Augmented reality has been described as the future of retail for roughly a decade. Some of it arrived. A great deal of it was a campaign that ran for a fortnight and was quietly retired.
This guide separates the two what AR does in retail, which applications have lasted, what the market actually looks like in India, where AR has limited application, and where the same underlying visual technology is doing less glamorous but more measurable work behind the shelf.
What is Augmented Reality in Retail?
Augmented reality overlays digital content onto a live view of the physical world, usually through a smartphone camera. In retail, that means placing a virtual sofa in a customer’s living room, showing how a pair of spectacles sits on their face, or bringing a shop-window display to life when a phone is held up to it.
It differs from virtual reality, which replaces the physical environment entirely. AR’s commercial advantage is that it requires no headset – the device is already in the shopper’s hand.
The Augmented Reality in Retail Market
Global Picture
AR in retail sits within a broader immersive technology market growing rapidly from a small base. Growth forecasts are consistently strong across research houses, though the absolute figures diverge widely depending on what each study counts as AR and whether hardware, software and services are included.
India: Adoption And Market Context
India is among the faster-growing AR markets, driven by smartphone penetration, cheap mobile data and a young consumer base. IBEF identifies retail as one of the principal AR adoption sectors in India, naming Myntra, IKEA and Lenskart among the retailers offering AR-based services that let customers evaluate products without visiting a store.
A caution worth stating plainly for anyone using this section for planning, published estimates of the Indian AR market vary by several multiples between research houses, depending on scope and methodology. Treat the direction as reliable and any single figure as indicative.
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How Retailers Actually Use AR
Virtual Try-On: Fashion, Eyewear And Beauty
The most commercially established application. Shoppers see how a product looks on them before buying – spectacle frames, cosmetics, watches, footwear.
- Lenskart 3D Try-On lets customers see how frames sit on their face before purchase. Eyewear is arguably the strongest fit for the technology the product sits in a fixed position on a recognisable feature, and the purchase decision is substantially about appearance.
- Sephora Virtual Artist applies makeup shades using facial recognition, addressing a category where colour matching is the primary uncertainty and physical testers carry hygiene constraints.
- Myntra has offered AR-based try-on features within its app, extending the approach to apparel and accessories in the Indian market.
Fit, as opposed to appearance, remains the harder problem. Showing how a garment looks is achievable; showing how it will fit a specific body remains substantially unsolved, which is why returns in apparel have proved more stubborn than AR marketing suggests.
Home Preview And Spatial Placement
IKEA Place remains the reference implementation, a 3D model of a product placed to scale in the customer’s own room through the phone camera. It works because the underlying uncertainty – will this fit, and will it look right in my space – is genuinely difficult to resolve any other way, and because furniture is a considered, high-value purchase where the effort is justified.
The same logic extends to appliances, flooring, paint and fixtures, and it is where AR has generated the most durable commercial value.
In-Store Ar And Interactive Packaging
The least durable category, and the one most often cited as evidence of AR’s arrival. Zara is the standard example. In April 2018 the brand ran an AR campaign across 120 stores worldwide, shoppers pointed a phone at a marker in the shop window or an in-store podium and saw short sequences of models presenting the collection, with the option to buy directly. It was well executed and widely covered.
Industry Trends Indicate That In-Store Retail Audit
It also ran for two weeks. It was a campaign, not a capability – and that distinction is the most useful thing the example teaches. In-store AR has repeatedly generated strong launch coverage and limited sustained use, because it asks the shopper to download an app and hold up a phone while standing in a shop, which is friction the experience has to overcome every single time.
Interactive packaging faces the same barrier for the same reason.
What AR Delivers – and What the Evidence Shows
The claims commonly made for AR are these. The evidence behind each varies considerably, and it is worth being clear which is which.
| Claim | Assessment |
|---|---|
| Higher purchase confidence | Well supported in categories where the uncertainty is visual – furniture placement, eyewear fit, cosmetic shade. The mechanism is clear and the effect is intuitive. |
| Reduced returns | Supported in appearance-driven categories, weaker in fit-driven ones. Apparel returns are driven substantially by sizing, which current AR does not resolve. |
| Higher conversion | Reported by several platforms, though published figures come largely from AR vendors and the retailers deploying them, so treat vendor-sourced numbers with the usual caution. |
| Increased basket size | The least evidenced of the four. Frequently asserted, rarely quantified independently. |
| Improved engagement | Demonstrable at launch. Sustained engagement is the harder question and where most in-store AR has underperformed. |
Where AR Has Not Worked
Published guidance on AR in retail is almost uniformly positive, which makes it a poor basis for a decision. Four failure patterns recur.
