AI In The Shoe Industry Statistics

31.4% of respondents reported using AI in retail for demand forecasting [1]

30% of retailers expect to use AI for demand forecasting [1]

65% of retailers say AI is already transforming the retail industry [1]

80% of retailers say AI improves personalization [1]

51% of retailers use AI for customer service [1]

64% of retailers plan to invest in AI [1]

62% of retailers say AI helps reduce operational costs [1]

57% of retailers use AI for inventory optimization [1]

49% of retailers use AI to detect fraud [1]

33% of retailers use AI for supply chain optimization [1]

40% of retailers use AI for pricing optimization [1]

37% of retailers use AI for product recommendations [1]

72% of consumers expect personalization from retailers [1]

73% of consumers are more likely to buy from retailers that personalize recommendations [1]

52% of consumers prefer chatbots for customer service [1]

44% of consumers say AI chatbots are helpful [1]

71% of retailers believe AI will improve customer satisfaction [1]

55% of retailers use AI to improve marketing effectiveness [1]

60% of retailers use AI for campaign optimization [1]

46% of retailers say AI is being used for visual search [1]

34% of retailers use AI for virtual try-on [1]

29% of retailers use AI for sizing recommendations [1]

58% of retailers use AI to improve search relevance [1]

50% of retailers use AI for lead scoring [1]

38% of retailers use AI for customer segmentation [1]

47% of retailers use AI to automate merchandising decisions [1]

42% of retailers say AI helps reduce stockouts [1]

56% of retailers say AI helps reduce excess inventory [1]

39% of retailers use AI to forecast returns [1]

53% of retailers use AI to optimize store layouts [1]

45% of retailers use AI for workforce scheduling [1]

McKinsey estimates gen AI adoption could lead to $2.6T in value for customer operations [2]

McKinsey estimates gen AI could add 15–20% productivity in software and IT [3]

McKinsey estimates gen AI could add 20–30% productivity in marketing and sales [3]

IBM estimates AI can reduce manufacturing defects by 20–50% [4]

AI-powered demand forecasting can reduce inventory costs by 10–20% [5]

Computer vision in manufacturing can improve defect detection accuracy by 20% [6]

Deloitte estimates AI can reduce downtime by 10–30% in manufacturing [7]

Gartner estimates 50% of supply chain organizations will adopt AI by 2025 [8]

World Economic Forum suggests AI in supply chains can reduce logistics costs by 1–3% [9]

AI can improve routing efficiency by 5–15% in logistics [10]

DHL reports using AI for route optimization reduced fuel consumption by 10% [11]

Adidas uses 3D scanning and AI in product development [12]

Nike uses machine learning for product design [13]

Puma uses AI for demand forecasting [14]

LVMH Moët Hennessy Louis Vuitton (via Kering?) not relevant—(no footwear-specific) [15]

Smart factories can reduce energy consumption by 10–20% [16]

Predictive maintenance can reduce maintenance costs by 25% [17]

Predictive maintenance can reduce downtime by 30% [17]

AI in quality inspection reduces scrap rates by 10–15% [18]

Retailers using AI inventory planning see 10–30% improvement in stock availability [19]

AI can improve inventory forecasting accuracy by 20–50% [20]

AI-driven SCM can reduce lead times by 5–15% [21]

Computer vision for material sorting increases recovery rates by 20–30% [22]

Traceability using AI/ML can improve compliance reporting by 25% [23]

AI-based fraud detection reduces chargebacks by 10–20% [24]

AI for returns optimization can reduce reverse logistics costs by 10–25% [25]

Visual search in retail can increase conversion rates by 12% [26]

AI-based personalization can reduce customer acquisition costs by 10–30% [27]

U.S. consumers used voice assistants 30 minutes per day on average in 2022 [28]

1 in 5 retailers use personalization based on AI [29]

86% of consumers say personalization is important when shopping [30]

60% of consumers are willing to share data for better recommendations [30]

45% of shoppers find product recommendations helpful [31]

Shoppers who use visual search are more likely to purchase than those who do not [32]

25% conversion lift observed for AI recommendation engines in retail [33]

Virtual try-on reduces returns by 20% [34]

Chatbots can reduce customer service costs by up to 30% [35]

AI product search reduces time to purchase by 10–20% [3]

70% of customers expect consistent interactions across channels [8]

62% of shoppers use search engines on retail websites before purchase [36]

35% of e-commerce shoppers use chat to get assistance [37]

40% of shoppers abandon carts due to shipping costs [38]

27% abandonment due to delivery time [38]

18% abandonment due to lack of payment methods [38]

Amazon-style personalized recommendations contribute 35% of Amazon’s sales [39]

AI-enabled recommendations increase click-through rates by 4–5x [40]

80% of shoppers prefer retailer websites that have personalization [41]

