Survey of 1,000 United States consumers puts average retail app ownership at ten per device, of which five went unopened in the past month and three have never been opened at all. Adobe circulated the findings to media on August 21, 2026, four months before the peak of the holiday download season.

Nearly three in four customers have installed a brand or retail app to claim a single discount or complete a single purchase, then removed it, according to Adobe. The figure is 72%, and it sits at the centre of research the company published through its Adobe for Business blog and distributed to trade press on Friday, August 21, 2026.

The study surveyed 1,000 consumers across the United States. Adobe states a 95% confidence level with a margin of error of plus or minus 3 percentage points, and notes that the results are self-reported, meaning they may reflect perceptions rather than logged behaviour.

That caveat matters more than usual here. App deletion is a measurable event on a device; asking people to recall it is not the same as counting it. Adobe does not pair the survey with panel or SDK telemetry.

Ten apps, five dormant, three untouched

The ownership number is the study's most concrete finding. Customers report holding an average of ten retail or brand apps, five of which they have opened in the past month, and three of which they have never opened at all, according to Adobe. Half the installed base is inactive within a thirty-day window, and close to a third has never returned a single session.

Install motivations concentrate on incentives. According to Adobe, the leading reasons for downloading a retail app are joining a loyalty or membership programme (45%), receiving a one-time discount or promotion (42%), and obtaining an easier shopping experience (37%). Respondents could select more than one reason, which is why the three figures exceed 100% when combined with the remainder of the list.

The uninstall side of the ledger is more instructive, because it separates cost from indifference. According to Adobe, the reasons customers give for deleting retail apps are: no longer needed for the original purpose (64%), takes up too much storage (43%), lack of ongoing relevance or utility (43%), lack of incentives or deals (38%), and notification fatigue(30%).

Two of those five are functionally the same complaint expressed differently. "No longer needed" at 64% and "lack of ongoing relevance" at 43% both describe an app that stopped earning its place after the transaction closed. Storage, at 43%, is the only reason on the list that has nothing to do with marketing decisions.

Notification fatigue ranks last, at 30%. That ordering runs against a common assumption in lifecycle messaging, where over-sending is often treated as the primary churn driver. In this dataset, being irrelevant beats being noisy by a wide margin.

What buys a place on the home screen

Adobe asked separately about home screen placement, which functions as a proxy for perceived utility. Frequent use dominates at 61%, followed by ease of navigation at 24% and exclusive offers or early access to products at 23%, according to the research.

The wording drifts slightly between Adobe's blog and the summary the company distributed to press. The blog describes the second factor as "ease of navigation" in one passage and "ease of use" in another, while the media summary uses "user-friendliness." The underlying figure is 24% in all three renderings.

A related question asked what respondents value in their favourite retail app. Ease of navigation and use led at 27%, followed by personalised deals and rewards at 22%, a single place to track orders and purchases at 19%, and helpful tips or post-purchase support at 9%.

The gap between 61% for frequent use and 24% for ease of navigation is the more useful comparison. Habit, not interface quality, is what Adobe's respondents cite when explaining why an icon stays visible.

Order status outperforms promotional offers

Notification performance follows the same pattern. According to Adobe, the alerts most likely to drive a retail app open are order or delivery status updates (39%), personalised discounts or special offers (37%), price drops on saved or viewed items (33%), expiring rewards, points or credits (30%), and wishlist items back in stock (13%).

Transactional messaging leads promotional messaging, though by two percentage points, well inside the study's stated margin of error. The two categories are statistically indistinguishable in this sample. What separates them cleanly is the bottom of the list: restock alerts on wishlist items collapse to 13%, less than half the rate of expiring rewards.

Price drops on items a shopper has already saved or viewed sit at 33%, which places behaviourally triggered messaging above generic promotion but below simple delivery visibility.

The AI feature ranking is a logistics list

The section of the research that Adobe positions most prominently concerns artificial intelligence features. Respondents were asked which in-app AI capabilities would make them more likely to keep a retail app.

Order tracking and status updates led at 65%. Loyalty points and rewards tracking followed at 57%. Instant returns processing reached 42%, tailored product comparisons 31%, personalised restock and sale alerts 28%, and automated customer support or troubleshooting 23%.