- Campaign, not capability : Many celebrated deployments ran for weeks. The launch coverage persists in industry articles long after the feature has been withdrawn, which is how eight-year-old pilots end up cited as current practice.
- Download friction : Any experience requiring an app install at the point of use loses most of its audience. AR that lives inside an app the shopper already has performs very differently from AR that needs a new one.
- Device dependency : AR quality varies sharply with handset capability. In a market where much of the audience uses entry-level Android devices, the experience many shoppers actually get is not the one shown in the demonstration.
- Cost against use : Building a credible AR experience requires 3D asset creation for every SKU. For a wide range this is a substantial and recurring cost, and it is why AR has concentrated in categories with limited SKU counts and high unit values.
AR in the Indian Retail Context
Modern Trade, E-Commerce And Quick Commerce
This is where AR in India lives. E-commerce platforms and app-based retailers can embed AR where the shopper already is, which removes the download barrier that has limited in-store deployments. Categories with clear visual uncertainty and manageable SKU counts – eyewear, furniture, cosmetics, home décor – are where the investment has concentrated and where it has held.
For Detailed Insights Into What Is Retail Conversion Rate
Why Ar Has Little Application In General Trade
Worth stating plainly, because no published guidance does. The great majority of Indian retail outlets are kirana and standalone stores. There is no app, no display infrastructure, frequently no self-service shelf, and a shopper who is not browsing in a way AR could assist.
For a brand whose volume comes from general trade, AR is not a distribution or availability lever and should not be evaluated as one. The in-store technology that affects sales in that channel is considerably less glamorous, whether the product is on the shelf, visible, correctly priced and in the agreed position.
Industry Trends Indicate That Modern Trade vs E-Commerce
The Other Side of Visual Technology: Shelf Recognition
There is a second application of visual technology in retail that receives a fraction of the attention and generates considerably more measurable value.
A note on terminology, because it is frequently blurred. Shelf recognition is computer vision rather than augmented reality, AR overlays digital content onto a live view, while shelf recognition analyses a captured photograph. They share underlying techniques and are often discussed together, but they are not the same thing, and conflating them overstates what AR does in-store.
What Image Recognition Does On The Shelf
A photograph of a bay, processed by a trained model, returns structured data, which SKUs are present, how many facings each holds, whether the arrangement matches the agreed planogram, what share of the shelf the brand occupies, and what competitors are doing alongside.
Work that previously required a person counting facings by hand becomes a photograph and a score. That makes high-frequency measurement economically viable at national scale, which is the difference between auditing a sample occasionally and measuring the estate continuously.
Why It Needs Photographs From Real Stores
The constraint is straightforward and frequently overlooked, the model is useless without images, and the images have to come from inside stores. Someone has to visit the outlet, stand in front of the bay and take the photograph – at the right frequency, across the right store universe, with verification that the visit happened and the image is current.
This is why shelf recognition is an operational capability rather than a software purchase. The algorithm is the easy part.
How PPMS Uses Visual Recognition in Retail Execution
PPMS operates the photographic layer that shelf recognition depends on.
Every store visit is captured through FRAMe, our proprietary field application, with geo-tagged and time-stamped photographs of shelf and store conditions reaching the brand’s dashboard the same day. AI-based shelf metrics convert those images into structured measurement – facings, share of shelf, planogram compliance and competitor presence – and FRAMe’s back-end auditing module independently validates and scores submissions, so the input to the model is verified rather than assumed.
The Scale Behind It: Over 15,000 employees across 1,500 towns and cities, covering 1,40,000 stores in modern trade vs general trade and emerging channels, with 27 years of operating history and full statutory compliance including SEDEX certification. Clients include ITC, PepsiCo, United Spirits, Unilever, Samsung, Tata Consumer Products, Marico and Dabur.
In one deployment, a brand operating at 78% store compliance with no real-time visibility reached 94% compliance after implementing FRAMe audits with live dashboards. Issue resolution time fell from three weeks to two days, and the programme delivered a 20% sales lift representing ₹10.8 crore in incremental revenue.
The Future of AR in Retail
Three developments are worth watching, stated with appropriate caution given how much AR forecasting has aged badly.
- AR inside apps people already use : The most likely path to sustained adoption is AR embedded in e-commerce and quick commerce apps rather than standalone AR apps, because it removes the download barrier that has limited every in-store deployment so far.
- Cheaper 3D asset creation : Generative tooling is reducing the cost of producing product models, which is the main constraint on AR across wide ranges. If that cost falls far enough, the economics change for categories currently priced out.
