The Ultimate Guide to Video Podcast Analytics (2025 Edition)

Video podcasting has transformed a once audio-only medium into a multi-platform content ecosystem. Top creators now publish episodes across Spotify, YouTube, and other channels, meaning podcast performance must be tracked on more than one platform (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). To truly understand and grow your show’s audience, you’ll need to leverage each platform’s native analytics (Spotify for Podcasters and YouTube Studio) and possibly augment them with third-party tools like Mondo Metrics for a unified view. This guide provides an in-depth look at analyzing video podcast performance on Spotify and YouTube, the key metrics to monitor, how to interpret and act on the data, and how Mondo Metrics compares and complements native analytics.

Analyzing Video Podcast Performance on Spotify

Spotify’s podcast analytics (accessible via Spotify for Podcasters on web) offer insights into how listeners and viewers engage with your video episodes on Spotify. Below are the key performance metrics Spotify provides and how to use them:

• Plays (Streams) – The total number of times your episodes were played for at least 60 seconds. Spotify counts a “play” (or stream) once a listener or viewer has streamed 60+ seconds of an episode (How we count plays, starts, and streams - Spotify). This includes video views, which are counted toward your total plays (Video analytics - Spotify). A higher play count indicates greater reach. Monitor plays per episode to identify which topics or guests attract more listeners. Remember that if your podcast is hosted on Spotify’s platform, this play count includes downloads as well (How we count plays, starts, and streams - Spotify), whereas if hosted elsewhere it will count Spotify in-app plays only.
• Unique Listeners – The number of distinct Spotify users who listened to your podcast in a given period. This “Audience size” helps gauge how wide your listener base is, beyond just play counts (since one person can play multiple episodes). Growth in unique listeners over time means you’re successfully expanding your reach. Check this in the Audience section of Spotify analytics and track it month-to-month.
• Spotify Followers – Users who follow your podcast on Spotify. Followers are analogous to subscribers – they’re your most loyal audience who get updates about new episodes. An increasing follower count is a positive sign of growing loyalty. Spotify displays your total followers (and typically shows net gain over time). For example, you can see what percentage of listeners end up following your show (conversion to followers) (Understanding audience discovery metrics on Spotify - Spotify). A high conversion rate suggests your content motivates occasional listeners to become regular fans.
• Viewers & Watch Time (for Video Episodes) – For each video episode on Spotify, you can see Viewers (unique viewers) and Watch Hours (Video analytics - Spotify). Viewers is the count of unique Spotify users who watched the video for at least 60 seconds (Video analytics - Spotify). Watch Hours is the total time (in hours) people spent watching the episode on Spotify (Video analytics - Spotify). These metrics reveal the reach and depth of engagement with your video podcasts on Spotify. For instance, if an episode has many viewers but low watch hours, viewers didn’t stick around for long (indicating potential issues with content pacing or topic relevance). Aim to increase both viewers (by promoting your video episodes) and watch hours (by making content more engaging throughout).
• Audience Retention – Spotify provides an audience retention chart for each episode, showing what percentage of listeners/viewers are still engaged at each point in the episode (Audience retention - Spotify). It also highlights the median play time (the timestamp where 50% of the audience has stopped listening) (Audience retention - Spotify). Use this to pinpoint drop-off points: if you see a steep dip 10 minutes in, analyze what might have caused people to leave (perhaps a less interesting segment or ad break). High retention (a flatter curve) means listeners stay through most of the episode – a sign of compelling content. To improve retention, structure episodes to hook listeners early and maintain interest (for example, avoid long tangents or place ads at natural breakpoints). Over time, try to push the median play time later into the episode, indicating more people listen longer.
• Impressions and Discovery Metrics – Spotify tracks how often your show or episodes appear to potential listeners in the app (these appearances are counted as Impressions). In Spotify Analytics under Discovery, you can see how many people you “reached” (impressions), how many showed interest (e.g. clicked your show or started an episode), and how many actually streamed for 60+ seconds (Understanding audience discovery metrics on Spotify - Spotify) (Understanding audience discovery metrics on Spotify - Spotify). This acts as a rough “click-through rate” for your podcast within Spotify. For example, if your show has a lot of impressions but relatively few streams, it means many users see your podcast listing but don’t click play (Understanding audience discovery metrics on Spotify - Spotify). That could signal your title or cover art isn’t enticing enough. Spotify even shows where those impressions come from (Home, Search, Charts, etc.) (Understanding audience discovery metrics on Spotify - Spotify) (Understanding audience discovery metrics on Spotify - Spotify). Tip: If you discover most impressions come from Spotify search, ensure your podcast metadata (title, description) is optimized and your cover art stands out so that searchers are compelled to listen (Understanding audience discovery metrics on Spotify - Spotify). If impressions are high but conversion to plays is low, consider tweaking your episode titles or promotional description to better attract listeners (Understanding audience discovery metrics on Spotify - Spotify).
• Engagement (Spotify-specific) – While Spotify doesn’t have likes or comments for podcasts, it does offer interactive features like polls and Q&A on episodes. Track participation in these (e.g. how many listeners vote in a poll or respond to a Q&A) as a qualitative engagement metric. Additionally, episode rating (if Spotify allows listeners to rate podcasts) and the ratio of followers to listeners can serve as an engagement indicator. A high follower-to-listener ratio or a lot of user responses on episodes means your audience is actively engaged. Encourage listeners to follow, respond to polls, or share feedback – this will boost engagement rates and can also improve your standing in Spotify’s algorithm.
• Demographics & Audience Info – Spotify provides data on listener demographics and other traits. In the Audience section, you can see your listeners’ age ranges, gender breakdown, and top geographic locations (Audience stats - Spotify). You can also see what platforms/devices they use (e.g., iOS, Android, desktop) (Audience stats - Spotify). Use this information to tailor your content and marketing: for instance, if you have a much younger audience on Spotify than you expected, you might tweak your references or promotion strategy to fit that demographic. Or, if one country has a growing listener base, consider giving shout-outs to that region or even adding local topics which can further boost engagement there. Demographics won’t directly increase views or listens, but they help you understand who your audience is so you can better serve them.