The ordering is worth reading carefully. The top three items on a list of AI features are order tracking, loyalty balance tracking and returns. None of those is a generative capability in any strict sense. Each describes retrieving a status from a back-end system and presenting it clearly. The features that involve model reasoning, namely product comparisons and automated troubleshooting, sit at the bottom at 31% and 23%.

Adobe also reports that 41% of respondents said built-in AI-powered post-purchase support would make them more likely to keep a retail app on their home screen, while 21% said such features would make them less likely to delete it. The company presents both numbers without reconciling them, and they measure closely related dispositions at roughly a two-to-one difference.

A separate finding covers input methods: one in three users, or 33%, said the ability to interact through voice or image search would make them more likely to keep a brand or retail app installed.

Category and generational splits

Favourite retail app categories break down as grocery and food delivery (39%), apparel and accessories (25%), electronics (11%), beauty and personal care (7%), and home goods and furniture (5%), according to Adobe.

The generational breakdown is presented in the same percentage units, which creates ambiguity. Adobe lists Gen Z at electronics (14%) and beauty or personal care (8%), Millennials at apparel and accessories (27%), Gen X at grocery and food delivery (39%), and Baby Boomers at home goods and furniture (6%).

Gen X's grocery figure of 39% is identical to the all-respondent grocery figure, and the Baby Boomer home goods figure of 6% differs from the overall 5% by a single point, well within the margin of error. The generational cut is framed as showing which cohort is "more likely" to name a category, but the numbers as published do not always demonstrate a difference large enough to survive the study's own error band. Subgroup sample sizes are not disclosed, and a 1,000-person national sample divided across four generations yields cells where a three-point margin at the total level becomes considerably wider.

Where Adobe's products enter the argument

The research is not published in isolation. Two commercial products appear throughout the document.

Adobe Brand Concierge is positioned against the discovery findings. Adobe describes conversational commerce as the ability for customers to ask questions, discover products or services and receive relevant suggestions from real-time interactions through natural conversations with an AI assistant or chat experience. The company defines an AI shopping assistant as a customer-facing AI layer that powers conversational product discovery, recommendations and guided buying experiences.

Product Support Agent, described as part of Adobe CX Enterprise, is positioned against the post-purchase findings covering order management, returns, troubleshooting and support. Product Support Agent was among the six agents Adobe made generally available on September 10, 2025, when the company launched AI agents built on Experience Platform Agent Orchestrator. At that launch it was described as a tool for resolving issues for Adobe's own enterprise customers, including case creation and tracking inside user workflows. The retail app study repositions it as a consumer-facing post-purchase layer.

There is a deployment question the research does not address. Adobe's published product description for Brand Concierge, effective 11 November 2025, states that the product may be deployed on customer sites excluding mobile applications, alongside limits of 25,000 ingested URLs and 10,000 catalogue products. Adobe's implementation documentation, by contrast, describes Brand Concierge as embeddable across websites, mobile apps and integrated SDKs for custom deployments. A study whose entire subject is retail mobile app retention is therefore paired with a product whose licensing terms and technical documentation disagree on whether mobile applications are in scope.

Two dates on one study

The source material carries two publication dates that do not align. The Adobe for Business article is bylined to the Adobe for Business Team and carries the date stamp 08-12-2026. The media distribution, sent on August 21, 2026, describes the study as having launched that day.

Under United States date convention, 08-12-2026 reads as August 12, 2026, nine days before the media push. The discrepancy is small but relevant to anyone dating the finding in a competitive analysis or a citation.

Adobe's own commerce numbers sit alongside the study

The page hosting the research carries Adobe's Prime Day 2026 measurement in its recommended reading module. According to Adobe, United States shoppers spent a record 26.4 billion dollars during the 2026 Prime Day event, up 9.3% year over year, with mobile and AI driving the growth, and AI-referred shoppers converting 40% better.

