{"id":30713,"date":"2018-11-12T23:51:45","date_gmt":"2018-11-13T04:51:45","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/"},"modified":"2018-11-12T23:51:45","modified_gmt":"2018-11-13T04:51:45","slug":"is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/","title":{"rendered":"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity?"},"content":{"rendered":"

Few industries have experienced a reckoning as brutal and relentless as that of high-end fashion. The accessibility of ecommerce and the affordability of fast fashion have rapidly democratized a business whose trend dictatorship once relied on elitism as much as it did quality design. Yet amidst this upheaval, one brand has leveraged sensational design to emerge an industry megastar: Gucci. Driving 9 quarters of double digit revenue growth has been a torrent of millennial shoppers \u2013 a notoriously fickle demographic with flimsy brand loyalty and tall customer experience demands.[1]<\/a>,<\/sup>[2]<\/a> In this age of rapidly evolving consumer preferences, Gucci faces a daunting challenge: How to sustain momentum with a customer base loyal only to the next big thing?<\/p>\n

Gucci\u2019s millennial traction has primarily stemmed from product novelty \u2013 a dangerous strategy given fleeting trend cycles and fierce industry competition. Going forward, machine learning must become a critical business tool as the brand\u2019s runaway new customer growth inevitably slows, and it increasingly relies on client retention to drive performance. Through amassing extensive customer databases, more and more savvy retailers have applied machine learning to predict future transactions and win customer loyalty. Such technology allows marketing professionals to forecast not only second purchase timing, but also products selected.[3]<\/a> For example, customer data may reveal first-time shoe buyers typically purchase a handbag within 6 months of the first transaction. This can fuel highly effective client outreach campaigns, which improve marketing ROI and broaden a brand\u2019s repeat customer base. The personal styling company Stitch Fix takes predictive analytics even one step further \u2013 to product design. By analyzing the purchase behavior of its customers, Stitch Fix identifies voids in its current merchandise selection and swiftly produces such designs themselves.[4]<\/a> These efforts not only transition one-time shoppers to repeat clients, but also reduce the risk of fashion misses in a highly subjective industry.<\/p>\n

While Gucci has taken preliminary steps to address data-driven opportunities, it has largely prioritized infrastructure above all else in the near-term. As a nod to its \u201cdigital competence\u201d, L2 Research ranked Gucci the best performing digital fashion brand in 2016 and 2017 \u2013 across web, digital marketing, social media and mobile.[5]<\/a> While L2\u2019s scorecard primarily rates operational prowess, a meaningful digital presence still denotes extensive, omnichannel data collection \u2013 which powers comprehensive client insights and advanced customer analytics. Gucci anticipates additional IT and Customer Relationship Management (CRM) investments in the coming quarters.<\/p>\n

In the medium-term, Gucci has also commenced a production cycle revamp, with the goal of accelerating customer demand reaction time. Based on its customer data findings, Gucci will likely look to manufacture popular styles and produce new designs more quickly.[6]<\/a><\/p>\n

While these foundational investments are well-spent, Gucci must now rapidly move to address its analytics opportunity \u2013 and build a more predictable revenue stream grounded in known customer preferences rather than moonshot trend creation. As its first priority, Gucci should recognize those trends apparent in (what exists of) its repeat customer base. Predictive analytics can identify which products drove a second and third purchase \u2013 and Gucci can seek to replicate that behavior in first-time shoppers through personalized messaging and ad placement.<\/p>\n

In the short- medium-term, Gucci should look to inform its design process with customer analytics. Historically, its brand leadership has balked at data-driven product design \u2013 fearing that data may poison the creative process. CEO Marco Bizzarri has said, \u201cYou need to start with creativity\u2026 it doesn\u2019t start with numbers.\u201d[7]<\/a> Although the role of machines in trend creation is certainly contentious, the complete exclusion of analytics in design evolution ignores a vital customer development opportunity. \u00a0To return to a previous example, if Gucci learns first-time shoe purchasers typically produce handbags as their second transaction, Gucci should invest in a broader accessory collection, across silhouettes and price points. This awareness of customer behavior allows the brand to not only predict purchase behavior down to the SKU-level, but to also ensure no product gaps exist in upcoming season collections.<\/p>\n

If Gucci fails to retain its one-time, millennial customer base, it faces a material business risk. The value of analytics in customer targeting and merchandising strategy is tangible, and its utilization is ever more urgent in a business reliant on an unreliable clientele. With that said, however, the fashion industry\u2019s view on machine learning and its role is largely split. On the one hand, we hear Marco Bizzarri asserting, \u201cYou need to start with creativity\u201d[8]<\/a>; and on the other hand, we see Gap transitioning to an entirely data-driven design model. Do sweeping customer retention strategies become moot if a company can repeatedly predict and command fashion trends? And at what point might machines cut out the creative process altogether?<\/p>\n

 <\/p>\n

(773 words)<\/em><\/p>\n

 <\/p>\n

[1]<\/a> Kering Investor Presentations, October 2016 \u2013 October 2018, http:\/\/www.kering.com\/en\/finance\/publications<\/a>, accessed November 2018.<\/p>\n

[2]<\/a> Michael Osborne, \u201cBrands Need To Step Up Their Game To Win Over Millennials,\u201d CommunityVoice, Forbes.com<\/em>, September 26, 2017, https:\/\/www.forbes.com\/sites\/forbesagencycouncil\/2017\/09\/26\/brands-need-to-step-up-their-game-to-win-over-millennials\/#3a8f7a9f1b32<\/a>, accessed November 2018.<\/p>\n

[3]<\/a> \u201cBig Data Drives Luxury Brands Growth Beyond Digital,\u201d February 12, 2018, Luxe Digital, https:\/\/luxe.digital\/digital-luxury-reports\/big-data-drives-luxury-brands-growth-beyond-digital\/<\/a>, accessed November 2018.<\/p>\n

