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This guide highlights the key performance indicators for the retail industry and where investors should look to find an investment edge.
The health of the retail industry is driven by consumer spending, which forms a significant portion of a country’s GDP. The retail industry is composed of companies or retailers who sell goods or services to end consumers through brick-and-mortar stores or through online business models, acting as a link between manufacturers and consumers.
The global shift towards digital commerce has also led to the rise of omnichannel retailers who sell through both online and offline platforms, with the online banner often used to enhance the store-based brand. Store developments continue to see a strong focus on frictionless and seamless experiences. From creating an integrated smartphone-enabled, in-store shopping experience, to dedicating a store entirely to online orders and expanding click and collect offerings, many of the world’s largest retailers are moving quickly to embrace a digital future for stores.
Key performance indicators (KPIs) are the most important business metrics for a particular industry. When understanding market expectations for the retail industry, whether at a company or industry level, here are some of the retailer KPIs to consider:
Retailers
Automotive Retailers
Online Retailers
Retailer revenue comprises merchandise sales, recognized at the point-of-sale and ecommerce sales, recognized upon the shipment of a product to the customer. The retail industry’s business model is primarily based on comparable-store sales growth, also known as same-store sales (SSS) growth or like-for-like (LFL) growth. Comparable-store sales are sales from stores that are operational for more than 12 months. Note that many companies are inconsistent about whether they include online sales in comparable-store sales. Comparable-store sales eliminate the sales impact from new store openings, closings or acquisition, to measure the sales growth of a retailer on a comparable basis. This makes comparable-store sales the most important metric that is generally analyzed across retailers. Comparable-store sales is a function of store traffic, which is the change in the number of people visiting a store, and ticket, which is the change in spending per customer.
A new or acquired store’s sales growth is the impact on sales due to a change in the number of stores operated by a retailer, during a given period. It is calculated as the product of square footage growth and new store productivity. New store productivity measures the sales generation efficiency of a new store in its first year as a percentage of the performance of a pre-existing or same-store. New store productivity of 100% would indicate a similar performance of a new store compared to a pre-existing or same-store.
Retail revenue is derived from total growth, which is the sum of comparable sales growth and new stores’ sales growth. More often than not, for retailers, retail revenue equals total revenue, which is further broken down by distribution channels such as store-based sales or ecommerce sales. Retailers could also have other revenue segments such as wholesale and licensing to sum up to total revenue.
Companies in the automotive retail industry primarily focus on the following reportable business segments:
Each of these business segments is modeled in a similar manner, which is by bifurcating these segments into same-store sales and new or acquired store sales. Same-store sales and new or acquired store sales are calculated by multiplying the units sold in the respective stores with the average selling price (ASP). Comparable sales growth is also a frequently tracked growth metric that measures the growth of a retailer on a same-store basis. Depending on the nature of the business, some companies also provide a break up of retail and wholesale revenue streams.
Online retailers operate their business segments under a first-party (1P) business model, a third-party (3P) business model, or a combination of the two.
In a 1P operating model, the retailer purchases goods or services from suppliers and sells them to consumers by listing the goods on its website or app. Additionally, the retailer may also sell its own private-label products. The revenue generated from such an operating model is termed first-party revenue. In a 1P model, the entire amount of gross sales, also termed gross merchandise value (GMV) flows into the retailer’s revenue.
In a 3P operating model, the company acts as a marketplace where sellers list their goods or services to sell to buyers. Both parties use the company’s website and/or app and the company charges a fee to the seller in the form of a take rate. Gross merchandise value multiplied by the take rate equals the total 3P revenue that a company will then book on its income statement.
Gross merchandise value (GMV) is computed by multiplying the number of orders in a given period by the average basket size. The number of orders is calculated by multiplying the number of active customers by the number of orders per customer. In some cases, GMV can also be calculated by multiplying the active customers by the GMV per customer. The sum of 1P and 3P revenue is platform revenue, which refers to the revenue earned by selling goods or services via the company’s online platform.
Digital advertising is also an important source of revenue for some online retailers. Additionally, retailers generate fulfillment and shipping revenue on processing and delivering goods to end-users. Often retailers include fulfillment and shipping revenue in platform revenue.
Visible Alpha offers 63 retailer comp tables, comparing forecasts for key financial and operating metrics to make it easy to quickly conduct relative analysis, whether you are interested in looking at key values for Walmart competitors or GMV for Amazon and other online retailers. Every pre-built, customizable comp table is based on key operating metrics.
This guide highlights the key performance indicators for the retail industry and where investors should look to find an investment edge, including: