Before You Clone a YouTube Channel, Check These 7 Signals

If you want to clone a YouTube channel, the first mistake is choosing the channel because it looks successful.

A channel can have:

• millions of subscribers
• one enormous viral video
• polished thumbnails
• expensive production
• a recognizable format

and still be a terrible blueprint for your own channel.

The better question is:

Is this channel's success repeatable, current, transferable, and realistic enough to reverse-engineer?

That is what matters before you clone anything.

And by "clone," we mean something specific:

reverse-engineer the public strategy, then build original videos from the underlying patterns.

Not copy the creator's:

• videos
• scripts
• titles
• thumbnails
• identity
• branding
• voice
• footage

OverseerOS research across multiple independent YouTube datasets reveals seven signals worth checking before you turn another creator into a channel blueprint.

The strongest channels to model are not necessarily the biggest.

They are the ones where you can separate:

repeatable strategy

from:

one-off success

The Direct Answer

Before cloning a YouTube channel's strategy, check these seven signals:

1. Does the channel produce repeated breakouts, not just one viral hit?
2. Is the strategy still working now?
3. Are recent videos strong relative to the channel's existing audience?
4. Does the underlying topic demand work on independent channels?
5. Does the opportunity transfer across different channel sizes?
6. Can you realistically reproduce the operating model?
7. Can the strategy survive after removing the creator's identity and proprietary advantages?

If several of those fail, you may be reverse-engineering an exception rather than a system.

Key Findings

This article synthesizes several independent OverseerOS research studies.

The datasets should not be added together and treated as one giant study. Each was designed to answer a different question.

The findings include:

• In a study of 3,625 mature long-form videos across 94 channels, 53 channels produced at least four 5x breakouts.
• Those repeatable-breakout channels had a median subscriber count of only 45,400, showing that repeatability was not limited to giant channels.
• In a separate longitudinal study of 4,820 videos across 241 channels, channels with 2+ earlier 3x breakouts produced another 3x breakout in the next 10 videos 77.1% of the time, compared with 50.0% among channels with no earlier 3x breakouts.
• Across 625 channels, the strongest observed long-form video was a median 37.6x larger than the channel's recent median.
• Only 13.9% of those channels had their strongest observed video among their recent 10 qualifying uploads.
• Across 9,944 videos from 152 active channels, 44.7% of channels had materially changed at least one major structural signal compared with data only 3 to 6 months older.
• That increased to 63.2% when current behavior was compared with 6 to 12 months earlier and 83.6% against 1 to 2-year-old behavior.
• In a repeated-observation study, recent views relative to subscriber count had a 0.599 Spearman correlation with observed short-term subscriber growth in the strict 10-video cohort.
• Across 3,937 million-view long-form videos from 884 channels and 42 niches, only 1.6% of first-time topic wins produced a second independent million-view winning channel within the following year.
• Once two independent channels had already won on the topic, 11.6% produced a third. After three independent winners, 27.9% produced a fourth.
• Across 227 recurring topic waves, 74.0% crossed at least two subscriber-size tiers.
• The median size difference between the largest and smallest winning channel within a recurring topic wave was 6.82x.
• Among 50 topic waves with at least three independent winning channels, 100% crossed multiple size tiers.

The combined lesson is simple:

Do not clone success. Clone evidence of repeatability.

What Does It Mean to Clone a YouTube Channel?

A useful definition is:

YouTube channel cloning is the process of reverse-engineering the public strategy behind a successful channel and adapting the transferable patterns into an original content system.

That can include studying:

• audience promise
• topic selection
• recurring formats
• title structures
• thumbnail mechanics
• hooks
• pacing
• video structure
• publishing cadence
• breakout patterns
• content gaps

What it should not mean is:

Make cheaper versions of somebody else's videos.

The strongest outcome of channel cloning is not similarity.

It is understanding.

You should finish the research knowing:

Why does this channel win, which parts appear repeatable, and how can I apply those principles without reproducing the creator?

That is what a real channel blueprint is for.

Signal 1: Does the Channel Produce Repeated Breakouts?

Start here.

One viral video proves:

one video worked.

It does not prove:

the channel has a repeatable system.

OverseerOS analyzed 3,625 mature long-form videos across 94 channels with relatively strong catalog coverage.

