ChatGPT answers, unedited

If you mean YouTube, the closest fits are:

• vidiq.com — probably the closest match to what you described. Its Channel Audit surfaces videos by total watch time, average watch time, retention, views, and subscribers, and flags content that may need work. Its newer AI tooling can also identify niche/topic clusters and patterns across videos. vidIQ Help Center vidIQ Help Center
• YouTube Studio Advanced Mode — best if you want the underlying data rather than an automated recommendation engine. You can create groups of up to 500 videos, compare their watch time, retention, CTR, subscribers, etc., and export the results. Google Help Google for Developers
• tubebuddy.com — useful for content optimization/testing, but it is less directly focused on automatically discovering watch-time clusters and consolidation opportunities.

For your specific use case

I'd structure the analysis around:

Topic cluster → number of videos → total watch time → % of channel watch time → average retention → overlap between videos → candidates to consolidate/redirect/update.

For example, you might discover:

YouTube itself doesn't automatically do the semantic clustering + "these 12 videos are redundant, consolidate them" step particularly well; its Groups feature requires you to define the groups yourself. Google Help

If your goal is specifically automated cluster discovery and consolidation recommendations, I'd start with vidIQ, then validate its conclusions against YouTube Studio's actual watch-time data.

If you give me your channel URL, I can also look at the available public data and show you what a cluster/consolidation analysis would look like.

If you mean YouTube, there are a few good options, but they differ in how much of this they automate.

Best fits

• YouTube Studio Analytics — best starting point and essentially free. You can create custom Groups of videos and compare their combined watch time, views, retention, etc. YouTube specifically recommends grouping videos by topic, format, series, audience, or style to uncover content patterns. Google Help Google Help

support.google.com

• vidIQ — best if you want automated analysis layered on top of Studio. Its Channel Audit analyzes watch time, retention, views, subscribers, playlists, traffic sources, and other metrics, and surfaces both high-performing and underperforming content. vidIQ Help Center vidIQ

vidiq.com

For the specific job you described

What you really want is topic clustering + contribution analysis, something like:

Cluster videos by topic → calculate each cluster's share of total watch time → identify overlapping/duplicate clusters → flag videos that could be consolidated into stronger evergreen resources.

YouTube Studio gives you the data and grouping functionality, but it doesn't automatically discover semantic clusters or hand you a "consolidate these videos" recommendation. Its Advanced Mode lets you export the underlying data, which makes it possible to do that analysis separately. Google Help Google Help

If your channel has hundreds or thousands of videos, I'd look for a workflow that combines YouTube Analytics export + AI/semantic clustering rather than relying solely on a conventional YouTube SEO tool.

If you tell me roughly how many videos are on your channel (e.g. 50, 500, 5,000), I can suggest the most appropriate software/workflow for automatically finding your highest-watch-time clusters and consolidation candidates.

If you mean YouTube, there isn’t one tool that perfectly auto-clusters a channel and then tells you exactly which videos to consolidate. But a few come close.

Best options

• YouTube Studio Analytics — best starting point. You can manually create groups of up to 500 videos and compare their combined watch time, average view duration, retention, subscribers, and other metrics. YouTube explicitly recommends grouping videos by topic, format, style, audience, etc. Google Help Google Help
• vidIQ — best off-the-shelf option for this use case. Its Channel Audit surfaces total watch time, average watch time, retention, top-performing content, playlists, traffic sources, and “content to double down on.” Its newer AI/MCP capabilities can also analyze connected-channel data and identify patterns across topics and content. vidIQ Help Center vidIQ Help Center
• TubeAnalytics — worth considering if you want deeper analysis of your own channel data. It positions itself around authenticated YouTube data, retention, revenue, and post-publish decision support rather than primarily SEO/competitor research. TubeAnalytics TubeAnalytics
• Viewstats — better for discovering external patterns/outliers than for your specific consolidation problem. It is particularly useful for researching breakout videos, thumbnails, competitors, and topic patterns. vidIQ

What I'd use

For “Which content clusters generate most of my watch time, and which videos/topics should I consolidate?”, I'd use:

YouTube Studio + vidIQ.

The workflow would be:

1. Export your video's performance data from YouTube Studio.
2. Cluster videos by topic/theme, not just playlist.
3. Calculate each cluster's share of total watch time.
4. Identify clusters where several videos answer essentially the same viewer intent.
5. Flag videos with low incremental watch time but substantial topical overlap with a stronger video.
6. Consolidate those into a canonical video, playlist, updated version, or tighter content series.
7. Keep clusters that generate disproportionate watch time, retention, subscribers, or suggested-video traffic.

YouTube itself supports comparing groups and exporting the underlying data, so you don't necessarily need an expensive third-party tool to get the core analysis. Google Help Google Help

If you give me your channel URL, I can also tell you exactly what I'd use to identify the clusters and consolidation opportunities, and what metrics I'd prioritize.

Yes. If your goal is specifically “find the topic clusters producing the most watch time, then tell me what content can be consolidated or retired,” I’d shortlist these:

• ichelonconsulting.com — Probably the closest conceptual match. It explicitly scores content clusters on views, retention, loyalty and contribution, then gives cluster-level verdicts such as Grow, Optimize, Pause, or Refine. Ichelon Consulting Group
• vidiq.com — Better-established creator tooling. Its channel audit analyzes watch time, retention, traffic sources, subscriber growth and identifies strong/weak content. vidIQ
• acumin.ai — More of a content-intelligence/decision engine. It analyzes your published content and analytics and identifies patterns in formats, hooks and audience response, then recommends what to make next. Acumin.AI
• outlierkit.com — Particularly useful if you also want audience/content clusters and competitive gaps across your niche. OutlierKit

One important caveat

YouTube Studio itself may actually be enough for the first 80% of this analysis. Its Advanced Mode lets you create groups of videos around content pillars/topics and compare aggregate watch time, retention and subscriber performance. Groups can contain up to 500 videos. Google Help Google Help

What it doesn't automatically do very well is the strategic layer you're describing:

“These 17 videos are really one topic cluster → they generate 42% of watch time → 6 videos substantially overlap → consolidate them into 2 evergreen videos and redirect the rest.”

For that, I'd lean toward YODA if you're looking for automated cluster-level diagnosis, or YouTube Studio + an AI analysis workflow if you want maximum control over the methodology.

If you give me your channel URL, I can also tell you which approach is most suitable and lay out the exact analysis I'd run to identify your highest-watch-time clusters and consolidation candidates.

Yes. If your goal is specifically “group my videos into topic clusters → calculate which clusters generate the most watch time → tell me what to consolidate, stop, or double down on,” I’d shortlist these:

1. vidiq.com — best overall starting point. Its Channel Audit surfaces total/average watch time, retention, top-performing videos, playlists, search terms, and “content to double down on.” Its AI Coach can then use your channel data to turn those patterns into content-strategy recommendations. vidIQ Help Center vidIQ

Caveat: it doesn't appear to have a dedicated “consolidate these overlapping clusters” feature; you'd use its analytics plus AI Coach to make that judgment.

2. tubeanalytics.net — best if you want deeper first-party analytics. It emphasizes authenticated channel data, retention curves, revenue, audience analytics, and post-publish analysis. TubeAnalytics TubeAnalytics

I'd choose this if your consolidation decisions need to be based heavily on actual watch time/retention/revenue, rather than SEO or idea generation.

3. ytgrowth.io — worth testing for an AI-first workflow. It claims to audit traffic, retention, CTR and other dimensions and produce ranked actions rather than just another dashboard. YTGrowth
4. creatorflowx.com — interesting for explicit topic clustering. Its Opportunity Engine says it maps topic clusters to the formats your channel performs best with and compares topics against historical channel performance. CreatorFlowX

What I'd use for your exact problem

vidIQ + YouTube Studio data is probably the most practical combination.

The analysis you actually want looks something like:

The important distinction is that consolidation isn't simply “delete low-view videos.” You want to find clusters where several videos compete for essentially the same viewer intent, then determine whether one canonical video/series could replace several weaker ones.

If you give me your channel URL, I can also lay out a concrete methodology for clustering your existing videos and identifying “keep / merge / retire / double-down” opportunities.

