---
title: "State of holidays for subscription apps 2026 report"
description: "Discounts didn't decide the holiday season for subscription apps. Timing did. Here's what 4.7M first payments show about the January peak."
url: "https://adapty.io/blog/state-of-holidays-for-subscription-apps/"
language: "en"
slug: "state-of-holidays-for-subscription-apps"
category: "industry-insights"
date: "2026-09-23T12:50:57.388Z"
date_modified: "2026-10-08T09:03:31.588Z"
author: "Dalibor Vasic"
---

# State of holidays for subscription apps 2026 report

## TL;DR

- The market gained 26% over the holidays. The median app gained 5.8%.
- January is when the season happens. Trials surge on New Year's Day, with first payments nine days later on January 10th. Install-to-paid runs 39.4% in mid-January against 30.5% in October, and refunds fall.
- Your category picks your weeks. Business peaks on Black Friday and is 21% down by January. Games are 36% up at New Year. Health & Fitness bottoms out at Christmas, then takes off in early January.
- Buyers drifted to weekly all season, 64% to 71% of first payments, which pulled the average payment down 12% without anyone changing a price.

Every November, LinkedIn fills up with the same advice: discount hard, raise the budget for Black Friday week.

The advice is borrowed from e-commerce.

Black Friday sells discounted coats and TVs, and a meditation app has nothing to put in a cart.

Retail demand spikes that week, and we wanted to know whether subscription demand follows it.

**So we counted every US app on Adapty, week by week**, October 2025 through January 2026, and marked the **five moments the season is planned around:** Black Friday, Cyber Monday, Christmas, New Year, and the "New Year, New Me" stretch through mid-January.

Here’s what we found.

> **Note:** **How we counted:** Every US app on Adapty, week by week, October 2025 through January 2026. 4.7 million first payments, $74.4 million in revenue. Weeks are indexed against a baseline October week.

> **Tip:** **Watch the webinar**. We walked through this data live with Phil Carter, founder and CEO of Elemental Growth, and Maxim Borisik from Adapty. Phil works with 40+ subscription apps, and you'll find his comments next to the charts below. [Watch the recording →](https://luma.com/app-djbx)

## **The market peaked at +26%. The median app at +5.8%.**

Total revenue across all US apps peaked in the first week of January, 26% above a normal October week.

Read that number alone and the season looks like a win for everyone.

![US subscription app revenue peaked 26% above October in early January, while the median app gained 5.8%](https://adapty.io/uploads/01_revenue_fan_styled-1.png)
*Don’t count on the holiday to bump your sales. Instead, try to find your own week.*

**But if you look at one app at a time,** you’ll see that some apps spend November and December below their normal October revenue.

The spread starts widening in November.

By New Year, the top tenth of apps **sits 163% above** its October baseline, the bottom tenth **66% below**.

![By New Year, the top 10% of apps sat 163% above their October baseline and the bottom 10% sat 66% below](https://adapty.io/uploads/chart-black-friday-1.png)

Phil Carter traces most of that spread to category:

> If you broke it down by category, you'd start to see why the top apps grow so much more than the median app. Plenty of categories don't care much about Black Friday and Cyber Monday.

Use your own October as the baseline. The market number will flatter you.

## Business peaks on Black Friday. Fitness peaks in early January

*Business* apps peak in Black Friday week and go quiet by January.

*Games* peak at New Year, where 36% of Games apps hit their best week.

*Health & Fitness* and *Education* bottom out at Christmas, then take off in early January.

*Entertainment* holds up in every window.

![Business apps peak in Black Friday week, Games at New Year, and Health & Fitness and Education in early January](https://adapty.io/uploads/02_category_heatmap_styled.png)
*Numbers show that your category may pick your season.*

So a business app puts its weight on Black Friday. A fitness or productivity app works better during the "new year, new me" period.

Both land their biggest week on January 5-11. People make resolutions on New Year's Day and pay for them the week after.

Some categories peak outside this window altogether. Phil spent years in EdTech:

> In EdTech, Super Bowl season is August and September, when new students start the school year. Those two months can make or break the entire year for a business like Quizlet or Chegg.

Health & Fitness sits at the other end:

> A typical health and fitness app makes anywhere from 15% to 25% of its annual revenue in the month of January.

If your peak is back-to-school, plan the holidays as your second season.

## 57% of apps made less on Black Friday than in a normal October week

Plenty of apps treat Black Friday week as the main event. Yet, it's the week apps end up furthest apart.