Using Spotify Analytics to Improve Content: Regularly review these Spotify metrics after each episode drops. For example, check retention graphs a few days post-release to see if a particular segment caused churn – then adjust your format in future recordings (perhaps move that segment later or shorten it). Watch your follower growth and try to correlate spikes with specific episodes or marketing pushes (did an episode that featured a guest or a viral topic gain you more followers than usual?). Monitor impressions and how they translate to plays: if you get featured on Spotify’s charts or playlists (causing impressions to spike), capitalize on it by ensuring the episode that new listeners land on has a strong hook. Overall, treat Spotify’s analytics as a feedback loop to refine your content strategy – doubling down on what works (topics with high completion rates or above-average follower conversion) and improving what doesn’t (episodes with early drop-offs or stagnant audience growth).

Analyzing Video Podcast Performance on YouTube

YouTube is now one of the most important platforms for podcasts, often acting as a discovery engine for new audiences (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). YouTube’s native analytics (in YouTube Studio) are very robust, offering a wealth of data about how viewers find and engage with your video podcast episodes. Key YouTube performance metrics to focus on include:

• Views – The number of times your video was watched. YouTube counts a view typically after a few seconds of play. For a podcast episode (which might be long-form), views alone don’t tell the full story, but they measure reach. Keep an eye on views to gauge the overall popularity of each episode and your channel’s growth trajectory. Also note Unique Viewers (in YouTube’s Audience tab) which estimates how many distinct people those views come from – useful for understanding true reach versus repeat views.
• Watch Time – The total accumulated time people have spent watching your video, usually measured in hours or minutes. Watch time is a critical metric for YouTube success. It’s literally “the total amount of minutes viewers have spent watching your videos” (YouTube Analytics: The 15 Metrics That Actually Matter ). High watch time signals to YouTube that your content is engaging, and it influences YouTube’s algorithm in promoting your videos (YouTube Analytics: The 15 Metrics That Actually Matter ). For a podcast, which often runs long, maximizing watch time is key. Check the Watch Time report in YouTube Analytics to see which episodes got the most watch minutes (YouTube Analytics: The 15 Metrics That Actually Matter ). You can even compare watch time across videos to identify your most engaging episodes or segments (YouTube allows grouping videos by playlists or tags to compare metrics) (YouTube Analytics: The 15 Metrics That Actually Matter ). If a 30-minute episode has far less watch time than a 60-minute episode, it could mean fewer people clicked or they didn’t watch as long – investigate via retention metrics.
• Audience Retention – YouTube provides detailed retention analytics, showing exactly where viewers drop off during the video. The audience retention graph plots the percentage of viewers watching at each moment of the video (YouTube Analytics: The 15 Metrics That Actually Matter ). This helps you pinpoint sections that cause viewers to leave. For example, you might see a dip 5 minutes in – perhaps your intro is too long, or a less interesting topic came up. YouTube’s retention report even gives two views: absolute retention (how your video keeps viewers over its duration) and relative retention (how your video’s retention compares to other YouTube videos of similar length) (YouTube Analytics: The 15 Metrics That Actually Matter ). Aim for a high absolute retention – ideally a steady line without steep declines until maybe towards the end. Also note if your relative retention is “above average” or “below average” for that length; this indicates if your podcast holds attention better or worse than typical videos of similar length (YouTube Analytics: The 15 Metrics That Actually Matter ). Use these insights to adjust your content flow: for instance, if you notice viewers re-watching or pausing at certain points (YouTube highlights re-watch peaks), that content resonated – consider expanding on that in future episodes. Conversely, if a segment consistently causes drop-offs, refine or remove it in future recordings (YouTube Analytics: The 15 Metrics That Actually Matter ) (YouTube Analytics: The 15 Metrics That Actually Matter ). High retention is rewarded by YouTube’s algorithm with more recommendations (YouTube Analytics: The 15 Metrics That Actually Matter ), so improving this metric can directly lead to growth.
• Average View Duration & Percentage Viewed – These metrics summarize retention in numeric form. Average view duration tells you the average time each viewer spends watching your video (total watch time divided by total views) (YouTube Analytics: The 15 Metrics That Actually Matter ). Average percentage viewed tells you what portion of the video the average viewer watched (e.g. 50% of a 30-minute video) (YouTube Analytics: The 15 Metrics That Actually Matter ). These are useful for comparing episodes of different lengths. For instance, a 10-minute highlight video might have 70% average viewed, whereas a 60-minute full episode might have 40%. Longer videos naturally have lower percentage viewed, but if one episode’s percentage is much lower than others of similar length, it underperformed in engagement. Track average view duration trends – if you can raise this over time, it means people are watching more of your content on average (a great sign). YouTube favors videos with higher average watch time, so longer view durations can improve your SEO on the platform (YouTube Analytics: The 15 Metrics That Actually Matter ). To improve these metrics, focus on strong openings, maintaining pacing, and delivering value continuously so viewers don’t drop off early.
• Impressions & Click-Through Rate (CTR) – YouTube tracks how many impressions your video’s thumbnail receives (how many times it’s shown to users on YouTube) and the CTR – the percentage of those impressions that turned into views (clicks). The Impressions click-through rate essentially measures how compelling your title and thumbnail are at convincing people to watch (YouTube Analytics: The 15 Metrics That Actually Matter ). A high CTR means your video caught viewers’ attention effectively, indicating a strong topic, title, or thumbnail design (YouTube Analytics: The 15 Metrics That Actually Matter ). For example, an impressions CTR of 8% or above is generally considered good on YouTube (though it varies by niche and traffic source). Note that CTR often starts high among your subscribers and then settles lower as the video is shown to broader audiences (YouTube Analytics: The 15 Metrics That Actually Matter ). Track the CTR in the Reach tab of YouTube Analytics. If an episode’s CTR is low, consider optimizing the thumbnail (make sure it’s clear and attractive) or tweaking the title to be more enticing. However, always pair CTR with retention data: A high CTR is great, but if viewers leave immediately, the title/thumbnail might have been misleading (YouTube Analytics: The 15 Metrics That Actually Matter ). Ensure your content delivers on what the thumbnail/title promise, otherwise a strong CTR followed by a retention drop can hurt your video’s performance (viewers feel “tricked” and YouTube notices the quick exits). Likewise, if CTR is low but those who do click have high watch time and engagement, it may mean the content appeals deeply to a smaller audience (YouTube Analytics: The 15 Metrics That Actually Matter ). In that case, improving the packaging (title/thumbnail) could attract more of the right viewers without sacrificing engagement. Use CTR as a diagnostic: it tells you if the interest in your topic/presentation is high. To improve CTR: experiment with different thumbnail styles, use compelling episode titles (while staying honest), and consider the first line of the description as well since it shows up in preview.