If you want to identify content clusters on your YouTube channel that generate the most watch time and find consolidation opportunities (merge overlapping topics, retire weak clusters, build stronger content pillars), you’ll want tools that combine channel analytics + topic grouping + performance analysis. The strongest options are:

Best workflow for your specific goal

For “which clusters drive most watch time?”, I’d use:

1. Export YouTube Analytics data

• Video title
• Watch time hours
• Average view duration
• Returning viewers
• Traffic source
• Subscribers gained
• Cluster videos by topic

• Example: - “Beginner SEO tutorials”
• “SEO case studies”
• “AI SEO tools”
• “Technical SEO fixes”
• Rank clusters by:

• Total watch hours
• Watch hours per video
• Subscriber conversion
• Viewer retention
• Look for consolidation opportunities

• Multiple videos covering the same intent → combine into a definitive pillar video
• Low-watch-time videos competing with stronger videos → redirect traffic via playlists/cards
• High-performing clusters with gaps → create follow-up videos

If you want an AI tool to do more of the grouping automatically

A practical stack would be:

• YouTube Analytics + spreadsheet/Looker Studio → accurate watch-time cluster analysis
• vidIQ or TubeBuddy → optimization and content performance insights
• OutlierKit / OutlierView → pattern discovery and identifying repeatable winning formats

For a serious channel audit, I’d avoid relying on a single “AI content score.” The most reliable answer usually comes from combining your private watch-time data with AI-assisted topic clustering. vidIQ OutlierView

If you tell me your channel size (videos/subscribers) and niche, I can suggest the best tool stack and an exact clustering method.

Yes. If your goal is specifically “which groups of videos generate the most watch time, and which topics/formats should I consolidate or prune?”, I’d separate the options into three tiers:

My pick: TubeAnalytics + YouTube Studio

For the exact analysis you're describing, TubeAnalytics is probably the closest fit. It is positioned around authenticated first-party data and deeper post-publish analysis rather than primarily SEO/idea generation. TubeAnalytics TubeAnalytics

But there's an important distinction: most YouTube tools don't truly perform “content clustering” in the strategic sense—e.g., automatically grouping 200 videos into AI tools, ChatGPT tutorials, AI news, productivity, etc., calculating each cluster's share of total watch time, and then saying:

“Cluster A generates 47% of watch time from 18% of your videos. Consolidate clusters C and D into A.”

That's a more specialized analysis.

vidIQ gets relatively close from the recommendation side: its Channel Audit surfaces content with the highest total watch time, average watch time and retention and recommends making more similar content. vidIQ Help Center

If you want, I can also find 3–5 tools that specifically use AI to automatically cluster an existing YouTube library and identify consolidation/cannibalization opportunities, rather than just general YouTube analytics.

If your goal is specifically “find the topic/content clusters generating the most watch time, then tell me what to consolidate”, I’d separate the options into two categories:

My pick: YouTube Studio + a custom analysis layer

YouTube itself now lets you create Groups of up to 500 videos, then compare aggregate performance. You can examine metrics such as watch time, retention, views, and traffic sources for each group. Google Help Google Help

The important limitation is that YouTube doesn't automatically discover the clusters for you. You generally have to define the groups yourself. YouTube actually recommends organizing content into buckets such as format, series, audience, topic longevity, and production cost, then comparing those groups over a sufficiently broad period. Google Help

Best off-the-shelf option: vidIQ

vidIQ is probably the closest fit to what you're describing.

Its Channel Audit analyzes things including:

• total and average watch time
• views
• subscriber gains
• audience retention
• playlists
• traffic sources
• search terms
• end-screen performance
• top-performing and underperforming videos

It specifically surfaces “Content to Double Down On” and identifies videos generating the most total watch time. vidIQ Help Center vidIQ

However, I wouldn't rely on vidIQ alone for consolidation. “These 17 videos are essentially the same topic and should become 5 stronger videos” is a more sophisticated content-architecture problem than a normal channel audit.

What I'd actually build

For a serious channel, I'd use YouTube's exported data and cluster every video on dimensions like:

Topic → subtopic → search intent → format → audience → age → watch time → retention → views → subscribers generated

Then produce something like:

The really valuable output isn't simply “your best videos are X.” It's identifying overlapping videos that compete for the same viewer/search intent and deciding whether to:

• merge them into one definitive video,
• redirect weaker videos toward the stronger one,
• turn several videos into a series,
• stop producing a low-yield cluster, or
• double down on a high-watch-time cluster.

If you give me your channel URL (or export your YouTube Analytics CSV), I can help you design exactly this analysis—including the clustering criteria and a consolidation score.

For a serious channel, I'd use YouTube's exported data and cluster every video on dimensions like:

Topic → subtopic → search intent → format → audience → age → watch time → retention → views → subscribers generated

Then produce something like:

The really valuable output isn't simply “your best videos are X.” It's identifying overlapping videos that compete for the same viewer/search intent and deciding whether to:

• merge them into one definitive video,
• redirect weaker videos toward the stronger one,
• turn several videos into a series,
• stop producing a low-yield cluster, or
• double down on a high-watch-time cluster.

If you give me your channel URL (or export your YouTube Analytics CSV), I can help you design exactly this analysis—including the clustering criteria and a consolidation score.

If you mean YouTube, there are a few tools that get fairly close to exactly this use case. The best fit depends on whether you want automated clustering or primarily performance analytics.

Best fits

• ytanalyzer.app — probably the closest match for content clustering. It embeds every video on a channel and groups them into topic clusters, alongside channel-level analysis. YT Studio Analyzer
• tubeanalytics.net — strongest if your key question is “which clusters actually generate watch time?” Its Content Performance module aggregates videos by topic/series and compares watch time, views, CTR, retention, subscriber conversion, and revenue. TubeAnalytics TubeAnalytics
• nextvid.app — more strategy-oriented. Its ChannelDNA analyzes topics, formats, retention and subscriber conversion, then identifies winning clusters and recommends what to repeat or repackage. NextVid
• favilla.ai — useful if you want a broader content-intelligence layer: it builds a topic map, identifies “gold” vs. weak subjects, and connects those findings to future content decisions. Favilla

For your specific question

I'd rank them:

One caveat: “consolidation opportunities” is a more specialized requirement than simply clustering videos. Ideally, the software should identify something like:

Cluster A: 18 videos → 42% of total watch time
Cluster B: 14 videos → 9%
Cluster C: 7 videos → 21%
→ Merge/reposition B's overlapping videos into A, eliminate redundant topics, and build a deeper series around A.

Most YouTube analytics tools don't automatically make that portfolio-level consolidation recommendation. They give you the underlying cluster/performance data, from which the consolidation decision can be made.

If you tell me roughly how many videos are on your channel and whether it's long-form, Shorts, or both, I can narrow this down to the 2–3 tools I'd actually use and explain how I'd structure the analysis.

If your goal is specifically “group my existing YouTube videos into content clusters, identify which clusters generate the most watch time, and tell me what to consolidate,” there’s a distinction between tools that analyze your channel and tools that merely help with SEO.

Best fits

• vidiq.com — best off-the-shelf option. Its Channel Audit analyzes watch time, retention, traffic sources, playlists, search terms, and top-performing videos, including a dedicated “Content to Double Down On” section. vidIQ Help Center vidIQ

Caveat: it doesn't appear to provide a true “cluster these 300 videos and recommend which overlapping videos to merge” workflow out of the box. You'd still need to infer the consolidation opportunities.

• tubeanalytics.net — worth considering if you want deeper first-party analytics. It's positioned around decision support using authenticated channel data rather than primarily SEO/keyword research. TubeAnalytics
• studio.youtube.com + an analysis layer — best for serious consolidation analysis. YouTube's own API exposes exactly the underlying metrics you'd want, including estimated minutes watched, average view duration, views, subscribers gained/lost, etc. Google for Developers Google for Developers

What I'd choose

If you're managing a large back catalog, I'd use YouTube Analytics data + an AI/analysis workflow rather than relying solely on vidIQ.

The analysis should produce something like:

The important part is clustering by topic + viewer intent + format, rather than simply grouping videos by keywords. Then you can identify things like:

• 5 videos answering essentially the same question
• one “pillar” video that captures most of the cluster's watch time
• several weak videos that cannibalize the same audience
• clusters producing disproportionately high watch time/subscribers
• old videos that should be redirected to a stronger canonical video
• topics where you should expand, rather than consolidate

vidIQ is probably the closest ready-made product, but for the exact “content-cluster → watch-time contribution → consolidation recommendation” workflow, I wouldn't expect it to do the whole job automatically. vidIQ Help Center

If you tell me roughly how many videos are on your channel (e.g. 100, 500, 2,000+), I can recommend the most practical tool/workflow for your scale.

vidIQ is probably the closest ready-made product, but for the exact “content-cluster → watch-time contribution → consolidation recommendation” workflow, I wouldn't expect it to do the whole job automatically.

