Retail Modernization: Unlocking Actionable Insights

Disparate systems and siloed data make it nearly impossible for retailers to effectively run analytics that provide insight into the business and its customers. Modernizing legacy infrastructures and moving data to a centralized location within a cloud platform lets retailers reduce IT spend (from costly maintenance), leverage advanced technologies to transform structured data into actionable insights, and turbocharge productivity. Integrated data gives retailers the foundation for insights that power data-driven decisions.

Consumers today have almost unlimited buying options and access to information — wherever they are and whenever they want. They use a range of devices, shop in a variety of new and different ways, and are continuously bombarded with information across all digital channels. With each action taken by a consumer, a trail of data follows — impressions, clicks, views, transactions. From that consistent flow of information, brands have mountains of data to continually digest and interpret.

However, the challenge many retailers face is drawing actionable insights from singular streams of data and taking data-driven actions to improve business performance. In order to optimize business processes and quickly adapt to consumer expectations, retailers must first improve operational efficiency. They can do this through the utilization and organization of big data, including proper data management, a modernized infrastructure, and a cloud strategy that increases operability, scalability and productivity. Furthermore, they can provide access to advanced data processing and analysis technologies.

The Need to Unlock Insight

Throughout the majority of enterprise retailers, data siloes and disparate systems make it nearly impossible to effectively run analytics that provide insight into the business and its customers.

In a survey by SiteCore, brands report harvesting an average of eight pieces of data, ranging from transactional details to behavioral insights and trends. Although the most common types of customer data that brands collect online are email addresses, names and postal addresses, some brands additionally collect behavioral metrics around devices used, browsing habits and purchase patterns. In the same survey, 42 percent of brand respondents reported a lack of integration between data collection apps. Additionally, nearly 51 percent of retailers can’t share data between systems. With many sources of data and the inaccessibility created by different platforms, a key consideration is how the data can be used to gain insight. Without a workable data strategy and vigilant governance, the data gathered will never be fully employed.

A data-first strategy is the driving force for innovation and customer marketing initiatives, whereas data governance outlines the rules by which data is collected, stored and accessed. A well-designed data governance policy ensures data integrity and security. Structuring and defining data through data governance has valuable benefits throughout a company.