If you create short-form video series, retention rate is the single most important metric you can track. Views tell you how many people found your content. Retention tells you how many stayed. For series specifically, retention has two dimensions: how long viewers watch each individual episode (in-video retention) and whether they come back for the next episode (episode-to-episode retention). Both matter, but episode-to-episode retention is what separates a hit series from a collection of standalone videos.
The first question every creator asks is: what is a good retention rate? The answer depends on your platform, genre, series length, and audience. This guide provides the benchmarks you need for 2026, along with the context to interpret them and the strategies to improve them.
Two Types of Retention: In-Video vs. Episode-to-Episode
Before looking at benchmarks, it is critical to distinguish between the two types of retention that matter for series creators. In-video retention measures how much of a single episode viewers watch. If your 60-second episode has an average watch time of 45 seconds, your in-video retention is 75%. This metric reflects the quality and pacing of individual episodes. Episode-to-episode retention measures what percentage of viewers who watched one episode went on to watch the next. If 100,000 people watched Episode 3 and 65,000 watched Episode 4, your Episode 3-to-4 retention is 65%. This metric reflects the strength of your narrative hooks, cliffhangers, and overall series appeal.
Both types of retention interact. Poor in-video retention on Episode 3 (viewers swiping away before the end) usually leads to poor episode-to-episode retention from Episode 3 to Episode 4. Viewers who do not finish an episode are unlikely to seek out the next one. However, the reverse is not always true. You can have high in-video retention (viewers watch each episode fully) but low episode-to-episode retention if your cliffhangers are weak or your series does not create enough narrative urgency to bring viewers back.
2026 Retention Benchmarks by Platform
These benchmarks are based on data from thousands of short-form series across major platforms in early 2026. They represent the median performance for actively published series with at least 10 episodes.
TikTok Series Retention Benchmarks
| Metric | Below Average | Average | Good | Excellent |
|---|---|---|---|---|
| In-Video Retention | Below 55% | 55-65% | 66-80% | Above 80% |
| Ep1 to Ep2 Retention | Below 40% | 40-55% | 56-70% | Above 70% |
| Ep1 to Ep5 Retention | Below 15% | 15-25% | 26-40% | Above 40% |
| Ep1 to Ep10 Retention | Below 8% | 8-15% | 16-25% | Above 25% |
TikTok retention rates are generally lower than other platforms because the For You page algorithm exposes episodes to many casual viewers who are not intentionally following the series. This inflates view counts on early episodes while depressing retention ratios. A 55% Episode 1-to-2 retention on TikTok is actually quite healthy because a significant chunk of Episode 1 viewers were served the video by the algorithm and had no prior interest in a series.
YouTube Shorts Series Retention Benchmarks
| Metric | Below Average | Average | Good | Excellent |
|---|---|---|---|---|
| In-Video Retention | Below 50% | 50-62% | 63-78% | Above 78% |
| Ep1 to Ep2 Retention | Below 35% | 35-50% | 51-65% | Above 65% |
| Ep1 to Ep5 Retention | Below 12% | 12-22% | 23-35% | Above 35% |
| Ep1 to Ep10 Retention | Below 6% | 6-12% | 13-22% | Above 22% |
YouTube Shorts retention rates tend to be slightly lower than TikTok for series because YouTube's Shorts shelf mixes content more aggressively and series discovery is less intuitive. However, YouTube's playlist and subscription features mean that viewers who do engage with a series tend to be more intentional. If your YouTube numbers are within 5-10 points of your TikTok numbers, you are performing comparably well on both platforms.
ReelShort Series Retention Benchmarks
| Metric | Below Average | Average | Good | Excellent |
|---|---|---|---|---|
| In-Video Retention | Below 70% | 70-80% | 81-90% | Above 90% |
| Ep1 to Ep2 Retention | Below 60% | 60-72% | 73-85% | Above 85% |
| Ep1 to Ep5 Retention | Below 35% | 35-50% | 51-65% | Above 65% |
| Ep1 to Ep10 Retention | Below 20% | 20-35% | 36-50% | Above 50% |
ReelShort retention rates are significantly higher across the board because the audience is self-selected. People download ReelShort specifically to watch serialized content, so they arrive with higher intent. If your ReelShort retention numbers match the TikTok benchmarks, something is wrong. You should expect ReelShort retention to be 15 to 25 percentage points higher than the equivalent metric on general-purpose platforms.
