across the company.
Empowering Non-Technical Teams With Datalore
GreenJinn realized they lacked the right tools to allow their non-technical teams to manage data independently, which led to a heavy reliance on the tech team. To address this, they implemented Datalore, a collaborative data science platform that empowered their operations and insights teams to handle data extraction and analysis themselves, reducing the burden on the tech team.
“Datalore gave us the flexibility to handle extraction and analysis without relying on the tech team for every request.”
— Marco Patrini, Operations & Insights Lead at GreenJinn
With collaborative SQL and Python notebooks and automated scheduling for reports, Datalore significantly streamlined GreenJinn's data workflows, enabling more efficient and seamless data management across teams. The platform’s user-friendly interface empowered non-technical staff to access, extract, and analyze data independently, while integrating seamlessly with tools like Google Looker.
Use case 1: B2B client reporting
GreenJinn's client reporting process was previously manual and time-consuming, taking up to two days per report. The operations team relied on the tech team to extract, clean, and set up data for client reports.
With Datalore, the operations team automated the entire process, from data extraction to report generation. Using SQL queries and Python code, they were able to pull data into Datalore, analyze it, and generate ready-to-use reports in under half a day. The platform’s flexibility allowed the team to maintain the same report formats while scaling the output by 70% to meet increased client demand without additional resources.
“We cut delivery times drastically, scaling our reports without any disruptions.”
— Daniel Sonny Agliardi, Tech Lead at GreenJinn
Use case 2: internal KPIs reporting
GreenJinn's internal KPI reporting process was similarly fragmented, with data spread across various spreadsheets and requiring significant manual effort. Datalore allowed the team to consolidate data extraction, analysis, and visualization into a single platform.
Using shared SQL and Python notebooks, multiple team members collaborated in real time on KPI analytics. The Report Buildersimplified turning Jupyter notebooks into clean reports, while Metric cells highlighted key KPIs. With interactive visualizations, the team could easily track performance metrics and adjust strategies. Thanks to this real-time data access, GreenJinn improved their KPI achievement by 35%, enabling faster responses to ongoing feedback.
“We turned our KPI reporting into a streamlined process, which helped us respond faster to internal feedback.”
— Marco Patrini, Operations & Insights Lead at GreenJinn
Results: 200%+ ROI, efficiency, and scalability
By implementing Datalore, GreenJinn achieved a 200%+ return on investment (ROI), thanks to the time saved and enhanced efficiency across internal and client-facing processes.
The key results include:
- 60% faster insights delivery, reducing report turnaround from 1.5–2 days to under half a day.
- 70% increase in client report output, allowing for more reports with the same resources.
- 35% improvement in internal KPI achievement, driven by real-time data access and streamlined reporting.
- One full day per week freed up for the tech team, enabling them to focus on core product development instead of repetitive data tasks.
“Datalore delivered an impressive 200%+ ROI by freeing up our resources and streamlining both internal and client workflows. The time savings alone have been invaluable.”
— Daniel Sonny Agliardi, Tech Lead at GreenJinn
“Datalore has transformed how we approach data, empowering our teams and improving efficiency across the board.”
— Marco Patrini, Operations & Insights Lead at GreenJinn
The adoption of Datalore has allowed GreenJinn to scale operations, optimize decision-making, and free up valuable resources, leading to substantial business performance improvements and a significant ROI.
Similar Customer Stories
neXDos
Dr. Steffen Möllenhoff, Managing Partner at neXDos
Previously, neXDos prototyped, backtested, and future-proofed their trading algorithms by hosting JupyterLab and JupyterHub. But this approach was problematic due to complexity in many areas, including managing the server environment, carrying out frequent updates, and handling the associated plugins within JupyterLab.
Venerable
Alexandria Morales-Garcia, Investment Risk Analyst at Venerable
One of the major problems facing our effectiveness was this interrelated web of spreadsheets. Now imagine one of these spreadsheets gets an error and you didn't realize. So three spreadsheets later, now you have to go back, fix that sheet, and all the other sheets that relied on it, and hopefully, you didn't send it out internally or, even worse, externally.
Drama & Company
Youngrae Lee, Big Data Center Team Lead at Drama & Company
Before adopting Datalore, Drama & Company used a standalone Jupyter server for its data research needs. However, this setup often faced performance hiccups. Transferring the research results to a data pipeline, distributing the code written by researchers, and other similar tasks proved to be tough and time-consuming. Drama & Company realized the need for a more robust and scalable data science platform.