A strong breakout in that study meant a video reaching at least:

5x the median performance of the channel's other qualifying videos.

The channels separated sharply.

The median channel in the 4+ group had:

seven 5x breakouts.

And approximately:

17.5%

of its qualifying mature videos reached the 5x threshold.

That is radically different from finding one giant winner.

A channel with seven major outliers lets you ask:

• What topics repeat across the winners?
• What title promises repeat?
• What thumbnail mechanics recur?
• Does the same format keep working?
• Which audience tensions appear again and again?
• What separates the winners from the channel's ordinary videos?

Now you have a pattern to investigate.

Why the second breakout matters

Another OverseerOS study looked forward instead of simply counting historical winners.

We analyzed:

4,820 videos across 241 channels

and split each channel's scored history into:

• first 10 videos
• next 10 videos

Then we grouped channels by how many 3x breakouts appeared in their first 10.

The result:

When we raised the future threshold to 5x:

This does not mean earlier viral videos caused later viral videos.

It does suggest that:

repeated abnormal performance contains more useful strategic information than one abnormal result.

The cloning rule

Before cloning a channel, do not ask:

What is its biggest video?

Ask:

How many times has this channel proven it can outperform its own baseline?

That is a much stronger first filter.

Signal 2: Is the Strategy Still Working Now?

A channel can be historically brilliant and strategically stale.

This is one of the easiest mistakes to make when reverse-engineering YouTube channels.

You find a successful creator.

Their most viral videos are from:

• 2023
• 2024
• early 2025

You study those videos as if they describe the channel in 2026.

But channels change.

They change:

• formats
• upload schedules
• video length
• titles
• thumbnails
• niches
• production style
• audience focus

We measured how quickly that happens.

OverseerOS analyzed:

9,944 long-form videos across 152 active channels

Every channel had enough uploads to compare four time windows:

• latest 0 to 90 days
• 91 to 180 days
• 181 to 365 days
• 366 to 730 days

We tracked three public structural signals:

• median title length
• median video duration
• publishing cadence

Compared with the latest 90-day period:

3 to 6-month-old behavior

44.7% of channels

had materially changed at least one major structural signal.

6 to 12-month-old behavior

63.2%

had changed.

1 to 2-year-old behavior

83.6%

had changed.

That means competitor research has an expiration problem.

The correct way to use old winners

Old videos are still useful.

They can reveal:

• durable evergreen demand
• historical breakout formats
• long-term positioning
• the channel's development

But they should not automatically define:

what the channel is doing now.

A stronger framework is:

Before cloning a channel, always separate:

current system

from:

historical system

If you mix them together, you can end up cloning a strategy the original creator already abandoned.

Signal 3: Are Recent Videos Strong Relative to the Audience?

Subscriber count can make a competitor look stronger than it currently is.

A channel with:

2 million subscribers

may look like an obvious blueprint.

But if its recent videos average:

60,000 views

while a 150,000-subscriber competitor repeatedly reaches:

250,000 views

the smaller channel may contain more interesting current evidence.

This is why relative performance matters.

In an OverseerOS repeated-observation study, we connected changes in public channel statistics with recent long-form performance.

For the strict subset with:

10 mature recent long-form uploads

we calculated:

median recent views ÷ current subscribers

and compared it with observed short-term subscriber growth.

The Spearman rank correlation was:

0.599

We repeated the test using:

• latest 5 mature videos
• latest 8
• latest 10

The relationship stayed within:

0.591 to 0.614

That does not prove strong views-to-subscriber ratios cause subscriber growth.

But it tells you something important when choosing a channel to model:

A channel's current ability to reach viewers relative to the audience it has already accumulated is more informative than subscriber count alone.

Compare these channels

Channel A

Subscribers:

1,200,000

Recent median:

65,000

Recent views per subscriber:

approximately 5.4%

Channel B

Subscribers:

90,000

Recent median:

140,000

Recent views per subscriber:

approximately 156%

Channel A is bigger.

Channel B is producing much stronger current reach relative to its existing subscriber base.

If your goal is to find:

current audience momentum

Channel B deserves serious attention.

The cloning rule

Before cloning a successful channel, check:

• recent median views
• subscriber count
• recent peak views
• whether multiple recent uploads exceed the subscriber base
• whether recent performance is improving or deteriorating

The question is:

Is this audience still responding?

