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5 ways big data gives online retailers a competitive advantage

Online retailing is intensely competitive, which means businesses must latch onto anything that gains even a slight advantage.

So it’s surprising to see that one quarter of organisations are collecting data but not analysing it; meaning they are unable to truly leverage the insights that can be provided by big data.* By using data insights to identify opportunities, businesses can dramatically increase their sales.

The right analysis can also identify where to cut costs and unnecessary processes, which can contribute to the bottom line. For example, data insights can help retailers optimise inventory and supply chain processes.

It’s important to understand that not all data analytics will provide equal value. Therefore it’s crucial to use a disciplined process to explain what the data actually means for business practices. For example, it’s more important to know why a customer behaves a certain way than to simply know that they behave that way.

An emphasis on reporting instead of analysing and extracting insights limits the value of the data retailers do collect. Even traditional analysis can’t answer the most important questions, such as which of the organisation’s valuable customers is most likely to defect to a competitor, how price changes will affect sales, what the demand will be for a particular product, what lift a promotion will deliver, etc.

Retailers need a sophisticated approach that identifies and exploits a wide range of potential relationships between the attributes and variables in their data. For example, analytics might reveal that some customer segments have been over or under-valued previously, letting the business target future promotional campaigns based on a customer’s value, rather than just their demographic profile.

Here are five key ways online retailers can improve their interactions with customers using big data:

  1. More than just knowing how the customer behaves, big data lets retailers find hidden insights, such as the drivers behind that behaviour. This lets them predict future behaviour and target marketing efforts more effectively.
  2. Big data shows the pivot points that push customers to the point of purchase. How, where, when and what messages online retailers deliver need to map to these pivot points for best results.
  3. If retailers develop an analytic ecosystem, they can connect different types of data in ways that reveal new insights. This lets decision makers explore data and make smarter decisions faster. It also lets retailers use operational systems, such as integrated marketing applications, to quickly operationalise new insights and let marketing teams move from managing campaigns to managing customer interactions across the brand.
  4. Data-driven strategies can influence decisions about everything from pricing to supply chain, and more. For example, offering flexible fulfilment options according to customer requirements can increase sales.
  5. By understanding what customers are looking at, retailers can deliver real-time messages, offers, recommendations, rewards and local promotions. With a deeper understanding of customer behaviours and preferences, retailers can help guide them through their shopping journey and provide the convenient, seamless experience the connected customer expects.

*Teradata Data Analysis Index 2016

Alec Gardner is Teradata’s general manager for advanced analytics in Australia and New Zealand. an

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