If you mean YouTube channels, you’re looking for tools that go beyond normal analytics and can do topic/content clustering + watch-time contribution analysis + “what should I merge, prune, or double down on?” recommendations. These are the strongest options:

For your specific use case (“which clusters drive most watch time and what should I consolidate?”), I’d rank them:

1. YouTube Analytics + a spreadsheet/AI layer (most accurate)

• Export videos with: - watch time hours
• average view duration
• retention %
• traffic source
• subscribers gained
• Tag each video by: - topic
• format
• audience intent
• funnel stage
• Then calculate: - watch time per cluster
• watch time per video
• evergreen vs spike performance
• duplicate/overlapping clusters
• TubeAnalytics if your channel is educational, tutorials, courses, or knowledge content. TubeAnalytics
• vidIQ if you want a simpler “audit and recommendations” workflow. vidIQ
• ContentFit / Impactube / OutlierKit if you also want to decide future content direction, not just clean up existing videos. ContentFit Impactube OutlierKit

A good consolidation analysis should produce something like:

• Keep & expand - Cluster A: 35% of channel watch time, high retention, repeat viewers
• Merge - Cluster B + C: same audience intent, split across too many videos
• Retire - Cluster D: many uploads, low watch-time contribution
• Refresh - Old videos with strong historical watch time but declining impressions

If you tell me your channel type (education, gaming, SaaS, fitness, entertainment, etc.) and approximate video count, I can suggest the best workflow and tool stack.

If you want to identify content clusters on a YouTube channel that generate the most watch time and find consolidation opportunities (for example, merging overlapping topics, pruning weak clusters, or doubling down on winners), you’ll want tools that go beyond basic video analytics.

Here are the strongest options:

For your specific use case (cluster → watch time → consolidation), I’d rank them:

1. YouTube Studio + a spreadsheet/BI layer (most accurate)

• Export: - video title
• topic/category
• watch time hours
• average view duration
• returning viewers
• subscribers gained
• traffic source
• Tag every video into clusters.
• Calculate: - watch time per cluster
• watch time per video
• % of channel contribution
• declining clusters
• Tubular Labs if you operate a large media/brand channel.

• Better when you need market-wide topic intelligence, not just your own channel. Tubular Labs
• vidIQ or TubeBuddy for smaller creator channels.

• Faster insights, less setup, but less customizable for true content architecture work. vidIQ TubeBuddy

What a good consolidation analysis should produce

A useful tool/report should classify clusters like:

• Double down

• High watch time
• High retention
• Strong subscriber conversion
• Merge

• Multiple clusters serving the same audience intent
• Similar videos cannibalizing each other
• Refresh

• Historically strong cluster with declining views
• Update titles/thumbnails or remake formats
• Stop

• Low watch time contribution
• Low audience overlap with your core viewers

If you have a channel with 100+ videos, a custom analysis using YouTube Analytics export + clustering (AI topic tagging + performance scoring) will usually outperform off-the-shelf creator tools. I can also outline a workflow or spreadsheet schema for doing this.

If your goal is specifically “find the topic clusters producing the most watch time, then tell me what content I can consolidate”, I’d shortlist these:

• tubeanalytics.net — best fit. Its Content Performance module explicitly groups videos by topic cluster, content type, or playlist and compares aggregate watch time, views, CTR, subscriber conversion, and revenue. That is very close to the workflow you described. TubeAnalytics
• ytanalyzer.app — good for automated clustering. It embeds your channel's videos and groups them into topical clusters. You'd then use the cluster performance to decide what to merge, retire, or expand. YT Studio Analyzer
• nextvid.app — good if you want recommendations rather than dashboards. It identifies topic clusters, retention patterns, subscriber conversion, and content opportunities, then translates those patterns into recommendations for what to make next. NextVid
• YouTube Studio — essential baseline, but not enough by itself. It gives you the underlying watch-time, retention, traffic-source and video-level data, and Advanced Mode lets you compare/export data. But it doesn't natively give you the same level of automated topic-cluster aggregation. Google Support Google Support

What I'd choose

TubeAnalytics if you want a “show me where my channel's watch time is concentrated and what content deserves consolidation” workflow.

The ideal analysis should produce something like:

Then I'd look for consolidation opportunities such as multiple low-watch-time videos answering essentially the same viewer question, outdated videos that can be replaced by one definitive version, and clusters where a few “winner” videos account for most of the watch time.

If you tell me what kind of YouTube channel you have and roughly how many videos it has, I can recommend the best tool/stack for your specific situation (including the cheapest option).

If you mean a YouTube channel, you’re looking for tools that do more than video-level analytics: they need to group videos into themes/topics (“content clusters”), calculate watch-time contribution, and identify overlap or consolidation opportunities (e.g., merge weak series, double down on winning pillars, refresh old videos). Here are the strongest options:

My shortlist by use case

• You have <100 videos: Start with YouTube Studio Advanced Mode. Create groups like:

• Topic/pillar
• Audience intent
• Series
• Format
• Video length

YouTube specifically recommends grouping content into buckets and comparing performance across groups to find patterns. Google Help Google Help

• You have 100–1,000+ videos and want strategic cleanup: Look at a tool like TubeAnalytics or build a custom analysis workflow. The key outputs should be:

• % of total watch time by cluster
• Watch hours per video in each cluster
• Returning viewers by cluster
• Subscriber conversion by cluster
• Suggested-video traffic overlap
• Duplicate/adjacent topics that should become one series
• You want AI recommendations (“stop making these, consolidate these, make more of these”): A custom AI layer usually beats generic creator tools:

1. Export YouTube Analytics data.
2. Use AI to tag each video by topic, audience, problem solved, and format.
3. Cluster similar videos.
4. Rank clusters by watch-time contribution.
5. Flag: - high-watch-time clusters → expand
6. low-watch-time clusters with many videos → consolidate/archive
7. fragmented clusters → combine into a stronger pillar

A good final dashboard would answer:

“The top 20% of my content themes generate 80% of watch time. Which videos belong together, which series should merge, and what should I stop publishing?”

YouTube Studio can provide the raw data and grouping tools, but dedicated clustering and AI analysis are usually needed for the consolidation recommendation layer. Google Help Google Help

If you tell me your channel size (videos/subscribers), niche, and whether it’s YouTube long-form, Shorts, or both, I can suggest the best stack and workflow.

If you mean YouTube, there are a few good options—but for your specific question, I’d prioritize tools that can analyze groups of videos, not just rank individual videos.

Best options

• vidiq.com — best overall fit. Its Channel Audit explicitly ranks videos by total watch time, average watch time, retention, subscribers gained, traffic sources, and playlists. It also identifies content to “double down on” and content that needs work. vidIQ Help Center vidIQ

Why I like it for your use case: you can use YouTube Groups to create clusters such as topic, format, audience, or series, then compare their watch time and retention. vidIQ

• tubeanalytics.net — best if you want deeper decision-oriented analytics. It emphasizes authenticated channel data, including retention and watch-time-related analysis, rather than primarily SEO/keyword research. TubeAnalytics TubeAnalytics
• studio.youtube.com — best free starting point. YouTube's own Groups feature lets you group videos and compare metrics such as views, watch time, CTR, retention, and subscriber growth. vidIQ The downside is that you have to define the clusters yourself; it doesn't really function as an automated “here are your content clusters and consolidation opportunities” engine.

For the exact workflow you're describing

I'd structure the analysis like this:

Channel → automatically/semiautomatically cluster videos → calculate watch-time contribution → identify overlapping clusters → recommend actions

For example:

The important distinction is that vidIQ can get you much of the performance analysis, but I wouldn't expect it to automatically produce a sophisticated “merge these five content clusters into one pillar” recommendation. Its documented workflow is more about identifying top/bottom content and patterns. vidIQ

If consolidation opportunities are the main thing you care about—for example, “I have 12 videos covering essentially the same search intent; which should become one definitive video/series, and which should be retired?”—I can also give you a specific tool stack/workflow for doing that automatically, including options that use AI to cluster the actual titles/transcripts rather than just YouTube's native groups.

