Future of shoe and fashion retail
Three boxes of incoming goods before opening, and the reorder runs on gut feeling again: you know these moments. Around 86 percent of retail revenue is still generated in brick-and-mortar stores (HDE). Those who combine this on-site strength with their own clean data have the better cards. The DezemberHub WANDEL model shows six stages for that.
Framework
DezemberHub WANDEL model
From everyday store life
Four scenes as they happen every week in a shoe store. If you recognise yourself here, this page is written for you.
Tuesday morning, half past eight. Three boxes of incoming goods are in the warehouse, and before the first customer rings, you type in position by position: item number, colour, size run, purchase price. Two hours you're missing in the evening.
The sales rep is waiting for your budget, the reorder should go out today. The best-seller list would be the right basis, but the last clean report is from the start of the month. So gut feeling decides again. Usually it works out. Usually.
A regular customer has fallen in love with a model and needs a 38 in width H. On the shelf there's a 37 and a 39. Whether the partner branch has the 38 in stock you're not sure, and the customer is in a hurry.
At ten in the evening someone asks their phone for running shoes in Munich. Whether your store appears in the answer isn't decided in that moment but long before: in your product master.
The future of shoe and fashion retail is digital and brick-and-mortar at once. Dedicated shoe stores have more than halved since 2010 (BTE), yet brick-and-mortar retail remains the largest channel with around 86 percent of revenue (HDE). The winners will be specialist retailers who cut costs, offer experience, sell across branches and maintain their data so that POS, AI and AI search can build on it.
The DezemberHub WANDEL model offers inspiration for exactly this path. It combines [W] less busywork, [A] a trial with real data, [N] nearness to the customer, [D] clear insight, [E] shopping experience and [L] listing in AI bots, practical for shoe retail, specialist fashion retail and specialist sports retail.
Documented figures
Nine documented metrics that show why now is the right moment for change. Each figure is linked directly to its original source.
Swipe to see all columns
| Key figure | Value | Year | Source |
|---|---|---|---|
| Dedicated shoe stores in Germany since 2010 | more than halved (from over 5,000 to around 2,500) | 2025 | BTE |
| Brick-and-mortar shoe retail in the first half of 2025 | around -4%, while online shoe purchases rose +7.6% (Q2) | 2025 | BTE |
| Operating costs in retail since 2020 | around +30%, with revenues below 2019 levels | 2025 | BTE |
| Share of brick-and-mortar retail in total retail revenue | around 86% (online share 13.4%) | 2024 | HDE Online Monitor 2025 |
| Online shoppers in Germany who bought via Instagram in the last three months | 34%, ahead of Facebook (29%) and YouTube (28%) | 2025 | DHL E-Commerce Trends Report 2025 |
| Retail companies planning, testing or using AI | 83%, of which 16.2% in broad use | 2025 | HDE/Safaric Consulting |
| Retail companies that see AI as a competitive advantage | 61 % | 2025 | Bitkom |
| The fashion industry's biggest opportunity according to executives | Artificial intelligence, ahead of product differentiation and sustainability | 2026 | McKinsey/BoF State of Fashion 2026 |
| AI labelling obligation under the EU AI Act (Article 50) | mandatory from August 2, 2026 | 2026 | EU AI Regulation |
More verified figures on shoe retail, fashion, e-commerce and AI in retail in the Statistics hub.
The framework
The model is deliberately an inspiration, not a prescription: you know your store best, the six stages point you the direction. Each stage is operational: [W] automate busywork, [A] fit it with real data, [N] nurture nearness to the customer, [D] gain clear insight, [E] create a shopping experience and [L] become findable in AI search.
Stage 1
Three boxes of incoming goods should not cost two hours of typing.
Less busywork is the first WANDEL step, and concretely it means: the system takes work off your hands. Master data comes from the supplier catalogue instead of the keyboard, goods receipt runs with a scanner in minutes, order suggestions are ready calculated. With operating costs that have risen by around 30 percent since 2020 according to BTE, that is not comfort but economics. And your team has time again for what no system takes over: the customer on the floor.
Stage 2
No customer buys shoes without trying them on. In exactly the same way, you try the new system on first, with your real items instead of demo data.
A trial with real data means the switch is not treated as a leap into the unknown but as a fitting. You see your real items, sizes, stock and revenue in the new system, alongside ongoing operations, without your store noticing anything. This way you check at your leisure whether the processes from POS to e-invoicing fit you and whether you find your footing in the system, before go-live begins.
Stage 3
You know your regular customers by name. Your system should know their sizes and favourite brands too.
Nearness to the customer means backing personal advice with data: loyalty card, purchase history, sizes and preferences are maintained in the system, across store and online channels. When the reorder arrives, the regular customer waiting for her size gets a notice, instead of leaving it to chance. That turns walk-in customers into regulars.
Stage 4
Reorder best-sellers, mark down slow movers in time: gut feeling is too expensive for that.
Clear insight means: you see at any time what's selling and what's sitting. Best-seller lists, sell-through per branch, real margin after fees and returns, plus markdowns and dynamic, data-based prices with a fair, transparent approach. The AI assistant prepares reorders, budgets and pricing decisions from your real numbers. The decision stays with you, and your data stays yours: exportable at any time, kept locally on request.
Stage 5
The 38 in width H is missing, the partner branch has it in stock: sell it and ship it home.
Shopping experience means two things: staging and advice that no one replicates online, and connected selling across branch and buying-group boundaries. If the size is missing on site, the team checks availability in other branches or with buying-group partners, sells and ships to the customer's home. The sale stays in the house instead of being lost online.
