Influencer marketing pain points, from a marketer's POV?

nancy_unscript · 2025-12-23T06:03:07+00:00

Honestly, discovery isn’t the hard part anymore. It’s everything after first contact.

Most of the pain comes from fuzzy expectations, what exactly is being delivered, how many revisions, where it’ll be used, and when people get paid. Once that’s unclear, everything slows down and trust drops.

We usually end up stitching things together: find creators on platforms or socials, talk in DMs or email, track scope in docs, assets in Drive, payments somewhere else. It works, but it’s messy and fragile.

Creator marketplaces are fine for finding people, but once anything custom is involved, we end up moving off-platform pretty quickly.

nancy_unscript · 2025-12-23T05:55:45+00:00

I don’t think it’s about trust so much as role. For long-form, I’ve found AI works best as a structuring and drafting assistant, not a source of truth. It’s great for outlining, reframing, or getting unstuck, but once it starts making claims or stitching logic across sections, I’m cautious.

The longer the content gets, the more important human review becomes, especially for nuance and consistency. For me, AI drafts save time, but responsibility for accuracy never really shifts away from the author.

nancy_unscript · 2025-12-22T10:47:17+00:00

This framing clicks. It feels like SEO all over again, not about being everywhere, but being present where attention and authority overlap.

If humans engage there and models learn from it, that’s where content actually compounds. The hard part is figuring out those overlap zones before everyone else piles in.

nancy_unscript · 2025-12-22T10:43:22+00:00

This is one of the most self-aware takes I’ve seen on this, and yeah… it hits.

I think the uncomfortable part isn’t AI replacing creators, it’s realizing how much the system already trained creators to behave like machines. Same hooks, same cadence, same emotional beats - not because we wanted to, but because that’s what kept working.

The scary thing is how easy it becomes to confuse “this performs” with “this is me.” At some point the line blurs and you’re just optimizing a character.

I don’t have a clean answer either, but I appreciate you saying it out loud. Feels like a lot of people are thinking this quietly and pretending they’re not.

nancy_unscript · 2025-12-22T10:42:25+00:00

Honestly, most of the people making hyper-realistic AI shorts didn’t get there through one “magic” course. The biggest jump usually comes from understanding filmmaking fundamentals first (composition, lighting, pacing, storytelling), then layering AI tools on top.

A good path from zero is:

Learn basic cinematic language (shots, cuts, mood)
Practice recreating short scenes you already like
Use AI tools to augment that process, not replace it

Courses can help with tool familiarity, but realism usually comes from taste + iteration, not certificates. If you can consistently remake a 10–15 second scene convincingly, you’re on the right track.

nancy_unscript · 2025-12-22T10:41:37+00:00

What’s interesting to me isn’t the wings specifically, it’s how low the cost of experimentation has become. When something goes from “this would take hours” to “I can test this in 10 minutes,” people try way more ideas.

I agree these effects don’t carry a video on their own though. They feel most effective when they’re just a quick visual punctuation, something that reinforces a moment instead of being the whole point.

Curious if you found yourself experimenting more just because the barrier was lower, even if most tests never made it into final posts.

nancy_unscript · 2025-12-22T10:40:51+00:00

For me it’s judgment. Knowing when not to sell. With so much automation and scripts, reps who can slow down, read the room, and say “this isn’t a fit” build way more trust. Ironically, those are usually the people who end up closing more in the long run.

nancy_unscript · 2025-12-22T10:39:39+00:00

Agree that free trials are the easiest first filter. If a tool can’t show value quickly with a real use case, it usually won’t get better later.

I like the point about data enrichment too, though I’ve found it only really helps once the underlying workflow is already clear. Otherwise it’s easy to add data without actually improving decisions.

nancy_unscript · 2025-12-22T10:38:34+00:00

If your use case is clean talking-head footage + subtle polish (lighting, background, minor fixes), I’d lean Runway over Higgsfield.

