SpotsNow

Podcast ad attribution has been a guessing game for buyers for years — host-reads vs dynamic insertion vs platform fragmentation makes clean signal really hard to pull. Curious how you handle the dynamic-vs-baked-in distinction in the data. (I built PolyMind to surface signal from prediction-market trades, and 'extracting clean signal from noisy streams' is a problem I keep running into across very different domains.)

Very interesting. Was there a moment from the last few months where a publisher or advertiser used SpotsNow in a way you didn't design for, but it ended up showing you what the product is actually becoming?

The "data exists but was locked behind enterprise contracts" framing is exactly the gap I keep seeing in adjacent markets too. Coming from finance content creation — I run the ModeLoop Podcast on Spotify (https://open.spotify.com/show/0m1oR8AyQv17DVpc5MmirG) — the thing podcasters in any niche struggle with isn't measuring downloads, it's understanding the competitive ad picture in their category. SpotsNow giving the publisher side the "who else is being advertised on shows in your topic" view would be a meaningful unlock — and the open-inventory marketplace closes the loop nicely. Curious if you're planning category-level benchmarks (e.g. average CPM ranges by topic vertical) for smaller publishers who don't have direct comps.

Hey, the audio pixel attribution part is the headline feature for me honestly. promo codes always undercount and brand-lift studies take weeks. quick question, are the pixels embedded at the publisher level or in the ad creative itself? assuming there's a tradeoff between accuracy and publisher buy-in there.

Nice, congrats on the launch! Are you planning to scale to any other channels, like shorts, reels/tiktoks etc?

Very interesting! Can I see not just where a specific company is advertising, but where companies in a whole industry are advertising? In particular, I need to understand where travel startups place their ads and which exact ones they use. Is that possible?

very niche-ish product. The team behind this looks top tier ;) @campritchard good luck!

Super interesting product. congratulations on the launch!

Super interesting idea! I honestly haven't really thought about podcast ads but now tempted to try out this new marketing channel.

Congrats on the launch Cam. Interesting product that I would love to test.

Do you measure business outcomes in addition to impressions, views, and clicks?

Hey Product Hunt 👋 frontend engineer here.We spent the last few months obsessing over one thing - making podcast ad data actually feel explorable instead of buried in spreadsheets. Most competitive intel tools in this space feel like they were built to justify the enterprise contract. Dense tables, ten-click flows, dropdowns inside dropdowns, ui that hasn't been touched since 2014. we went the opposite direction at SpotsNow with clean, simple and intuitive user-interfaces.Audio ads are a different beast, you need to hear the ads, see saturation patterns, understand show context, all without it turning into a mess.Type a brand, get something useful on the first interaction.Listen to ads inline without breaking your flow.Build a real campaign in under a minute with over 59k shows to choose from.User experience matters here more than people think, when the tool is fast and clear, you spend your time on the actual decision (what to spend on, which show to pick) instead of fighting the interface.Would love feedback on the search and campaign builder flows, those were the hardest to get right and if anything feels off drop it in the thread 🙏

Really cool launch! Love the transparency angle here. Podcast ads have always felt like a black box.

Wishing you good luck with the launch!

This is actually really useful. Podcast advertising has always felt weirdly opaque compared to every other paid channel. Love that you combined competitive intel + direct inventory access in one workflow.

Congrats on launching, Cam! Not coming at this as someone who's built competitive-intel tools, more as the "researches podcast ads / pull up your brand" person you mentioned. I'm getting an iOS app ready to launch and came at this as a would-be buyer: pulling up specific brands and shows works very well. And I'm excited to try the marketplace features too.One observation that might be relevant to the taxonomy work you said you're investing in: my instinct as a buyer was to navigate by theme — "relationships," "dating," "wellness" — to find shows that fit my app. That's not how the tool thinks (it's organized around industry tags / specific advertisers, which makes sense once it clicks).

A very interestig idea, congratulations on the launch!

Also from my side, congrats on the launch, Cam! I agree, the marketplace angle is what makes this genuinely different Quick question: how do you handle attribution for shows that don't use promo codes? Curious if you rely on self-reported data from brands or if there's some crawling/inference magic happening under the hood.

Hey Product Hunt 👋 Cam here, founder of SpotsNow.Here's a thing that's always bothered me about podcast advertising: it's one of the only major ad channels where you can't easily answer the basic competitive questions. Who's advertising on my favorite show? What's BetterHelp actually spending on podcasts this quarter? Which new brands just started testing the channel? Which shows are over-indexed on CPG vs. fintech vs. DTC?The data exists. But it's been locked behind enterprise contracts, the UIs feel like 2014, and there's no way to act on what you learn without leaving the tool and writing a bunch of emails.SpotsNow is the version I wanted: Free access to podcast ad spend data across 60,000 shows, with a modern interface that doesn't make you fight it, and (the part I'm genuinely most excited about) a built-in marketplace of open inventory so the second you spot a show that fits your campaign, you can actually request a spot from the publisher right there.A few things we'd love help with today:1. If you research podcast ads: spotsnow.io is open. Pull up your favorite advertiser or your own brand. Tell us what you wish were there.2. If you've built Competitor Intelligence tools: I'd love your read on our category taxonomy and confidence scoring - that's where we're investing next.3. If you run a podcast or network: there's a free way to list open inventory and reach the buyers who are already researching shows like yours.Huge thanks to the early users who stress-tested this when the dataset was a tenth of its current size. Today it goes wide. Roasts, questions, feature requests, all welcome. 🙏