• Engagement Metrics (Likes, Comments, Shares) – Engagement rate on YouTube can be gauged by how viewers interact: the number of likes (thumbs up), comments left, shares of your video, and even new subscribers gained from the video. These interactions are indicators of how much your content resonated. High likes and comments relative to views mean the audience found the episode valuable or evocative. Monitor the Like/Dislike ratio (though dislikes aren’t public, you see them in analytics) – predominantly positive feedback is good. Read through comments to gather qualitative feedback; responding to comments can further boost engagement and build community. Encourage engagement by prompting viewers to like and subscribe or discuss a particular question in the comments. While “engagement rate” isn’t a single built-in metric on YouTube, you can compute it (e.g. (likes + comments + shares) / views * 100%) to compare how interactive different episodes are. For instance, a video with 10,000 views and 500 combined interactions has a 5% engagement – if another has 10%, that episode sparked more activity. Shares are an often overlooked metric in the Engagement tab – if people are sharing an episode, it had impact. High engagement not only builds community but also feeds the algorithm: videos with lots of engagement can get a slight boost in visibility. To improve engagement, make sure to ask questions, create shareable moments (a memorable quote or insight might prompt viewers to share), and perhaps use YouTube’s interactive features like pinned comments or chapter markers to make engagement easier.
• Subscriber Growth – Track how your subscriber count changes, especially how many subscribers each video is netting. In YouTube Analytics, under Audience, you can see Subscribers gained or lost per video and overall (YouTube Analytics: The 15 Metrics That Actually Matter ) (YouTube Analytics: The 15 Metrics That Actually Matter ). Subscribers are your core fans who are likelier to receive notifications and watch future content (YouTube Analytics: The 15 Metrics That Actually Matter ). A video that brings a lot of new subscribers indicates you’ve struck a chord – perhaps the topic drew in new people or first-time viewers liked it enough to subscribe. On the flip side, if you see a video caused unsubscribes, analyze why – was the content off-brand or controversial? Use the Subscribers Report to identify which episodes, topics, or even release times yield the most new subs (YouTube Analytics: The 15 Metrics That Actually Matter ). For instance, you might find that interview episodes with high-profile guests cause a spike in subscriptions, meaning those are bringing new people to your channel. Doubling down on such content could accelerate channel growth. Additionally, pay attention to subscriber notifications: YouTube shows what percentage of your subscribers have “All notifications” on – encourage viewers to click the bell icon for notifications to boost views from your subscriber base (YouTube Analytics: The 15 Metrics That Actually Matter ). Tip: Subscribers tend to watch more content than non-subscribers on YouTube (YouTube Analytics: The 15 Metrics That Actually Matter ), so growing your subscriber base can lead to higher baseline viewership and watch time for each episode.
• Traffic Sources – This tells you how viewers found your video. The Traffic Sources report breaks down views and watch time by source: e.g. YouTube Search, Suggested Videos, Browse features (like the homepage or subscriptions feed), External (links from outside YouTube such as social media or embeds), etc. (YouTube Analytics: The 15 Metrics That Actually Matter ). This is crucial for understanding your podcast’s discoverability. For example, if a large portion of your traffic comes from Search, then optimizing your titles, descriptions, and tags for SEO (relevant keywords) can further boost that. If Suggested Videos (recommendations) are major, it means YouTube’s algorithm is pushing your content next to similar videos – analyze which videos commonly lead viewers to yours (YouTube shows “Traffic from Suggested” details) and consider networking or using similar tags. If External is low, maybe you’re not promoting enough on socials or your website. The Traffic Sources also show what’s driving watch time (YouTube Analytics: The 15 Metrics That Actually Matter ), not just clicks – a source that brings in viewers who stay long is valuable. Use this data to refine your promotion strategy: for instance, if you notice few people find your podcast via YouTube Search, you might start adding more descriptive titles or using the podcast keywords feature in YouTube’s Research tab to align with what people are searching for. On the other hand, if a lot of traffic comes from the YouTube home feed, it indicates YouTube is organically surfacing your content – maintaining a regular upload schedule and consistently engaging content will keep you in that rotation. Actionable insight: The Traffic Sources can guide where to focus outreach – e.g., boosting your presence on the sources that are underperforming, or capitalizing on ones doing well (if you get a lot of Suggested traffic from a particular creator’s audience, maybe collaborate with them). Overall, knowing how viewers find you helps ensure you’re not overly reliant on one channel and reveals opportunities to grow your audience through SEO or cross-promotion (YouTube Analytics: The 15 Metrics That Actually Matter ).
• Audience Demographics – In YouTube’s Audience tab, review your viewers’ demographics: age, gender, top countries, and even things like watch time by country or subtitle usage. Similar to Spotify’s demographics, this helps you understand who your viewers are. If, say, 80% of your YouTube viewers are 18-24 year-olds and primarily male, that’s useful for tailoring content, references, or even sponsorship targeting. Additionally, YouTube provides metrics like When your viewers are on YouTube (peak times/days your audience is online) – use this to schedule premieres or uploads for maximum impact. It also shows new vs. returning viewers – for a podcast, you want a healthy amount of returning viewers (indicating a loyal following), but also new viewers (indicating growth). Strive to convert new viewers into returning viewers by encouraging subscription and creating content series or themes that encourage people to come back. If your new viewers metric is high but returning is low, it might mean people check out an episode but don’t stick around – you may need stronger calls-to-action or more consistent content quality to retain them.

