As retailers in India constantly adjust to shifting customer preferences, data becomes a crucial tie between the brick-and-mortar and online experience. Data is a window into the customer base, helping to drive individual engagements, moving marketing from a push model to custom offerings, and ensuring stock can match purchasing demands.
However, many retail managers, marketers, buyers and team leads are limited in their ability to access and use relevant information properly. The majority of the time the issue is cultural, based on the company not being fully data-driven. Part of the problem also can be an individual and collective lack of knowledge on how to access and analyze data. The other common issue is a lack of understanding of how powerful this information can be to drive greater sales margins and attract new customers.
Before the COVID-19 situation, we all knew that typically, there are heavy shopping periods — Back to School, December holidays and the change of seasons — and with these periods comes a mountain of data. In the midst of shrinking margins and many retailers closing their doors, data analytics has the potential to uncover key customer behavior insights while improving operational efficiency. However, when staff are left foundering in the analytic darkness due to a lack of data literacy and access, sales can suffer.
Retail leaders are looking for ways to go beyond just the initial sale to make each customer interaction special and a path to ongoing engagement. Managers must look beyond just sales and use analytics to connect back to the supply chain and inventory data in order to effectively build a cohesive customer engagement strategy. This requires retailers to educate all employees on how to access and use more relevant data, and there is an emerging new methodology known as DataOps that helps address these issues and needs.
DataOps is a new approach to agile data integration, tackling this need from a holistic perspective of people, processes and technology. Rather than just providing technology, for example arming a salesperson with a tablet and POS data, it focuses on improving an individual’s knowledge of how to use data to drive collaboration, leveraging automated data flows from different departments across an organization. When done correctly, DataOps creates a set of processes that can help retailers better manage and use their data in real time to transform customer experience and drive greater sales.
Building The Data Supply Chain For Analytics
One of the first steps is implementing modern data architectures that can handle the growing data volume. Open architectures based on hybrid and multi-cloud provide the greatest efficiency, along with the agility to access and leverage customer behavior and shopping experiences at all points of interaction.
Cloud data lakes and warehouses are critical parts of a modern data management platform. They use continuous data integration by pulling together points from various databases and locations so that the needs of real-time analytics are met. Change data capture (CDC) technology provides a non-invasive method to capture data and metadata changes from core application systems and databases, and stream them in real time to the data management and analytics platforms. CDC works in conjunction with data lake and warehouse automation applications to provide near real-time, analytics-ready data wherever it is required.
A core component of a DataOps framework is the creation of an enterprise data catalog — an internal marketplace that lists what data is available for analytics. This marketplace informs anyone who is using the data for analytics, whether it be managers, customer service agents or buyers, about how the data was collected, shared and modified. The catalog should also transparently provide additional governance tasks, such as giving access to specific data to specific people based on role, or masking any Personally Identifiable Information (PII) to ensure regulatory compliance with laws such as GDPR or the CCPA.
An organized method for the collection, access and use of data is fundamental for DataOps frameworks. Retailers that already are using data-driven frameworks are experiencing greater insights and are able to adjust operations as needed.
For example, retailers using data insights to find outliers in their supply chain can see how their shipping costs per unit and transportation costs are reduced. Additionally, retailers like Harris Farms, a grocery retailer in Australia, are relying on real-time analytics to provide insight into inventory supplies, sales figures and customer behavior to ensure customers have the best experience possible.
Educating The Team Beyond The Sale
While organizing data is critical, it is of limited value if there is no understanding of its potential application. Data must be analyzed regularly to uncover new insights and gaps. When access is made easier in a governed approach, individuals gain greater knowledge about the available information and how best to use it, helping to build their data literacy skills.
Data knowledge and collaboration across teams is key to building data literacy. Simple aspects, such as sharing information about when a new data set is created and shared in the data marketplace, fosters greater collaboration across internal teams. A positive feedback loop on the data’s value and use is created while enhancing the individual and collective understanding of data.
Retailers that have educated teams with greater data literacy are able to uncover valuable insights in time to truly transform customer experience. In the case of Planet Hollywood, the team uses integrated data analytics and visualized dashboards to uncover daily customer trends across their portfolio of restaurants. By collaborating together and looking at company operations and customer experience through solid data points, retailers can best plan their next marketing campaign, place product orders and address any concerns with the supply chain. Additionally, Fanatics, a global leader in licensed sports merchandise, relies on cloud-based services and analytics to learn more about their customer’s buying trends and make the buying process smoother for customers.
Taking your data to the next level should be a priority. Retailers that bring together their customer care, supply chain, sales and management teams through data are more likely to succeed and build customer brand loyalty with positive experiences. This is how DataOps was born, to fill in the gaps and break the internal silos, so all departments and executives can unlock the full potential of their data for improved experience.
About the author
A 20-year marketing veteran, Dan Potter is VP of Data Integration Product Marketing at Qlik. In this role, Potter is responsible for product marketing and go-to-market strategies related to modern data architectures, data integration and DataOps. Prior to this he held executive positions at Attunity, Datawatch, IBM, Oracle and Progress Software, where he was responsible for identifying and launching solutions across a variety of emerging markets including cloud computing, real-time data streaming, federated data and e-Commerce.