These benchmarks represent medians, not targets. Your goal should be to improve your retention rate relative to your own historical performance, not to hit an arbitrary number. A creator who improves from 35% to 45% Episode 1-to-2 retention has made meaningful progress, even if 45% is only 'average' in the benchmarks.
Factors That Affect Retention Rate
Retention is not purely a measure of content quality. Several structural factors influence your numbers in ways you should account for when interpreting data.
Genre
Different genres have inherently different retention profiles. Thriller, mystery, and romance series tend to have the highest episode-to-episode retention because they create strong narrative urgency. Comedy series retain well per-episode (people watch the whole clip) but sometimes have lower episode-to-episode retention because each episode can feel self-contained. Educational or documentary-style series have the lowest average retention because viewers may consume individual episodes based on topic interest rather than sequential narrative drive.
Series Length
Longer series naturally have lower end-to-end retention. A 10-episode series retaining 30% of its audience to the finale is a different achievement than a 50-episode series retaining 30%. When comparing retention across series of different lengths, look at the retention curve's shape rather than the endpoint. A series that retains 60% through Episode 20 before dropping to 30% by Episode 50 has a different problem (late-series fatigue) than one that drops to 30% by Episode 5 and holds steady (weak early episodes, loyal core audience).
Publishing Cadence
How often you publish affects retention. Daily publishing generally produces higher retention because viewers stay in the habit of checking for new episodes. Weekly publishing creates longer gaps where viewers may forget about the series. Batch publishing (dropping all episodes at once) enables binge behavior, which typically shows high initial retention but can lead to faster audience exhaustion. Test different cadences and measure the retention impact directly.
Audience Source
Where your viewers come from dramatically affects retention. Organic viewers who discover your series through the algorithm tend to have lower retention than viewers who come from your existing audience (followers, subscribers). Viewers acquired through cross-promotion from another creator's series tend to have higher retention than algorithm-discovered viewers but lower than your existing audience. If you see a sudden retention drop, check if your traffic source mix changed, since a viral episode that brought in a large casual audience will temporarily depress your retention ratios.
How to Measure Retention Accurately
Measuring retention correctly is harder than it sounds. Here are the key principles.
- Use consistent time windows. Always compare Episode N views at the same point in its lifecycle to Episode N+1 at the same point. Comparing Episode 1's lifetime views to Episode 2's 7-day views will give you a misleading retention number.
- Account for late discovery. Some viewers will discover your series after it is complete and binge from Episode 1 to the end. These viewers will improve the retention numbers of early episodes over time. For real-time decision-making, use a fixed-window metric (like 7-day views), not lifetime views.
- Separate returning viewers from new discoverers. On platforms where this data is available, distinguish between viewers who came from a previous episode and viewers who discovered this episode independently. Your 'true' retention rate should ideally count only returning viewers, though this level of granularity requires tools beyond native platform analytics.
- Track both absolute and relative retention. Absolute retention is the percentage of Episode 1 viewers retained at each subsequent episode. Relative retention is the percentage of the immediately preceding episode's viewers. Both views tell you different things. Absolute shows the overall funnel. Relative shows where specific episodes cause problems.
Measure Retention the Right Way
Reelytics calculates episode-to-episode retention automatically across TikTok, YouTube Shorts, and ReelShort. See both absolute and relative retention curves, segmented by cohort and traffic source.
See Your Retention DataStrategies to Improve Retention
Now that you know what good looks like and how to measure it, here are proven strategies to improve your series retention.
Nail the First Three Episodes
The largest retention drop in any series happens between Episode 1 and Episode 3. This is where casual viewers decide whether your series is worth their time. Your first three episodes need to accomplish three things: establish a protagonist the audience cares about, introduce a central conflict or mystery that creates urgency, and demonstrate the quality level viewers can expect going forward. If you can get a viewer to Episode 4, the probability that they continue to Episode 10 increases dramatically.
