Data in retail – The next reset waiting to happen
Article by Rosemary DeAragon, Global Head of Retail & CPG, Snowflake
The modern-day customer yearns for new experiences, be it dining, travel or retail. According to NielsenIQ Retail Measurement Services, the Asia Pacific FMCG sector experienced a 5.2% growth in the first quarter of 2022 compared to 5.9% in 2021. At the same time, consumers are looking forward to omnichannel e-commerce, new experiences, and greater convenience from their online purchases.
Thus, personalization should be deployed at every touchpoint, including marketing, pricing, and promotions, for both in-store and online customer interactions, and support. To create a comprehensive personalization strategy, leading retail brands are increasingly using data.
Here’s how you can use data to deliver a shopping experience that customers will value:
Understand customers’ needs and desires: Retailers use customer data to gain a better understanding of customers and what they are looking for in a shopping experience. Personal data, including engagement data, behavioral data, and sentiment data can all help provide a clear 360-degree view of the customer.
Personalize customer communications: Using data, retailers can create personalized customer journeys to strengthen buyer relationships. Insights from data allow retailers to send customized emails and direct mail tailored to interests based on customer profiles. Data also enables specific personalization, serving relevant content to a website visitor in real-time based on the user’s engagement data.
Improve product recommendations: Retailers can leverage browsing patterns and past purchase history to increase the relevancy of automated product recommendations. This type of data can also inform suggestions for additional purchases that pair with products already in the shopping cart.
Optimise customer experiences: The in-store shopping experience can be personalized by allowing retailers to send relevant notifications to customers’ mobile devices, providing helpful information and alerting them to new offerings and discounts.
Predict trends: Being able to predict what customers will want to purchase in the future enables effective inventory planning and strategic marketing. Predictive analytics can be used to analyze consumer behavior, social media trends, and a range of other data inputs such as weather, time of year, and more to see what will be in demand.
There are a few data capabilities that are essential for retailers to personalize the customer experience:
- Data collection and consolidation: Retailers need to combine customer purchase behavior data, email contact and response data, and external data such as lifestyle interest data into a single, scalable, consolidated customer hub so that it can be easily analyzed. The ability to ingest data from many different sources, including multiple clouds, as well as the ability to integrate directly with many of the top marketing platforms, is crucial. Top retailers are taking advantage of third-party data sources, including demographic, purchase intent, point-of-sale, weather, and consumer mobility data, to personalize the customer experience more thoroughly.
- Real-time capabilities: Website personalization relies on the ability to execute in real-time. As visitors click through a site, retailers need their analytics capabilities to keep pace each step of the way with visitors’ changing searches, clicks, and interests. The closer retailers can get to real-time personalization, the better the experience for customers. For this reason, a retailer’s data platform must be able to process streaming data quickly and integrate with marketing and e-commerce software platforms.
- Scalability: To deliver targeted, personalized communications and experiences, retailers must have scalability in their data and technology. Companies need a cloud-based infrastructure that has flexible storage resources and computing power that will accommodate the large amount of data needed for personalization.
As the retail industry undergoes a reset in the current competitive landscape, organizations can leverage data to build personalized, multi-channel, and in-store strategies that drive a new level of conversion and help improve profitability. A strong foundation of data puts the business on the right performance track and enables more options for the enterprise to share and exchange data to obtain better customer insights. Better insights mean better data-driven decisions, improved customer experiences and functional supply chains – something legacy infrastructures cannot deliver for the next generation of retail players.
The views in this article is that of the author and may not represent the views of Tech Wire Asia.
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