How retailers are leveraging analytics for smarter decision-making
We often hear that data is a business’s biggest asset. In the retail industry especially, the sheer volume of data generated – think customer profiles, payment transactions, social media interactions, website traffic and so on – means that companies have an endless stream of information heading their way. This abundance of data creates a valuable opportunity for retailers to truly understand their business, have sight of the latest market trends and know exactly what their customers want and how they like to shop. However, this promise comes with a big caveat. That data is only as valuable as their ability to collect, sort, and truly make sense of it.
And that’s where data analytics comes in.
Many retailers now have more data available to them than they can handle, thanks in large part to digitalization. Yet those leading the way collect, aggregate and analyze their data effectively, and turn those insights into measurable results.
Their success transcends retail sectors. Fashion and luxury retail companies have increased sales by 10%, McKinsey calculated, by harnessing the power of data for stock and store optimization. While in the high volume, low-margin grocery sector, McKinsey estimated that advanced analytics adds 2% to grocers’ earnings.
Data analytics supports retailers to find solutions to their biggest business issues and, through better decision-making, do things like:
Thanks to eCommerce and loyalty schemes, retailers can access a whole host of data about their customers and prospective customers. With this information, they can track interest levels in certain product lines, offer incentives to buy and make personalized recommendations to existing and future customers based on their purchasing behaviors and psychographic characteristics.
Through data analytics, retailers can avoid missed sales opportunities from stockouts or unnecessary carrying costs from overstocking. By accurately predicting demand, backed by real-time sales and stock visibility, they can optimize inventory levels at each store and tailor shelf and shop formats to make sure the right products are available at the right location at the right time.
As well as their own customer and sales data, retailers can harness external third-party data sources such as social media and weather records to make sure their stores are stocked with the right products at the right time. This enables assortment planning at a more granular level. For example, stocking merchandise to coincide with local sporting or entertainment events, or replenishing stock of sunscreen and hats in specific stores ahead of forecasted heatwaves.
Data-driven pricing and promotions unlock opportunities for retailers to stay ahead of market trends, match competitor pricing, and effectively market products at different price points to maximize customer spend. Dynamic pricing strategies help retailers balance supply and demand, better understand customer price sensitivity and boost overall sales.
In a world where customer experience is key, retailers can analyze customer behaviors and foot traffic to tailor store layouts, product placement, and even how they allocate staff at certain times of day. These measures enhance the in-store experience by avoiding unnecessary queues and making each customer visit as appealing and convenient as possible.
One of the biggest obstacles to effective data-driven strategies is data management and quality. In the Harvard Business Review report titled “Why Retailers Fail to Adopt Advanced Data Analytics,” retail executives admitted that they struggle to organize their siloed data. They also need help making decisions at a granular, store level.
Here are some of the steps that, as a retail executive, you can take to implement data-driven strategies for better business outcomes:
If you are using separate solutions to run different parts of your business, you risk collecting a lot of disconnected, ultimately unusable data. Unified retail management solutions connect all facets of the business, including POS, financials, store operations, inventory and supply chain. They gather all data within a centralized platform, allowing you to easily access and analyze it.
Retailers have an opportunity to collect data that brings transparency to their operations. For example, you could introduce GPS sensors in transportation units or add RFID tags and smart labels to inventory so they can see exactly where their merchandise is.
Sophisticated data analytics tools give retailers access to clear and actionable information that supports them to make timely decisions. Through tailored dashboards and reports, they can see the information that matters to them and seek answers to questions such as why certain products are popular or why they are being returned.
Advances in AI and machine learning add a new layer of analytic capabilities to unlock new insights and revenue opportunities. AI allows retailers to process vast amounts of data faster than ever and identify patterns they might otherwise overlook to build a deeper understanding of consumer preferences.
By investing in modern unified retail management software like LS Central you can get clear data, advanced data analytics capabilities, and are able to add on the AI capabilities offered by the Microsoft Dynamics 365 suite of solution. Moving to a modern unified software solves your data quality issues and puts you on track to connect your organization, unlock the true value of your data and, ultimately, drive sales. Contact our team of experts to get started on your data transformation journey.
By LS Retail
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