Using YouTube Analytics to Improve Content: The rich data from YouTube can directly inform your content strategy. For example, if audience retention graphs show viewers drop off whenever you segue into a certain segment (like off-topic chatter), consider tightening or cutting that segment. Use comments as qualitative data – are viewers asking for certain topics or giving feedback that something was too long? If CTR is an issue, A/B test different thumbnail styles or titles on a few videos and see which approach yields better CTR and watch time. If an episode unexpectedly took off via YouTube’s algorithm (e.g. high suggested traffic, high new viewer count), analyze why – was it a trending topic or a highly searched keyword? Perhaps do more episodes on that theme or optimize past episodes’ metadata to ride the wave. Experimentation is key: try tweaking one aspect at a time (title format, thumbnail design, video length, etc.) and use the analytics to gauge the impact. Also, pay attention to audience feedback loops: YouTube’s analytics are nearly real-time (with a real-time view count and 48-hour data) so you can see early performance of a new episode in the first 24–48 hours and promote it extra if it shows potential (high CTR or high avg view duration early on can signal the video might perform well if given a push). Lastly, leverage YouTube’s advanced features for engagement – for instance, end screens and info cards: YouTube Analytics will show card click-through rates (how many clicked on your info cards) (YouTube Analytics: The 15 Metrics That Actually Matter ) (YouTube Analytics: The 15 Metrics That Actually Matter ), which can tell you if your audience is interested in related content you’re plugging. High card clicks might mean your cross-promotion is effective; low might mean you need to introduce those cards more verbally in the video. Continuously refine your approach using the data, and your video podcast should see steady growth in viewership and engagement.

Collecting, Interpreting, and Acting on Analytics Data

Having all these metrics at your fingertips is valuable, but the real power comes from interpreting the data and turning insights into action. Here’s a step-by-step approach to make the most of your analytics:

1. Regularly Collect and Consolidate Data: Develop a routine for gathering your podcast metrics. For example, after each new episode, check both Spotify and YouTube analytics at set intervals (24 hours, 7 days, 30 days post-release) to capture performance over time. You might use a simple spreadsheet to record key metrics for each episode – such as Spotify streams, Spotify retention (median listen time), YouTube views, watch time, average view duration, etc. This historical log lets you spot trends (e.g. “episodes with topic X average 20% more views” or “retention improved after we shortened our intro”). Both Spotify and YouTube allow data export (CSV files) for deeper analysis if needed. Consistently collecting data ensures you have a baseline to compare against when you experiment with new ideas.
2. Interpret the Metrics in Context: Numbers by themselves don’t tell the whole story – always interpret them in context. For each episode, ask: Why did it perform this way? For instance, if one episode’s YouTube views are twice your channel average, investigate factors like: Was the topic trending? Did a notable guest bring their audience? Was the thumbnail particularly effective (high CTR)? Did you promote it more on social media? Conversely, if Spotify retention dropped on an episode, listen back at the timestamp where the drop occurred – was there a change in audio/video quality or content that might have put people off? Use comparative context too: compare an episode’s performance on Spotify vs YouTube. It’s possible an episode had average performance on Spotify but went viral on YouTube (maybe due to visual elements or YouTube’s algorithm picking it up). This tells you that format or subject resonated more with video viewers – insight you can use for future planning. Also compare performance to your own past episodes (is this episode doing better or worse than your last 5? Why might that be?) and to any benchmarks you have (if you know similar podcasts typically have a 50% retention, how do you stack up?). Interpretation is about finding the story in the data – perhaps “Episode 10’s success came from a high click-through rate and solid retention, meaning the topic interested a lot of people and the content paid off their interest”.
3. Identify Patterns and Key Drivers: As you interpret data over multiple episodes, certain patterns will emerge. You might notice, for example, episodes under 40 minutes have higher average completion rates than those over an hour – a sign that your audience prefers a tighter edit. Or maybe whenever you feature a guest, you see a spike in Spotify followers gained that week – indicating that guests attract new listeners who then stick around (so maybe feature guests more often or have them promote the episode to their followers). Look at correlations: Does higher YouTube engagement (likes/comments) correlate with more Spotify plays for that episode (perhaps due to overall interest in the topic)? Does releasing on a certain day of the week result in better performance (maybe your audience has a preferred content consumption day)? Use the data to test hypotheses. For example, “Our data suggests episodes about business topics get more shares. Let’s do more of those and see if the growth continues.” Or, “We lost subscribers on the episode where we changed our format – maybe that change wasn’t well-received, so we should rethink it.” By pinpointing what drives growth or declines, you can make informed decisions rather than guesses.
4. Act on Insights to Refine Your Strategy: Data is only as good as the actions you take from it. Take the patterns and lessons you’ve identified and apply them proactively to your content strategy. Some concrete actions might include:
   • Content Planning: Craft your editorial calendar based on what works. If analytics show your audience loves a specific segment or topic (e.g., tech news in your podcast gets high retention), make it a regular feature. If certain YouTube titles or thumbnails consistently draw higher CTR, adopt that style for future episodes. Essentially, double down on content that strikes a chord, and pivot away from content that underperforms.
   • Format and Pacing Adjustments: Use retention analysis to tweak your format. For instance, if many viewers skip the first 2 minutes (you see a dip then a plateau), consider shortening your intro or adding a teaser at the very start to hook viewers. If mid-roll ads cause drop-offs, try integrating sponsor messages more organically or at different timestamps. Over time, these adjustments, guided by data, will improve the viewer experience and metrics.
   • Promotion and SEO: Act on traffic source data. If YouTube analytics show low search traffic, invest time in better SEO: update video descriptions with relevant keywords, add detailed timestamps/chapters (YouTube indexes those for search), and ensure your titles contain terms your target audience might search. If external traffic is low, ramp up promotion outside of YouTube – share clips on Twitter, Instagram, or LinkedIn with links to the full episode, or engage in communities (subreddits, forums) related to your podcast’s niche. Conversely, if you see a lot of traffic is coming from, say, Facebook embeds, perhaps focus promotional efforts there or even consider a small ad campaign to boost those posts. On Spotify, if the “Where people find your podcast” data shows most find you via search, maybe the keywords in your show description are helping – continue to optimize those (and ensure your episode titles on Spotify are clear, since Spotify’s search might surface them).
   • Audience Engagement and Retention: If your data indicates that engagement drives growth (e.g., episodes with more comments and community interaction lead to more new subscribers), then invest in your community. For YouTube, engage in the comments, maybe do a post-episode live Q&A to foster loyalty. On Spotify, consider using the Q&A and Poll features each episode and mention them on air (“If you’re on Spotify, vote in the poll!”) to drive engagement there. Engaged viewers/listeners are more likely to become evangelists for your show, sharing it with others.
   • Experimentation and A/B Testing: Use insights to try new things in a controlled way. For example, if you suspect shorter episodes might improve retention without hurting watch time, test it: release a shorter-than-usual episode and compare its metrics to your average. Platforms like YouTube let you experiment with thumbnails and even the new Research tab to test interest in topics. Treat each episode as an opportunity to learn – if the experiment works (analytics improve), incorporate the change; if not, revert and try a different approach. This iterative improvement, guided by metrics, will gradually optimize your podcast.
   • Growth and Acquisition: Identify what metrics need the most improvement for growth and set goals. If you need more reach, focus on impressions, CTR, and new unique listeners/viewers. If reach is fine but conversion is low, focus on retention and followers/subscribers. Each metric can suggest a different strategy: e.g., to boost impressions on Spotify, consider collaborating with other podcasts for cross-promotion (more people see your show); to boost YouTube suggested views, perhaps create content around trending topics or optimize engagement so the algorithm recommends it. By acting on specific metrics, you make your growth strategy data-driven.
5. Iterate and Evolve: The digital landscape and audience preferences change, so continually iterate. What works today might plateau later. That’s why “advanced” creators keep an eye on trends in their analytics. Maybe you notice over a year that your YouTube audience is increasingly watching on TV devices (YouTube Analytics shows device types) – that might prompt you to ensure your visuals and text are readable on a big screen, or that you’re catering to a more laid-back living room audience. Or Spotify may roll out new analytics (for instance, new metrics or new markets data); be ready to incorporate those into your strategy. Schedule periodic deep-dives (say, quarterly) where you review overall channel/show performance: identify macro trends like “audience grew 50% in the 18-24 range” or “average watch time per viewer is up by 30 seconds compared to six months ago.” These help validate that your actions are yielding results. Ultimately, keep a feedback loop: Data -> Insight -> Action -> (repeat). Over time, this will significantly sharpen your content strategy and accelerate audience growth.