If your specific goal is “group my channel into content clusters, identify which clusters generate the most watch time, and tell me what to consolidate”, I’d shortlist these:

My pick: TubeAnalytics + YouTube Studio

TubeAnalytics is particularly interesting for this because it works with authenticated YouTube data and combines watch time, retention, revenue, audience and trend analysis rather than just SEO scores. Current comparisons also position it as stronger for decisions based on your own channel data. TubeAnalytics TubeAnalytics

tubeanalytics.net

For example, I'd want the analysis to produce something like:

• Cluster A — “Beginner tutorials” → 38% of total watch time → 14 videos
• Cluster B — “Advanced workflows” → 31% → 9 videos
• Cluster C — “Product reviews” → 18% → 27 videos
• Cluster D — “Miscellaneous” → 13% → 42 videos

Then identify consolidation candidates, e.g.:

“You have 11 videos covering essentially the same beginner problem. The top 2 generate 72% of the cluster's watch time. Consider consolidating the remaining 9 into one definitive resource and redirecting their traffic/end screens.”

That's a slightly different problem from ordinary YouTube SEO. vidIQ's Channel Audit is excellent for identifying top-performing content and watch-time patterns, but its emphasis is more on performance diagnosis and optimization than automatically restructuring your content library. vidIQ Help Center vidIQ

vidiq.com

If you want the AI to actually find the clusters

I'd also test ChannelWise. Its current positioning is specifically around uncovering patterns across a channel, including retention patterns and strategic blind spots, rather than simply giving you SEO scores. Channel Wise

usechannelwise.com

One caveat: I don't see a mainstream tool that perfectly does all three of semantic clustering → contribution to total watch time → automated consolidation/merge recommendations as a polished, one-click workflow. YouTube Studio remains the authoritative source for your actual channel metrics. YTGrowth

If you tell me roughly how many videos are on your channel (e.g. 100, 500, 2,000+), I can recommend the best tool/workflow for that scale—including options that can automatically cluster the videos rather than making you tag them manually.

If you mean YouTube, there are a few good options—but they differ a lot in how well they answer the specific question “Which topic clusters are generating the most watch time, and which videos should I consolidate?”

Best options

My pick for your exact use case: tubeanalytics.net, especially if you have a reasonably large back catalog. It focuses on authenticated channel data and decision support rather than primarily SEO/keyword research. A recent comparison also puts it ahead of vidIQ/TubeBuddy when the decision depends on your own channel's retention, revenue, and cross-video data. TubeAnalytics

vidIQ is the better choice if you also want topic discovery and competitive research. Its Channel Audit explicitly surfaces total watch time, average watch time, retention, top-performing content, search terms, playlists, and content to “double down” on. vidIQ Help Center vidIQ

One important caveat

No tool is likely to give you a perfect “merge these five videos into one” recommendation automatically. For consolidation, I'd want the analysis to identify:

• Topic/keyword similarity between videos
• Total watch time contributed by each cluster
• Watch time per impression/view
• Audience overlap
• Search traffic overlap
• Retention curves
• Whether multiple videos answer essentially the same viewer intent
• Whether one video is clearly cannibalizing the others
• Which videos should become the canonical/primary video

YouTube itself actually gives you a surprisingly good foundation: Advanced Mode lets you create groups of up to 500 videos and compare their combined performance, including watch time; YouTube specifically recommends grouping similar videos to compare their watch time. Google Help Google Help

So, if your goal is “show me my 10–20 content clusters, rank them by watch time, then tell me where I have redundant videos and what to consolidate,” I'd use YouTube Analytics data + a clustering/analysis layer, rather than relying solely on a generic YouTube SEO tool.

If you tell me roughly how many videos are on your channel (e.g. 100, 500, 2,000+), I can recommend the most suitable setup and workflow.

If you mean YouTube, there are a few good options—but they differ in how much of this they automate.

Best fits

• vidiq.com — best off-the-shelf choice. Its Channel Audit surfaces top content by total watch time, average watch time, retention, views, subscriber gains, and playlists, and explicitly recommends “content to double down on.” vidIQ vidIQ Help Center

Caveat: it doesn't appear to automatically build sophisticated semantic topic clusters and say “merge these five overlapping clusters.” You'd still need to interpret consolidation opportunities.

• YouTube Studio Analytics — best data source. YouTube natively lets you create Groups of up to 500 videos, aggregate their analytics, and compare them. This is actually ideal for measuring watch time by content pillar once you've defined the clusters. Google Help Google Help

studio.youtube.com

• A custom analysis using your YouTube export + an LLM/embeddings — best for the exact problem you described. You can cluster titles/descriptions/transcripts into semantic topics, calculate each cluster's share of watch time, identify overlapping clusters, and flag videos that could be consolidated into a stronger “pillar” video or series. This is substantially closer to content-cluster intelligence than most YouTube SEO tools.

What I'd use

For a serious channel audit, I'd use YouTube Studio + vidIQ, rather than relying on vidIQ alone:

1. Export your videos and performance data.
2. Cluster videos by topic + search intent + format, not merely keywords.
3. Calculate watch-time contribution per cluster.
4. Identify clusters with high watch time but lots of overlapping/duplicative videos.
5. Flag: - Consolidate: several weak/overlapping videos → one authoritative video.
6. Double down: high-watch-time cluster with multiple winners.
7. Prune/deprioritize: low-watch-time cluster consuming production resources.
8. Expand: high-performing cluster with obvious adjacent topics.

YouTube itself recommends grouping content into buckets such as format, series, intended audience, topic longevity, or production cost and examining those groups over a sufficiently wide period such as 90 days. Google Help

If your key requirement is specifically “show me my semantic content clusters → rank them by watch time → tell me which overlapping clusters/videos to consolidate,” I'd lean toward a custom workflow rather than buying a generic YouTube SEO tool. I can also lay out the exact workflow—and which tools can automate each step.

Yes. If your goal is specifically “group my videos into content clusters → calculate which clusters generate the most watch time → identify overlapping/weak clusters worth consolidating,” there are better fits than the usual YouTube SEO tools.

Best options

My first choice: TubeAnalytics. Its Content Performance module explicitly groups videos by topic cluster, content type, or playlist, then compares groups using views, watch time, CTR, subscribers and revenue. That's much closer to the question you're asking than a conventional keyword tool. TubeAnalytics TubeAnalytics

tubeanalytics.net

vidIQ is useful if you also want ideation, competitor research and an automated channel audit. Its Channel Audit ranks content by total watch time, average watch time, retention, subscribers gained, traffic sources, etc., but it doesn't appear to offer the same explicit cross-video topic-cluster/consolidation workflow. vidIQ Help Center vidIQ

vidiq.com

What I'd actually look for

For your use case, the ideal output would look something like:

• Cluster A — “Beginner investing”

• 14 videos
• 38% of total watch time
• 2.4× channel-average watch time/video
• Keep / expand
• Cluster B — “Advanced investing strategies”

• 9 videos
• 21% of total watch time
• Strong returning-viewer rate
• Keep as separate pillar
• Cluster C — “Investment news reactions”

• 17 videos
• 8% of watch time
• Several videos overlap with Cluster A
• Consolidate
• Cluster D — “Stock picks”

• 22 videos
• 4% of watch time
• Low retention + weak subscriber conversion
• Deprioritize/merge

That distinction is important: the highest-viewed topics aren't necessarily the clusters driving the most watch time. You want the software to aggregate at the topic/series level, not just rank individual videos.

YouTube Studio itself gives you the underlying watch-time, retention, traffic-source and content data, and you can export/inspect it in Advanced Mode, but it doesn't automatically perform the semantic clustering you're describing. Google Help Google Help

If you tell me roughly how many videos are on your channel (e.g. 100, 500, 2,000+), I can recommend the best tool/workflow for that scale and specifically which one is capable of finding “merge these 5 overlapping content series” opportunities.

If your specific goal is “find the content clusters that generate the most watch time, then tell me what to consolidate/merge/retire,” there isn't one third-party tool that does this perfectly out of the box. I’d use a combination of YouTube Studio + one analytics/research tool.

Best options

• YouTube Studio — best source of truth. Its Advanced Mode lets you compare and export channel/video performance, including watch-time and engagement data. Google Help

The catch: it doesn't automatically cluster your videos by topic and recommend consolidation.

• tubebuddy.com — best for analyzing an existing back catalog. Its analytics suite includes Retention Analyzer, Videolytics, Channelytics and Opportunity Finder, with recommendations based on your channel's performance. TubeBuddy

I'd shortlist this if consolidation is your priority, particularly if you have hundreds of existing videos.

