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Three ways to turn your retail data into profit

JY Pook, Asia-Pacific Vice President at Tableau Software | March 2, 2015
Retailers that are looking to continue to remain competitive need fast, complete self-service analytics, the sooner the better.

Retail business decision makers need to be able to see and understand data fast to react to changing consumer preferences. One of the ways that retailers can help business users quickly understand data is through visualization. Humans interpret visuals about 60,000 times faster than text.[2] A data visualization tool that can present complex data through charts, graphs, etc. will help users make sense of data fast.

In the Hype Cycle for Retail Technologies 2013 report, Gartner analyst Robert Hetu wrote that sophisticated yet simple-to-use data visualization tools must be added to retailers' analytical toolkits, since these tools are required to utilize the knowledge that merchants rely on to drive analytic views of information from broad data sources.

Additionally, in the fast-moving retail industry, business decision makers need to be working with up-to-date data. Retailers can choose a data visualization tool that allows for data is to be updated or refreshed automatically once a dashboard is built. This way, business users who are working on the dashboard are assured that they are tapping on the latest available data at all times.

At Metro, one of Singapore's largest department stores, staff use a simple data analytics tool to keep track of inventory levels. By going through historical data, they were able to discover that customers rarely buy shoes with half sizes. With this information, they lowered the orders for slow-moving shoe sizes and minimised wastage. In fact, Metro has been able to maximize profit and reduce overhead costs by optimizing their supply chain to ensure that there is a constant stock of 'hot' items and less of others.

3)    Provide data access across multiple data sources
To accurately gain a 360-degree view of a customer, business decision makers need a cohesive view of data generated in multiple channels and delivered in differing formats.

Previously, data workers would clean and consolidate data into a data warehouse. This was a challenge because:

  • Retailers need information fast. A typical data warehousing project can take a year or more. This is too long for most retail businesses.
  •  As the data comes from different sources, centralized storage does not mean that users will be able to access the data that they need in a timely manner.
  •  Data sources are continuing to change and evolve. The recent surge in mobile shopping -- or mCommerce -- for example, is a retail channel that was practically non-existant until about five years ago. It is now fast becoming a key channel in retail that every retail business needs to pay attention to.

Retailers need data analytics tools that can connect to and blend data from multiple sources. This helps them stay current and remain effective in the future. They also save time, as there is no need to move the data to one data warehouse. Business users can access the data that they need faster and make better, more informed decisions while the data is still relevant.

 

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