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Predicting consumer tastes with big data at gap

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9 - 517 - 115 R E V : J U L Y 10, 2017


A Y EL E T I S R A ELI


J I LL A V ER Y


Predicting Consumer Tastes with Big Data at Gap


In January 2017, Art Peck, chief executive officer and HBS MBA ‘79, was struggling to turn around Gap Inc. following two years of declining sales in an environment where many brick and mortar retailers were under pressure. Peck took over as CEO in February 2015, after serving as president of growth, innovation, and digital, when he envisioned and implemented Gap’s digital strategy using an analytical approach (see vitae in Exhibit 1). Gap’s troubles were not new to Peck; the company had been struggling to regain its footing since 2000.


One way he hoped to improve operations was to eliminate the positions of creative director for each of the firm’s fashion brands and to replace them with a more collective creative ecosystem fueled by the input of big data. Creative directors were the visionaries of a fashion brand, serving as guardians of its image and providing its taste inspiration and wellspring of ideas. These designers, such as Karl Lagerfeld for Chanel and Christopher Bailey for Burberry, established a design direction for each line, created a small number of inspiration pieces, and oversaw and approved the designs of other products in the line. Their personal vision established and reinforced the look, feel, tone, and spirit of the brand.


However, Peck was critical about the amount of power this concentrated in one individual. Many creative directors with top notch design experience had come and gone during his tenure without


making a significant mark to boost sales. Labeling creative directors “false messiahs”,1 Peck reflected, “We have cycled through so many, and each has been proclaimed as the next savior.”2 Instead of betting the future on the next savior, he replaced creative directors with a decentralized, collective process that no longer required the approval of a creative director. Rather than relying on a single person’s artistic vision, Peck pushed the company to use the mining of big data obtained from Google Analytics and the company’s own sales and customer databases as the backbone to inform the next season’s assortment. Ideas could thus arise anywhere, even from Gap’s external vendors, and would no longer have to be vetted by a creative director serving as maestro of the collection. Once a trend was spotted, it could be immediately and simultaneously incorporated into all three of the company’s brands, hitting stores within three months. “There is now science and art, and they can come together,” in this new process, proclaimed Peck.3 With the elimination of his creative directors, he was upsetting the delicate balance between creativity and commercialization, between designers and merchants, that existed at most fashion brands and that had supported Gap Inc.’s fashion cycles for decades.


Peck was also considering expanding online distribution by selling Gap’s brands on Amazon, an online retailer. His previous role at Gap taught him the importance of e-commerce and digital and he


Professor Ayelet Israeli and Senior Lecturer Jill Avery prepared this case. This case was developed from published sources. Funding for the development of this case was provided by Harvard Business School and not by the company. HBS cases are developed solely as the basis for class discussion. Cases are not intended to serve as endorsements, sources of primary data, or illustrations of effective or ineffective management.


.


517-115 Predicting Consumer Tastes with Big Data at Gap


expressed his opinion that Gap could be at a disadvantage if it didn’t consider the Amazon opportunity. Selling on Amazon could provide an additional datastream about customer purchasing


behavior to inform Gap’s decision making.4


Company Overview


Gap Inc. was founded in 1969 by Donald and Doris Fisher and their son, Robert was chairman of the board in 2017. Gap was one of the creators of specialty retailing, retailers that focused on a particular product category rather than carrying a wide assortment and produced their own private label branded goods. It remained the largest example of the genre, with 135,000 employees and 3,659 company owned and franchised retail locations in 50 countries, accounting for 36.7 million square feet of selling space,


which generated global sales of $15.5 billion.5 (Also see Exhibit 7).


Gap Inc. managed five brands: Gap, Banana Republic, Old Navy, Athleta, and Intermix, and had historically been the authority on American casual style. The Gap brand offered female and male consumers casual, classic, clean, comfortable basics: jeans, khakis, button down shirts, pocket tees -- at accessible prices. Some called it democratic fashion, “ordinary, unpretentious, understated, almost lowbrow,” while others labeled it iconic: “They elevated incredible basics to not just an iconic status in terms of clothing, but also a spirit – you felt like there was such a strong attitude, so much energy.”6 In 1996, Gap was at the height of its cool; actress Sharon Stone wore a Gap turtleneck on the red carpet of the Academy Awards.


In 1983, Gap Inc. acquired Banana Republic, moving into a higher price/quality tier. Luxurious materials were combined with detailed craftsmanship to support more expensive price points and attract a higher income consumer. In 1994, Gap Inc. created a new brand, Old Navy, to compete with discount department stores and mass merchandisers, such as Sears and Target, ushering in a period during which it became chic for consumers of all income brackets to shop for a bargain. Offering “wardrobe must-haves” at “prices you can’t believe,” embedded in a fun shopping experience, Old Navy was an immediate success with families, becoming the first retailer to reach $1 billion in annual sales within four years of its launch.7 Two acquisitions followed, Athleta (2008) a women’s fitness apparel brand, capitalized on the shift in women’s fashion from a jean-based foundation to activewear apparel. Intermix (2012) a multi-brand retailer of luxury and contemporary women’s apparel, offered consumers the “most sought-after styles” from a carefully curated selection of “coveted designers.”