Not:

How many people subscribed over the channel's lifetime?

Signal 4: Is the Channel Built on One Giant Outlier?

This is the outlier trap.

OverseerOS analyzed a current cohort of:

625 channels

Each had at least:

10 mature recent long-form uploads.

We calculated the median views of the recent 10.

Then we compared that baseline with the strongest long-form video observed for the channel in our research corpus.

The median top-video ratio was:

37.6x

At the 75th percentile:

165.1x

At the 90th percentile:

713.7x

And:

• 92.0% had a top observed video at least 5x their recent median
• 77.6% had one at least 10x
• 59.5% had one at least 25x
• 32.2% had one at least 100x

That is why sorting a channel by "Popular" can be dangerous.

You are intentionally looking at:

the least representative result.

Only:

13.9%

of the 625 channels had their strongest observed video among their recent 10 qualifying uploads.

The median top observed video was approximately:

410 days old.

More than half were over one year old.

What to do instead

Use the channel's giant outlier as a research question.

Ask:

Why did this video escape the normal range?

Then compare it with:

• recent baseline
• other outliers
• similar videos that failed
• newer versions of the topic
• other channels covering the same demand

You can explore this problem deeper in The YouTube Outlier Trap.

The cloning rule

If the channel's entire attractiveness disappears when you remove one video:

do not treat the channel as a proven blueprint yet.

You may have found an extraordinary video.

That is not the same thing as finding an extraordinary content system.

Signal 5: Does the Topic Work on Independent Channels?

Suppose a competitor normally gets:

40,000 views

Then one video gets:

1.8 million.

That is exciting.

But what did it prove?

It proved:

that topic, on that channel, with that package, at that moment, worked.

It did not automatically prove:

the topic itself is broadly transferable.

To test that, OverseerOS analyzed:

3,937 million-view long-form videos across 884 channels and 42 niches.

We identified:

11,512 distinct niche-topic signals

and tracked whether the same topic later produced another million-view winner on an independent channel in the same niche.

Each channel could only confirm a topic once.

That prevents one creator making six videos about the same thing from being counted as six independent market confirmations.

Among:

9,749 topics

with a full year of observation after their first independent million-view win, only:

1.6%

produced a second independent million-view winner within the following 365 days.

That is the part creators should remember.

One winner was usually:

one winner.

But once the topic had two independent winning channels, the signal changed.

After two independent winners

11.6%

produced a third within one year.

After three independent winners

27.9%

produced a fourth.

The progression was:

1.6% → 11.6% → 27.9%

That does not mean a three-channel topic gives your next video a 27.9% chance of going viral.

It means repeated independent success was associated with much stronger evidence that the subject could produce another major winner elsewhere.

A useful validation ladder

This should not become a rigid law.

Emerging trends can be valuable precisely because few creators have found them yet.

But if your entire reason for cloning a channel is:

One of their videos went viral on this topic.

you do not yet have much evidence that the topic travels.

Signal 6: Does the Opportunity Transfer Across Channel Sizes?

A common objection is:

Sure, the topic works, but only because the creator is huge.

Sometimes that is true.

Which is why cross-size evidence matters.

OverseerOS analyzed:

227 recurring YouTube topic waves

across:

213 channels and 26 niches.

Every topic had produced a million-view long-form video on at least two independent channels.

Then we compared the current subscriber sizes of the winning channels.

The result:

74.0%

of recurring topic waves crossed at least two subscriber-size tiers.

The median largest-to-smallest channel-size difference was:

6.82x.

And:

• 64.8% spanned at least a 3x size difference
• 53.7% spanned at least 5x
• 41.0% spanned at least 10x
• 27.8% spanned at least 25x
• 8.8% spanned at least 100x

The strongest recurring topics were even more interesting.

Among:

50 topic waves with at least three independent winning channels

every single wave crossed multiple subscriber tiers.

And:

80.0%

included winning channels at least 10x apart in size.

The median size spread was:

35.9x.

That tells us something extremely useful for channel cloning.

A topic or format becomes more interesting when it does not depend on one very specific channel scale.

Similar-sized competitors and different-sized competitors have different jobs

Use channels around your size for:

• realistic baselines
• expected views
• operational comparison
• production benchmarking

Use channels of different sizes for:

• idea discovery
• market validation
• format transferability
• demand research

Do not ignore giant channels.

