Use data visualization to monitor e-commerce performance
The Big Picture
A leading CPG company for baby foods recently started selling through its own and third-party e-commerce stores. While e-commerce contributed approximately 20% to 30% of sales across markets, there was limited monitoring of consumer behavior for the recently launched websites.
The company wanted to build a long-term and comprehensive roadmap for e-commerce. The company had the data, but the data was dispersed among various online and offline sources including Google Analytics, CRM database Magento, and multiple spreadsheets. To start with, the company wanted to harmonize and integrate the data dispersed in multiple locations.
Then, the company wanted to build a visualization solution to provide an e-commerce business health overview that would deliver automated insights on e-commerce health. The solution also needed to enable guided analysis to identify drivers and drainers of sales, and provide catch-connect-close analysis. This process needed to be scalable across time, volume of data, and velocity of data.
To solve the company’s challenges, a dashboard was designed based on the following key points: overall e-commerce health (growing or declining); consumer shopping behavior; drivers and drainers of sales; campaign performance analysis; and content, channel, and device performance analysis.
The approach identified the right KPIs to use for effective decision-making. Various mock-ups were created before finalizing the design. APIs were developed for getting the data from various sources. In addition, a what-why-how framework was deployed to design the critical dashboards.
As a result of the engagement, the company attained a visualization solution. The solution would enable quicker decision-making by identifying areas of focus in order to improve business results. With minimum clicks, the solution would also provide visibility to e-commerce performance. In addition, a standard data updating process would allow for frequent data refreshes and correlate data from different sources.