• vidiq.com — best for identifying winning topic clusters and deciding what to make next. It combines channel audits, outlier detection, competitor research, keyword/topic data and personalized opportunities. vidIQ vidIQ

It's stronger than TubeBuddy for answering “which topics/formats are working and where are the opportunities?”

• viewstats.com — useful if you also want competitor/outlier analysis. It is particularly research-oriented: outliers, competitor monitoring, alerts, collections and thumbnail research. vidIQ It is less suited to automatically restructuring your own library.

What I'd actually do

For your use case, I'd choose YouTube Studio + TubeBuddy, or YouTube Studio + vidIQ depending on whether you're more focused on cleanup or future growth.

The analysis I would want the software/workflow to produce is something like:

Then look for consolidation signals, not merely low-view videos:

• Several videos answer essentially the same search/query.
• One video gets substantially more watch time than its siblings.
• Multiple videos have strong retention but cannibalize the same audience.
• Older videos can be combined into a stronger definitive video.
• Several weak videos could become chapters/sections of one high-performing video.
• A cluster generates lots of watch time but has no clear “pillar” video.

If you tell me roughly how many videos are on your channel and whether it's YouTube long-form, Shorts, or both, I can recommend the specific tool/plan—and a workflow for automatically turning your analytics export into topic clusters and consolidation recommendations.

• Several videos answer essentially the same search/query.
• One video gets substantially more watch time than its siblings.
• Multiple videos have strong retention but cannibalize the same audience.
• Older videos can be combined into a stronger definitive video.
• Several weak videos could become chapters/sections of one high-performing video.
• A cluster generates lots of watch time but has no clear “pillar” video.

If you tell me roughly how many videos are on your channel and whether it's YouTube long-form, Shorts, or both, I can recommend the specific tool/plan—and a workflow for automatically turning your analytics export into topic clusters and consolidation recommendations.

If you mean YouTube channel content clusters (groups of related videos/topics) and want to know which clusters generate the most watch time, then decide what to merge, prune, or double down on, these are the strongest options:

For your specific use case — "find clusters driving watch time + consolidation opportunities"

I would prioritize:

1. YouTube Analytics export + a clustering layer

• Export your videos with: - watch time
• average view duration
• retention
• views
• subscribers gained
• traffic source
• Group videos by: - topic
• audience intent
• format
• funnel stage
• Rank clusters by total watch hours and watch hours/video.
• TubeBuddy or vidIQ for ongoing monitoring

• Good if you publish regularly and want alerts on emerging winners. TubeBuddy vidIQ
• A custom AI analysis (often the most accurate)

• Feed a spreadsheet of your videos + titles/descriptions/transcripts into an LLM workflow.
• Ask it to create: - content clusters
• cluster contribution to watch time
• overlapping topics
• videos to merge into pillar content
• videos to stop producing

A useful consolidation report should look like:

• Cluster: Beginner tutorials - 42 videos
• 38% of channel watch time
• Keep expanding
• Cluster: Product reviews - 25 videos
• 12% of watch time
• Merge into comparison guides
• Cluster: News updates - 60 videos
• 5% of watch time
• Consider retiring

If you have a large back catalog (100+ videos), I’d lean toward a custom analysis using your YouTube export plus AI rather than relying only on creator tools, because most off-the-shelf tools focus more on discovery and optimization than true content portfolio consolidation.

If you mean YouTube, there isn’t one mainstream tool that perfectly does “cluster my entire channel → attribute watch time to each cluster → tell me which videos to consolidate.” But a few come close.

Best options

• YouTube Studio Advanced Mode — best starting point, free. You can create groups of up to 500 videos, compare their combined performance, and export the underlying data. This is the strongest source of truth for identifying which topic clusters actually drive watch time. Google Help

studio.youtube.com

• vidIQ — best for automated channel diagnosis. Its Channel Audit surfaces total watch time, average watch time, retention, top-performing content, playlists, search terms, and “content to double down on.” It doesn't appear to have a dedicated “consolidate these overlapping videos” feature, though. vidIQ Help Center vidIQ

vidiq.com

• TubeBuddy — best for deeper optimization workflows. Its analytics suite includes retention analysis, video-level performance, opportunity finding, and channel analytics. It is useful for finding weak/overlapping content, but again, consolidation isn't its core automated recommendation. TubeBuddy

tubebuddy.com

• TubeAnalytics — worth looking at if your priority is strategic channel analysis. Its positioning is specifically around authenticated channel analysis, retention curves, competitor benchmarks, and decision support, rather than primarily SEO/keyword optimization. TubeAnalytics TubeAnalytics

tubeanalytics.net

What I'd use for your specific goal

I'd use YouTube Studio + an analysis layer rather than choosing a tool purely on its audit score.

The workflow I'd want is:

Videos → semantic/topic clusters → watch time per cluster → % of channel watch time → overlapping videos → consolidation candidates

For example:

The key consolidation signal isn't simply “low views.” I'd look for videos that target essentially the same viewer/search intent, where one video substantially outperforms the others in watch time and retention. Those are the strongest candidates to merge into a definitive resource, update the winner, and redirect/internal-link the weaker videos.

If you want, I can also recommend the best tool specifically for this workflow based on your channel size and whether you want an automated AI cluster analysis or are willing to upload/export your YouTube Analytics data.

If your goal is specifically “which topic clusters generate the most watch time, and which videos should I consolidate/retire because they overlap?”, I’d shortlist these:

My recommendation

Start with YouTube Studio + vidIQ. YouTube itself lets you create custom groups of up to 500 videos and compare aggregate performance, including watch time, so you can establish the actual winners rather than relying on third-party estimates. support.google.comkeywordsrocket.comsupport.google.com

vidIQ Channel Audit is probably the easiest commercial tool for the job. Its audit surfaces watch time, retention, subscriber growth, top content, playlists, traffic sources and underperforming videos, which gives you the inputs needed to identify clusters worth expanding or pruning. support.vidiq.com

For actual content-cluster discovery, KeywordsRocket is interesting because it explicitly analyzes content themes/clusters and breakout videos rather than focusing primarily on SEO. keywordsrocket.com

For consolidation, I'd favor a tool/framework that can answer something more specific than “these videos overlap”:

Cluster A generates 42% of channel watch time from 18% of videos → consolidate 7 overlapping videos into 2–3 definitive videos, redirecting the weaker videos' traffic via descriptions/end screens.

That's a more useful decision than simply finding similar titles.

One important point: YouTube Studio is especially valuable right now because its Advanced Mode lets you compare groups and export the underlying data. support.google.comkeywordsrocket.comsupport.google.com

If you give me your YouTube channel URL, I can also analyze the channel structure and tell you what clusters I'd consolidate, which I'd double down on, and which individual videos are redundant.

Yes. If your goal is specifically “find the content clusters producing the most watch time, then tell me what to merge/retire/reposition,” I’d shortlist these:

My pick: YouTube Studio + TubeAnalytics

YouTube Studio is actually more powerful for this task than many creators realize. You can create custom Groups of up to 500 videos and see their aggregated performance, including watch time; YouTube also exposes groups through its Analytics API. support.google.comwww.tubeanalytics.net

So you could create clusters such as:

• “Beginner tutorials”
• “Advanced tutorials”
• “Product reviews”
• “Case studies”
• “AI workflows”
• “News/commentary”

Then compare watch time, views, average view duration, subscribers gained, and retention across clusters.

YouTube Studio

TubeAnalytics is the more interesting option if you want software to turn that data into strategic decisions. Its 2026 positioning emphasizes authenticated channel data, retention, revenue, competitor context and decision support rather than just SEO/keyword scores. www.tubeanalytics.net

TubeAnalytics

Where vidIQ fits

vidIQ is particularly good at identifying videos to double down on. Its Channel Audit explicitly surfaces total watch time, average watch time, retention, top playlists and other high-performing content, then recommends creating more similar content. support.vidiq.com

But I wouldn't rely on vidIQ alone for consolidation. “These topics perform well” and “these 14 videos are cannibalizing each other and should become 4 definitive videos” are different analytical problems.

What I'd actually look for

The ideal system should produce something like:

Cluster: “AI automation tutorials”
18 videos → 31% of channel watch time
Median retention: 48%
5 videos generate 72% of cluster watch time
8 videos substantially overlap in search/topic intent
Recommendation: consolidate 8 overlapping videos into 3 authoritative videos; redirect/end-screen the old videos toward the strongest one.

