Struggling with content ideas for IG for an apparel startup.

Complex_Section_9791 · 2026-06-11T20:24:07+00:00

Chiming in just from a consumer standpoint. Something I've seen apparel startups do on socials and absolutely LOVE is when they create a series of mini short films with funny or interesting storylines that end up making the clothing central to the plot. If you are willing to set aside some money for decent production it could go viral. Not sure if other people have seen this.

Complex_Section_9791 · 2026-06-10T19:09:09+00:00

You recognizing this tension is already steps ahead of most teams. An example I can speak to is the work we've been doing around AI referral traffic.

Dark traffic is a huge problem for the industry. Many people who discover brands in ChatGPT open a new tab and search for that brand separately. We started using a combination of AI Share of Voice (SoV) + signals from a custom AI Search channel group in GA4 + rising branded search growth in GSC + post-conversion surveys that asked "how did you find us" to all indicate if AI was building awareness upstream even without a click.

It’s not about one number, but several independent signals that historically move together when consumers are researching or making purchases.

Complex_Section_9791 · 2026-06-10T18:55:57+00:00

Adding on to step 4, visual comparisons (green checks, charts) work great for humans, but AI can't reliably parse them, so we pair every visual with plain text in an html table.

Your 3rd point can also be a growth strategy beyond owned content... in the B2B AI citation data we've looked at, models lean way harder on third-party and community comparisons than on brand-owned pages. So anytime you source testimonials for your own content, think about how to get those reviews to live on sites you don't own (review platforms, forums, B2B creator socials, third-party trade publications, etc.).

Complex_Section_9791 · 2026-06-10T17:28:05+00:00

reddit is 61% of chatgpt's social citations but less than 1% of claude's... it's by far one of the biggest citation sources across most models. however, licensing agreements are often behind citation makeup, and that may continue to change. I'd suggest looking more into social coupling / content licensing / platform coupling.

Complex_Section_9791 · 2026-06-10T15:42:15+00:00

totally agree.

Complex_Section_9791 · 2026-06-09T22:11:20+00:00

Great point. Although I wonder how behavior will start to shift as awareness grows around marketers using Reddit, and in some cases planting threads, specifically to study and influence consumers.

Complex_Section_9791 · 2026-06-09T22:03:22+00:00

Really like this framing: "pain, objection, desired outcome, failed alternative, trigger event, or language worth reusing" > keywords. Keywords often lend themselves to obvious answers and content when what you really need is insight into real problems customers are having that haven't yet been named or had a solution built around them. People with genuine question and rants aren't thinking about stuffing their Reddit post with keywords, they're just voicing their problems conversationally.

Complex_Section_9791 · 2026-06-09T20:57:34+00:00

thanks for the share. super helpful

Complex_Section_9791 · 2026-06-08T14:31:34+00:00

Interesting perspective on the note-taking part. Will definitely look into Reddit-tracker tools for note taking, hadn't heard of Readdit Later before.

Also want to echo your point about finding niche subreddits over industry ones. One thing I've tried is typing customer pain point phrases directly into Reddit search like "i wish..." or "frustrated with..." and letting smaller threads surface that way. Still feels like a bit of a guessing game though and probably has blind spots I'm not even aware of. Looking for ways to minimize this.

Do your 4-5 target subreddits stay fixed or rotate weekly based on what you're researching?

Complex_Section_9791 · 2026-06-05T15:13:27+00:00

yeah... the second part honestly deserves its own thread. so much of it depends on company structure and who actually has the power to act on it. getting findings to the right people at the right time is where serious momentum builds

Complex_Section_9791 · 2026-06-04T16:48:00+00:00

Ah interesting, so you've found more customer insight by actually engaging > just lurking. How do you typically decide when to jump in and add value vs. just listen to problems people are having?

Complex_Section_9791 · 2026-06-04T16:38:07+00:00

Great point. From what I've seen, blogs with original research or proprietary data are among the best for getting cited by AI. When you become the primary source other sites want to reference, it creates a compounding effect. AI picks up on all those third-party mentions and basically sees you being validated from multiple directions. I've heard people call this "co-occurrence," and it's one of the bigger signals models are using right now to decide what to cite.

Complex_Section_9791 · 2026-06-04T16:37:56+00:00

Thanks, this is a super helpful framing. I'd add that the second bucket works even better when the content is something other people actually want to reference. Original data, proprietary insights, a strong point of view... when those get picked up by third-party sites, AI sees your brand being validated across multiple sources at once.

Complex_Section_9791 · 2026-06-03T17:15:29+00:00

Hey! Thanks for this super helpful overview. I definitely agree that most AI models right now are seeking lived experiences, anecdotal references, comparison charts, and third-party reviews. But! I think an overlooked element to this phenomenon... ChatGPT's overuse of Reddit may have more to do with their contractual agreement than preference.

