Tag: The Photography Channel

  • Social Media Monthly Report – October 2025

    Social Media Monthly Report – October 2025

    In September, I spent 34 hours and released nothing. October increased to 41 hours and produced a single episode — progress, but not momentum.

    This is the third Social Media Monthly Report — part of an ongoing effort to show what it takes to build a creative media business from the ground up. The goal isn’t performance; it’s documentation. What works, what doesn’t, and how much time disappears between the two.


    October was a slow grind back toward momentum — progress measured mostly in wasted hours.

    Executive Summary

    October’s target was straightforward:

    • Publish 4 videos.
    • Invest ~40 hours, with post-production under 50%. 

    The aim was to hold a steady output before adding specific targets for views, watch time, or subscribers. Instead, I tried to rebuild the lost momentum from the previous month with limited results. Being away from the camera for so long resulted in wasted production efforts. Some shoots were too poor to use, leading to repeated work that could have been avoided if I weren’t so rusty. Inconsistency remains the major factor plaguing the channel.

    Here is the month in numbers.

    Key Metrics


    SEPOCTChange
    Impressions2,3538,547+6,194
    Views138448+410
    Click-through Rate (CTR)3.8%3.6%-0.2 pp
    Total Watch Time (Hours)7.426.6+19.2
    Subscribers175182+7

    A single upload this month, compared to none last month, naturally increased impressions — no surprise there. Views and watch hours remain low, and CTR held steady; the problem is still output, not packaging. 

    Production Breakdown


    SEP (Hours)SEP (%)OCT (Hours)OCT (%)
    Pre-Production13.0039%8.0020%
    Production3.009%12.5030%
    Post-Production7.2521%10.7526%
    Publishing00%0.251%
    Marketing4.6714%1.504%
    Other5.7517%8.0020%
    Total33.67100%41.00100%

    Of the 41 hours, 20% went into production—mostly shooting and reshooting the same two episodes. One episode was successfully released and the second is in the final stages of post-production — with ~4 hours of work needed for release. Video editing accounted for about 10% of the time; the drop in post-production hours happened because the second video is still not finished, not because editing got faster.

    The failed production sessions caused frustration, broke momentum, and led to mundane admin work that didn’t move the channel. Given that pattern, here’s what has to change.

    After-Action Notes

    Continuing to claw back momentum remains the priority. The main bottleneck is spillage—production waste, the time invested that never turns into a finished episode. Every input hour must move something forward. With a one-man schedule, there’s little margin for inefficiency; progress depends on focus, not volume.

    Next Month (November 2025)

    The goals are simple:

    • Publish 4 videos.
    • Invest ~40 hours, with post-production under 50%.
    • Minimal waste: Under 5% of time invested in other tasks. Zero spillage in production hours.

    The aim is still to hold this output steady for the next six months before adding specific targets for views, watch time, or subscribers. The key is consistency and regaining momentum.

    Closing

    This is the cost of doing the work — measured in hours, not hype. October was about regaining motion through waste; November is about keeping motion while cutting the waste down. One month, one set of numbers, one small step towards consistent rhythm.

    For those who prefer the full data in one go, I’ve pulled the charts into a short deck. The “boardroom version” of this report — 45 seconds, numbers only.

    This is the third in a monthly series. The next Social Media Monthly Report will follow in December (after month-end). If you want to keep track of how the numbers move, subscribe.

  • 279,339 Impressions, 151 Views — The Anatomy of an Algorithmic Misfire

    Video #21 was just another weekly video in my YouTube photography channel. Within a few days I watched in disbelief as the number of impressions reached 279,339. The algorithm was pushing my videos! My disbelief quickly turned to dismay as the click-through-rate hovered around 0%. 109 views from almost 280,000 impressions! The algorithm must be broken.

    The Spike That Made No Sense

    It made no sense. A single video, similar in structure to the 20 preceding it, yet 279,339 impression out of 290,369 impression for the entire channel. 280,000 views that drove a little over 100 views to the channel.

    I was trying to remain calm. I uploaded 20 videos, some got less than 10 views, my subscriber base hovered at 6 for months. The algorithm finally pays attention to my work and all I get is 100 views? 

    My anger quickly turned to curiosity. Something doesn’t add up. This has to be some kind of algorithmic misfire. Something is not aligned properly under the hood. Either my content is unbelievably bad (a possibility) or YouTube’s engine is sending my video to the wrong audience. 

    Time to pop the hood and take a closer look.

    Under the Bonnet

    Time to inspect everything carefully and meticulously. A full diagnosis. Even though the channel was small and new there should be enough data to provide some clear insights. 

    Here are the full stats from YouTube’s analytics; everything visible under the hood:

    Impressions279,339
    Total Views151
    Views from Impressions109
    CTR0.05%
    Average View Duration0:42
    Average Percentage Viewed30.1%

    The numbers are quite clear: massive exposure with zero conversion. The video was heavily surfaced, the algorithm was obviously targeting the wrong audience — no clicks. Let’s check out the traffic sources.

    Suggested videos51%
    YouTube Search29.8%
    Channel pages6.0%
    Other YouTube features4.6%
    Direct or unknown3.3%
    Others5.3%

    Over half of impressions came from suggested videos and not from the home feed. This probably means that the algorithm clustered my video with similar videos based on thumbnail, titles, or other reason and somehow got it wrong. Let’s dig deeper into other audience signals.

    Top geographiesNot enough data
    Age DistributionNot enough data
    Gender DistributionNot enough data
    New vs Returning viewersNot enough data
    Subscribed vs non-subscribed viewers88.7% Subscribed

    No luck. This is a new channel with very little views. There is simply not enough data. The fact that 88.7% of watch time was from subscribers reinforces what we already know but adds nothing new.

    Computer50.9%
    Mobile Phone25.2%
    TV16.4%
    Tablet7.5%

    No much information added from device type either. Let’s look at viewer engagement next.

    Viewer Retention (30 Seconds)42%
    Viewer Retention (60 Seconds)25%
    Viewer Retention (90 Seconds)23%
    Viewer Retention (120 Seconds)17%
    Viewer Retention (End of video)5%

    Viewer engagement is not stellar but it is inline with other videos. 3.5% end screen element clicks (4.4% channel average), 10 comments, 7 likes, and 0 dislikes. An underperforming video but still no explanation for the algorithmic misfire (nobody clicked).

    Last check. Let’s look at the top referring videos.

    The Wrong Crowd


    ImpressionsCTRViewsAVD
    Chill Time Jazz Haven Pt 3538,0370%120:24
    Jazz for Life Pt 2032,0640%10:19
    Funny Jazz Pt 1219,0290%10:05
    Chill Jazz Time Pt 234,7040%

    I think we found the problem. For some reason the algorithm thinks my photography videos look identical to chill-jazz and city-ambience videos.

    I looked at the videos, and to be honest, I could understand why a machine would make that mistake. The soundtracks were almost identical, the mood and ambience were similar. So were the pacing and the visuals. My choice of category: “Travel & Events” did not help things either. 

    Most human viewers saw the absurdity immediately; but the algorithm saw only patterns and a shared visual tone. The machine didn’t misunderstand me (or the 280,000 viewers that were recommended my video). It recognized me — just as something I wasn’t.

    Mixed Signals

    The easy conclusion is the algorithm failed. Which in many ways it did. But the signals I was sending the machine were unclear. It was a Signal to Noise ratio problem: there was not enough clear signaling on my end and the machine simply mirrored the noise.

    The algorithm was hitting the target I painted but not the target I wanted.

    I needed to improve my thumbnails, fine tune my titles, I need to communicate better with my viewers. The algorithm is not broken — I need to do better. 

    Signal Over Noise

    What I did right (Signal)

    • Title: Direct, keyword-rich, and accurately describes subject, activity, and gear.
    • Tags were all relevant and accurate. I avoided spam tags or irrelevant terms, which kept metadata clean and credible.
    • Accurate geographic tagging. Mentioned specific district and city.
    • Thumbnail Likely clean, photographic, not clickbait. Aligns with brand tone and audience expectation.
    • Early data suggests honest audience behavior
    • 88.7% of watch time from subscribers → engagement remains loyal. Retention (42% after 30s, 17% at 2m) within normal limits for short, quiet videos.

    What I did Wrong (Noise)

    • Chose the Wrong Category Set to Travel & Events. This category associates with city walks, ambience, and travel vlogs — not documentary street photography. Result: the algorithm pushed it to passive “background viewing” audiences instead of creator-interest clusters.
    • Over-repetitive Title Format. A repeated title structure made different videos appear algorithmically identical. Machine-learning models read this as a series clone, reducing semantic distinction and triggering similarity-based recommendations. Category and Title Reinforced Each Other
    • Thumbnail Too Neutral. Likely mirrored prior uploads — muted color, calm street composition. Visual similarity can further confirm “duplicate content” signals across uploads.
    • No Early Disambiguation in Description The copy doesn’t tell the viewer what type of video it is until the third line. Without a strong first-sentence keyword the algorithm groups it generically.
    • Tags Under-specified for Creative Intent. Location tags reinforce the travel angle. Mix in intent-level tags.
  • Social Media Monthly Report – September 2025

    Social Media Monthly Report – September 2025

    August took ~35 hours to produce two episodes of The Photography Channel. September took ~34 hours and produced none. Zero releases this month. 

    This is the second in a series of Social Media Monthly Reports. Each month, I’ll share numbers, hours, and notes that show what it actually takes to build a creative media business. Even if it means revealing the ugly truth.

    Executive Summary

    September’s target was straightforward:

    • Publish 4 videos.
    • Invest ~60 hours, with post-production under 50%.
    • Streamline editing to save time.
    • Track the same KPIs as August for month-over-month comparison.