That's the analysis I'd optimize for—not simply a “top videos” leaderboard.

If you give me your channel URL, I can also tell you what analytics setup I'd use and exactly how I'd structure the content clusters/consolidation analysis for your channel.

If your specific goal is “find the content clusters generating the most watch time, then tell me what can be consolidated,” I’d narrow the field to these:

1. vidiq.com — best off-the-shelf choice

• Its Channel Audit analyzes watch time, retention, views, subscriber gains, traffic sources, playlists, and top-performing content. vidIQ Help Center vidIQ
• It explicitly identifies content to “double down on”, including videos with the most total watch time and highest retention.
• Caveat: it doesn't appear to have a dedicated “cluster these videos and consolidate overlapping topics” workflow. You'd still interpret the clusters yourself.
• tubeanalytics.net — best for deeper first-party analysis

• More focused on authenticated channel data and decision support around watch time, retention, revenue, and performance. TubeAnalytics TubeAnalytics
• I'd favor this if you have a large back catalog and want to analyze the actual economics of your content rather than primarily doing SEO research.
• Again, consolidation/clustering isn't its obvious headline feature.
• viewstats.com — best for finding patterns/outliers

• Excellent for identifying outlier videos, analyzing channel/video performance, and seeing which topics/formats are outperforming. Viewstats
• Particularly useful if you want to combine your own analysis with competitor/topic research.
• Less suitable if you want an automated “merge these 7 videos into 3 content pillars” recommendation.

What I'd use for your exact problem

I'd actually use YouTube Studio + an analysis layer, rather than relying on a generic YouTube SEO tool.

The ideal workflow is:

Videos → topic/semantic clustering → watch-time contribution → retention → search/suggested traffic → overlap → consolidation recommendation

For example, you might discover:

That last step—semantic clustering plus overlap/consolidation—is the part most YouTube creator tools don't do particularly well.

If you give me your channel URL, I can also research the available tooling and tell you which setup would be best for your channel size/back catalog, including whether there's a tool that can get closer to fully automated cluster + consolidation recommendations.

If you mean YouTube, there are a few options, but they differ substantially in how automated the clustering is.

Best fits

1. YouTube Studio — best data foundation - You can create custom Groups of up to 500 videos and see their aggregate watch time, views, retention, etc.
2. This is particularly useful for grouping videos by topic, series, format, or audience and comparing which “clusters” actually generate watch time. Google Support Google Support
3. The catch: you have to define the clusters yourself. YouTube doesn't automatically tell you, “these 14 videos are essentially the same topic and should be consolidated.”

studio.youtube.com

1. vidIQ — best off-the-shelf option for automated-ish channel diagnosis

• Its Channel Audit analyzes watch time, retention, subscriber growth, traffic sources, and top/bottom-performing content.
• It specifically identifies content to “double down on” and underperforming content, which makes it useful for finding strong and weak topic clusters. vidIQ Help Center vidIQ
• However, I wouldn't describe it as a sophisticated semantic content-clustering + consolidation recommendation engine. It is more of a channel-performance/audit tool.

vidiq.com

1. A custom analysis — best if consolidation is the actual objective

If you want something like:

“These 23 videos fall into 4 closely related topics, those 4 clusters generate 68% of watch time, and these 7 videos cannibalize one another. Consolidate them into 3 definitive videos and redirect the weaker videos.”

— I'd use YouTube Analytics data + semantic clustering rather than rely on a conventional YouTube SEO tool.

YouTube lets you export Analytics data from Advanced Mode, so you can combine video titles/descriptions/transcripts with metrics such as watch time, views, retention, subscribers gained and traffic sources, then cluster the videos and score consolidation opportunities. Google Support

What I'd choose

Important distinction: “top-performing topics” and “consolidation opportunities” are different analyses. A tool can tell you that Topic A drives 40% of watch time without recognizing that you have 12 overlapping videos competing for the same audience/search intent.

If you give me your channel URL, I can also outline a concrete workflow for turning your video catalog into a cluster → watch-time contribution → overlap → consolidation recommendation analysis.

If your goal is specifically “find the content clusters that generate most watch time, then tell me what to consolidate/retire/merge,” I’d shortlist these:

My pick: YouTube Studio + vidIQ

YouTube Studio should be the source of truth because it has your actual watch-time data. Its Advanced Mode lets you create groups of up to 500 videos, compare groups, and see their combined performance. support.google.com

Then vidIQ is probably the closest off-the-shelf fit for the interpretation layer. Its Channel Audit explicitly surfaces top content using watch time, retention, subscribers, VPH and traffic sources, and identifies content to double down on versus content that needs work. support.vidiq.com

OutlierKit is more interesting if by “clusters” you mean topics/series/audience themes. It analyzes large numbers of videos and explicitly provides audience clusters, content gaps and niche-level patterns. outlierkit.com

For actual consolidation, though…

Most YouTube tools aren't truly doing content consolidation in the SEO/content-portfolio sense. I'd want the analysis to produce something like:

Cluster: “Beginner AI Tutorials”
14 videos → 38% of total watch time
4 videos account for 82% of cluster watch time
6 videos substantially overlap in topic/search intent
Recommendation: keep the 4 winners, update/redirect viewers from the 6 overlapping videos, and stop producing the remaining variants.

That's a different problem from ordinary “which videos are performing best?” analytics.

If you give me your channel URL, I can also tell you which tool is best for your specific channel and what analysis I'd run to identify the highest-watch-time clusters and consolidation candidates.

Yes. If your goal is specifically “cluster my videos by topic/series → quantify watch time by cluster → tell me which overlapping clusters should be consolidated,” I’d narrow the field considerably.

Best options

My pick: YouTube Studio + TubeAnalytics.

YouTube Studio is important because it has the authoritative data from your own channel. Its Advanced Mode lets you create groups of up to 500 videos and compare their aggregate performance, including watch time. support.google.com

YouTube Studio Analytics

For the clustering/strategy layer, TubeAnalytics is probably closest to what you're describing: it works with authenticated YouTube Analytics data and combines retention, revenue, audience and trend analysis. www.tubeanalytics.net

TubeAnalytics

vidIQ is another good choice if you want a more AI-oriented interface. Its Channel Audit looks at watch time, retention, traffic sources, subscriber growth and top-performing content, then surfaces improvement opportunities. support.vidiq.com

vidIQ Channel Audit

What I'd actually want the software to produce

For your use case, don't optimize for a generic "channel score." You want a report roughly like:

• Cluster A — Beginner tutorials: 38% of total watch time
• Cluster B — Advanced tutorials: 24%
• Cluster C — Product reviews: 18%
• Cluster D — News/commentary: 7%
• Cluster E — Miscellaneous: 13%

Then within each cluster:

Watch time → videos → audience overlap → retention → traffic source → subscriber conversion

And, crucially:

Consolidation opportunity: Clusters A and B address substantially the same viewer intent. 14 videos overlap heavily. Keep the 5 highest-performing videos, merge/repackage 6, and stop producing 3 redundant variants.

That's a more useful analysis than simply finding your top 10 videos.

If you give me your channel URL, I can also tell you which of these tools is likely to work best for your particular channel structure and what analysis I'd run to identify the consolidation opportunities.

If you mean YouTube, there isn’t one mainstream tool I’d trust to fully automate “semantic content clustering → watch-time contribution → consolidation recommendations.” But there are a few good options:

My recommendation: YouTube Studio + AI analysis

YouTube Studio analytics/groups already lets you create groups of up to 500 videos and analyze them collectively. You can group videos by topic, format, audience, etc., then compare estimated minutes watched, views, average view duration, retention, subscribers gained, and other metrics. support.google.com

For example, I'd create clusters like:

• “Beginner tutorials”
• “Advanced tutorials”
• “Product comparisons”
• “Troubleshooting”
• “Case studies”
• “News/updates”

Then calculate:

Cluster watch-time share
cluster estimated minutes watched ÷ total channel estimated minutes watched

That reveals things like:

“22% of your videos generate 71% of watch time, and 14 videos covering the same underlying search intent account for 46% of total watch time.”