![57% of subscription apps made less in Black Friday week than in a normal October week, and 43% made more](https://adapty.io/uploads/apps_made_less_vs_made_more.jpg)

- **57% of apps** made less that week than in a normal October week
- **43% made more**, and a third of those made at least 50% more
- Only 18% finished within 10% of a normal week

Add every app together, and the week moved revenue by 0.3%.

It isn't most apps' big week either. Black Friday was the best week of the season for 7% of them. New Year week was the best for 16%.

**Price cuts don’t explain the gap.** Of the apps that made more on Black Friday than in a normal October week, 10% actually lowered their subscription price.

The same was true for apps that made less: 10% cut their price.

**Actual price cuts were rare throughout the season.** In any given week, fewer than 4% of apps lowered their subscription price, and the cuts around Christmas were just as deep as those around Black Friday.

**Whatever separated the two groups, it wasn’t simply a lower price.**

Phil's explanation is targeting. Most apps run one sale for everyone, and that sale costs them twice:

> Too often a site-wide sale ends up being a blunt instrument when what you really need is a scalpel. You cannibalize subscribers who would have paid full price, and you pull forward demand from people who would have bought two or three weeks later anyway. Then you get a hangover: a week or two after Black Friday where nobody buys, because everyone with any interest already cashed in on the 50% discount.

AI apps carry a third risk. Every subscriber costs you inference, so a deep discount on a paid-acquisition user can land below break-even:

> Headspace and Calm could get away with 50% discounts because their marginal cost of serving a subscriber was close to zero. If you're an AI app, you have real costs to cover. Don't copy-paste the 50% everybody else is running.

### Give each segment its own discount

Phil's alternative to the blanket sale is what he calls strategic discounts: a different depth for each group of users, based on what that group will pay.

**Measure willingness to pay by segment.** His team runs pricing studies (Van Westendorp, Gabor-Granger, conjoint) to see how willingness to pay differs between younger and older users, or between students, teachers, and professionals.

**Read intent from behavior.** A daily active user who has completed your key actions gets a smaller discount. A user who hasn't gets a deeper one, as long as serving them stays cheap.

Keep it legal. Student, teacher, and military discounts are standard. Pricing that favors one group over another on a protected characteristic, such as race, is illegal.

> Discounting done well comes down to matching your price with the willingness to pay of each individual user.

On a larger team, this takes three owners. Marketing runs the ad and email calendar. Product makes sure every click lands on the right paywall with the right discount. A monetization lead decides which group gets 50%, 40%, or 30%, and documents why.

With Adapty [targeting](https://adapty.io/paywall-targeting/), each segment sees its own paywall based on country, ad source, or user attributes.

## Apps showed more paywalls to the same people and sold less

Across the whole market, **paywall views ran 29%** above the October average in Black Friday week.

![Paywall views rose 29% above October in Black Friday week, driven by repeat views from the same users](https://adapty.io/uploads/07_paywall_views_by_week_styled.png)

That number is the market total, and it hides two things.

1. It isn't new people. **Unique viewers rose about 6%**. The same users saw more paywalls.
2. It isn't most apps. **The median app's views ran 5%** below October's level. A minority of apps drove the entire increase.

And the extra views converted worse. **Conversion per viewer fell to 2.39%** the week before Black Friday, against 2.6% in October, and didn't recover until January, when it peaked at 3.34%.

## January buyers convert 29% better and refund less

The worry about holiday traffic is that it's cheap attention that churns out in February. The data says otherwise, on every measure we have.

- They convert better. **Install to paid was 30.5%** for October cohorts and **39.4%** for the week of January 12th.
- They refund less. 3.58% in October, 2.91% at Christmas, 3.16% in early January.
- They're worth the same a year later. New Year weekly subscribers are worth **$47.54** against October's **$48.13**, annuals $47.76 against $48.09.

![Install-to-paid conversion rose from 30.5% for October cohorts to 39.4% for the week of January 12th](https://adapty.io/uploads/08_conversion_by_install_week_styled.png)

Nothing about your paywall changes in January. The people in front of it are readier to buy, which makes it the traffic worth having your paywall ready for.

## New Year's revenue shows up on January 10th

New Year's Day is when people resolve to change something. Trials peak that day, **49% above a normal October day**, the busiest trial day of the season.

![Trials peaked on January 1st and first payments nine days later, on January 10th](https://adapty.io/uploads/10_nine-day_lag_daily_7-day_avg.png)

Nine days later, they pay for it. **First payments peak on January 10th**, 55% above normal, with **revenue at 38%**. The same peak shows up in the weekly view: January 12th to 18th was the busiest week of the season by transaction count, 42% above a normal October week.