- Visual recognition moving faster than AR : The business application – shelf measurement, compliance scoring, competitor detection – is advancing more quickly and delivering more measurable return than the consumer-facing side, with considerably less attention.
One Forecast Worth Retiring: Metaverse-based shopping has been predicted repeatedly and has not materialised at commercial scale. It may yet. It should not appear in a planning document as a near-term assumption.
Frequently Asked Questions
1. How do retailers use AR?
Principally through virtual try-on for eyewear, cosmetics and accessories; home preview for furniture and fixtures; and in-store or packaging-based experiences. The first two have proved commercially durable; the third has largely run as campaigns.
2. Did Zara use augmented reality?
Yes, as a campaign. In April 2018 Zara ran an AR experience across 120 stores worldwide for approximately two weeks, in which shoppers pointed a phone at a marker in the shop window or an in-store podium to see short sequences of models presenting the collection. It was a time-limited campaign rather than a standing capability, which is a useful illustration of how much in-store AR has worked.
3. Which Indian retailers use AR?
IBEF identifies Myntra, IKEA and Lenskart among Indian retailers offering AR-based services. Lenskart’s 3D try-on for frames is the most established, reflecting eyewear being a strong category fit for the technology.
4. Does AR actually reduce returns?
In categories where the uncertainty is visual – furniture placement, frame shape, cosmetic shade – the evidence is reasonably strong. In apparel, returns are driven largely by sizing and fit, which current AR does not resolve well, so the effect is weaker than commonly claimed.
5. What does AR cost to implement?
The main cost is 3D asset creation for every SKU, which recurs as ranges change. This is why AR has concentrated in categories with limited SKU counts and high unit values, and why it is rarely viable across a broad FMCG range.
6. Does AR work in general trade retail?
Largely no, Most Indian outlets are kirana and standalone stores with no app, no display infrastructure and often no self-service shelf. For brands whose volume comes from general trade, AR is not an availability or distribution lever and should not be evaluated as one.
7. Is shelf image recognition the same as AR?
No, though they are related and often discussed together. AR overlays digital content onto a live view; shelf recognition analyses a captured photograph to return facings, planogram compliance and share of shelf. Shelf recognition is computer vision, and it depends on someone physically photographing the shelf.
Reference List
1. India Brand Equity Foundation (IBEF) : India’s AR/VR Market, Growth and Technology Trends – identifies retail as a principal AR adoption sector in India and names Myntra, IKEA and Lenskart among retailers offering AR-based services. The brief-specified source and the most appropriate institutional citation for the India section.
https://www.ibef.org/blogs/india-s-ar-vr-market
2. Forbes / Retail Dive / Internet Retailing : Zara AR campaign, April 2018 – AR displays introduced across approximately 120 stores worldwide, with an initial two-week run; models shown via smartphone pointed at in-store sensors and window displays, with direct purchase through the app.
3. Glitchr Studio : Technical documentation of the Zara AR build – 120 participating stores, 12 sequences, developed for client Holooh using Unity, iOS, Vuforia and videogrammetry, April 2018. Confirms the campaign-based nature of the deployment.
https://www.glitchr-studio.com/portfolio-item/zara-augmented-reality/
4. Multiple research houses : India AR market sizing – estimates diverge substantially between providers (approximately US$789 million for 2023 from one source, US$3.7 billion for 2025 from another, US$4.7 billion for 2025 from a third), reflecting different scope definitions. Do not cite any single figure as settled. Commission or purchase a figure from a named house with stated scope.
Varies; see section 1.1
5. Deloitte–FICCI : “Spotting India’s PRIME Innovation Moment”, August 2025 – Indian retail projected to reach US$1.93 trillion by 2030; useful for sizing the addressable retail context around AR adoption.
6. PPMS Field Marketing : FRAMe product documentation – geo-tagged, time-stamped photographic capture, AI-based shelf metrics, back-end auditing and scoring module. Confirm current AI shelf metrics capability and accuracy with the product team before publishing claims about it.
7. PPMS Field Marketing : Published case study – store compliance 78% to 94%, issue resolution three weeks to two days, 20% sales lift, ₹10.8 crore incremental. Requires verification and client clearance before republication.
https://ppms.in/blog/5-ways-retailers-gain-a-competitive-advantage-with-mobile-apps/
8. PPMS Field Marketing : Published operational data – 15,000+ employees, 1,500 towns and cities, 1,40,000 stores, SEDEX certification. NOTE: photo volume and years-of-operation figures are inconsistent across ppms.in properties; reconcile before citing.