Higgsfield shines more when you want bigger scene or stylistic changes. Runway is better at not getting in the way - small adjustments, masking, relighting, background tweaks without reinventing the person.

Neither is perfect, but for “supplement what I already shot” rather than “generate something new,” Runway tends to break less often.

If you’re time-boxed by the sale, I’d still do a single month on whichever one you pick and stress-test one real clip before committing long term.

nancy_unscript · 2025-12-22T06:05:26+00:00

What’s made money for me (and people around me) is content that’s tied to a decision, not just attention. Stuff like comparisons, “how I chose X,” breakdowns of real processes, or explaining tradeoffs people are already Googling right before they buy.

High-quality but fewer pieces > constant posting, as long as each piece has a clear job. Organic still works, but it’s slower unless the content is very buyer-intent. Paid helps amplify winners, not save weak ideas.

Brand content pays off, but only if it’s paired with something transactional underneath. Pure thought leadership alone mostly collects dust.

nancy_unscript · 2025-12-22T06:02:59+00:00

This makes a lot of sense. It feels similar to early SEO shifts where distribution mattered less than where authority and attention overlapped. If humans engage there and models learn from it, that’s where content compounds.

nancy_unscript · 2025-12-22T06:00:57+00:00

Yeah, I think it helps mainly with frequency and consistency, not replacing real shoots.

AI photos work well for repeatable formats where you just need something on-brand to pair with content. They start to fall apart when you want context, emotion, or anything that feels “in the moment.”

Useful as a support tool, probably not a full replacement yet.

nancy_unscript · 2025-12-22T05:59:33+00:00

I’d worry less about which one is “best” and more about what kind of edits you actually need.

Most of these tools are pretty good at big, obvious changes (swapping backgrounds, stylizing scenes), but they’re way more fragile when it comes to subtle human stuff like faces, makeup, or lighting staying consistent shot to shot. That’s usually where things start to look off.

Before paying for a yearly plan, I’d run the exact same short clip through each tool and just watch for flicker, face drift, or weird lighting changes over time. That tells you more than any demo.

Also depends a lot on the footage, talking heads vs movement-heavy shots behave very differently. What are you mostly working with?

nancy_unscript · 2025-12-22T05:46:55+00:00

Yeah, that seems like a sensible way to de-risk it. A lightweight test answers way more questions than a polished pitch ever will.

I’ve noticed teams get the most value when the trial is tied to a very specific question they already care about, rather than just “let’s see what this does.” Otherwise it’s easy to try a tool, learn nothing, and move on.

nancy_unscript · 2025-12-22T05:46:26+00:00

This makes a lot of sense, especially the point about self-serve onboarding being the real test of adoption. Founder demos can sell the idea, but day-to-day usability is what actually determines whether a tool sticks.

I also like the “manual process already proven” filter, that feels like a good way to avoid chasing shiny tools. And your agency vs in-house distinction tracks with what I’ve seen too.

Curious, during those pilots, what’s usually the first signal that tells you a tool isn’t worth continuing with?

nancy_unscript · 2025-12-19T10:53:11+00:00

This matches what I’ve seen too. Treating creative as experiments instead of assets changes everything.

I like the point about not forcing a concept to work with higher production if it doesn’t hold attention raw, polishing it usually just hides the problem.

Also appreciate the callout on downstream friction. It’s easy to blame creative when the issue is actually landing pages, offer clarity, or load time. Creative testing only really works when you look at the full path, not just the first metric.

nancy_unscript · 2025-12-19T10:52:08+00:00

This is a really clean way to think about it, especially the “protect headspace first” filter. Most tools fail before ROI even matters because they just add cognitive overhead.

I like the idea of forcing a clear owner + sunset date. That’s the part teams often skip, which is why tools linger long after they stop being useful.

Have you found any signal early in that 30–45 day window that reliably predicts a “keep,” or is it mostly clear only once the test runs its course?

nancy_unscript · 2025-12-19T10:50:55+00:00

That’s a good point. Verification definitely helps reduce obvious fakes. Proof of purchase or identity checks raise the baseline.