Whatever is live on your paywall on January 1st is what that traffic converts against on the 10th.

Phil's advice is to start before the calendar tells you to:

> Don't wait until January 1st to start marketing. If the peak in trial starts happens in the first days of January, you should be priming the pump over December, so when people come out of the holidays with a New Year's resolution, you're right there.

Trial length sets how long the lag runs. Phil's defaults are 7 days for consumer apps, 14 to 30 for prosumer, and 3 for AI apps, where every trial day costs you inference. Match the length to how long a user needs to see your product's value.

## Weekly plans took share all season, and everything else followed

More buyers picked **weekly**. It went from 64% of first payments in late October to 71% by the week of January 12th, while **annual** fell from 21.6% to 18.1% and **monthly** from 13.2% to 9.3%.

![Weekly plans grew from 64% to 71% of first payments between late October and mid-January, as annual and monthly shrank](https://adapty.io/uploads/06_plan_mix_styled.png)

Two things followed from that, and neither was a decision anyone made.

The average payment dropped about 12%. Prices stayed the same, so the drop is the mix: more people buying the cheapest plan.

**Intro offers doubled in reach.** The cheaper first period covered 12% of purchases in October and almost 25% in January. Nobody switched on a new discount. More buyers just landed on the plans that already had one.

## The typical annual subscriber is worth three times the typical weekly one

Year-one revenue per subscriber, net of refunds:

- **Weekly:** $48.13 average, **$12.99** median
- **Annual:** $48.09 average, **$39.99** median

The averages match. The medians don't. Weekly's average is held up by a few subscribers who stay for months, while most pay twice and leave.

The money also arrives at different times. Annual collects 83% of its first-year value in the first 90 days. Weekly collects 60%, and every week in between is another chance to cancel.

Phil adds a cash-flow argument:

> Say your annual plan costs $100 and your weekly plan costs $5. Most weekly subscribers won't retain for 52 weeks. They churn in the first three or four. With the annual plan, you get the $100 up front, and if you grow through Meta, Google or TikTok, that's the money you reinvest to acquire your next subscriber.

## What actually moved growth over the holidays

Discounting didn't.

What did work comes in two groups: things you can't change, and one thing you can.

**Things that happen to you**

- **Your category picks your weeks.** Business peaks in Black Friday week and is 21% down by January. Games are 36% up at New Year. Health & Fitness is 30% down at Christmas and 13% up in early January.
- **Traffic concentrates in a few apps.** Paywall views rose 29% across the market and not at all for the median app.
- **January buyers are better buyers.** Install-to-paid went from 30.5% to 39.4%. Refunds fell from 3.58% to 2.91%.
- **The mix shifts to weekly.** Weekly went from 64% to 71% of first payments. Introductory pricing doubled, from 12% to 24.6%.
- **The money lands nine days after the trials.** Trials peak January 1, first payments January 10.

**The thing you decide:** What's on your paywall when they arrive.

And the eight weeks aren't one audience. Black Friday traffic converts worse, January traffic converts better, and the plan people pick changes between them.

## Five paywall tips for a successful holiday season

The percentage off is the largest element on most holiday paywalls. It's also the one variable with no signal in our numbers: 10% of apps that beat their October ran a store seasonal offer, and 10% of apps that didn't beat it ran one too.

Five things worth more than the number.

> **Tip:** **We saved 30 Black Friday campaigns to a Figma board**. Almost every one sent the same offer to everybody, including the two segments that can't redeem a new-subscriber discount. [Grab the board →](https://www.figma.com/design/7vcoOR3uOQhg6mdmXKFGRT/Black-Friday_Library?m=auto&t=hfKjkC1idGowzPM0-6)

### Ship more than one version across the eight weeks

November and January are not the same audience. Conversion per viewer bottoms out at 2.39% the week before Black Friday and peaks at 3.34% in January. Plan mix moves, too, weekly, from 64% to 71% of first payments. A paywall that runs unchanged from November 24th to January 18th was written for one of those audiences and guesses at the other.

![Holiday paywalls from apps that change offer and design between Black Friday and January](https://adapty.io/uploads/black-friday-holiday-paywall-examples.jpg)

### Sell the outcome, not the sale

Every holiday paywall shows a discount. In a week when every competitor's screen says 30% off, the number stops being a reason to pick you.