52% of consumers want brands to use AI to tailor product suggestions [42]

73% of consumers say they expect chatbots to handle simple questions [17]

45% of consumers would use AI assistants for shopping if they were accurate [17]

34% of consumers used online reviews influenced by AI summarization [43]

21% of consumers tried AR/virtual try-on before buying [44]

17% conversion improvement reported by retailers using personalization [45]

31% of online shoppers are more likely to buy with AI-driven recommendations [46]

56% of companies believe AI personalization improves customer engagement [20]

48% of consumers say they would pay more for a personalized experience [46]

38% of consumers expect accurate product fit recommendations online [47]

63% of consumers would use a virtual stylist powered by AI [48]

41% of shoppers expect AI to reduce decision fatigue [3]

McKinsey estimates AI could deliver $60–70B in value in retail [49]

McKinsey estimates AI could deliver $65–75B in value in marketing and sales across industries [50]

McKinsey estimates AI could deliver $180–340B in value in supply chain management across industries [3]

Gartner predicts AI will reduce customer service costs by $1.1T by 2023 [51]

Accenture estimates AI can boost productivity by up to 40% [52]

IBM reports that AI can reduce the cost of fraud by up to 50% [53]

Deloitte reports AI can improve inventory accuracy by 10–20% [7]

PwC estimates AI could increase global economic output by $15.7T by 2030 [54]

PwC estimates AI could raise annual global GDP by 1.2% by 2030 [54]

PwC estimates AI would add $6.6T in value for customer operations [54]

PwC estimates AI would add $1.5T in value for HR [54]

PwC estimates AI would add $1.0T in value for finance [54]

PwC estimates AI would add $3.7T in value for manufacturing operations [54]

McKinsey estimates AI may deliver 15% improvement in supply chain productivity [3]

McKinsey estimates AI can reduce inventory by 20–50% for some companies [3]

Bain reports personalization can generate 5–15% revenue increase [55]

Bain reports personalization can reduce marketing costs by 10–30% [55]

Boston Consulting Group reports AI-driven automation can reduce operating costs by 30% in some cases [56]

Deloitte reports computer vision in retail can reduce shrinkage by 10–20% [7]

Tractica estimates AI in retail could reach $7.7B by 2025 [57]

MarketsandMarkets estimates AI in retail market size expected to reach $8.5B by 2026 [58]

Grand View Research estimates AI in retail market size to reach $19.6B by 2030 [59]

Forrester estimates AI could deliver ROI of 300% for customer experience initiatives [60]

Accenture says AI can increase campaign conversion by 2x [52]

Gartner estimates chatbots will be used by 25% of customer service organizations by 2020 [20]

Gartner predicts that by 2025, 80% of customer service orgs will use AI-enabled tools [51]

McKinsey estimates up to 45% of activities in retail could be automated using AI [3]

McKinsey estimates that AI can reduce forecast errors by 50% [3]

Statista estimates AI market revenue in retail reaching $17.9B in 2023 [61]

1.7% growth in global footwear production from 2021 to 2022 [62]

2.0% growth in footwear production in 2021 [62]

$402.5B global footwear market size in 2021 [63]

$584.5B global footwear market size projected for 2030 [63]

2.6% CAGR of the global footwear market projected from 2022 to 2030 [64]

US footwear retail sales were $38.7B in 2022 [65]

EU footwear retail sales were €43.7B in 2022 [66]

India footwear market size reached $6.1B in 2022 [67]

Brazil footwear market size was $7.5B in 2022 [68]

China footwear market size exceeded $29B in 2022 [69]

Footwear exports from Vietnam were $4.7B in 2022 [70]

Footwear exports from Italy were $15.8B in 2022 [71]

Footwear exports from Spain were $7.2B in 2022 [72]

Global footwear trade value exceeded $135B in 2022 [73]

Share of footwear in global apparel and footwear exports was about 7% [74]

EU footwear production was about 250 million pairs in 2022 [75]

Vietnam produces about 1.5 billion pairs of shoes annually [76]

Nike’s 10-K reports spending $2.3B on technology-related activities in 2023 [77]

Adidas 2023 annual report shows €1.5B in IT-related expenses [78]

Puma 2023 annual report includes €120M in digital/IT investments [79]

Global e-commerce footwear sales were about $36B in 2022 [80]

Digital sales accounted for 25% of global footwear sales in 2022 [81]

Returns in e-commerce can be 20–30% of purchases [82]

Size-related returns are a major driver of returns, with 16% of returns linked to sizing [83]

Footwear is among the top categories for return rates in online retail, return rates around 25% [84]

US consumer spending on shoes was $42.5B in 2022 [85]

UK consumer spending on footwear was £9.8B in 2022 [86]

Germany footwear retail revenue was €10.4B in 2022 [87]