If you’re like most small retail shops, you’re constantly navigating the murky relationship between supply and demand. More specifically, you ask yourself “How much inventory can I afford and will it appeal to my customers?” Almost every retailer has had the experience of having too little merchandise, resulting in lost sales and unhappy customers. Conversely, store owners who buy too much find themselves later discounting the price, or selling at a loss, just to move the inventory. In some extreme cases this ‘miscalibration’ can even cost the entire business.
Experiencing problems with inventory management is actually an indication of a deeper and even more vexing problem: a poor understanding of the customer. Selecting products has traditionally been more of an art than a science for small retail shops where owners have relied on their own taste or a ‘best guess’ about what might resonate with their customers. Now, in our modern era of business data and intelligence, retail shops can make much more informed decisions about what to stock. This is the new era of analytics – and it’s not just for Walmart and Amazon anymore.
Many small businesses initially feel intimidated when they hear about analytics. But the reality is these retailers often already have data about their customer interactions in their systems; they are just challenged to access the information and transform it into actionable insight. When evaluating the next order to a supplier, retailers can use analytics to answer questions such as: Have my customers purchased similar products in the past? Are there particular seasons or months when these types of products are most popular? What feedback have I had from specific customers in the past that would indicate whether they would want this other product?
Using analytics for better customer service and inventory management
New customer insights can inform more than inventory decisions; they can also foster an even deeper understanding of the customer to create a rich feedback loop. Here’s how the process works:
Making Smarter Inventory Decisions
First, a retailer needs a system to convert their existing customer insights into useful analytics for making more informed decisions about new products. Then, retailers can use this same data from their system to proactively recommend the new products they’ve ordered when that particular customer comes into the store.
Analytics increases sales because customers who feel a store owner is responding to their individual tastes and needs are more satisfied and – ultimately – more likely to purchase the product. Increasingly, customers expect more personalized attention because it’s what they experience in the digital world (i.e. Amazon suggests a book based on a previous purchase).
Capturing Customer Sentiment
The final step is collecting new customer insights on an ongoing basis to generate more insightful analytics down the road. In this way, customer analytics creates a whole system whereby the relationship between inventory and customer desire are more and more closely aligned to the point where inventory ‘errors’ become a thing of the past.
Today’s business environment for retailers is more competitive than ever. For example, brick and mortar shops are facing increased competition from online retailers that can minimize inventory management problems because they secure the sale even before they place an order with a supplier. Analytics is increasingly becoming an essential component of operating all retail businesses and for finding the balance between inventory and sales.
Data is the key to discerning a customer’s desires. Small retail stores are realizing they need adopt more precise and effective business practices, or risk becoming obsolete.
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This post has been originally published here.