Mondo Metrics: Leveraging a Third-Party Analytics Tool

Native analytics from Spotify and YouTube are powerful, but they each live in their own silo. As a podcast creator distributing video content across multiple platforms, you might want a unified view of your show’s performance. This is where Mondo Metrics comes in. Mondo Metrics is a third-party analytics platform built specifically to consolidate and enhance podcast analytics across audio and video platforms. It offers capabilities beyond what native tools provide, helping you see the “big picture” and extract deeper insights.

What Mondo Metrics Offers (Beyond Native Tools):

• Cross-Platform Aggregation: Mondo Metrics pulls data from all your distribution channels – Spotify, YouTube, Apple Podcasts, and even social media platforms – into one dashboard (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). Instead of juggling multiple analytics interfaces, you get a single cohesive view of your podcast’s total reach and performance. For example, Mondo can aggregate podcast downloads/plays + YouTube views + social video views to show your Total Episode Impressions across platforms (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). This blended view means if an episode got 5k plays on Spotify and 15k views on YouTube, you see 20k total – valuable for understanding true audience size and for reporting to sponsors or stakeholders. As Mondo’s team puts it, “Mondo aggregates podcast performance across audio, video, short-form, web, and social, giving you a single view of your show’s true reach and ROI.” (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) This holistic approach acknowledges that a podcast today is a multi-platform media brand, not just an RSS download count.
• Unified Metrics & Comparative Insights: With data combined, Mondo Metrics can provide insights that native platforms alone can’t. For example, it can help answer questions like “Which platform delivers the most engagement for my podcast?” or “Do my YouTube viewers stick around longer than my Spotify listeners?”. By connecting the full ecosystem, you can directly compare performance metrics side by side. Mondo might show that a certain episode had a 60% average completion on YouTube vs. 40% on audio – prompting you to investigate differences in audience or content format. It also can calculate metrics like cumulative watch time across platforms or average listening/viewing time per user across platforms, which give a more complete measure of content consumption. Essentially, Mondo transforms fragmented metrics into actionable cross-platform insights (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics) (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics).
• Advanced Tagging and Content Analysis: Mondo Metrics offers sophisticated content analysis tools not available in the native analytics. One standout feature is its AI-powered content tagging (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). It can automatically tag and organize your content by themes, topics, guests, or custom criteria (using AI to, say, detect topics or keywords in your episodes) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). These tags let you analyze performance at a granular level. For instance, you could compare all episodes tagged “tech news” vs. “interviews” to see which category averages more watch time or engagement. Or tag by guest name and see which guest brought the most new viewers. Head-to-head comparisons become easy: Mondo allows you to instantly compare content groups or series (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics) – something that would be manual in native tools. For example, you might compare your first 10 episodes vs. your latest 10 to quantify growth, or compare performance of episodes in Season 1 vs. Season 2. This level of analysis helps pinpoint winning strategies (maybe episodes under a certain theme consistently outperform others – knowledge you can use to guide content planning) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics).
• Custom Metrics and Formulas: Unlike fixed native dashboards, Mondo lets you define custom metrics or KPIs that matter to you (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). Want to track an “engagement score” combining data from Spotify and YouTube (e.g., total comments + Q&A responses, or a weighted score of retention plus follower growth)? Mondo’s platform supports creating tailored formulas and metrics (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). This is extremely useful for advanced creators who have specific goals or unique success criteria. The platform’s flexibility means you aren’t limited to what Spotify or YouTube considers a metric – you can measure what matters for your podcast’s strategy (with help from Mondo’s team if needed to set up complex metrics) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics).
• Integrated Social & Web Analytics: Mondo doesn’t stop at Spotify and YouTube. It can integrate data from social media (Facebook, Instagram, TikTok, X/Twitter, etc.) and even website analytics if you host a site for your podcast (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). This is a big plus if you promote your podcast via social clips or have a web page with an embedded player. You can track, for example, how a TikTok clip of your podcast drove traffic or listens on other platforms, or see all comments/engagement across platforms in one place. By consolidating these, Mondo saves you the time of manually combining data and lets you see cross-platform effects (like whether a spike in Twitter activity correlates with a bump in Spotify streams). In short, it provides a 360-degree view of content performance across all channels (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics).
• Actionable Insights & Recommendations: While specific features may evolve, Mondo’s philosophy is not just to show data but to highlight what to do next (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). Their platform and consulting emphasize surfacing insights – e.g., identifying underperforming areas or growth opportunities – so you can take action. Mondo might highlight trends such as “Your YouTube audience is growing faster than audio – consider creating more video-centric content” or “Engagement on social clips is driving podcast listens – try posting more clips.” Some of this comes from their expertise and possibly AI-driven analysis. Essentially, Mondo acts as an analytics advisor, bridging the gap between raw data and strategic decisions, whereas native tools leave the interpretation largely up to you.

