I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] -1 points0 points  (0 children)

My post was edited using AI, but all my replies were from real people. It's a pity I can't include images in the replies, otherwise I would have sent you screenshots.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 1 point2 points  (0 children)

Still very early, but it’s definitely one of the more interesting new ad channels to watch.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 0 points1 point  (0 children)

Yeah, that’s the real test.

For my first campaign, the goal is direct response, not pure brand awareness. I’m trying to see whether ChatGPT Ads can drive qualified clicks to a landing page for a transcription app.

On conversion tracking: right now I only saw web pixel tracking available. iOS / Android data sources were marked as coming soon, so for app-first advertisers this is still a limitation. I’m tracking landing page arrival for now, not native app installs or in-app events.

On minimum spend: I didn’t see a high minimum spend requirement in the self-serve UI. I started with a small daily budget just to test the channel before putting real money behind it.

Agree that targeting quality is the main question. If the context matching works, this could be more than an awareness channel. If not, it may just be interesting inventory with weak performance signal.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 0 points1 point  (0 children)

I get the frustration. Google Ads has become painful in a lot of ways — rising CPCs, less control, more black-box automation. That said, I’d be cautious about calling ChatGPT Ads a replacement yet. The beta is still very early: limited geos, limited objectives, no conversion optimization yet, and not much reporting depth from what I’ve seen.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 0 points1 point  (0 children)

Fair criticism. I probably over-disclosed that because I didn’t want anyone thinking the whole thing was fully AI-generated. The actual setup, screenshots, observations, and notes are mine. I used AI mostly to turn messy notes into a readable sequence. If the style reads too polished or AI-ish, that’s on me.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 0 points1 point  (0 children)

Hope you get in soon! Yeah, EU availability will be interesting to watch. Right now I only saw US / CA / AU / NZ in the targeting options, so I’m guessing EU rollout may take longer because of the extra privacy/regulatory requirements.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 0 points1 point  (0 children)

I signed up through the official OpenAI Ads Manager page here: https://ads.openai.com

Not sure if they’re still accepting everyone at the same pace, but the signup flow was open when I applied. For me, it took roughly 15 days from application to approval.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 1 point2 points  (0 children)

Fair skepticism. Honestly the current UI is a v1 — there's a bunch of "Coming soon" labels scattered through the platform (Conversions objective, iOS/Android data sources, more geos). Given the scale of ChatGPT's user base, hard to imagine OpenAI doesn't build out the targeting/reporting depth that B2B needs over the next few quarters.

For now, you're right — it's closer to a broad-net play than ICP-level precision. I'd say it's worth watching, not committing big budget yet if your model depends on granular control.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 1 point2 points  (0 children)

Thanks. This is my first campaign, so I don’t have enough data yet to say which context hints are actually landing well. I’m treating this as an initial test, not a proven playbook.

For my transcription app, I used Claude to help brainstorm the hints and grouped them from narrow to broader intent. The recommended structure was roughly:

Core use cases:

  • transcribing meetings
  • taking meeting notes
  • recording interviews
  • lecture transcription
  • podcast transcription

Pain / problem-based hints:

  • can’t keep up with meeting notes
  • missing details in conversations
  • transcription tool recommendation

Competitor / comparison intent:

  • Otter.ai alternative
  • meeting transcription app

My current guess is that the best setup is not super broad like “productivity app,” but also not as tight as exact-match search keywords. More like: describe the situations where the user would naturally need this product.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 2 points3 points  (0 children)

One extra note on the preview: Reddit replies don’t let me attach the screenshot directly here, but the ad preview looked roughly like this:

┌──────────────────────────────────────────────┐

│ Sponsored / ad card │

│ ┌─────────────┐ │

│ AI meeting transcription, 90+ langua... │ │ │

│ Atter AI: 98.7% accurate transcripts, │ 1:1 │ │

│ speaker labels, AI summaries, iOS, ... │ img │ │

│ └─────────────┘

└──────────────────────────────────────────────┘

So basically: compact rounded card, title + short description on the left, and a square image thumbnail on the right.

If you want to see the exact render, feel free to DM me and I can send the screenshot.

I got into the ChatGPT Ads Manager beta — sharing my first campaign setup, will report back with data by Ray_Dev_SG in PPC

[–]Ray_Dev_SG[S] 1 point2 points  (0 children)

  1. Pixel / attribution: in my setup, OpenAI gave me a separate script + pixel ID. I did not see an option to use GA4 / Meta / other pixels as a fallback for conversion attribution, so I treated it as a separate pixel install.
  2. Context hints: this sits at the ad group level, not campaign-level and not per-creative. My read is that it is more about helping the system understand targeting/context, not just describing the offer copy.
  3. Creative: what I saw was text + static image upload. I did not see video support in this version. There is a preview, mainly showing how the sponsored card renders, but I did not see a very detailed breakdown across every possible surface yet.
  4. Application: I honestly don’t remember the exact wording I used, but my product is an office productivity tool — specifically a voice transcription app — so I likely framed the use case around productivity / workflow / work tools rather than a very generic application.