In 1983, Millard “Mickey” Drexler became chief executive officer. During his tenure, sales grew from $480 million to $14 billion in 2000 and Gap’s market cap swelled to $42 billion. Drexler, described as “a visionary executive [that] helped transform Gap from a grab-bag of styles into a trend-setting machine that made simple clothes look great, even elegant,”8 was dubbed “the merchant prince” for his trendspotting, design instinct, and merchandising prowess. However, after being one of the first to predict the rise of business casual in the 1990’s, Drexler lost his magic touch, as he attempted to inject more fashion into Gap to attract younger shoppers who were migrating to edgier competitors. After eight consecutive quarters of declining sales, Drexler left Gap in 2002. Explained fashion writers,


Clothing companies…depend upon the vision and taste of just one person...Everything at Gap depends upon Drexler’s eye; it isn’t like making turbine engines. If he’s off the mark…if he approves a line of clothes in colors that aren’t just right, sales collapse and so does Gap’s stock price. That is why Gap can never really be like


Coca-Cola – there is no Gap formula hidden in some vault; there’s only Mickey Drexler.9


2


Predicting Consumer Tastes with Big Data at Gap 517-115


Two CEOs followed but were unable to restore Gap’s success in what the New York Times called “a remarkable comedown for a chain that once seemed to dictate how America dressed”10 (see Exhibit 2 for sales and net profit since Gap’s IPO in 1976 through 2016).


Every season, Gap produced hundreds of unique products, each offered in a variety of colors and sizes. While the online website typically offered the entire product assortment, each brick-and-mortar


store, with an average footprint of 10,000 square feet,11 was somewhat limited due to space constraints and offered a carefully curated subset of the product line. Gap’s assortment in each of its primary categories (women, men, children, and baby) consisted of two types of products: basics with styles that endured across seasons and more fashion-forward, designed items that captured the spirit of a particular season. Creative directors influenced the full product line, but their touch was most heavily felt on the latter group, where more fashion innovation was desired.


Digital and Big Data at Gap Inc.


As president of growth, innovation, and digital, Peck invested heavily in digital capabilities to address consumers’ shift to omnichannel shopping, focusing on dissolving the wall between the physical and digital channels. He observed, “Our customers are omni today and that is a fundamental reality. Many of our customers begin their journey with our brands on their phone and they finish it in our stores. Many of our customers begin their journey with our brands in our stores and they finish it on their phone.”12 He digitized the company’s entire product inventory and introduced retail services, such as reserve in store, find in store, and ship from store, which made it easy for customers to browse, purchase, and receive their items seamlessly across channels.


Peck promoted data-driven decision making and pushed his team to utilize big data to learn more about customers’ behaviors, and thereby deliver a better customer experience, “There’s lots of talk out there about big data—to me, big data, personalization is focused on an outcome of relevance. That’s


what we’re working on,” he explained.13 As the company moved into digital, Peck pushed his managers to continuously test and refine its new features as it listened to customers via its voice of the customer initiatives that tracked customer feedback and usage. A surprising finding arose: “Despite the explosive popularity of shopping not just online but via smartphones and tablets, 80% of Gap Inc.


customers still preferred to visit a store to try on the clothes.”14 As a result, Gap was working with Google and Avametric to develop an augmented reality app that allowed shoppers to test out different looks in order to improve their online and mobile shopping experiences.


Data-driven decision making required that customers be trackable and Peck lamented that customers were identifiable online but anonymous when they shopped in a store. He searched for ways to have customers opt-in to self-identify when they shopped in a store. He elucidated,


It is an opportunity to bring our personalization capabilities and customization relevance to bear in a store environment…60% of people visiting the website are recognized as unique visitors, enabling Gap to personalize experiences based on things like browsing and purchase history. Doing so is providing movement on numbers like conversion, time on website, click-through-rate…Good things happen for the customer if they’re willing to self-identify and tell us who they are at the beginning of a shopping experience. They do on the website, they don’t in our stores. If you come into our stores today, we won’t recognize you until you tender, if we recognize you then. This...is about providing…the opportunity to self-identify in order for the company to create a much