Setting Up and Integrating Mondo Metrics:

Getting started with Mondo Metrics involves a few steps to integrate all your accounts. Here’s a general overview of the setup and integration process:

• Sign Up / Demo: First, you’d sign up for Mondo Metrics (likely via their website and possibly scheduling a demo, as they cater to creators and networks). They will set up an account or dashboard for your podcast or organization. Since Mondo Metrics is a professional platform (with enterprise-level capabilities), you might be in contact with their team to tailor the setup to your needs.
• Connect Your Data Sources: Mondo will need access to the platforms you want to track. Typically, this means linking your Spotify for Podcasters account, YouTube channel, and any other platforms (Apple Podcasts, social media accounts, etc.) to Mondo. The process is usually OAuth or API-based: for example, you might log in via Spotify to authorize Mondo to fetch your analytics data, and similarly log in to Google/YouTube to authorize access to your channel analytics. Mondo Metrics emphasizes it can bring together data from Spotify, Apple Podcasts, YouTube, Facebook, Instagram, and more (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics), so you’ll likely go through each relevant platform and grant permissions. The integration is read-only for analytics – it just pulls stats, not altering anything on your accounts.
• Data Import and Verification: Once connected, Mondo will import your historical data (how far back may depend on APIs; YouTube’s API can provide historical stats, and Spotify’s can provide at least recent analytics). It may take a short time for all the data to populate into your Mondo dashboard. You’ll want to verify that your key metrics are showing up correctly (e.g., the latest episode’s plays on Spotify in Mondo match what you see on Spotify’s dashboard, etc.). The Mondo interface likely has a way to select which podcast or show you’re looking at (if you host multiple shows, it can handle network-level data too).
• Configure Tags and Groupings: To get the most out of Mondo, you may need to set up some initial configurations:
  • Define your content tags or categories. Mondo can auto-tag content using AI (by themes or series) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics), but you might also want to create custom tags or verify the automated ones. For example, tag episodes by season, format (remote vs in-person interviews), or topic categories. This will enable those powerful comparisons later.
  • If your show exists in both audio and video formats, ensure Mondo knows, for instance, that your Spotify episode X and YouTube episode X are the same episode. There may be an interface to link an audio episode with a YouTube video manually (if Mondo doesn’t auto-match by title or date). This way, it can truly aggregate per-episode performance across platforms.
  • Set up any custom KPIs you want to track. Mondo’s team can help if you want a specific metric (say, “social engagement rate” combining several inputs) displayed on your dashboard.
• Explore the Dashboard: Once configured, you’ll have a dashboard that might include visualizations like:
  • A timeline of total audience engagement across platforms.
  • Top episodes with combined viewership.
  • Demographic breakdown combining Spotify (for age/gender of Spotify listeners) and YouTube (for age/gender of YouTube viewers) to see your overall audience profile.
  • Audience overlap insights, such as how many of your YouTube viewers are also Spotify listeners (if determinable by patterns or surveys) – Mondo mentions understanding the overlap between podcast listeners and social followers (Podcast Analytics » Mondo Metrics) (Podcast Analytics » Mondo Metrics).
  • Multi-platform retention curves or funnel (how many people start on one platform vs continue on another, etc., if such tracking is possible).
  • Automated reports or alerts (e.g., an email report each week summarizing your stats).
• Automate Reporting: One of Mondo’s benefits is automating the laborious task of reporting. Instead of manually compiling screenshots from Spotify and YouTube, you can use Mondo to generate comprehensive reports. You might set up a weekly or monthly report that highlights key metrics across all platforms, which can be shared with your team or sponsors. This saves time and ensures consistency. Mondo specifically advertises the ability to “eliminate manual exports and combining sheets” by consolidating data in one place (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). Take advantage of this by scheduling routine reports and focusing your energy on analysis rather than data collection.

Best Practices for Using Mondo Metrics Effectively:

• Use Cross-Platform Insights for Strategy: With everything in one place, look for insights that weren’t visible before. For example, if Mondo shows that YouTube contributes 70% of your total audience and Spotify 25%, you might allocate more resources to YouTube production quality or exclusive YouTube content. Or if Spotify has smaller reach but much higher engagement per user, maybe focus on converting those engaged Spotify listeners into promoters for your show. The idea is to let the data guide how you prioritize platforms. Many creators are surprised to find, for instance, that their “podcast” is primarily viewed on YouTube – an insight that could lead them to invest in better video equipment or YouTube-specific SEO. Mondo’s unified reach metric prevents you from undervaluing a platform where you have lots of viewers just because another platform’s metrics loom larger individually (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics).
• Leverage Content Tagging to Refine Content Plans: Take advantage of Mondo’s tagging and comparison feature to really drill down into what works. For example, run a comparison of episodes by guest: you might discover interviews with entrepreneurs get 30% more combined watch time than interviews with academics. Or compare by topic: perhaps episodes about “AI technology” have skyrocketed in views in the last quarter across both platforms (indicating audience interest in that topic). These insights help you make data-backed decisions on upcoming content – e.g., schedule more episodes on high-performing topics or consider spinning off a popular segment into its own series. Also pay attention to formats: compare solo episodes vs guest episodes, or in-studio vs remote-recorded ones. If one format clearly outperforms in retention or engagement, you have evidence to do more of it. Mondo essentially allows A/B analysis after the fact on your content library, which is incredibly valuable for continuous improvement.
• Monitor the Audience Funnel: Much like Spotify’s discovery funnel (impressions → plays → followers), Mondo can reveal a broader funnel: how audience moves from platform to platform. For example, you might see a pattern where a viral YouTube clip led to an increase in Spotify listeners for the full episode. If you notice that when you post short video clips on Instagram or TikTok you subsequently get more YouTube views, that’s an important insight – it means your social content is effectively driving people to your long-form content (so you should continue and perhaps increase that effort). Mondo’s ability to correlate metrics across platforms can confirm whether your cross-promotion strategies are working. Use this to optimize your marketing: focus on channels that actually yield downstream listeners/viewers. As noted in the Mondo blog, creators often ask “Did short-form clips generate long-form lifts?” – Mondo can help answer that (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics).
• ROI and Sponsor Reporting: If you monetize through sponsors or ads, Mondo Metrics can greatly simplify demonstrating ROI. Instead of telling a sponsor “we got 10k downloads for your ad,” you can report “This episode reached 25k people across audio and video”. Since Mondo shows a blended impression model (audio + video + other) (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics), you can provide a more comprehensive account of an episode’s performance. Additionally, if you run campaigns (like a special promotion across multiple platforms), use Mondo to track the combined impact. Mondo also touts features like benchmarking against peers or industry averages (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) – if available to you, use those to see where you stand and to set realistic growth goals or demonstrate your podcast’s value versus others.
• Keep an Eye on Platform-Specific Nuances: While Mondo is great for the big picture, don’t completely abandon the native analytics. Mondo might not capture every nuance (for example, YouTube comments sentiment or the exact shape of a retention curve). Use Mondo to alert you to issues or wins (like “overall retention is down this month”) and then investigate within the native platform for detail (“ah, it’s because of that one video’s drop-offs”). Also, remember that each platform’s algorithm might value things differently – Mondo aggregates metrics, but you should still recall that, say, YouTube cares a lot about watch time and CTR, while Spotify might care more about followers and completion rate. Use Mondo’s insights hand-in-hand with platform-specific optimizations.
• Stay Consistent with Data Updates: Ensure your Mondo Metrics is regularly syncing with your latest data. Most likely it updates via API frequently (possibly daily). Still, when you release a new episode, verify that it appears in Mondo and that data is coming in. If something looks off (e.g., an episode missing or numbers not matching recent data), reach out to Mondo support – it could be an integration issue. Keeping the tool accurate is key to trusting your insights.
• Take Advantage of Mondo’s Expertise: Mondo Metrics is not just software; they position themselves as a consultancy as well (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). They even offer services like insights consulting and custom dashboard development (Video Podcast Analytics » Mondo Metrics). As an advanced creator, don’t hesitate to leverage this. For instance, if you want a specific analysis (like cohort analysis of listeners who migrate from YouTube to Spotify over time) that’s not straightforward, Mondo’s team might help create a custom report. Or they might help you interpret a puzzling trend with their industry experience. The platform is used by media companies and networks, so it’s built with high-level strategy in mind – use those advanced features and human expertise to inform your decisions.

