Share this
Best practices in data management to become customer-centric
by Jan Hendrik Fleury on Apr 2, 2019 1:44:53 PM
The Rituals solution at Google Insights
Every company that is willing to become customer-centric needs to get the essential basics in its architecture and data management right. Our client Rituals Cosmetics has been a leading retail brand over the past few years in terms of annual revenue growth and customer satisfaction. And that is not only thanks to the quality of their products and excellent leadership alone.
At Google Insights Congress in March 2019, Rituals and Crystalloids together demonstrated how a robust yet flexible data management architecture has, for years, enabled Rituals Cosmetics to become extremely customer-centric. And by customer-centric, we don’t only mean the end consumer, but also the business journey of the staff who need to have actionable and reliable insights for sales, product management and finance.
The background
To become customer-centric, Rituals has been focussing on the back-end of the company, by optimising their ICT projects and big data management systems. They wanted all their data to be accessible and manageable from every touch point.
What’s more, they required their information systems to be flexible, easily adaptable to their needs, and they wanted a single customer view instead of a fragmented one. And of course, lowering the IT costs and preventing lock-in from best of breed vendors would be a nice bonus.
The Solution
Crystalloids implemented the data management solution - Rituals Google Cloud. By integrating every possible data source, like Exact, Demandware, Salesforce, Selligent, GA360, Arvato and through different API’s built on the Google Cloud, Crystalloids created the company's own data management platform.
As applications, data and demands change continuously we are working closely together in an agile way adopting DevOps to deliver what the business needs. This architecture and way of working is the best practice to many nightmares of marketers, analysts, IT and the financial departments.
The Result
Rituals can now gather and store all the data information about customers and products in one place, making sure the information is available for all different touch-points in real-time.
Thanks to the program, Rituals can capture real-time customers' data from all their stores and touch-points and keep these in the Google data lake, combining on- and offline data.
All data from the Customer Journey are collected and linked in the Cloud. This architecture is suggested as a place to start.
Crystalloids is a leading Google Cloud Platform Partner in cloud-based data warehousing, big data and analytics. We integrate all possible touch points and connect the best of breed applications in a loosely coupled way.
You will find a full description of the loyalty architecture part of the Rituals Google Cloud case on our website. Note that loyalty management is just one of the many solutions made possible by the data management solution.
Share this
- November 2024 (3)
- October 2024 (2)
- September 2024 (1)
- August 2024 (1)
- July 2024 (4)
- June 2024 (2)
- May 2024 (1)
- April 2024 (4)
- March 2024 (2)
- February 2024 (2)
- January 2024 (4)
- December 2023 (1)
- November 2023 (4)
- October 2023 (4)
- September 2023 (4)
- June 2023 (2)
- May 2023 (2)
- April 2023 (1)
- March 2023 (1)
- January 2023 (4)
- December 2022 (3)
- November 2022 (5)
- October 2022 (3)
- July 2022 (1)
- May 2022 (2)
- April 2022 (2)
- March 2022 (5)
- February 2022 (3)
- January 2022 (5)
- December 2021 (5)
- November 2021 (4)
- October 2021 (2)
- September 2021 (2)
- August 2021 (3)
- July 2021 (4)
- May 2021 (2)
- April 2021 (2)
- February 2021 (2)
- January 2021 (1)
- December 2020 (1)
- October 2020 (2)
- September 2020 (1)
- August 2020 (2)
- July 2020 (2)
- June 2020 (1)
- March 2020 (2)
- February 2020 (1)
- January 2020 (1)
- December 2019 (1)
- November 2019 (3)
- October 2019 (2)
- September 2019 (3)
- August 2019 (2)
- July 2019 (3)
- June 2019 (5)
- May 2019 (2)
- April 2019 (4)
- March 2019 (2)
- February 2019 (2)
- January 2019 (4)
- December 2018 (2)
- November 2018 (2)
- October 2018 (1)
- September 2018 (2)
- August 2018 (3)
- July 2018 (3)
- May 2018 (2)
- April 2018 (4)
- March 2018 (5)
- February 2018 (2)
- January 2018 (3)
- November 2017 (2)
- October 2017 (2)