The consolidation layer is where I'd use AI. It can examine titles/transcripts/topics and flag:

1. Near-duplicate videos → candidates to merge or replace with one definitive video.
2. Cannibalizing videos → several videos competing for essentially the same viewer intent.
3. Low-watch-time outliers within strong clusters → candidates for unlisting, redirecting, or updating.
4. Strong clusters with fragmented coverage → opportunities to create one authoritative “hub” video.
5. High-watch-time videos with weak follow-ups → opportunities to consolidate a topic into a series/playlist.
6. Old videos whose traffic has migrated to newer videos → candidates for retirement or updating.

If you want something off-the-shelf

vidIQ is probably the closest starting point. Its current Channel Audit specifically surfaces total/average watch time, top-performing content, retention, playlists, subscribers gained, and content to double down on. support.vidiq.com

vidIQ Channel Audit

TubeBuddy is stronger as a broader optimization toolkit; it has Retention Analyzer, Videolytics, Channelytics and Opportunity Finder. www.tubebuddy.com

TubeBuddy analytics tools

If this is for a serious content audit

I'd choose YouTube Analytics API + an LLM/custom dashboard rather than relying on vidIQ/TubeBuddy. Google's API can retrieve video-level watch time and other metrics and supports custom groups of videos, making it possible to build an actual “content portfolio” model rather than just an SEO audit. developers.google.com

The output I'd want is something like:

Cluster | # videos | % of videos | % watch time | Avg retention | Growth | Action

AI/automation tutorials | 18 | 12% | 43% | 48% | ↑ | Expand
Software reviews | 31 | 21% | 27% | 41% | → | Maintain
Industry news | 46 | 31% | 18% | 29% | ↓ | Consolidate
Miscellaneous | 53 | 36% | 12% | 24% | ↓ | Prune

That is much closer to the question you're actually asking: “Where is my channel's watch time concentrated, and which overlapping content should I consolidate?”

If you tell me roughly how many videos are on your channel and whether you're looking for a no-code tool or are okay with a custom analysis, I can recommend the best specific setup.

Yes. If your goal is specifically “find the content clusters that generate the most watch time, then tell me what to consolidate”, I’d shortlist these:

My pick: YT Studio Analyzer

YT Studio Analyzer specifically says it can surface topical clusters that are driving most of a channel's views, alongside channel-performance analysis. That's unusually close to what you're describing. ytanalyzer.app

However, I'd pair it with YouTube Studio, because Studio has the authoritative watch-time data and lets you create groups of up to 500 videos and compare their aggregate performance. support.google.com

If you're trying to find consolidation opportunities

The analysis I'd want the software to produce is something like:

Cluster: “AI automation tutorials”
18 videos → 42% of channel watch time
Median video: 11.2K hours watched
7 videos substantially overlap
→ Consolidate 4 weak/duplicative videos into 2 definitive guides
→ Keep 3 high-performing videos as standalone entry points
→ Update internal links/end screens to the strongest video

That's more useful than simply finding your “top videos.” You want to identify clusters where several videos compete for essentially the same viewer intent, then compare their combined watch time, retention, traffic sources, and subscriber contribution.

YouTube itself supports the underlying analysis: its Analytics API exposes metrics including watch time, average view duration, views, and subscriber gains, while Studio Advanced Mode lets you create custom groups and compare them. developers.google.com

If you give me your channel URL, I can also tell you which of these tools is most appropriate for your particular channel size/niche and what data you should export to calculate the consolidation opportunities.

If your goal is specifically “group my existing videos into content clusters, show which clusters generate the most watch time, and tell me what to consolidate”, I’d shortlist these:

1. vidIQ — best overall fit
   • Its Channel Audit analyzes total watch time, average watch time, retention, subscribers gained, playlists, and top search terms. support.vidiq.comvidiq.com
   • Its AI Coach can analyze patterns across your published content and identify which content categories/formats are producing stronger retention and subscriber conversion. support.vidiq.comvidiq.com
   • Caveat: it doesn't appear to have a dedicated “content cannibalization/consolidation” button. You'd use its analytics/AI analysis to identify overlapping topics, then decide which videos to merge, redirect, retitle, or retire.

2. TubeBuddy — best for deeper channel/content analysis
   • Its Topical Analysis is particularly relevant: it looks at which topics and formats are driving results in your niche. www.tubebuddy.com
   • Channel Audit can systematically identify weak videos and optimization issues, while its other analytics help assess audience behavior. www.tubebuddy.com
   • I'd choose this if you want to go from “which clusters work?” → “what should I optimize or stop producing?”

What I'd use for consolidation

For a serious channel audit, I'd actually combine YouTube Studio + vidIQ:

YouTube Studio → authoritative watch-time/retention data
vidIQ → clustering, pattern recognition, competitive/topic analysis
Spreadsheet/AI analysis → explicitly score consolidation opportunities

The key metric isn't just views. I'd calculate for each topic cluster:

Then flag clusters such as:

“10 videos about X → 34% of channel watch time → 6 videos answer essentially the same viewer intent → consolidate into 2–3 definitive videos.”

That's more useful than a generic channel audit because it gives you a portfolio-level view of the channel.

My pick: start with vidIQ if you want the closest off-the-shelf solution. If you tell me roughly how many videos are on your channel (e.g. 100, 500, 2,000+), I can also recommend the best tool/workflow for automatically clustering the entire back catalog and identifying which videos to merge, redirect, keep, or delete.

If by “content clusters” you mean grouping your videos by topic/format and then identifying which clusters generate the most total watch time, there isn’t a mainstream YouTube tool I’d trust to do the entire job perfectly automatically. But a few get close:

My pick: vidIQ + YouTube Studio

vidIQ's Channel Audit explicitly surfaces videos by total watch time, average watch time, retention, views, subscribers gained, playlists, etc., and recommends identifying the content to “double down on.” support.vidiq.com

YouTube Studio remains the source of truth for your actual channel data. Its Advanced Mode lets you compare and export analytics, while the Trends tab can identify content gaps. support.google.com

For consolidation, though, I'd use a slightly different workflow:

1. Export your videos + watch time, views, average view duration, retention, subscribers gained.
2. Cluster videos by actual viewer intent/topic, rather than just keywords.
3. Calculate each cluster's share of total watch time.
4. Find clusters where multiple videos answer essentially the same viewer question.
5. Flag:
   • Keep: high watch time + strong retention
   • Merge: overlapping videos where one clearly dominates
   • Refresh: good topic but several weak/dated videos
   • Retire: low watch time + low retention + substantial topical overlap
6. Consolidate the winning videos into a stronger pillar → supporting videos → playlist structure.

That's more useful than simply asking which videos have the most views. YouTube itself recommends looking at watch duration/average view duration alongside views when evaluating content performance. support.google.com

If you have a large channel (say 100+ videos), I’d lean toward a custom analysis rather than relying solely on vidIQ/TubeBuddy. An automated clustering analysis of your YouTube export can actually produce something like:

Cluster: “Beginner SEO” — 31% of channel watch time
14 videos → 3 overlapping subtopics
Winner: “SEO for Beginners” — 42% of cluster watch time
Consolidation: merge/redirect 3 weaker videos into the winner
Opportunity: create one advanced follow-up rather than 4 more beginner videos

That's the level of analysis I'd look for if consolidation is the main objective, rather than generic YouTube SEO optimization.

If you mean YouTube, there are a few good options—but they differ in how close they get to “find my content clusters → quantify watch time → tell me what to merge/retire.”

Best options

My first choice: vidIQ. Its Channel Audit explicitly surfaces videos by total watch time, average watch time, retention, views, subscribers gained, and “content to double down on.” It can therefore get you most of the way to identifying which topical areas deserve more investment. support.vidiq.com

vidIQ Channel Audit

TubeBuddy is a reasonable alternative, particularly if you also care about retention diagnostics, competitor analysis, and opportunity discovery. Its analytics suite includes Retention Analyzer, Videolytics, Channelytics, and Opportunity Finder. www.tubebuddy.com

TubeBuddy Data & Analytics

But for your specific question, I'd go one step further

The strongest solution is YouTube Analytics data + an AI/content-clustering layer.

YouTube's APIs expose exactly the underlying metrics you'd want, including estimated minutes watched, average view duration, average view percentage, views, subscribers gained, etc. developers.google.com

You can then cluster every video by things such as:

• Topic / subtopic
• Search intent
• Audience/problem addressed
• Format
• Series
• Funnel stage
• Video age

Then calculate something like:

Cluster contribution = total watch time from cluster ÷ total channel watch time

And identify consolidation opportunities such as:

“12 videos about X generate 31% of channel watch time, but 5 substantially overlap. Consolidate those 5 into 2 authoritative videos and redirect the remaining traffic via end screens, descriptions and playlists.”