Just do not use their raw view counts as your expected outcome.

Signal 7: Can You Actually Reproduce the Operating Model?

This is the signal creators skip most often.

They find a channel they love.

Then they clone:

• topic strategy
• thumbnails
• title style
• video format

But they ignore the machine required to produce it.

Suppose the competitor publishes:

every seven days

and every upload requires:

• 30 hours of research
• custom animation
• original interviews
• expensive footage
• expert writers
• professional narration
• a team of editors

Your one-person channel cannot simply adopt:

weekly cinematic documentaries

because the strategy looks successful.

The production system is part of the strategy.

In the 94-channel repeatability study, the channels with four or more 5x breakouts had a median recent long-form upload gap of:

7 days

The one-breakout group:

16 days

The zero-breakout group:

16.5 days

This does not prove faster publishing caused more breakouts.

The repeatable channels may simply have:

• larger teams
• easier formats
• better workflows
• stronger momentum
• more production capacity

But that is exactly why operational fit matters.

Check these before cloning the format

Ask:

• How often do they publish?
• How long are the videos?
• How much research is required?
• Is footage difficult to obtain?
• Does the format rely on travel?
• Does it require a recognizable host?
• Does it require expertise you do not have?
• Is the editing unusually complex?
• Can AI legitimately reduce the production burden without damaging quality?
• Can you sustain the format for 20 videos, not just two?

The wrong question is:

Can I make one version of this?

The right question is:

Can I operate this content system long enough to learn whether it works for me?

The Hidden Eighth Question: Does the Strategy Survive Without the Creator?

This is technically part of portability, but it deserves its own test.

Some channels work because of:

the system

Others work because of:

the person.

Those are very different cloning targets.

Imagine a channel built around:

• celebrity access
• rare professional credentials
• personal transformation
• founder reputation
• unique humor
• extreme athletic ability
• famous guests
• proprietary data
• unusual access to locations
• years of public trust

You can reverse-engineer the format.

You cannot automatically transfer the underlying advantage.

Creator-dependent strategy

Example:

I Asked 50 Billionaires How They Invest

If the creator can actually call 50 billionaires, the access is part of the product.

You cannot clone that by changing the title to:

I Asked 50 Millionaires How They Invest

if you have access to nobody.

System-dependent strategy

Example:

We Compared the Cheapest and Most Expensive Productivity Apps

The value may depend much more on:

• research
• testing
• comparison
• storytelling
• packaging

Those are more portable capabilities.

The portability test

Remove:

• creator name
• creator face
• subscriber count
• fame
• proprietary access
• unique personal history

Then ask:

Is there still a content system worth adapting?

If the answer is yes, you may have found something portable.

If the answer is no, you may be admiring the creator rather than the strategy.

The 7-Signal Channel Cloning Checklist

Before turning a competitor into your blueprint, use this checklist.

A channel does not need to be perfect on all seven.

But the more signals that disappear, the weaker the blueprint becomes.

A Bad Channel to Clone

Consider a hypothetical competitor:

• 2.5 million subscribers
• biggest video: 18 million views
• current median: 90,000
• biggest video published 3 years ago
• no recent breakout
• current upload cadence slowing
• success heavily tied to the creator's personality
• production requires expensive travel
• no independent channels are winning with the same recent topics

This channel may still be:

successful

But as a blueprint for a new faceless creator?

Weak evidence.

You may be looking at historical brand equity rather than a transferable system.

A Much Better Channel to Clone

Now consider:

• 75,000 subscribers
• recent median: 110,000 views
• five recent 3x+ outliers
• two recent 5x+ outliers
• publishing every 8 days
• recurring topic families
• similar topics breaking out on other channels
• the same format has worked at different channel sizes
• production can be executed by a small team
• success does not depend on a famous host

This channel may look smaller.

But it contains:

far more usable evidence.

That is the competitor most creators miss because they are distracted by subscriber count.

Big Channels Are Not Automatically Better Blueprints

This deserves emphasis.

In the 3,625-video repeatability study:

channels with four or more 5x breakouts had a median subscriber count of only:

45,400

Channels with exactly one breakout had a median:

270,000

Channels with no 5x breakout had a median:

890,000

Do not interpret that as:

Small channels are better.

That would be the wrong conclusion.

The cohort was selected and observational.