By integrating Mondo Metrics into your toolkit, you essentially get a bird’s-eye view of your podcast’s performance that complements the ground-level details from native analytics. The combined knowledge can validate whether you’re truly growing overall, and where to focus next. Creators often find their “real reach” is larger than they thought once all platforms are accounted for (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics), which is encouraging and can push you to expand content in new ways.

Native Platform Analytics vs. Mondo Metrics (Comparison)

How do Spotify’s and YouTube’s native analytics stack up against a cross-platform tool like Mondo Metrics? Each has its strengths. Below is a comparison of features and considerations for Spotify Analytics, YouTube Analytics, and Mondo Metrics:

AspectSpotify for Podcasters (Native)YouTube Studio Analytics (Native)Mondo Metrics (Third-Party)Platform CoverageSpotify platform only (podcast audio & video on Spotify). Focused on listeners within Spotify’s ecosystem.YouTube platform only (all videos on your channel). Focused on YouTube viewers.Multiple platforms – Consolidates data from many sources (Spotify, YouTube, Apple Podcasts, social media, etc.) into one view (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). Provides cross-platform insights.Key Metrics AvailableStreams/plays, listeners, followers, retention chart, watch hours (video), impressions & conversion funnel, demographics (age, gender, location) (Audience stats - Spotify) (Video analytics - Spotify). Metrics are tailored to podcast consumption (e.g., starts vs. streams).Views, watch time, avg view duration, audience retention graph, impressions & CTR, likes/comments/shares, subscriber gain, traffic sources, demographics (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) (YouTube Analytics: The 15 Metrics That Actually Matter ). Very granular video engagement data (e.g., per-second retention, card clicks).Unified metrics (e.g., total audience reach = audio plays + video views) and custom KPIs. Provides metrics like combined impressions, cross-platform retention, engagement across platforms. Allows custom formulas (not limited to preset metrics) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). Loses some platform-specific granularity but adds holistic measures.Data Depth & InsightsGood depth for Spotify listening behavior: e.g., retention curve, median listen time, how listeners discovered your show (Audience retention - Spotify) (Understanding audience discovery metrics on Spotify - Spotify). Lacks visibility outside Spotify (won’t show if those listeners also watched on YouTube, for example).Excellent depth for YouTube viewing behavior: minute-by-minute engagement, relative retention, click-through rates, etc. Also provides comparative tools (e.g., compare to channel averages). But only covers YouTube – no info on audio platforms.High-level insights across the board. Great for seeing trends and performance at the show level. Can identify patterns that single-platform analytics miss (e.g., “Your YouTube audience watches longer than Spotify audience” or “Total impressions doubled due to multi-platform release”). Might not show per-second detail for each platform, but can highlight where to look. Emphasis on actionable insights (often guided by built-in intelligence) rather than raw data overload (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics).Ease of Use & InterfaceVery user-friendly, simple dashboard. Designed for quick overview (plays, audience, retention) without much customization. Limited to Spotify data means it’s straightforward.Robust interface with multiple tabs (Overview, Reach, Engagement, Audience, etc.). Lots of charts and the ability to dive deep or use advanced mode. Steeper learning curve due to many features, but well-documented.Centralized dashboard can save time (one login for all data). Initial setup is more involved (connecting accounts, configuring tags). Interface is powerful but might require some training or support to fully utilize advanced features. Once set up, it simplifies reporting (no need to manually merge data) (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics).Real-Time & Update FrequencySpotify for Podcasters updates analytics daily (and some metrics near-real-time for recent episodes). Not real-time for every play, but you get fresh data within 24-48 hours typically.YouTube offers real-time view counts for first 1–2 days and updates most metrics within 48 hours. Very timely insights (plus historic data anytime).Mondo’s data currency depends on source APIs – usually updates within a day of the source. It may not have real-time per-minute updates like YouTube’s interface, but for strategic analysis the slight delay isn’t an issue. Mondo can be configured to fetch data periodically.Unique FeaturesSpotify-specific insights like the discovery funnel (Impressions → Starts → Streams) (Understanding audience discovery metrics on Spotify - Spotify) (Understanding audience discovery metrics on Spotify - Spotify), which is unique to Spotify’s closed platform (helps gauge in-app promotion effectiveness). Also Spotify provides listener demographics drawn from user accounts (age, gender) which some other audio platforms lack.Unique to YouTube: metrics like relative retention (benchmarking your video’s retention vs others), YouTube search terms (what keywords led viewers to you) (YouTube Analytics: The 15 Metrics That Actually Matter ), and detailed engagement stats (e.g., how many clicked info cards or end screens). Also, YouTube’s suggestion and algorithm metrics (impressions, CTR) are platform-specific insights on content discovery.Mondo’s unique value is in comparisons and aggregations: e.g., compare performance by content type or guest across all platforms in one chart (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). It also offers AI tagging to categorize content automatically (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics), and potentially benchmarks across industry if available. Essentially, Mondo’s uniqueness is treating your podcast like a cross-platform content brand, with tools to measure efficiency and ROI at that macro level.CustomizationVery limited customization. You see the metrics Spotify provides; you cannot add new ones or deeply filter (beyond date range and episode selection). Reporting is mostly on-platform (export CSV for custom analysis if needed).Some customization: you can filter by content, compare views for different videos, choose date ranges, etc. In Advanced Mode, you can build custom reports or see specific combinations (e.g., views by country by video). But you cannot add metrics outside what YouTube tracks.Highly customizable. You can define custom dashboards, combine metrics from different platforms, and even create new metrics or ratios tailored to your goals (Mondo Metrics - Social, Podcast, Video, Web/Mobile Analytics). You also get support from Mondo’s team to create custom solutions or dashboards (Video Podcast Analytics » Mondo Metrics). This flexibility is a big advantage if you have specific KPIs (like “engagement score” or “audience overlap”) that native tools don’t directly provide.CostFree (Spotify’s analytics come with hosting on Spotify or even if your podcast is just listed on Spotify). There’s no additional cost to use Spotify for Podcasters analytics.Free (YouTube Analytics is available to all YouTube creators). All you need is a YouTube channel; analytics are provided regardless of channel size (though some data might require a minimum amount of views for accuracy, especially demographic data).Paid (Mondo Metrics is a third-party service likely with subscription or licensing fees – oriented toward creators, networks, or enterprises willing to invest in advanced analytics). The cost could be a consideration for independent creators, but it may be justified if the insights lead to growth or if you need pro reporting. Mondo often works via demos and contracts, suggesting a custom pricing model depending on your needs.When to UseUse Spotify’s native analytics for a deep dive into audio/video consumption on Spotify: great for understanding how Spotify listeners behave, tracking followers, and evaluating anything Spotify-specific (like the effect of being on a Spotify chart, or responses to Spotify episode polls). It’s your go-to for day-to-day monitoring of your Spotify audience.Use YouTube Analytics for managing and growing your YouTube presence: it’s indispensable for optimizing videos (thumbnails, retention, etc.), as YouTube’s algorithm heavily depends on these metrics. It’s also the best source for community engagement metrics (comments, likes) and understanding YouTube-specific traffic patterns. In short, for any video-level tweaks and channel growth on YouTube, rely on YouTube’s native analytics.Use Mondo Metrics when you need a holistic, strategic view of your podcast across all platforms. It’s ideal for intermediate/advanced creators who have a presence on multiple platforms and possibly multiple content formats. If you find yourself manually cobbling together data from different sources to see the full picture, that’s a strong signal you’d benefit from Mondo. It’s also great for reporting to others (network executives, sponsors) since it provides a clear summary of multi-platform performance. Think of native analytics as zoomed-in lenses for each platform, and Mondo as the wide-angle lens that captures everything in one shot.

