Automation isn't free, even when it's fast. Every task in your workflow pays back a different amount of time, and most teams pick the wrong ones first. The Content Automation ROI Ranker ranks your list by the return, using your own numbers.
Think of these numbers as a starting point, not a description of your team.
Pick the closest match, adjust what's off, or leave it as is. The ranking works either way.
Blended cost across everyone who touches this work. Drag the slider or type your own number. This turns hours into a figure your finance team recognizes, and it never leaves your browser.
This sets how much of each task's time counts as automatable, in every calculation on this page. Conservative counts less, Ambitious counts more. Switch anytime and watch the ranking move with it.
These are planning estimates, built from what this work actually takes in practice, not from a published study and not from measurements of your team. Tasks that share a system also share their saving: transcription, captions and soundbite selection all come off the same transcript, and the total counts each of them in full, so read it as a ceiling. Go back and adjust anything until it looks like your month. It's the order that matters, and that holds even when the numbers move.
This page ranks your automation candidates on return alone. It doesn't ask whether your team, your tools, and your approval chain can actually land them. That's what decides if the hours ever show up. Same three minutes, different question.
See if you're set up for itThe ranking is by task, never by vendor. Tools change every quarter. Your workflow's shape doesn't.
Every task here keeps a person in it. Automatic captions still need someone who cares about line breaks. The hours move from the mechanical part to the part only your team can do.
Hours reclaimed decide the ranking here. It doesn't know if a task is easy to approve or a fight to get through. The one at the top might not be the one you start with.
It's a range because return depends on difficulty, not length: a clean interview and a noisy roundtable score differently. Acting on it is scored separately, in the scorecard.
Automate whichever task costs the most hours a month that a machine can handle. It's rarely the task that feels most annoying: usually transcription, captions, logging, or asset hunting.
Multiply how often the task happens by how long it takes by the share automation can absorb, and that's the hours it gives back each month. Run those hours through the rate you set above to turn them into possible savings.
A busy team saves thirty to fifty hours a month once transcription, captions, logging, and search are automated: twenty small, ninety high-volume. Use your numbers, not an average.
Frequency usually wins. Twenty minutes done forty times a month adds up to thirteen hours, more than most big tasks take, which are usually full of judgment calls anyway.
The easiest tasks have a right answer you can check in seconds: transcription, caption timing, naming, versioning, and audio leveling. Judgment calls are the hard ones to automate.
Automating this work doesn't cut the team. It moves the month off mechanical work and onto what kept slipping. What you do with those hours is a leadership decision, not a software one.
AI still can't decide what the piece is about, or catch the moment someone says the truest thing by accident. It struggles with messy audio, so review time never drops to zero.

I'm Gustavo Fonseca, Senior Content Lead and post-production strategist in Vancouver, Canada. I came up through design, then broadcast, video and post, and somewhere in there the edit and the strategy merged into one job. I still edit full time, and I design the operation around it too: the workflows, the delivery specs, the handoffs that decide whether work ships on time or ships twice. The plan gets made by someone who still lives it every day.
I studied Cinema at UFSCar and did a postgraduate in Strategic Business Management at Mackenzie, both in Brazil, then Digital Marketing Strategy at Harvard Business School and AI Product Management at UBC. More at thegusta.com.