The lesson is:

Subscriber count did not identify the most repeatable breakout channels in this dataset.

A smaller channel can be a better research target if it repeatedly proves unusual performance.

That is exactly why Viral Channel Finder exists.

The interesting competitor may be the channel you have never heard of.

Before You Clone, Analyze the Channel in Layers

A proper channel blueprint should separate several layers.

Layer 1: Audience Promise

Complete this sentence:

People watch this channel because it consistently gives them...

Examples:

• frightening AI stories
• practical investing explanations
• historical mysteries
• high-stakes experiments
• simple business breakdowns
• relationship psychology

If you cannot identify the audience promise, you do not understand the channel yet.

Layer 2: Topic System

Identify:

• recurring subjects
• emerging subjects
• evergreen subjects
• failed topics
• breakout topics
• follow-up topics

Do not build the blueprint only from the winners.

Failure is part of the pattern.

Layer 3: Formats

Ask:

• Is it documentary?
• list?
• experiment?
• tutorial?
• breakdown?
• commentary?
• case study?
• challenge?
• investigation?

Then identify which formats repeatedly outperform.

Layer 4: Packaging

Study:

• title promise
• thumbnail question
• curiosity
• specificity
• visual tension
• information split between title and thumbnail

Avoid copying literal designs.

Model the communication logic.

Layer 5: Hooks and Structure

Ask:

• How quickly are stakes established?
• Does the opening reveal the result?
• Does it create an unanswered question?
• How does the script escalate?
• Where is evidence introduced?
• What keeps the viewer moving forward?

Layer 6: Operations

Map:

• cadence
• length
• research requirements
• editing complexity
• asset requirements
• voiceover
• team dependencies

Layer 7: Originality Boundary

Write down what you will not copy.

That includes:

• exact titles
• thumbnail layouts
• scripts
• visual assets
• branding
• voice
• creator stories

The final blueprint should describe:

principles

not:

duplicates

The Right Way to Use OverseerOS Channel Blueprint Cloner

The OverseerOS Channel Blueprint Cloner is designed around this distinction.

The useful workflow is:

1. Find candidate channels

Use existing competitors or discover emerging channels with Viral Channel Finder.

2. Validate the candidate

Run the channel through the free YouTube Channel Analyzer.

Check:

• recent videos
• public channel size
• publishing behavior
• top videos
• current relative performance

3. Look for repeatability

Do not clone because one video is enormous.

Look for multiple abnormal winners.

4. Build the blueprint

Extract:

• audience
• formats
• tone
• hooks
• topic system
• packaging patterns
• opportunities

5. Create original ideas

The output should move away from the source channel.

A useful blueprint lets you generate:

• new topics
• new angles
• new scripts
• new thumbnails
• new titles

while preserving only the strategic lessons.

That is why OverseerOS describes this as:

strategy cloning

not:

content cloning

The Difference Between Copying and Reverse-Engineering

If viewers can immediately point to the exact creator you copied, you probably stayed too close to the surface.

How We Built This Research Synthesis

This article combines findings from several independent OverseerOS studies.

They should not be interpreted as one unified sample.

Repeatable competitor study

3,625 mature long-form videos across 94 channels

Purpose:

identify channels repeatedly producing 5x channel-relative breakouts.

The strict cohort required:

• at least 20 mature long-form videos
• at least 80% captured catalog coverage
• videos at least 90 days old

Longitudinal repeatability study

4,820 videos across 241 channels

Purpose:

compare earlier breakout history with later breakout behavior.

Each channel contributed:

• first 10 scored videos
• next 10 scored videos

Competitor freshness study

9,944 videos across 152 active channels

Purpose:

measure how channel structure changes across:

• 0 to 90 days
• 91 to 180 days
• 181 to 365 days
• 366 to 730 days

Public momentum study

Repeated public observations were used to compare channel growth with recent video performance.

The strict recent-performance subset required mature recent long-form uploads and produced a Spearman relationship of approximately 0.599 between recent views relative to subscriber count and observed short-term subscriber growth.

Cross-channel topic-validation study

3,937 million-view videos across 884 channels and 42 niches

Purpose:

test how often one successful topic gained independent confirmation on additional channels.

Cross-size topic study

227 recurring topic waves across 213 channels and 26 niches

Purpose:

measure how often independently successful topics crossed channel-size tiers.