That figure describes total United States online spend across retailers during the event window. It reads differently from platform-level data covering the same days. CommerceIQ's first-look report found United States ordered revenue 1.7% below Prime Day 2025 with product page traffic down 10.3% and brand ad spend down 8.8%, even as unit conversion climbed 17.1%. The two datasets measure different populations, one the whole United States online retail market and the other brand performance on Amazon, and the divergence is a reminder that event-level growth claims depend heavily on denominator choice.

Why this matters for the marketing community

App install campaigns are budgeted as acquisition. This research prices them as rental.

If 72% of consumers have at least once installed an app for a discount and then removed it, and if half of an average consumer's ten retail apps go unopened in any month, then the cost per install figure that closes a media plan describes an event with an unmeasured and possibly short half-life. The metric that matters sits downstream, and Adobe's data does not supply it: the study reports stated intent, not retained sessions.

The finding also intersects with a body of consumer research covered over the past year. Adobe's June 2026 study of 1,003 United States consumers found 86% making at least one unplanned online purchase per month, a pattern that sits awkwardly beside an app population where most icons never get tapped. Its March 2026 research on journey friction reported that 94% of Millennials would switch brands over disconnected shopping experiences, with 69% abandoning a cart after being asked to re-enter details. Owned-channel friction, in Adobe's own framing across three studies, is the recurring failure point.

The competitive context for owned apps has also shifted. DHL's 2026 E-Commerce Trends Report, drawn from 29,000 shoppers across 29 countries, documented a 34-point gap between the share of sellers offering an app and the share of shoppers using one. Optimove's holiday survey of 648 United States consumers found 53% intending to buy only from retailers they used the previous year, with 72% consulting AI tools for shopping ideas. RTB House research published on 10 August 2026 found 42% of United States shoppers saying AI tools lengthen their final purchase decision, even as those tools out-scored social platforms on shopping trust.

The retention argument also runs into a distribution question. Conversational commerce inside a brand's own app competes for the same query that increasingly lands in a general-purpose assistant. At the IAB Australia summit, Amazon said its conversational chat agent now exceeds search bar usage in the United States, while Walmart's Sparky assistant was used by 81% of surveyed customers to check product availability and specifications. Where those queries resolve determines whether a brand-owned conversational layer is a retention asset or a duplicate.

For lifecycle and retail media teams, the notification ranking is the most immediately usable output. Order status at 39% and price drops on saved items at 33% are both triggered by first-party events already flowing through customer engagement platforms. Wishlist restock alerts at 13% consume the same permission and produce a third of the response.

For measurement teams, the ranking of AI features carries a different implication. The three capabilities consumers rank highest, at 65%, 57% and 42%, are order lookup, loyalty balance retrieval and returns initiation. Each is an integration problem before it is a model problem. Whether a conversational layer improves retention depends on whether the order management system, the loyalty ledger and the returns workflow are addressable at all.

Timeline

Summary

Who: Adobe for Business, the enterprise division of Adobe Inc., conducted and published the research. The findings concern retail and brand marketers, lifecycle and CRM teams, mobile acquisition buyers, and ecommerce operators. No named Adobe spokesperson is attached to the study; it is bylined to the Adobe for Business Team.

What: A proprietary survey of 1,000 United States consumers on retail app ownership, download triggers, uninstall reasons, notification response and preferred AI features. Headline findings include 72% having deleted a retail app after a one-time discount or purchase, an average of ten retail apps per device with five unopened in the past month and three never opened, order tracking leading the desired AI feature list at 65%, and order status updates leading notification response at 39%.

When: The Adobe for Business article carries the date stamp 08-12-2026. The research was distributed to trade press on August 21, 2026 and described in that distribution as launching that day.

Where: The survey covered consumers in the United States. The research was published on the Adobe for Business blog at business.adobe.com.

Why: Adobe positions the findings as support for two commercial products, Adobe Brand Concierge for conversational discovery and Product Support Agent for post-purchase service, both tied to Adobe CX Enterprise. For the wider marketing community, the data quantifies the gap between app installs bought as acquisition and app sessions retained as value, and ranks the post-purchase capabilities consumers say would close it, ahead of a holiday season in which install campaigns compete for space on devices already holding ten retail apps.