The screens that work put the outcome first. "Start learning Italian" above the discount. "Get the full Lensa experience for one year" instead of the percentage. A list of what's included, with the savings as a label on one row.

"50% OFF" in the top third of the screen leaves the argument to a caption.

![Holiday paywalls that lead with the outcome and keep the discount as a label](https://adapty.io/uploads/black_friday_examples_2.jpg)

Phil sees the same pattern with his clients:

> Simple paywalls that lead with an emotional appeal rather than a logical one tend to perform better, and that's particularly true during the holidays, because people make more impulsive purchase decisions, for themselves or as gifts.

### Show the trial timeline, especially in January

Trials peak January 1st; first payments peak January 10th. Those nine days are when people cancel.

A "Today / In 5 days / In 7 days" layout earns its space in January, when most of your revenue is sitting in trials that haven't converted yet.

![Trial timeline paywalls from apps showing what happens today, in 5 days and in 7 days](https://adapty.io/uploads/black-friday-holiday-paywall-examples-3.jpg)

### Put the weight on the plan you want sold

Weekly took share all season, 64% to 71% of first payments. Some of that is your layout: the plan in the biggest type is the plan people pick.

For most apps, the plan you want is annual. The typical annual subscriber is worth about three times the typical weekly one, and annual brings in 83% of its first-year money in the first 90 days. Weekly gets to 60% and takes all year.

![Holiday paywalls from apps that preselect and highlight the annual plan over weekly](https://adapty.io/uploads/black-friday-holiday-paywall-examples-4.jpg)

Phil's ways to steer buyers toward annual, from lightest to most aggressive:

- Select annual by default and label the savings ("Best deal", "Save 60%")
- Show annual's per-week price next to the weekly price
- Offer the free trial on annual only
- Show annual alone, with a "See all plans" link underneath

The last two will cost some conversion. Phil's case is that ARPPU, LTV, and cash flow make up for it. For Health & Fitness, he suggests testing an annual-only paywall in early January:

> A month later, people have lost all that momentum. Converting them into an annual plan in January is better for your business, and you could argue it's better for the customer because paying up front makes them commit to the habit.

### Match the placement to the week

Black Friday is a one-week moment with a real deadline, which is what full-screen and splash placements are for.

January is a seven-week drift where most of your revenue is sitting in trials that haven't converted.

A splash screen on January 3rd interrupts someone who already started a trial and is deciding whether to keep it. A banner doesn't.

![Full-screen Black Friday placements next to low-key January banners from apps](https://adapty.io/uploads/black-friday-holiday-paywall-examples-6.jpg)

**What to do:** Interrupt in Black Friday week, stay in the background through January, and put your effort into the trial reminder instead.

## Four screens in eight weeks

The season asks for more than one screen. An opener for late November, a gift-led screen for Christmas, a resolution screen for New Year's, and the trial reminder that carries you to January 10th.

Phil's advice is to lean into that, and personalize past the calendar too:

> People are in different headspaces across that period, so I wouldn't be shy about customizing your paywalls to fit the season. We've also seen a lot of lift from personalizing the value prop based on what the user told you in the onboarding quiz.

Four changes in eight weeks, on a calendar you don't control.

If your paywall ships inside the app binary, every one of those is a build, a review queue, and a staged rollout. Miss the window, and you've missed the week.

And the users who never update keep seeing your Christmas screen in February, converting badly, counted in your January numbers.

> This is the whole reason we built the [Flow & Paywall Builder.](https://adapty.io/flow-paywall-builder/) Design the screen, publish it the same day, schedule the swap for December 26th before you leave for the holidays, and roll it back the moment it underperforms. No build. No review. No release notes.

![Holiday paywalls generated from a text prompt in about five minutes with Adapty's agent skills](https://adapty.io/uploads/black-friday-builder-example.png)
*Flow & paywall builder lets you build screens with ease.*

Your competitors will ship one paywall this season. You can ship four.

## Can't design four screens? Prompt them.

Four screens in eight weeks is a design problem before it's a publishing one. Someone still has to draw them.

Or nobody does. Every screen below started as a sentence.

Adapty's skills plug into whichever coding agent you already use, read your live flow, and build a new one from a prompt:

![A holiday paywall built in Adapty's Flow & Paywall Builder and published without an app release](https://adapty.io/uploads/black-friday-holiday-paywall-examples-7.jpg)

It saves a draft for you to review. It won't publish on its own, and it won't invent a price or a review count.

These took about five minutes.[How it works →](https://adapty.io/blog/ai-coding-agent-paywalls/)

Your December is now an afternoon.

