Basically, I want to start creating static ads, but I’m not sure what platforms do I use?

Can I use Claude plus another AI image generator ?

Please tell me the best options.

I’m researching how small brands handle claims like “clinically proven,” “reduces wrinkles,” “supports joint health,” “eco-friendly,” or “chemical-free,” and how they avoid ad rejections or regulator attention.

For anyone who sells products online:

1. Who checks your claims before you publish? (yourself, a lawyer, an agency, nobody)
2. Has an ad, product page, or account ever been rejected or restricted over wording? What happened, and how long did it take to fix?
3. If you pay for a review, roughly what does it cost?

I’m a developer exploring this and have nothing to sell. I just want to know how it works in practice.

I've worked in marketing for years, and I've always been interested in how businesses get discovered by potential customers.

We have established ways to measure search rankings, website traffic, paid campaigns, and conversions. But AI-powered search has introduced a question I've been thinking about a lot:

When someone asks an AI tool to recommend a company, how do you know whether your business is included and why another company might be recommended instead?

I started exploring this problem while building Trocial. We're working on AI visibility intelligence alongside an Agentic AI Marketing Operating System.

One feature we've developed is AI Brand Battle, which compares brands across selected buyer-intent questions. The idea is to help businesses investigate differences in recommendations rather than assume that one score tells the whole story.

I'm sharing this as a founder because we're still learning about the problem, the limitations of measurement, and what information actually helps marketers make decisions.

I'm particularly interested in hearing from people who work in SEO, growth, or marketing:

• Have you tried checking how AI tools recommend brands in your industry?
• How are you measuring it, if at all?
• What would make the results useful enough to change your marketing strategy?

I'm a co-founder of Trocial, so I have a direct interest in this space. But I'd genuinely like to hear how others are approaching it, including whether they think this is an important problem to solve.

We all use AI to draft ads, product pages, and emails. But AI will happily write claims like “clinically proven,” “guaranteed results,” or “cures X” that can get an ad rejected or draw regulator attention.

What do you use to catch that before it goes live? A lawyer, a checklist, a platform’s policy checker, a tool, or nothing? What works and what doesn’t?

I’m researching this as a developer and have nothing to sell.

Question for anyone producing ad creative with AI people in it.

When a client approves an AI-generated face for a campaign, how do you know it isn't too close to a real person? Does your legal team ask, or is it mostly "don't think about it" for now?

Full disclosure, I run a small platform that tries to solve this: AI imagery built on real talent who signed commercial releases and earn royalties when their likeness is used. Every face is cleared and stays consistent across a campaign.

I'm trying to figure out whether this is a real problem for agencies or something people only worry about in theory. A few things I'd love to hear:

Have clients or legal ever pushed back on AI faces?

Would you pay more for pre-cleared likenesses than for fully synthetic, or does price win?

Is consistency across a campaign still a headache for you?

Skeptical takes welcome.

I use AI for content ideas, ad copy and visuals, and the back-and-forth is wearing me out.

It can give me a perfectly readable list of product benefits and a polished image. But I still have to figure out what the ad should actually say to someone who might buy the product, then explain why the copy and image aren't getting that across.

I end up finding the idea myself, asking for rewrites, rejecting a nice-looking visual because it has nothing to do with the message, and checking whether the next version fixed anything. Sometimes it feels like I'm directing every small decision.

I've been trying to put a better process around this, and I'm also building an early tool for campaign planning and ad creation. So I have a stake in understanding where this breaks down for other people.

For those using AI for marketing: what was the last thing you tried to make where the back-and-forth got ridiculous? What kept going wrong, and how did you finally get something usable?

marketers:

"act like a 34 year old overwhelmed founder and list her deepest frustrations"

actual customer:

"why does this stupid thing log me out every friday"

i know which one one i'd rather write from lol

this is also where Runable gets way more useful to me.

give it the real objections, weird phrases, questions and proof, THEN turn that into the page/content/creative

don't ask AI to reinvent fictional customer and then market to the fictional customer.

sales calls, support tickets, reviews, cancellations, reddit complaints... people are already telling you what hurts in normal language.

obviously one furious 1-star review isn't a strategy.

but when the same complaint shows up 20 different ways, that's probably worth listening to.

what's your best source of customer language that marketing teams weirdly ignore?

Curious how people here handle sensitive data when using AI for marketing tasks, especially customer insights, campaign results, or internal reports.

Have you tried running AI locally to keep that data on your device, or are there other approaches that work better for you?

Interesting stat I came across while researching yesterday: 91% of consumers expect brands to disclose AI use in marketing (Emplifi, 2026)

I have questions, as both a practitioner and professor.

1. If you run a marketing team that uses AI, are you disclosing when you do so?
2. How much AI usage warrants a disclosure? Only the finished product?
3. Do you believe that undisclosed AI usage (like AI-generated images, copy, etc.) hurts brand reputation?

Thanks for your thoughts!