Stage 6
Anyone who asks their phone for running shoes in Munich should find your store in the answer.
Listing in AI bots is the new visibility step, and it leads customers into the store. Anyone searching for running shoes in Munich, whether on Google, ChatGPT or Perplexity, should find the local specialist store with the right size and availability. For that, the assortment, location, opening hours and stock have to be machine-readable. The basis for this is not a trick but a clean product master.
What moves the market
These six forces drive the market. They are not a cause for concern but the fields on which specialist retail wins. Each force leads directly into a stage of the WANDEL model where it can be put into practice in your own store.
Operating costs in retail have risen by around 30 percent since 2020 (BTE), while revenues sit below 2019 levels. Those who stay automate the busywork: master data is loaded instead of typed in, the system calculates order suggestions.
Honest advice and reliable statements about goods were always the specialist retailer's strength. From August 2, 2026 the EU AI Act requires the labelling of AI content (Article 50). Transparency thus becomes the retailer's home advantage online too.
34 percent of online shoppers in Germany last bought via Instagram (DHL E-Commerce Trends Report 2025), and the TikTok Shop launched here in March 2025. Reach comes from real products and well-maintained inventory, and it now reaches into AI search.
Brick-and-mortar retail remains the largest channel with around 86 percent of revenue (HDE). Because buying online has become trivial, the store has to be a reason to come in: with advice and floor space that tells a story.
If a size is missing on site, the team checks other branches or buying-group partners, sells and ships home. The buying groups ANWR and SABU also made digitalisation and AI leading topics of their 2025 general meetings.
61 percent of retail companies see AI as a competitive advantage (Bitkom), and according to McKinsey and Business of Fashion, AI is the fashion industry's biggest opportunity. What matters is a fair approach: prices follow margin, age and sell-through, and you keep the sign-off.
Practical check
Change becomes tangible when it starts with data quality, POS security, inventory control and online findability. Start with the points that fit your store.
Between pre-orders, goods receipt and day-to-day business, there's rarely time for questions of principle. So these six impulses fit on a receipt: tick off what's already in place for you, and start with the first open item.
DezemberHub
A stocktake for the mind
Duplicates, missing sizes, unclear suppliers and wrong merchandise groups slow down every report.
What is permanently reordered needs different rules than promotional goods, seasonal goods or remaining stock.
Sales, returns, end-of-day closing and inventory should be viewed as one process, not as islands.
AI, online selling and advice only get better when availability does not have to be guessed.
Brand, model, colour, size, price, availability and category should be maintained in machine-readable form.
Good AI makes suggestions, the retailer keeps control over purchasing, price and promotions.
The future of shoe retail is digital and brick-and-mortar at once. Dedicated shoe stores have more than halved since 2010 (BTE), yet brick-and-mortar retail remains the largest channel with around 86 percent of revenue (HDE). The winners will be specialist retailers who cut costs, offer experience, sell across branches and keep their data clean for POS, AI and AI search.
Yes, if the data basis is right. 83 percent of retail companies plan, test or use AI (HDE 2025), and 61 percent see it as a competitive advantage (Bitkom). For small stores it is less the grand AI strategy that counts than the concrete benefit: reorder faster, manage markdowns, answer stock questions directly.
Dynamic pricing means aligning prices and markdowns with margin, age, stock and sell-through on a data basis instead of gut feeling. In specialist retail it is not about constant price swings that annoy customers but about deliberate, transparent decisions. The AI suggests, the retailer decides.
Yes. Despite consolidation, around 86 percent of retail revenue is still generated in brick-and-mortar stores (online share 13.4 percent, HDE 2024). Those who combine their strengths, namely advice, experience and local trust, with lean processes, connected selling and clean data stay competitive.
The DezemberHub WANDEL model is a 6-stage framework for shoe and fashion retailers in the AI age: [W] less busywork, [A] a trial with real data, [N] nearness to the customer, [D] clear insight, [E] shopping experience and [L] listing in AI bots. It is deliberately meant as inspiration, not a prescription: every store finds its own way, the six stages point the direction.
AI can only work with data that is structured and up to date. In shoe retail this concerns sizes, colours, widths, suppliers, branch stock, seasonal goods, NOS items and prices. A clean product master is therefore the basis for reliable AI answers, order suggestions and findability in AI search: what is missing or wrong in the product master, no AI can make up for.
A trial with real data means a retailer sees their own items, stock and revenue data in the new system before the new working routine begins. This makes the switch tangible and testable.
No. The AI assistant is included in every DezemberHub package. It works with the ERP data and answers questions about stock, reports and processes.
Listing in AI bots means structuring assortment and company data so that AI searches, shopping systems and future purchasing agents can better understand product data, availability and retailer information. This lets the local specialist store, with the right size and availability, appear in AI answers and bring customers into the store.
AI visibility brings walk-in customers: if someone searches for running shoes in Munich, the local specialist store with the right size should appear in the AI answer and the customer should come by. This requires machine-readable product data, current availability as well as location and opening hours. That way online visibility pays directly into in-store sales.
About this analysis
This analysis is maintained by the DezemberHub team, which works with shoe and fashion retailers every day. It is updated as soon as new documented industry figures are available. Last updated on July 1, 2026. Central sources: BTE Handelsverband Textil Schuhe Lederwaren, HDE, Bitkom, McKinsey and Business of Fashion, DHL E-Commerce Trends Report and the EU AI Regulation.
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