    The aim was to hold a steady output before adding specific targets for views, watch time, or subscribers. Instead, I tried to recreate outliers, chased perfection, and ended up with nothing: target hours were not met, zero videos were released, and inconsistency remains the major factor plaguing the channel.

    Here is the month in numbers.

    Key Metrics


    AUGSEPChange
    Impressions79702353-5570
    Views461138-323
    Click-through Rate (CTR)4%3.8%-0.2 pp
    Total Watch Time (Hours)20.97.4-13.5
    Subscribers174175+1

    No uploads meant fewer impressions, fewer views, and a sharp drop in watch time. CTR held steady; the problem was output, not packaging. 

    This is what a zero-release month yields.

    Production Breakdown


    AUG (Hours)AUG (%)SEP (Hours)SEP (%)
    Pre-Production9.2527%13.0039%
    Production3.4210%3.009%
    Post-Production18.0852%7.2521%
    Publishing0.501%00%
    Marketing00%4.6714%
    Other3.5010%5.7517%
    Total34.75100%33.67100%

    Out of 33.67 hours, 39% went into pre-production: planning and ideation loops. Video editing accounted for about 20% of the time; the drop in post-production hours happened because nothing was finalized, not because editing got faster. Publishing was zero.

    Second-order effects followed. Trying to recreate a prior outlier pushed more scripting and “one more pass” in the edit; two videos’ worth of footage ended up in the recycle bin. With no releases, momentum broke and hours drifted into mundane admin work that didn’t move the channel. Given that pattern, here’s what has to change.

    After-Action Notes

    With momentum, inertia works in your favor and production runs efficiently. Break it, and you pay dearly — clawing back to where you were takes extreme effort. 

    In an earlier post, I wrote about the mistake of chasing outliers. That’s where I slipped this month. 

    The correction is simple: protect the weekly release schedule, and accept imperfections in the cut so videos actually get released.

    Next Month (OCT 2025)

    The goals are simple:

    • Publish 4 videos.
    • Invest ~40 hours, with post-production under 50%.

    The aim is to hold this output steady for the next six months before adding specific targets for views, watch time, or subscribers. The key is consistency and building momentum.

    Closing

    This is the cost of doing the work — measured in hours, not hype. If you’re building your own machine, start by tracking your inputs.

    For those who prefer the full data in one go, I’ve pulled the charts into a short deck. The “boardroom version” of this report — 45 seconds, numbers only.

    This is the second in a monthly series. The next Social Media Monthly Report will follow in November. If you want to keep track of how the numbers move, subscribe.

  • Social Media Monthly Report – August 2025: How Long It Really Takes to Make YouTube Videos

    Social Media Monthly Report – August 2025: How Long It Really Takes to Make YouTube Videos

    August took ~35 hours to produce two episodes of The Photography Channel. More than half of that time disappeared into post-production. On average, each finished minute of video required about two hours of work. That’s the multiplier — the real cost of running a YouTube channel.

    This is the first in a series of Social Media Monthly Reports. Each month, I’ll share numbers, hours, and notes that show what it actually takes to build a creative media business.

    Executive Summary

    Two videos went live this month out of a target of four. In total, I spent 34.75 hours on the channel. Views came in at 461, a slight dip of 6% compared to July; watch time rose by 25% to 20.9 hours. Subscribers grew to 174, up 12 from last month.

    This month I fell short of the four-video target — not because of lack of ideas or problems in production; time slipped away in the edit, and I didn’t maintain the schedule.

    Production Breakdown


    HoursPercent
    Pre-Production9.2527%
    Production3.4210%
    Post-Production18.0852%
    Publishing0.501%
    Marketing00%
    Other3.5010%
    Total34.75100%

    The plan for August was four videos; only two were completed. July delivered four videos after a long gap since February, so inconsistency remains a factor.

    Out of 34.75 hours, 52% went into post-production, with video editing alone accounting for 37% of all time spent. Pre-production (ideas and scripts) continues to take a significant share, while production itself is lean and efficient. Admin and other tasks made up around 10%.

    Key Metrics



    Change
    Impressions7970-23%
    Views4616%
    Click-through Rate (CTR)4%
    Total Watch Time (Hours)20.925%
    Subscribers17412
    Total34.75100%

    The numbers are modest, but they’re honest. After a long break from YouTube and an uneven month, they set a baseline for what a small channel produces under strain.

    Next Month (SEP 2025)

    The goals are clear:

    • Publish 4 videos.
    • Invest ~60 hours, with post-production under 50%.
    • Streamline editing to save time.
    • Track the same KPIs as August for month-over-month comparison.

    The aim is to hold this output steady for the next six months before adding specific targets for views, watch time, or subscribers.

    Closing

    This is the cost of doing the work — measured in hours, not hype. If you’re building your own machine, start by tracking your inputs.

    For those who prefer the full data in one go, I’ve pulled the charts into a short deck. The “boardroom version” of this report — 45 seconds, numbers only.

    This is the first in a monthly series. The next Social Media Monthly Report will follow in October. If you want to keep track of how the numbers move, subscribe.