Pros and Cons Summary: Native analytics are free and granular – you should absolutely use them to refine content on their respective platforms. Spotify and YouTube will give you the nuts-and-bolts details and real-time feedback needed to execute tactics (like improving a title or adjusting content length). However, they operate in isolation. Mondo Metrics, while coming at a monetary cost and requiring setup, serves as a strategic integration tool – its strength is in aggregating and comparing data to inform high-level strategy and save you time on analysis. A con of Mondo is that it’s only as good as the data sources; you sometimes lose platform-specific nuances and you have to trust a third party with your data (though Mondo is an established provider). But the major advantage is seeing the forest rather than just the trees. For a growing podcast that already has traction on multiple platforms, using Mondo in conjunction with native analytics can provide the best of both worlds – detailed operational metrics and broad strategic insights.

Conclusion

In the world of video podcasts, success comes from both art and science – creating compelling content and rigorously analyzing how that content performs. As an intermediate or advanced podcast creator, you now have a wealth of analytics tools at your disposal. Spotify for Podcasters analytics help you understand your audio and video audience on Spotify: track streams, retention, and follower growth to ensure you’re keeping listeners engaged and steadily growing your base. YouTube Studio analytics offers an unparalleled view into viewer behavior on your videos: use it to fine-tune your titles, thumbnails, and content structure, capitalizing on metrics like watch time and CTR that drive YouTube’s recommendations. The key performance indicators – watch time, retention, click-through rate, subscriber growth, engagement, traffic sources, and demographics – each tell you something vital about your podcast’s health. By measuring and improving these, you set the stage for organic growth.

Equally important is the ability to connect the dots across platforms. That’s where a tool like Mondo Metrics becomes invaluable. It elevates your perspective from platform-specific details to an integrated overview, answering big-picture questions and saving you from fragmented analysis (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics). With Mondo, you can confidently say “This is how my show is performing overall, and here’s where to focus next.” (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics) It complements the native analytics by highlighting things you might otherwise miss – for instance, that your “small” YouTube channel plus your Spotify listens actually make a much larger total audience than you realized (The Problem with Podcast Analytics Today: Bridging the Divide Between Audio and YouTube Data » Mondo Metrics), or that a format tweak improved engagement across all channels, not just one.

As you absorb and apply all these analytics insights, keep your content vision at the forefront. Metrics are guides, not goals in themselves. They inform you if your message is landing with your audience and how you might sharpen it. Use them to iterate: experiment with informed confidence, since you’ll be able to see the results in the data. Over time, this cycle of creation and optimization will help you grow not just your numbers, but the impact and quality of your podcast.

In summary, embrace a data-informed mindset: dive into Spotify and YouTube analytics for actionable tactics, leverage Mondo Metrics for strategy and aggregation, and always loop back to adjust your content and distribution. With this comprehensive approach, you’ll be equipped to improve your content strategy and expand your podcast audience in a sustainable, intelligent way – turning analytics into a roadmap for continual growth and success in the video podcasting arena.