Each study answers a different question.

Together they create a more useful due-diligence framework than simply asking:

Is this competitor successful?

Limitations

These studies use public YouTube information observed by OverseerOS.

They are not randomized experiments.

The research corpora are not random samples of every YouTube channel.

Several analyses intentionally use selected cohorts with enough captured history to answer a specific question.

Public competitor data also cannot reveal:

• impressions
• private CTR
• audience retention
• watch time
• returning viewers
• traffic sources
• exact subscriber conversion
• revenue
• unpublished experiments

The topic-validation studies also focus on high-performing videos, including million-view cohorts, so their absolute percentages should not be generalized to every YouTube topic.

Current subscriber counts used in cross-size analysis do not reconstruct the exact subscriber counts the channels had when each historical video was published.

And none of the studies proves that:

• publishing faster causes breakouts
• certain channel sizes cause viral performance
• previous outliers cause future outliers
• repeating a topic causes views
• cloning a proven strategy guarantees success

The research helps answer:

Where is the evidence strongest?

It does not remove creative uncertainty.

What This Means for Creators

Before you clone a YouTube channel, stop asking:

Is this channel successful?

That question is too easy.

Ask:

Is the success repeatable?

Then:

Is it current?

Then:

Does it work beyond one giant outlier?

Then:

Does the demand appear on independent channels?

Then:

Can it transfer across different channel sizes?

Then:

Can I realistically produce it?

Finally:

Can I adapt the strategy while still making something recognizably mine?

If the answer survives all seven questions, you probably have something much more valuable than a viral competitor.

You have:

a blueprint candidate.

Final Verdict

The best YouTube channel to clone is not the biggest channel.

It is not automatically:

• the channel with the most subscribers
• the prettiest thumbnails
• the biggest viral video
• the highest production value

The better blueprint is the channel with the strongest evidence that its success comes from a system you can understand and adapt.

Look for:

repeated breakouts

current performance

audience momentum

cross-channel validation

cross-size transferability

operational fit

portable strategy

That is how you avoid copying somebody else's exception.

And start building your own repeatable channel.

FAQ

What should I check before cloning a YouTube channel?

Check whether the channel has repeated breakouts, current momentum, strong recent performance, independent topic validation, cross-size transferability, a realistic production model, and a strategy that can be adapted without copying the creator's identity or content.

Is it okay to clone a YouTube channel?

Reverse-engineering public strategy can be a useful research method. Copying another creator's videos, scripts, thumbnails, branding, or identity is different. The goal should be to extract patterns and create original content.

What is the best YouTube channel to clone?

The best research target is a relevant channel with repeatable, recent evidence rather than simply the biggest subscriber count. Multiple channel-relative outliers are generally more informative than one giant viral video.

How many viral videos should a channel have before I study it?

There is no magic minimum. One breakout is enough to investigate. Multiple independent breakouts give you much stronger evidence that there may be a repeatable strategy underneath the wins.

Should I clone a large YouTube channel or a small one?

Use similar-sized channels for realistic performance benchmarks, but study relevant channels of different sizes for topics, formats, and demand. OverseerOS research found many recurring million-view topics succeeded across channels with very different subscriber counts.

How recent should competitor research be?

For active channels, the latest 90 days is a useful primary operating window. In OverseerOS research, 44.7% of channels had already materially changed at least one major structural signal compared with data only 3 to 6 months older.

Is one viral competitor enough to validate a YouTube topic?

It is enough to create a hypothesis, but weak evidence of market-wide repeatability. In an OverseerOS million-view topic study, independent confirmation became much stronger after multiple different channels had already succeeded on the same subject.

Why should I compare views with subscriber count?

Subscriber count reflects accumulated audience size, not necessarily current reach. Comparing recent views with subscriber count helps reveal whether current uploads are still reaching strongly relative to the audience the channel has built.

What is a channel blueprint?

A channel blueprint is a structured model of the strategic patterns behind a channel, including audience promise, topic system, formats, titles, thumbnails, hooks, pacing, tone, publishing behavior, and repeatable opportunities.

How do I clone a YouTube channel without copying it?

Study the public strategy, identify repeatable patterns, extract the underlying audience and packaging mechanics, then rebuild those principles around original topics, titles, thumbnails, scripts, examples, and positioning.