more relevant set of experiences compared to when they shop anonymously.15


3


517-115 Predicting Consumer Tastes with Big Data at Gap


Gap developed email programs to provide relevant, personalized messages to consumers. These included rules and conditions that when run through a series of algorithms triggered an email to certain consumers. For example, if a consumer abandoned her cart, an email was sent to remind her of her forgotten goods. If it was a consumer’s birthday, a personalized greeting and promotion was offered. If one of the brands was offering a new product line in a category that a customer had previously purchased, an email notification was sent to her highlighting it. Gap also used personalization in its geosniffing efforts, a term used to describe a company’s ability to determine the physical location of a particular consumer and to send them relevant localized information in real time. Information gleaned from clickstream analysis allowed Gap to reach out to consumers who had visited one of its websites, with customized messaging based on what they were searching previously, or to deliver a different landing page based on a consumer’s browsing history and/or IP address. Peck recognized the importance of allowing customers to opt-in to this type of digital tracking, “the company is carefully walking the line between personalizing a customer’s experience in a way that’s relevant and helpful


without creeping them out…Privacy is a huge concern for us,” he avowed.16


Managing the closing of underperforming stores (200 in 2011, 175 in 2015, and 75 in 2016) was another arena in which Gap used data-driven decision making. The company used the collection of insights from consumers’ online browsing activity and engagement in social media platforms to help understand why consumers were not buying as much from Gap’s physical stores. Peck proclaimed,


Visits to good malls are not down, but the number of store visits inside a mall are down, which says to me that people are planning their store visits as a function of their engagement with the brand, oftentimes expressed on a smartphone. I would argue that nobody’s figured out what exactly the aspirational, holistic, emotional expression of a brand…looks like when it shows up on this device right now.17


This insight drove him to further develop Gap’s digital and mobile e-commerce platforms to drive customer engagement. According to Fast Company, Peck had Silicon Valley developers “camped out at Gap, Banana Republic, and Old Navy stores, incorporating customer and salesperson feedback into


code in real time.”18 Peck’s performance and analytical nature were key to his selection as CEO.


Peck as CEO: The First Two Years


Peck was appointed CEO in October 2014. He faced some key challenges:


1. Slow growth in core markets: Gap Inc. competed in the $3 trillion global apparel industry, which accounted for 2% of the world’s gross domestic product (GDP). The U.S. and Canadian markets accounted for over $250 billion and were expected to grow annually by 2% through


2025.19 These two markets accounted for 84% of Gap’s sales. Millennials were spending less on apparel. Speaking to investors at a retail conference, Peck claimed that “there are no compelling [fashion] trends driving the business” and lamented that there had been a change in consumers’


buying habits such that there was a lack of need to replenish her closet.20


2. Competition: The mid-tier apparel landscape (see Exhibit 3) was highly fragmented, overcrowded, and competitive.


3. Rise of e-commerce: Consumers were shifting their purchasing from brick and mortar stores to online channels. In the U.S., 19% of apparel was sold through online channels in 201621 and, in 2015, clothing became the bestselling online sales category, driven by Amazon’s increasing strength in apparel. Amazon, the world’s largest multi-line, multi-brand Internet-based retailer,


4


Predicting Consumer Tastes with Big Data at Gap 517-115


was on track to become the largest seller of apparel in the U.S. by the end of 2017. As online sales grew, brands did not need the same number of storefronts. Empty stores lined the American shopping malls, as both specialty retailers and department stores simultaneously faced pressure to close locations. Gap had over 3,000 physical stores. By 2017, Gap Inc.’s online sales exceeded $2.5 billion.


4. Rise of Fast Fashion: New competitors, such as H&M and Zara compressed supply chains, delivering low priced looks knocked off from luxury fashion runways within weeks of their unveilings. With an average product cycle time of ten months, Gap lagged competitors such as Zara that could deliver products to stores within four weeks due to their consumer-responsive and decentralized buying process that allowed individual stores to order small batches of product, wait to see how consumers responded to it, and then airlift additional products to backfill the store’s inventory within days. The speed and pace of the fashion cycle was dizzying,


with new styles appearing in stores on a weekly basis in a constantly renewing fashion cycle.22


5. Heavy and frequent discounting: Clothing was increasingly commoditized as consumers viewed the lower quality fast fashion offerings as disposable, yielding a need for low prices and heavy discounting. Retail analysts were concerned about an overabundance of price promotion at Gap, where 40% discounts were common.


6. Gap’s size and ubiquity was transforming from asset to liability: Consumers, looking to forge a unique identity were moving away from Gap’s classic offerings.


Given these challenges, Peck believed that product assortment was key and that Gap’s model for selecting the right assortment was failing. The market seemed to agree. In January 2015, a retail analyst commented “They flip flop between a little trending, a little Euro, a little strip, whatever. It just gives you a headache…They’ve been redesigning the clothes for a decade because there is a total lack of clarity around who they are designing for. Who do you think their shopper is? I think it depends on


the week.”23 The flagship brand was struggling to find its place, wedged in the awkward middle between competitors’ value and premium brands (see Exhibit 4). Consumers, particularly millennials were cooling to Gap’s brands (see Exhibits 5 and 6).


While Peck knew that he was facing a 15-year-old problem that could not be fixed overnight, the results for 2015 and 2016 were disappointing (see Exhibits 7, 8, and 9 for recent financial performance).

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