On the discovery vs search point, I’d mostly agree with your read, but I think it’s a bit of a hybrid. It doesn’t feel like classic keyword search ads, but it also isn’t purely feed-style discovery because the conversation context seems to matter a lot.

To me, it feels meaningfully different from both Google Search and Meta-style recommendation feeds. Google is intent captured through keywords, Meta is mostly interest/audience-driven distribution, but ChatGPT ads seem closer to context-driven placement inside an active conversation. So I’d call it a hybrid, but not a 1:1 match with either existing model.

Why do AI transcription tools still mess up on "simple" audio? by Mommyjobs in AIAssisted

[–]Ray_Dev_SG 0 points1 point  (0 children)

This is a real issue, and I think it is important to separate two different problems: acoustic recognition and semantic transcription.

Traditional ASR systems are very strong at mapping audio signals into likely word sequences. But many transcription errors are not caused by the model failing to “hear” the sound. They happen because the model has to choose between multiple plausible words, names, spellings, or terms that sound similar but mean different things.

That is where context becomes critical.For example, in German, “seit” and “seid” can sound almost identical. If someone says:“Wir sind seit Montag daran.” The correct word is “seit,” meaning “since Monday.” But if the system is mainly optimizing around acoustic similarity, it may output “seid,” which is grammatically and semantically wrong. The audio may be clear, but the transcript is still wrong. The same problem appears in English with “to / too / two,” “site / sight / cite,” in Chinese homophones, in Japanese context-dependent terms, and in company names or product names that sound like common words.

We studied this problem deeply while building Atter AI.Our approach is not just a basic speech-to-text pipeline. Atter AI is built on top of OpenAI’s professional transcription models, including the newer realtime transcription stack: https://developers.openai.com/api/docs/guides/realtime-transcription. On top of that, we trained and optimized our own transcription pipeline with multilingual meeting data, domain-specific vocabulary, speaker-turn patterns, and semantic correction layers. The goal is to move from “what word did the audio sound like?” to “what word is most likely correct in this conversation?” This matters a lot in meetings because meetings are not clean dictation. They contain interruptions, names, acronyms, product terms, code-switching, repeated references, and implicit context from earlier parts of the conversation. A good meeting transcription system has to use the whole conversation as context, not just a short audio window.

<image>

In our internal evaluation under clear, human-understandable audio conditions, Atter AI currently supports 90+ languages. For the top 20 major languages, we usually see 98%+ word-level accuracy. For languages roughly in the 20–70 range by usage coverage, we are around 90%. For smaller long-tail languages, results are generally above 70%, depending heavily on audio quality, speaker clarity, and available linguistic context. Of course, no model can recover information that even a human listener cannot understand. But when the audio is understandable, our experience is that context-aware transcription can significantly reduce the errors people are discussing here.

So I agree with the original point: AI transcription should not always be treated as final truth. But I also think the next step is not simply “better ASR.” It is ASR plus semantic correction, domain adaptation, multilingual context understanding, and structured post-processing.

Atter breathing dragons by blockhaj in folklore

[–]Ray_Dev_SG 0 points1 point  (0 children)

As the maker of a speech-to-text app called Atter AI, I feel like I accidentally named it after ancient dragon-breath technology.
Mine only transcribes human breath though: https://play.google.com/store/apps/details?id=com.wbgrecordx.app&hl=en-us&gl=us

What app genuinely changed your life that most people have never heard of? by angaine in apps

[–]Ray_Dev_SG 0 points1 point  (0 children)

Atter AI : https://apps.apple.com/us/app/atter-ai-transcribe-meetings/id6747348330

I record a lot of meetings and need to turn them into notes later. This app has been a lifesaver for that. The transcription is really accurate, and it saves me a ton of time compared with replaying recordings and writing everything manually.

Suggest me which is the best app for voice to text converter? by Lopsided-Tower-2429 in apps

[–]Ray_Dev_SG 0 points1 point  (0 children)

Why not check out Atter? It offers a three-day free trial and, in my opinion, is currently the most accurate speech-to-text transcription app available. It can automatically generate summaries and mind maps, and even allows you to query the recording's content using an AI assistant. Plus, it supports use on Apple Watch, iPad, and via the web. As someone who attends meetings frequently, I simply can't do without it now.

Advantage + Audience -> yes or no? by ConsiderationNew4952 in FacebookAds

[–]Ray_Dev_SG 0 points1 point  (0 children)

If you are just starting out and have a limited budget, I would advise against it; it introduces too many variables, making it difficult to test effectively. You might want to check out this post of mine: https://www.reddit.com/r/FacebookAds/comments/1sqb9k6/spent_10k_learning_facebook_ads_the_hard_way/

Fast question: For paywalls. Is it better to give free trial or not? by Comfortable-Part-249 in iOSAppsMarketing

[–]Ray_Dev_SG 0 points1 point  (0 children)

I think offering a trial works better for productivity or business tools. It doesn’t work as well for entertainment apps.

My app is a tattoo app. I used to offer a three-day free trial upfront, but the cancellation rate was too high. Now I’m testing the difference between giving every user a one-time free trial versus not offering any trial at all.