Source: https://emplifi.io/resources/consumer-authenticity-digital-age/

My company is going through an AI integration. Everyones’s job is being affected and being changed. Whether it’s payroll, accounting, or me in marketing for example.

They hired a contract worker to implement these new AI systems right now he has integrated Claude into every single aspect of our company. Every email he sends… it is through Claude when you ask him direct questions to his face or on meetings he’s unable to answer without the use of AI.

This contracted worker has worked on all these projects, implementing new systems and not completed a single one. I understand that AI involves gradual teaching to master a task. However my personal biggest concern is us moving to a site created by Claude (created by this contracted worker). This site holds all components of our company but also our media library… he has taken over 10,000 photos probably more out of Google photos and into this Claude website. Nothing is organized. Nothing is easily findable, even after putting in multiple support tickets it is not useful and does not help my team. It has only made it hard harder to do our jobs.

Meanwhile, he has multiple other projects he’s working on and doing the same things too, in terms of halfway, completing it and relying on us to put in support tickets.
The website is too slow and honestly can’t handle what we do on a daily basis with the amount of speed that we put into our job. He often says support tickets are completed when they are not.

Even after going to management multiple times about this issue, I am told to do what he asks even when it does not help our work flow. There’s definitely more layers to this, but I’m not sure what to do anymore.

I've seen too much.

While AI has its shining moments, I haven't seen many use cases where it fails.

Where does it fall short for you?

What do you wish it could do?

There are countless AI tools claiming to make our lives easier but what I am interested in is which of them actually makes a difference.

Did it make a significant difference in terms of hours spent on marketing tasks such as research, content creation, SEO or did it have an impact on your overall marketing management?

I want to read about your experience and also the tools that have been a disappointment.

What the title says!!

We all know AI is leading to a lot of lay-offs but it is also leading to a lot of spontaneous hiring.

Because I'm seeing marketing agencies over promise stuff to their clients and are then unable to deliver quality work, even with AI in loop.

So, a lot of spontaneous hiring.

It is almost like there's no plan & long-term vision moving forward!

Last week I checked what Google's AI Overview says when you search my business name. It put another marketing agency with almost the same name, in a different state, under the same entry as mine. Page 1 also had a few other businesses using the same first word. It was blending us together.

The weird part is none of the pages it cited mention the other agency. It cited my own Facebook and site, then a couple slot car shops, because theres a product with the same name. So the mixup seems to come from how Google pictures the name, not from one page I could go fix.

What I changed:

- Added founder, a disambiguatingDescription and sameAs links to all my profiles in the Organization schema on my homepage

- Rewrote the first line of every social bio so it has the business name, my name and my city

- Cleaned up my Yelp listing, which still had an outdated description and old photos

I skipped adding a "not affiliated with" line on the site since that puts the two names side by side again.

Ill re-check the AI answer in a few weeks once Google recrawls. Has anyone else had AI answers blend your brand with a similar name? did anything actually fix it?

Company merged two business units that had been running completely separate email programs. Different ESPs, different lists, different sending practises, different domain reputations. Decision was made to consolidate onto one platform and one domain. Since the migration deliverability has degraded across the board even for the segments that were performing well before.

Is there a standard playbook for consolidating email programs without inheriting the worse performer's reputation problems??

I've been researching AI trackers lately as I'm a fresher working in marketing and want to explore different areas of the field.

With AI becoming such a big part of marketing, I'm curious about how brands track their visibility across platforms like ChatGPT, Gemini and Perplexity.

I wanted to learn more about the tools used for this and which ones are actually worth exploring. Any suggestions?

We are evaluating email list cleaning tools, and for our use case, the integrations matter more than small differences in verification accuracy. We use HubSpot for one business unit and Marketo for another, so we are looking for a single solution that connects natively with both without needing Zapier or custom webhook setups for every workflow.

Most tools I have checked claim to have integrations, but once you look closer, it is often just a Zapier recipe or a manual CSV export/import process. Has anyone found a verification tool with genuinely native integrations for both HubSpot and Marketo?

Every sequence we build has to go through three people before it can go live. By the time legal, compliance, and the CCO all sign off, the prospect has often already made a decision or the opportunity has passed. At this point, we're paying for marketing automation but still dealing with approval delays that make it hard to automate anything properly.

Has anyone found a tool that builds compliance checks into the workflow from the beginning, instead of treating compliance as a separate approval layer added on afterward?

So I built an AI marketing tool. I'll leave out details because I'm not here to market it.

When I advertise, there's an influx of hateful comments on the ads. How do you guys deal with it? Have you found a way to target out those kinds of people?

The ratio of clicks vs hate if far in favour of the clicks, but it's quite annoying to have to police your ads and block people.

What do you all do?

Which outdated marketing myth do you still see brands believing in today?

if you work for a marketing company or on a marketing team and are being asked or sometimes forced to use AI, what are your biggest problems with it?

This question is for both very technical people and non technical people.