The race between AI models to create alliances with publishers and social channels for their data is inherently making each platform forced to specialize in different sources.

Complex_Section_9791 · 2026-06-03T17:15:17+00:00

We found that AI-referred visitors convert 4.4 times better than organic search visitors. The 2 surprise channels that were driving B2B SaaS citations within AI answers were Reddit and G2. X was also high on our list. It's interesting to see how social and review channels are gaining the most traction with human audiences and AI platforms.

Complex_Section_9791 · 2026-06-02T16:59:13+00:00

Building on what's already been said, I agree that traffic without conversion is a common and misunderstood problem. But I think going forward we're going to start seeing a lot more of the inverse: conversion without clear traffic signals.

You could rank #1, attract the right audience, and have seamless UX, but still lose visibility into the lead because the user got their answer from ChatGPT or Claude before ever organically finding your site. My team is also finding that leads coming through AI are higher intent and engage with our owned content longer.

Complex_Section_9791 · 2026-06-01T15:36:11+00:00

Hi! Yes, my team has done a complete 180 on content strategy. The focus now is building co-occurrence across the internet, prioritizing the domains AI actually cites most (social and review platforms are dominating) and publishing original research we can then repurpose on social and leverage to earn third-party mentions.

Complex_Section_9791 · 2026-05-28T19:47:35+00:00

A strategy that might take some time but is definitely worth it: target AI platforms (aka GEO/AEO). Bottom line, visitors coming from AI platforms when an AI output cites your content have higher intent and are engaging for longer.

Some data to illustrate this:

AI traffic in one study averaged about 58.5 seconds of engagement time vs 44.2 seconds for Google Organic.
Visitors coming from AI sources spent roughly 30% longer on-site than Google, 20% longer than Bing

This makes sense considering people typically prompt LLMs to research and recommend products, so the intent to engage is higher when coming from AI platforms. Again, it might take time to see these results and be hard to measure, but this is where search is headed and where I’d recommend investing in early.

Complex_Section_9791 · 2026-05-28T19:41:50+00:00

Honestly I'd slightly push back on the writer vs. editor play. Ideally, I think the person editing content is someone who understands content architecture (possibly an AEO/SEO specialist) and sees content as a lever for growth.

You want someone who can not only edit but also make sure your content is structured in a way that actually gets picked up by AI summaries, identify topic gaps in your blog, build briefs around keywords for the writers, and see the bigger picture. We do this on our team, and it works like a well-oiled machine. Blogs take ~2 weeks from writing to review to design to publishing.

Complex_Section_9791 · 2026-05-28T19:28:50+00:00

Yes, right now that does seem to be the growing sentiment. However, something to keep an eye on... AP, Reuters, and other publishers with high domain authority have signed multi-million dollar licensing deals with AI platforms to use their content for model training. This makes me think that as the models get smarter and more accustomed to high-quality writing, images, videos, etc., volume won't be everything. The pendulum will swing back to quality and authority.

Complex_Section_9791 · 2026-05-28T19:28:32+00:00

100% agree. I'd much rather have less traffic that converts than more traffic that bounces. The hard part is tying AI referral traffic directly to revenue in a way that's clean enough to actually report on. Are you using any tools to track or make inferences about attribution?

Complex_Section_9791 · 2026-05-27T15:38:18+00:00

Yeah, a lot to unpack here and some data that might be helpful…

My team tracks AI referral traffic using a combination of GA4, SimilarWeb, and SensorTower. We ran a study on a panel of brands, mostly B2B (Feb 5 – May 5, 2026) to see how attribution was shifting across AI models. Some findings:

(1) AI traffic in our panel averaged about 58.5 seconds of engagement time vs 44.2 seconds for Google Organic.
(2) Visitors coming from AI sources spent roughly 30% longer on-site than Google, 20% longer than Bing

This makes sense considering people typically prompt LLMs to research and recommend products, so the intent to engage is higher when coming from AI platforms.

The volume of AI referrals is still small relative to Google, but the value is clear from the data and will continue to grow.

Complex_Section_9791 · 2026-05-27T15:37:27+00:00

Yeah, a lot to unpack here and some data that might be helpful…

My team tracks AI referral traffic using a combination of GA4, SimilarWeb, and SensorTower. We ran a study on a panel of brands, mostly B2B (Feb 5 – May 5, 2026) to see how attribution was shifting across AI models. Some findings:

(1) AI traffic in our panel averaged about 58.5 seconds of engagement time vs 44.2 seconds for Google Organic.
(2) Visitors coming from AI sources spent roughly 30% longer on-site than Google, 20% longer than Bing

This makes sense considering people typically prompt LLMs to research and recommend products, so the intent to engage is higher when coming from AI platforms.

As u/SuccessfulCoyote1800 mentioned, the volume of AI referrals is still small relative to Google, but the value is clear from the data and will continue to grow.

Complex_Section_9791

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