How Localization Can Help Retailers Boost Growth and Relevance
Retailers are facing a tough combination of several major market forces: accelerated pace of innovation including digitization, increased competition, and more empowered customers. To grow — and to beat competition — it’s more important than ever that retailers offer customers the right products, in the right place at the right time.
Fortunately, retailers can focus on localizing product assortments to increase relevance and boost revenue. Successful localization first requires clustering similar stores on the basis of sales and customer data, including customer buying patterns, customer demographics, local weather, store size and other data points.
Once you’ve deciphered store clusters, you can use this analysis to create more localized store assortments that better match customer interests.
Use Data to Drive Growth and Stay Relevant
Here are three things all retailers can do to tailor product assortments to increase growth and relevance:
1. Let data you already have prop you up.
Before you can start using your data to help your company grow, you have to get familiar with it. Analyze product and customer data you already have. Run both basic and complex cluster analyses on that data to group similar stores and customer personas — you’ll likely gain some critical insights along the way.
Those analyses can help identify which product attributes (e.g., material, color, weight, shape, purpose) are most important to each cluster of stores and personas. Once you’ve narrowed down the attributes that are important for each cluster, use that data to stock the inventory you know will sell well.
2. Keep an organized system.
Many retailers still use an unorganized patchwork of processes and tools to manage product attributes. This leads to conflicting or incomplete versions of product data, which significantly limits analysis opportunities and requires lots of time to aggregate, validate and complete the data. Furthermore, errors and inaccuracies in customer-facing data results in poor customer experiences having a direct adverse impact on revenue.
A data enrichment or product information management (PIM) solution makes managing product data easier by providing centralized governance rules and automated workflows to ensure data accuracy. A next-generation PIM solution designed to work with both digital and brick-and-mortar ecosystems not only improves productivity, but also keeps product data clean by locking down what users can select as attributes for items, validating that the correct type of data is provided for different attributes, and ensuring that a product’s attributes are complete.
To support future growth, select a data enrichment or PIM tool that also allows appropriate users to easily add and edit attributes as needed.
3. Localize assortments and personalize experiences.
Once you’ve completed your store and persona cluster analyses and collected clean, rich product data, you can build localized assortment plans to meet your customers’ needs. Look for a tool that enables you to create, adjust and approve assortment plans quickly.
Your assortment planning tool should also let you validate whether the attributes of a given assortment plan fit with the attributes important to your store or persona clusters, which will help you adjust your plans for the products you’ll stock.
When you’re focusing on localization, you need the right tools to ensure data accuracy and provide insights so that you better understand your customers and their interests. You also need a powerful solution to translate those insights into localized product assortments — which will increase your sales and keep your customers happy.
Abnesh Raina is the CEO and founder of PlumSlice Labs, a company that provides a suite of web and mobile apps to help retailers stock and sell products more economically, creatively and efficiently.
