The hidden costs of using apparel shopping apps

Fashion retailers, and online clothing stores will often entice shoppers to download and use their official apps rather than simply ordering through a website. They’ll sometimes even offer significant discounts and bonuses to sweeten the deal. At some point, shoppers have to ask: why the push to use these apps, what’s in it for the retailers?

It’s reasonable to expect some personal-data collection and even data sharing when making a purchase online. Details like the customer’s name, payment details, address (for delivery), email address (for confirmations), and phone number (for delivery notifications) make sense. But how is data like the customer’s sexual orientation or contacts list relevant? Heightening concerns is the fact such data is not only collected but also shared with third parties.

Incogni’s researchers took a deep dive into the most popular apparel shopping apps from 59 countries as well as the shopping apps of the top apparel brands (by valuation) for the year 2023, ending up with a total of 180 apps. 

Our researchers analyzed the data, looking at data-collection and data-sharing practices as well as the reasons app developers give for collecting and sharing specific types of data. We also examined which of the collected and shared data points are optional, empowering consumers to withhold certain sensitive data.

Key findings

• 45 out of 180 investigated apps collect photos, 12 apps collect videos, 9 apps collect search history, and 6 apps collect information on sexual orientation.
• 24 apps share photos with third parties, 2 apps share sexual orientation, and 1 app shares health information.
• The greatest number of data points are collected and shared from customers in Oceania (15.9 and 8.7 data points, respectively), Europe (14.2 and 9 data points), and North America (12.3 and 8.1 data points).
• Among the most popular apps (by valuation), Nike and H&M collect the greatest numbers of data points, including photos and videos and even messages.
• PUMA, Under Armour, The North Face, and H&M share a concerning amount of sensitive data with third parties for the purposes of advertising and/or marketing.

Data collection and sharing

To show the scope of the problem of excessive data collection by apparel shopping apps, we identified 180 popular apparel retail apps and analyzed their data collection and sharing practices. 156 of these 180 apps were found to collect at least some data. The full list of apps, organized by country, can be found here.

This finding is surprising given that any app that allows for purchases is presumed to collect and/or share at least some data to facilitate transactions. Although the reasons for these apparent inconsistencies are unclear, it may have something to do with the way declarations made in the Google Play Store’s data safety section are handled. If Google uses a trust-based system, such data-collection-practice disclosures would be vulnerable to mistakes and misrepresentation.

Apps that are claimed to collect at least some data, collect an average of 11.5 data points.

Some data points stand out as being rather sensitive to give up to an app, even if making a purchase through it:

• Precise location (collected by 31 apps, including Nike, The North Face, Adidas, and Victoria’s Secret) 
• Sexual orientation (collected by 6 apps: Showniq – AI Stylist Của Bạn, Nike SNKRS: Shoes & Streetwear, Instreet, Boots TH, Pantaloons-Online Shopping App, and Zalando – online fashion store)
• Photos (45 apps, including: Nike: Shoes, Apparel & Stories, H&M – we love fashion, Victoria’s Secret, and Moncler Official Store)
• Videos (12 apps, including: Nykaa – Beauty Shopping App, Vinted – Buy and sell clothes, and Meesho: Online Shopping App)
• Contacts (6 apps: 29CM, Nykaa – Beauty Shopping App, Representante Eudora, LimeRoad: Online Fashion Shop, Myntra – Fashion Shopping App, and Meesho: Online Shopping App)
• Installed apps (12 apps, including: LimeRoad: Online Fashion Shop, Myntra – Fashion Shopping App, and Meesho: Online Shopping App)
• Web browsing history (9 apps, including Victoria’s Secret and Puma)
• SMS or MMS (6 apps: Nykaa – Beauty Shopping, AJIO Online Shopping App, Modanisa: Modest Hijab Fashion, Gloria Jeans — магазин одежды, Modanisa: Modest Hijab Fashion TR, and Instreet)
• Credit score (3 apps: Zalando – online fashion store, Riachuelo – Comprar roupas, and Boots TH)
• Voice or sound recordings (2 apps: Nykaa – Beauty Shopping App and Zarya App).

One app (Myntra – Fashion Shopping App) even collects health and fitness information from its users. 

These 156 data-collecting apps share an average of 5.6 data points each, compared to the 5.5 shared by the top brands’ apps. 