## Gifts, bells, paywalls

The season doesn't lift everyone.

**The market total rose, the median app didn't**, and at New Year the best tenth of apps sat 163% above their own October while the worst tenth sat 66% below. Revenue moved between apps.

So the market number can't tell you how your season went.

**Discounting didn't decide it.** Under 4% of apps ran a store seasonal offer, and the ones that beat their October ran them at the same rate as the ones that didn't.

**The week decided it.** Black Friday moved the market 0.3% and left 57% of apps below a normal October week.

**January is where the season happens:** trials peak on the 1st, payments on the 10th, and January buyers convert at 39.4% against October's 30.5%.

That's the best traffic you'll see all year, and it arrives while most teams have stopped looking. Whatever is live on your paywall on January 1st is what converts on the 10th. The coming months are when you have time to build it.

> **Note:** Unless you'd rather spend December on something else. [Book a demo](https://adapty.io/schedule-demo/), and we'll have your four screens ready before anyone on your team opens Figma.

## Methodology: how we measured the season

A big app's good week can hide a hundred small apps' bad ones, so every figure compares an app against itself rather than against the market.

**Each week is indexed to that app's own normal October week**: its October revenue divided by 31, multiplied by 7. A rise means the app beat its own ordinary week.

**We report two numbers throughout.** The market total adds every app's revenue together. The typical app is the median across apps. In this season, those two answers diverge in every cut we ran, which is most of what the report is about.

**Week-by-week and app-by-app figures run on a fixed cohort:** apps that reported at least 25 days in both October and January, above a minimum daily revenue floor in US October. Without that requirement, apps that left Adapty or had a tracking gap mid-season look like apps that had a bad holiday.

- Every US app on Adapty, October 2025 through January 2026
- 4.7 million first payments and $74.4 million in first-payment revenue
- Peak window means December 28th to January 11th
- A first payment is a subscription starting or a trial converting; revenue is gross, before store commission and tax

## FAQ

### Does Black Friday increase revenue for subscription apps?

For most apps, no. Across all US apps on Adapty, Black Friday week moved total revenue by 0.3%. 57% of apps made less that week than in a normal October week, and only 7% had their best week of the season then. Business apps are the exception: they peak in Black Friday week.

### When do subscription apps make the most money over the holidays?

In January. Trials peak on New Year's Day at 49% above a normal October day. First payments peak nine days later, on January 10th, at 55% above normal. January 12–18 was the busiest week of the season by transaction count.

### Do discounts help subscription apps during the holiday season?

Not in our data. Fewer than 4% of apps lowered their subscription price in any given week. Among apps that beat their October revenue, 10% ran a store seasonal offer. Among apps that didn't, it was also 10%. The discount didn't separate the apps that grew from the apps that didn't.

### Which app categories do best over the holidays?

It depends on the week. Business apps peak on Black Friday and are 21% down by January. Games are 36% up at New Year. Health & Fitness is 30% down at Christmas, then 13% up in early January. Entertainment holds up in every window.

### How many paywall changes should I plan for the holiday season?

About four in eight weeks: a late-November opener, a Christmas screen, a New Year resolution screen, and a trial reminder that runs until January 10th. Black Friday and January bring different audiences, so one paywall for the whole season will only fit one of them.

### Should subscription apps offer lifetime plans during the holidays?

Be careful with them. Lifetime plans attract your highest-intent users, who would likely pay for a subscription anyway. For AI apps, the risk grows: once someone buys lifetime, you owe them service for as long as you're in business, whatever their inference costs add up to.

### How long should a free trial be over the holidays?

Seven days for most consumer apps, 14 to 30 for prosumer apps, and 3 for AI apps, where inference makes long trials expensive. Set the length based on how long users need to see your product's value. Trials that start on New Year's Day convert around January 10th.

### Does a discounted first month work as a holiday offer?

It can bring people in, but expect more disputes and refund requests. Users understand free trials. A low first payment that jumps to full price reads closer to bait-and-switch.

### Do paid trials convert better than free ones?

Sometimes. A user who has paid something is more likely to stay. Phil Carter's view is that, for most apps, a paid trial overcomplicates the offer, and a plain free trial or no trial works better.

### Which holiday matters most for parenting and travel apps?

Phil Carter's instinct: parenting apps lean on Black Friday, Cyber Monday, and Christmas, since parents rarely make parenting resolutions. Travel and eSIM apps peak in January, when people plan spring and summer trips. Our data doesn't break these categories out, so check your own weeks.