[4]<\/a> Katrina Lake, \u201cStitch Fix\u2019s CEO on selling personal style to the mass market,\u201d 性视界 Business Review <\/em>Vol. 96, no. 3 (May\/June 2018): 40.<\/p>\n

[5]<\/a> Alizah Farooqi, \u201cTop 10 Fashion Brands in Digital,\u201d Gartner L2, <\/em>September 28, 2018, https:\/\/www.l2inc.com\/daily-insights\/top-10-fashion-brands-in-digital-4<\/a>, accessed November 2018.<\/p>\n

[6]<\/a> Hilary Milnes, \u201cTo maintain growth momentum, Gucci is bringing production in-house,\u201d Glossy<\/em>, October 31, 2017, http:\/\/blog.else-corp.com\/2017\/10\/to-maintain-growth-momentum-gucci-is-bringing-production-in-house-glossy\/<\/a>, accessed November 2018.<\/p>\n

[7]<\/a> Nikara Johns, \u201c5 Surprising Things CEO Marco Bizzarri Had to Say About Gucci,\u201d Footwear News, Yahoo, <\/em>November 20, 2017, https:\/\/www.yahoo.com\/lifestyle\/5-surprising-things-ceo-marco-212842856.html<\/a>, accessed November 2018.<\/p>\n

[8]<\/a> Ibid.<\/p>\n","protected":false},"excerpt":{"rendered":"

Gucci's runaway growth has largely stemmed from first-time, millennial customers \u2013 a notoriously fickle client demographic with little brand loyalty and tall customer experience demands. Will Gucci's hesitance to deploy machine learning be what proves it a fad, rather than an enduring fashion phenomenon?<\/p>\n","protected":false},"author":11471,"featured_media":30714,"comment_status":"open","ping_status":"closed","template":"","categories":[912,346],"class_list":["post-30713","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-luxury-retail","category-machine-learning","hck-taxonomy-organization-gucci","hck-taxonomy-industry-retail","hck-taxonomy-country-france"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"\nIs Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity? - Technology and Operations Management<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity? - Technology and Operations Management\" \/>\n<meta property=\"og:description\" content=\"Gucci's runaway growth has largely stemmed from first-time, millennial customers \u2013 a notoriously fickle client demographic with little brand loyalty and tall customer experience demands. Will Gucci's hesitance to deploy machine learning be what proves it a fad, rather than an enduring fashion phenomenon?\" \/>\n<meta property=\"og:url\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/\" \/>\n<meta property=\"og:site_name\" content=\"Technology and Operations Management\" \/>\n<meta property=\"og:image\" content=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Gucci-Image-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"3000\" \/>\n\t<meta property=\"og:image:height\" content=\"2000\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/\",\"name\":\"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity? - Technology and Operations Management\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Gucci-Image-1.jpg\",\"datePublished\":\"2018-11-13T04:51:45+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/#primaryimage\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Gucci-Image-1.jpg\",\"contentUrl\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/wp-content\\\/uploads\\\/sites\\\/4\\\/2018\\\/11\\\/Gucci-Image-1.jpg\",\"width\":3000,\"height\":2000},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Submissions\",\"item\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/submission\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity?\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/#website\",\"url\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/\",\"name\":\"Technology and Operations Management\",\"description\":\"MBA Student Perspectives\",\"potentialAction\":[{\"@type\":\"性视界Action\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/d3.harvard.edu\\\/platform-rctom\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity? - Technology and Operations Management","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/","og_locale":"en_US","og_type":"article","og_title":"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity? - Technology and Operations Management","og_description":"Gucci's runaway growth has largely stemmed from first-time, millennial customers \u2013 a notoriously fickle client demographic with little brand loyalty and tall customer experience demands. Will Gucci's hesitance to deploy machine learning be what proves it a fad, rather than an enduring fashion phenomenon?","og_url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/","og_site_name":"Technology and Operations Management","og_image":[{"width":3000,"height":2000,"url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Gucci-Image-1.jpg","type":"image\/jpeg"}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/","url":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/","name":"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity? - Technology and Operations Management","isPartOf":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website"},"primaryImageOfPage":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/#primaryimage"},"image":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/#primaryimage"},"thumbnailUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Gucci-Image-1.jpg","datePublished":"2018-11-13T04:51:45+00:00","breadcrumb":{"@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/#primaryimage","url":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Gucci-Image-1.jpg","contentUrl":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Gucci-Image-1.jpg","width":3000,"height":2000},{"@type":"BreadcrumbList","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/is-guccis-fad-shopper-dilemma-a-predictive-analytics-opportunity\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/d3.harvard.edu\/platform-rctom\/"},{"@type":"ListItem","position":2,"name":"Submissions","item":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/"},{"@type":"ListItem","position":3,"name":"Is Gucci\u2019s Fad Shopper Dilemma a Predictive Analytics Opportunity?"}]},{"@type":"WebSite","@id":"https:\/\/d3.harvard.edu\/platform-rctom\/#website","url":"https:\/\/d3.harvard.edu\/platform-rctom\/","name":"Technology and Operations Management","description":"MBA Student Perspectives","potentialAction":[{"@type":"性视界Action","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/d3.harvard.edu\/platform-rctom\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/30713","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission"}],"about":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/types\/hck-submission"}],"author":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/users\/11471"}],"replies":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/comments?post=30713"}],"version-history":[{"count":0,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/hck-submission\/30713\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media\/30714"}],"wp:attachment":[{"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/media?parent=30713"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/d3.harvard.edu\/platform-rctom\/wp-json\/wp\/v2\/categories?post=30713"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}