Something to be on the lookout for when choosing an apparel shopping app is what data ends up in the hands of third parties, especially those that have nothing to do with the given purchase. In our dataset of globally popular apps, we found that:

• Precise location is shared by 22 apps (including The North Face and Adidas)
• Names – 60 apps (including H&M – we love fashion, The North Face, Under Armour, and Puma)
• Email addresses – 60 apps (including H&M – we love fashion, The North Face, and Under Armour)
• Photos – 24 apps (including Adidas, Myntra – Fashion Shopping App, and  SHEIN-Shopping online)
• Emails (not email addresses) – 7 apps (including Modanisa: Modest Hijab Fashion, Voghion – Online shopping app, and Hacoo – sara lower price mart)
• SMS and MMS messages – 3 apps (Modanisa: Modest Hijab Fashion, adidas CONFIRMED, and Modanisa: Modest Hijab Fashion TR)
• Sexual orientation – 2 apps (Showniq – AI Stylist Của Bạn and Pantaloons-Online Shopping App) 
• Health information – 1 app (Myntra – Fashion Shopping App).

Further below, we explore how much of this information is shared for advertising purposes, but even data that isn’t immediately shared with marketers is still being shared among other companies, increasing the chances of users being affected by a data breach. 

Optional data

To understand to what extent users can safeguard their information while shopping online, we took a look at what data collection can be avoided while using these apps. It’s important to note that opting out of providing certain data points could lead to losses of functionality. 

In our dataset of 156 data-collecting apps, 35.9% of all data points collected were optional. Among the top brands’ apps, the proportion of optional data points was 52.1%.

Thankfully, we found that 4 out of the 6 instances in which sexual orientation was collected were optional. 

Purposes

To understand why all this data reaches the developers of the investigated apps, we took a look at what purposes are listed for both user-data collection and sharing. We paid particular attention to how many data points are used for advertising and/or marketing. 

Among the most popular brands’ apps, of all shared data points, 33% are shared for the purpose of advertising. That rate goes up to 59% for the 156 apps popular around the world. A cause for concern is how many apps share sensitive data with third parties for advertising or marketing purposes. In our dataset, we observed:

• 43 apps sharing users’ email addresses for advertising and/or marketing purposes
• 29 sharing names
• 22 sharing phone numbers
• 14 sharing purchase histories
• 6 sharing photos 
• and 6 apps sharing users’ addresses.

We found that the most popular retail brands’ apps provide an average of three purposes for each data point they collect. Unsurprisingly, app functionality comes up most frequently, accounting for 29% of all purposes. The second-most cited purpose for collecting user data was analytics (20% of all purposes) and the third was account management, which accounted for 15% of all purposes. Out of the seven available purposes, advertising or marketing was referenced fourth-most frequently, representing 14% of all purposes. 

Notably, the purposes given for sharing data skew more towards analytics and advertising and marketing than those given for data collection. For example, across the whole dataset, for data collection, advertising and marketing was the third-most cited purpose at 13.4%, but for data sharing it constituted 17% of all cited purposes.

We observed that this tendency was more pronounced for the most popular apps worldwide. Marketing was the third-most cited purpose behind collecting data (14.4%) but the second-most frequently cited purpose behind sharing it (18.8%). Account management saw the biggest difference in terms of how frequently it was cited as a purpose for data collection (10.1%) and data sharing (5.6%). 

When it comes to purposes given for sharing user data, the top apparel brands’ apps are more willing to handle your data for the purpose of marketing: 21% of all purposes for sharing data boil down to advertising or marketing, behind app functionality (30%) and analytics (24%).

Country comparison

Next, we looked at which countries tend to use the most data-hungry apparel shopping apps. We began with a breakdown of the globe into six regions: Oceania, Europe, the Americas, Asia, and Africa.

Apps popular with users in Oceania (Australasia, Melanesia, Micronesia, and Polynesia) collected the highest number of data points on average, at 15.9, while sharing an average of 8.7 data points (second-highest among the six regions). Apps popular in this region had, on average, 4.8 optional data points (also second-highest among the six regions).

Within Oceania, Australia stands out for the amount of data apparel apps collect there (at an average of 16 data points per popular app). Apps in Australia also share an average of 8.9 data points. New Zealand is not far behind with 15.8 data points collected and 8.5 shared on average.

