“Channel” is a term retailers use to describe the mechanism through which customers shop and retailers connect with the customers. These channels include in-store, online, catalog, call center, mobile apps, social media, and so forth. Omnichannel is the means by which retailers and consumers engage with each other across touchpoints through one seamless customer experience. There is truly a plethora of touchpoints, including in-store, website, mobile site, mobile apps, Snapchat, Twitter, Pinterest, Instagram, Facebook, YouTube, and Amazon. The digital landscape also describes the mix of channels.
Due to the increase in channels, retailers are adjusting their business processes and technology to support omnichannel initiatives. Some retailers have separate buying teams for e-commerce versus in-store. In general, retailers are moving away from having separate buying teams to enhance the seamless transition between the channels. If two people are buying for swimwear, for example, it becomes much more difficult to have a cohesive message between in-store and online.
The increase in omnichannel shopping brings its own challenges for retailers. As e-commerce sales continue to grow, store volume declines. We call physical store locations “brick and mortar.” Controlling inventory is one of the top challenges. Declining volume in brick-and-mortar locations results in less of a need for inventory to maintain productivity and profitability.
However, studies have shown that customers still enjoy shopping in these locations. They may walk through a store and then purchase via their mobile phone a couple hours later. This behavior is called showrooming. Showrooming brings large complexities to retailers. Maintaining inventory levels as well as staffing to support an increase in traffic but a decline in sales is a challenge. As e-commerce sales started to increase, retailers invested in fulfillment centers, large distribution centers that fulfill online, catalog, and call center orders.
In the last couple of years, since the rise of showrooming, retailers are transitioning to in-store fulfillment. In-store fulfillment supports presentations for customers walking through the stores and supports the staffing for these brick-and-mortar locations. Of course, there are still challenges with this type of approach. Mainly, shipping costs can become a large burden as multiple items in a customer’s order may come from different locations. In-store fulfillment from multiple store locations can also have a negative impact on customer experience because the customer is getting 20 boxes in the mail, all at different times. For example, the customer’s top may come from store 1, the skirt may come from store 2, and the associated accessories may come from store 3. This creates additional shipping fees for the retailer because the customer only paid one shipping fee, but the retailer had to ship three separate boxes.
To solve this problem, optimization has become a critical piece in the equation. Typically, legacy fulfillment mechanisms were driven by business rules. Business rules are a lot of “if.. then” statements. Optimization, however, is the selection of the best available scenario, which takes into account multiple factors. In this example, these factors may be the locations that have the largest amount of items in the purchase order, the geographic distance to the shipping address, the amount of inventory of each item within the order, and the like.
An additional challenge that has arisen since the explosion of e-commerce and mobile is the competition. Customers have information at their fingertips. They can find any and all information, including competitor product availability, competitor pricing, and even coupons! Let’s face it, who hasn’t Googled or looked on Amazon before making a large purchase? Customers are able to check pricing in the middle of retail locations. There is even a “shopping” filter on Google. Couponing has become a hobby in recent years along with thousands of coupon sites and apps. In order to stay in the game, competitor pricing is a key element when thinking about pricing strategies for digital channels.
The third challenge with the rise in e-commerce and the digital landscape is marketing and personalization. E-mail has been flooded in recent years with offers upon offers. Whether it’s a percentage off, extra off on clearance, or free shipping, inboxes are being flooded with offers, relevant or not. Offers via apps are also a key strategy. But all of these interaction points with the customer add more complexity to the marketing efforts. We discuss the topic of pricing and marketing efforts in more detail in Chapters 5 and 6.
With these added complexities come large amounts of data. Retail data can be sales, product inventory, e-mail offers, customer information, competitor pricing, product descriptions, social media, and much more. Combined, this is described as big data, or large sets of data that are leveraged to make better business decisions. There has been a lot of buzz and hype about the term “big data” in the last couple of years.
Big data can be described in two ways: structured data and unstructured data. Different types of data can support different initiatives within retail.
In order to leverage the insights gained through analytics successfully, structured versus unstructured data in retail is a key topic to understand. Structured data is data that sits in a database, a file, or a spreadsheet. It is generally organized and formatted. In retail, this data can be point-of-sale data, inventory, product hierarchies, and so on. Unstructured data does not have a specific format. It can be customer reviews, tweets, pictures, and even hashtags.
Now that you know what structured versus unstructured data in retail is, let’s talk about how to use it. Customer reviews are a great way to understand why a certain product is or isn’t working. Word clouds are tools to visualize large amounts of customer reviews. Finding keywords that are used frequently can give insight into product features. For example, if “fits small”
is frequently used, then the retailer can be proactive by adding this to the product description or above the size selection. This will reduce customer returns and money lost on shipping fees.
Unstructured data can also be studied for sentiment analysis. This gives insight into whether the customer’s response is positive, negative, or neutral. A great example of this is being able to analyze customers’ Twitter responses. Let’s say you post a tweet with products you are thinking about buying for your spring line, including a sketch of the design along with a descriptive hashtag such as the brand and the item name. Leveraging advanced technologies, the retailer is able to obtain customer responses related to the hashtag from Twitter and analyze the responses for sentiment analysis. This analysis enables retailers to understand customers’ responses before the retailer even buys the product. This technique can also be utilized in season and give merchants insight into areas of opportunity or risk so that they can best manage their business.
As you can probably tell from reading this chapter, the changing retail environment has made it critical to understand analytics for more detailed analysis of business decisions. Complexities in e-commerce and the digital landscape and new challenges from omnichannel strategies and the world of big data have led to advanced analytics becoming an integral part of retail. In the following chapters, we are going to walk through applications of analytics within the retail environment, including assortment management, pricing decisions, marketing strategies, store operations, and cybersecurity.
Chapter 2
Merchandise Financial Planning
Assortment” is a term used to describe the product offerings carried by a retailer. Managing this assortment is a critical piece to creating a successful and profitable business. This assortment needs to change with the seasons. It needs to change with the recent fashion trends and consumer trends. Assortments need to reflect what is going on in the marketplace. If people are no longer buying Kodak cameras or overalls, then you definitely don’t want them in your assortment. But assortment management is also about having a business plan and meeting financial goals. At the end of the day, no matter how beautiful an assortment is, it has to drive profitability for a retailer or designer to stay in business.
Management of assortment starts at a high level. Specific financial targets must be met. Quite often, these high-level