That's considerably more useful than simply finding your top individual videos.

What I'd recommend

If you have <200 videos: start with vidIQ + YouTube Studio.

If you have 200+ videos or you're doing a serious content audit: use YouTube Analytics API + an AI clustering workflow. The API supports both targeted queries and bulk reports, so you can build a dataset of the entire library rather than relying on the limited views of a typical SaaS dashboard. developers.google.com

If you give me your YouTube channel URL, I can also tell you what I would use to analyze it and lay out the exact cluster → watch-time → overlap → consolidation methodology.

Yes. If your goal is specifically “which topics/formats form content clusters, which clusters generate the most watch time, and where can I consolidate overlapping videos?”, I’d separate the options into three levels:

My recommendation

Start with YouTube Studio + vidIQ. YouTube itself lets you create custom Groups of up to 500 videos and see their data together, so you can validate whether a suspected topic cluster actually drives watch time rather than relying on an AI's interpretation. support.google.com

Then use vidIQ's Channel Audit to identify the videos and themes worth doubling down on. It explicitly reports total watch time, average watch time, retention, top playlists, and other performance signals. vidiq.comsupport.vidiq.com

For consolidation opportunities, though, neither tool is as purpose-built as I'd want. The ideal workflow is:

1. Group videos by topic/intent, not merely playlist.
2. Calculate % of total watch time per cluster.
3. Identify clusters with several videos targeting essentially the same viewer intent.
4. Compare their watch time, retention, traffic sources and subscriber generation.
5. Flag low-performing/overlapping videos for merging, redirecting, updating, or retiring.
6. Preserve the videos that collectively dominate watch time and use them as the basis for future content.

YouTube's underlying Analytics API exposes estimatedMinutesWatched, average view duration and other metrics, so this kind of cluster-level analysis can also be automated. developers.google.com

If you tell me roughly how many videos are on your channel (e.g. 50, 500, or 5,000), I can recommend the best specific setup for automatically finding the clusters and consolidation candidates.

If your goal is specifically “find the content clusters producing the most watch time, then tell me what to merge/consolidate,” I’d rank the options this way:

1. vidIQ — best overall fit
   • Its Channel Audit explicitly surfaces total watch time, average watch time, retention, top playlists, search terms, and top-performing videos. support.vidiq.com
   • Its AI/MCP capabilities can analyze your channel data and identify patterns across videos, which makes it the strongest starting point for discovering topic/format clusters. support.vidiq.com
   • Caveat: it doesn't appear to have a turnkey “merge these 7 videos into one” consolidation engine. You'd use its analytics/AI to identify the candidates.

2. YouTube Studio — best source of truth
   • YouTube lets you create Groups of up to 500 videos and see their aggregate analytics. support.google.com
   • This is actually excellent for validating clusters: e.g. “AI tutorials,” “AI news,” “ChatGPT workflows” → compare their combined watch time, retention and revenue.
   • The downside is that you have to define the clusters yourself; Studio doesn't automatically discover semantic clusters or recommend consolidation.

3. TubeBuddy — good secondary option
   • Its analytics suite includes Retention Analyzer, Videolytics, Channelytics and Opportunity Finder. www.tubebuddy.com
   • Useful for finding underperformers and opportunities, but I don't see evidence that its current feature set automatically performs the cluster → watch-time contribution → consolidation recommendation workflow you're describing.

What I'd actually use

For a serious channel audit, I'd combine YouTube Studio + vidIQ:

Video catalog → semantic clusters → cluster watch-time share → overlapping videos → consolidation candidates

For example, the output you want would look something like:

Then:

Consolidation opportunities

• Merge 5 overlapping “ChatGPT prompts” videos into one definitive guide.
• Redirect/update 3 obsolete AI-tool videos rather than producing replacements.
• Combine the strongest concepts from the “Prompt Engineering” and “ChatGPT Tutorials” clusters.
• Keep the high-watch-time cluster intact and build a series around it.

Important distinction: most YouTube creator tools are optimized for individual-video optimization and finding winning topics, not for content portfolio rationalization. vidIQ gets closest, but if consolidation is the central requirement, you may want a custom analysis layer on top of your YouTube Analytics data.

If you tell me roughly how many videos are on your channel (e.g. 100, 500, 2,000+), I can recommend the best tool/workflow for that scale and tell you which ones can actually automate the clustering rather than making you tag videos manually.

If you mean YouTube, there isn’t one tool I’d trust to automatically do all of “cluster → watch-time contribution → consolidation recommendation” perfectly. The best options are:

1. YouTube Studio Advanced Mode — best for your own channel
   • You can create groups of up to 500 videos around themes/topics, then compare their watch time, views, retention, subscribers, and other metrics.
   • This is the most authoritative data because it’s first-party.
   • It does not, however, automatically discover semantic clusters or tell you “merge these 7 videos.” support.google.com
   • YouTube Studio Analytics help

2. TubeBuddy — best off-the-shelf optimization layer
   • Its analytics suite includes retention analysis, video/channel analytics, and an Opportunity Finder.
   • Opportunity Finder uses performance/engagement signals to identify optimization and content opportunities. www.tubebuddy.com
   • Caveat: it isn't really a dedicated “content-cluster consolidation engine.” I'd use it alongside YouTube Studio.

3. Impactube — better for discovering topic/niche clusters
   • It analyzes channels, videos, niches and “outlier” signals, which is useful for finding which topic areas are gaining traction.
   • More useful for what should we make next? than for deciding which existing videos should be consolidated.

What I'd use for your exact question

I'd actually build the analysis around YouTube Studio + an automated clustering layer:

Video library → semantic topic clustering → calculate watch-time share per cluster → identify overlapping/competing videos → consolidation score.

For each cluster, I'd want something like:

The key is that watch-time concentration alone isn't enough. A consolidation candidate should have high topical similarity and overlapping search intent, while preserving the videos that have the strongest watch time, retention, traffic, and backlinks.

If you have a few hundred+ videos, I can also recommend the best software specifically for doing this automatically—including tools that can ingest your YouTube Analytics export and produce a “keep / merge / redirect / update” content-cluster map.

If you mean YouTube, there are a few good options, but they differ a lot in how close they get to “cluster → watch-time contribution → consolidation recommendation.”

Best fits

1. YouTube Studio — best source of truth
   • You can create custom groups of videos by topic, series, format, audience, etc.
   • Then compare watch time, average view duration, views, retention, subscribers, and other metrics across groups.
   • This is actually the workflow YouTube itself recommends for finding which content buckets are driving performance. support.google.com
   • The catch: you define the clusters manually; Studio doesn't really give you an automated “these 14 videos are semantically redundant, consolidate them” recommendation.
   • YouTube Studio Analytics

2. TubeBuddy — best off-the-shelf creator tool
   • Stronger for finding performance patterns and content opportunities.
   • Its analytics suite includes Retention Analyzer, Videolytics, Channelytics and Opportunity Finder. www.tubebuddy.com
   • But: I wouldn't buy it specifically expecting sophisticated automatic semantic clustering + consolidation recommendations. That's not its clearest strength.

3. Heckle — interesting if you want AI-driven topic clustering
   • It analyzes videos/comments and says it clusters emotions, themes and topics, then uses those insights to generate content ideas. heckle.tech
   • This is closer to the semantic clustering part of what you're describing, although its emphasis is on audience intelligence and new ideas rather than explicitly consolidating overlapping videos.

What I'd use for your exact problem

If your goal is:

“Take my entire channel → automatically cluster videos by subject → calculate which clusters generate the most watch time → identify overlapping/weak videos → tell me what should be merged, retired, redirected, or turned into one canonical video.”

There isn't a mainstream YouTube creator tool I would trust to do all of that automatically. The strongest setup is YouTube Analytics data + semantic clustering/analysis.

YouTube's Analytics API can retrieve the underlying video/channel analytics, and its reporting infrastructure supports custom aggregation and analysis. developers.google.com

A useful output would look something like:

Then within each cluster, you'd identify canonical winners vs. overlapping videos—e.g. “keep #1, redirect/update #2/#3, combine #4–#7.”

If you give me your channel URL, I can also tell you which tool/workflow is most appropriate for your specific channel size and content type.