Apps popular in Europe come in second in terms of data collection. They collect an average of 14.2 data points and share 9 (which is the highest of any region). Notably, when looking at the global data-collection rankings, 4 of the top 5 countries are European: Sweden (ranked 1st), United Kingdom (ranked 2nd), Norway (ranked 4th), and Denmark (ranked 5th). 

Mobile apparel shopping in North America is done using the third-most data-collecting set of apps. Within North America, apps popular with US users collect an average of 12.3 data points and share 8.1. Apps preferred by Canadians collect the most data in the region: 14.1 data points on average, while US residents give up 14 data points on average. 

Apparel shopping apps popular with users in Asia ranked fourth by data collected, where an average of 11.5 data points were collected and 7.7 were shared. Within Asia, India saw the highest number of data points collected by apparel apps, at 14.4. 

Apps popular with users in Africa were found to collect 10.5 data points on average and share 6.5. Within the African region, South Africa stood out as the country with the clothing apps that collect the most data, at 11.4 data points, sharing 6.

Lastly, users in South America gave up the least amount of data to their most popular apparel apps: 10.3 data points on average, almost a third less than users in Oceania. Although, notably, the apps popular there collected 7.8 data points on average, more than in Africa and Asia. In South America, Brazil stood out as favoring more data-hungry apps, which on average collected 14 data points. 

Most popular apparel apps by valuation

To better understand what types of data most people give up when making changes to their wardrobe, in this section, we look at the data-collection and sharing practices of the top apparel brands’ apps. Our researchers identified the top 10 apparel brands by valuation (for 2023) and checked which of those brands offered mobile apps that allow for purchases to be made. It’s on these apps that we focused in this section to investigate trends that are more globally universal.

These apps were found to collect an average of 14.4 data points. They were found to share an average of 8.5 data points.

Notably, 2 out of the 10 most popular apps are also found amongst the top 10 most data-collecting apps. Nike and H&M collect 18 data points each and are tied for 7th most data-collecting app with 4 other apps. 

We found that these apps share a concerning amount of personally identifiable and otherwise sensitive data with third parties for the purposes of advertising and/or marketing, including:

• Users’ names, shared by PUMA
• Phone numbers, shared by Under Armour, The North Face, and H&M
• Users’ email addresses, also shared by Under Armour, The North Face, and H&M.

Thankfully all 10 of the top brands’ apps encrypt users’ data as it travels from their devices to the developer and allow users to request that their data be deleted.

Conclusion

A mousetrap only works because the mouse doesn’t understand why the cheese is free. Variations of this phrase regularly do the rounds in the cybersecurity and privacy-advocacy communities. The incentives associated with using proprietary apps to buy apparel—or even just the convenience of doing so—come with hidden costs.

It’s arguably easier to tap on an app icon than it is to dig up a bookmark or type in a URL. As our research shows, though, these and other benefits come at a price. Consumers are, of course, free to decide whether the deal on offer is right for them, but this has to be an informed decision. It is our hope that research like this will go some way towards helping consumers get the most bang for their personal data.

At the very least, they should know that the cheese in front of them is demonstrably not free.

Methodology

Incogni’s researchers used the rankings provided by AppMagic¹ (in the Shopping: Fashion & Beauty) to find the most popular apps in 59 countries. For each country, they noted the top 10 most popular free apps in the “Shopping: Fashion & Beauty” category for the year 2023. App names and their rankings were noted on December 18th. Our researchers separately identified the top apparel brands by valuation,² filtering for those brands that offer apps facilitating purchases. These brands’ apps were added to the list for investigation. 

Incogni’s researchers went on to collect information found in the data safety sections of the Google Play Store pages of the identified apps. The information was aggregated on country and regional bases for some analyses. Data collection from the Google Play Store took place on December 19th. 

The data used in this study is available here: Public dataset.

Note on data:

Some apps might have been miscategorized in AppMagic’s ranking. This was discovered when some apps were found to collect no data, which is highly unlikely for any application that allows purchases. 

Sources

1. AppMagic. “Top Apps.” Apps. Accessed January 3, 2024. https://appmagic.rocks/top-charts/apps?store=1&tag=243578&date=2023-01-01&aggregation=year. 
2. Brand Finance. “Apparel 50 2023 Ranking.” Brandirectory. Accessed December 22rd, 2023. https://brandirectory.com/rankings/apparel/table.

Visuals

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