Retailers Need Higher Quality Data Faster to Meet Customer and Business Challenges3 min read
The combination of post-pandemic changes in consumer behaviour and disruption to global supply chains from geo-political turmoil, all amid a wider economic slowdown, mean retailers need to change business models and become more agile if they are to remain competitive and profitable.
There are several specific actions that will be required to both engage better with customers and build more resilient supply lines with product manufacturers. But at the heart of all these new capabilities will be more sophisticated management of the many more terabytes of data that need to be analysed to ensure the correct decisions are made.
A first step towards ensuring global supply chains do not turn from an asset to liability should be the creation of a “digital twin”, effectively a virtual mirror image of existing operations that can simulate business conditions and allow potential scenarios and actions to be tested. A “digital twin” is an autonomous digital entity that gathers real-time data from sensors and data points across the supply chain using the latest technology tools including AI, ML, and analytics.
The ability to model what-if scenarios and prepare for agile switching operations becomes a critical tool that integrates the entire chain, from supplier management, warehouse, and transport to final mile optimization for resource savings and optimal distribution models. This comprehensive approach can then capture all the disparate data points and run data mining and automation techniques to translate those terabytes into meaningful actionable insights. It means better-informed decisions.
A key factor towards delivering better insight into changing customer behaviour and repurposing physical stores with the digitalizing of customer experience will be the deployment of better product intelligence. Customer loyalty is certainly more fragile and price-conscious, meaning retailers need to do more to bridge the gaps developing between physical stores and online activity.
The use of IoT and video recognition tools enable better quality, customer-centric shopping experiences by keeping one step ahead of customer expectations. This retail intelligence can help improve in-store layouts, manage inventory, monitor, and avert in-store queues, as well as enhance shoplifting detection with video recognition of customer behaviour.
Increased automation of pricing processes from data collection and competitor analysis enables easier and even personalised repricing recommendations. This can boost the effectiveness of future sales promotions, with forecasts that enable quick decisions about products, discount levels, and promotion mechanics to strengthen customer loyalty and maximize both value and volume sales.
The success of these combined actions is dependent upon being fed with correct data—in the right place and at the right time. Securing this requires excellent data infrastructure that not only brings all the information together but also makes sure it is cleaned, harmonized, normalized, and modelled to meet decision-making needs. Such cloud-based infrastructure initiatives will break data silos and allow the holistic views of operations, customers, and supply chains to manage tight margins and improve profitability.
SoftServe is ready to share with you its portfolio of success stories from our retail clients where we are already proven partners and advisors. You can discover how data migration and integration, and the building of omnichannel and 360-degree views of retail operations will generate customer insights at scale to underpin the future growth and success of your businesses.