End Every Episode on an Open Loop
The Zeigarnik effect tells us that people remember incomplete tasks better than completed ones. Apply this to your episodes by ending every one on an open loop: an unanswered question, an unresolved tension, a reveal that raises new questions. The cliffhanger does not need to be dramatic. Even a small moment of uncertainty ('She reached for her phone, and the name on the screen was...') is enough to pull viewers into the next episode. Audit your current episodes. If any episode ends with a sense of closure rather than anticipation, that is likely a drop-off point.
Optimize Your Hook Speed
In short-form video, you have less than two seconds to convince a viewer to stay. For series episodes, this is compounded: even returning viewers will swipe away if the first moments do not immediately re-engage them. Start each episode with a moment that has intrinsic visual or emotional interest. Do not open with a recap of the previous episode; instead, open with a compelling moment from the current episode and weave in any necessary context naturally. Your in-video retention curve will show you exactly where viewers drop off in the first few seconds. If you see a steep drop before the 3-second mark, your hook needs work.
Maintain Consistent Quality
Uneven quality is a silent series killer. If Episode 5 has noticeably worse audio, lighting, or acting than Episodes 1 through 4, viewers will leave even if the story is strong. Audiences build expectations based on your best episodes and judge subsequent episodes against that standard. This does not mean every episode needs to be your best work; it means no episode should feel like a step down. Consistent production quality builds trust, and trust is the foundation of retention.
Use Data to Identify and Fix Weak Points
This is where analytics create a direct feedback loop with your creative process. Identify your worst-performing episode-to-episode transition (the pair with the lowest retention). Watch the ending of the first episode and the beginning of the second episode critically. Ask: would I come back? What is the open loop? Is the hook engaging? Is there a quality dip? Then apply what you learn to future episodes. Creators who do this systematically improve their retention rates by 10 to 20 percentage points within two to three series.
I used to think retention was about having a great story. It is about having a great story AND understanding exactly where the audience experience breaks. Analytics showed me the breaks I could not see by watching my own content.
Using Reelytics to Track Retention Trends
Reelytics provides several features specifically designed for retention tracking and improvement. The Retention Curve view shows your absolute and relative retention for every series, letting you spot drop-off points at a glance. The Episode Comparison view lets you see how different episodes compare on in-video retention, so you can identify which hook and pacing styles work best. The Trend view shows how your retention metrics are changing over time across your last several series, so you can see whether your creative improvements are translating to measurable results.
Most importantly, Reelytics tracks retention across platforms. If you publish the same series on TikTok and ReelShort, you can see how each platform's audience retains differently. This helps you tailor your content strategy to each platform rather than assuming one-size-fits-all. Creators using Reelytics for cross-platform retention tracking often discover that specific episodes that underperform on one platform overperform on another, providing insights into each platform's audience preferences.
Know Your Retention Numbers
Stop guessing whether your retention is good enough. Reelytics gives you platform-specific benchmarks, episode-level retention curves, and trend tracking so you can measure, compare, and improve with confidence.
Track Your Retention FreeKey Takeaways
- There are two types of retention for series: in-video (how much of each episode viewers watch) and episode-to-episode (whether viewers return for the next episode). Track both.
- Benchmarks vary significantly by platform. TikTok retention rates are naturally lower than ReelShort due to algorithm-driven casual viewer exposure. Compare against the right platform benchmarks.
- Genre, series length, publishing cadence, and audience source all affect retention. Account for these factors when interpreting your data.
- Measure retention using consistent time windows and distinguish between returning viewers and new discoverers when possible.
- The highest-impact strategies for improving retention are nailing your first three episodes, ending every episode on an open loop, optimizing hook speed, and maintaining consistent production quality.
- Use analytics to create a feedback loop. Identify your weakest episode transitions, diagnose the cause, and apply the fix to future episodes. This process compounds over time.