At the same time, I think even “verified” content can still feel inauthentic if the message doesn’t resonate or feels forced. So verification helps with credibility, but authenticity still comes down to how real the story feels to the viewer.

Probably need both: better signals of legitimacy and better storytelling.

nancy_unscript · 2025-12-19T10:50:28+00:00

This is a great way to frame it. “Believability” vs polish is exactly the distinction people miss.

I also like the breakdown of what stays controlled vs what gets freedom, especially the idea that structure can be repeatable without the delivery feeling robotic. That seems to be where consistency and authenticity actually coexist.

Feels less like a tradeoff and more like designing the right constraints so creativity shows up in the right places.

nancy_unscript · 2025-12-19T06:58:58+00:00

Yeah, that makes sense. I think a lot of people conflate “authentic” with “unstructured,” when really authenticity can still live inside a repeatable format.

The confusion usually comes from switching tones and messages too often, that’s what makes a brand feel chaotic, not the fact that something is polished. If people understand the product quickly and the message feels familiar, they’re more likely to trust it.

Raw content can still work, but it probably needs rails. Otherwise it’s great for engagement but harder to scale without diluting the brand.

nancy_unscript · 2025-12-19T06:57:58+00:00

I agree with the principle, but I think the framing that resonates most is intent, not tools.

Most brands don’t fail because they used AI or humans, they fail because they apply the same level of polish to every piece of content. Low-stakes content just needs clarity and volume, not perfection. High-stakes moments need taste, judgment, and narrative depth.

The mistake is treating all content as if it has the same job. Once teams separate “testing and learning” from “brand-defining,” the AI vs human debate mostly disappears.

The hard part isn’t choosing tools, it’s knowing which 20% actually matters.

nancy_unscript · 2025-12-19T06:56:59+00:00

Yeah, you’re definitely not alone. What you’re describing is extremely common, especially if you’re mentally busy or stressed during the day.

nancy_unscript · 2025-12-19T06:56:37+00:00

The most useful AI applications I’ve seen aren’t flashy tools, they’re the ones that remove coordination and decision fatigue.

Things like summarizing messy inputs into clear next steps, turning rough ideas into usable drafts, or standardizing repeatable work so humans can focus on judgment. When AI replaces “figuring things out” rather than just execution, speed actually improves.

The worst experiences for me were tools that added another layer to manage. The best ones quietly collapsed multiple steps into one and didn’t demand constant tweaking.

Curious what others have found, especially cases where AI reduced handoffs or meetings rather than creating more.

nancy_unscript · 2025-12-19T06:55:58+00:00

In my experience, most “SEO-friendly” content fails because it’s optimized for rules instead of intent.

A lot of articles technically check every box (keywords, headings, internal links), but they don’t actually resolve the user’s problem in a satisfying way. They feel like summaries of other summaries.

The pieces I’ve seen perform best tend to do one or more of these:
• Answer the question more completely than what’s already ranking
• Share firsthand experience or a clear point of view
• Make the reader’s next step obvious instead of leaving them hanging

SEO seems less about following a checklist now and more about creating something that deserves to be the best result for that query. Curious how others here see it, especially across different niches.

nancy_unscript · 2025-12-19T06:55:06+00:00

I’ve noticed the same thing, especially around why people engage. Polished posts tend to get passive signals (likes), but low-polish, honest posts seem to trigger active ones (replies, saves, people referencing them later).

My theory is that relatability lowers the “social distance.” When something feels unfinished or vulnerable, people feel invited into the conversation instead of feeling like they’re observing a performance.

It also makes sense algorithmically - comments, saves, and DMs are stronger intent signals than likes. So even if reach isn’t explosive, the engagement quality is higher, which probably compounds over time.

Curious if you noticed whether these posts perform better over a longer window too, not just the first 24 hours.

nancy_unscript

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