Think about your own work or business in this area: Maker launch on producthunt: Agentic AI advertising platform to plan, launch, and optimize cross-channel campaigns across Google Ads, Meta, LinkedIn, Reddit, and X. Autonomous campaign management pow What is the single biggest problem you have there right now? Be specific about what it costs you (time, money, customers) and what you have already tried.

Allan Hickleneutral

My biggest problem right now is the sheer time sink of manually managing campaigns across Google, LinkedIn, and Meta. I'm the only full-time marketer, so every hour spent tweaking bids or setting up new audiences is an hour I'm not spending on strategic planning or deeper analysis. It costs me probably 10-15 hours a week that could be better spent. I've tried setting up more automated rules within the platforms themselves, but they're often too rigid and don't account for the nuances of our B2B SaaS funnel. What I'm really struggling with is stitching together truly cross-channel optimization without constant manual oversight. I'm curious if an 'agentic' approach could actually deliver on planning, launching, and optimizing autonomously across all these channels, rather than just automating isolated tasks.

Simulated interest: 70/100

Beatrice Mullernegative

The biggest problem I face is the sheer amount of manual data reconciliation needed. My team and I spend an inordinate amount of time pulling data from different platforms – Meta, Google, X – and stitching it together in Sheets to understand true cross-channel performance. We estimate this eats up at least 5-8 hours per analyst per week, directly impacting our ability to strategize and test new creative. We've tried building more robust internal reporting but it's a constant battle to keep up with platform changes and ensure attribution accuracy. It feels like we're always a step behind, reacting rather than proactively optimizing.

Simulated interest: 85/100

Armin Sanderneutral

An autonomous AI platform to manage campaigns across Google, Meta, LinkedIn, Reddit, and X? That sounds ambitious. My biggest challenge is the sheer time spent manually consolidating data from these disparate platforms into spreadsheets for our finance team. It's incredibly time-consuming, easily taking hours each week, and I worry about errors creeping in. While we're experimenting, having a system that autonomously plans, launches, and optimizes across all these channels without my team needing to be in the weeds of reporting is appealing, but I'd need to see how it handles our specific financial reporting requirements and budget sign-off processes. What's the actual cost of this?

Simulated interest: 50/100

Akshita Bhadreshaneutral

The biggest problem we face right now is the sheer time it takes to manage our campaigns across Google, LinkedIn, Meta, and Reddit. Pulling data, analyzing it, and then making adjustments manually consumes so much of my limited time – I estimate it costs me at least 10-15 hours a week. This is time I'd rather spend on strategy or product. We've tried creating more structured spreadsheets and setting up automated alerts, but it's still a fragmented process. The idea of an 'agentic AI' platform sounds intriguing, especially for autonomous campaign management, but I'd need to see concrete evidence of its efficiency and cost-effectiveness. How autonomous are we talking, and what level of control do we retain?

Simulated interest: 70/100

Hugues Rogerneutral

An autonomous platform for cross-channel campaigns sounds interesting, especially for consolidating Google, Meta, and LinkedIn. My biggest immediate problem is the sheer volume of manual reconciliation and reporting. It consumes hours each week that could be spent on strategy or client interaction. We're currently using a combination of our reporting suite and Excel, but it's a constant battle to ensure accuracy and timely delivery. The time lost on this is probably the biggest cost, but it also leads to delays in getting the most granular performance data to clients, which they are increasingly demanding.

Simulated interest: 50/100

Rachael Botsfordnegative

The biggest headache for me right now is the manual data consolidation. I'm juggling four clients, each with a different stack – Google, Meta, LinkedIn, even Reddit. Pulling all that data into spreadsheets to see the full picture and track ROI takes hours every week. I’ve tried setting up custom UTMs, which helps with attribution, but the actual reporting still involves a lot of copy-pasting. It’s inefficient and leaves less time for strategic work.

Simulated interest: 60/100

Hanna Nijlandneutral

An autonomous AI platform for campaign management across Google, Meta, LinkedIn, and Reddit sounds interesting, especially the promise of automating planning and optimization. My biggest current problem is the sheer time my team spends on manual QA. It's not just the hours; it's the risk of errors slipping through, which can impact our budget and lead quality. We've tried implementing stricter checklists, but it's still a bottleneck. I'm also curious how 'autonomous' it truly is – does it require significant oversight or setup from my team?

Simulated interest: 60/100

Marlon Ziemenegative

The biggest problem right now is the sheer volume of manual reporting and data reconciliation. I'm spending hours each week piecing together data from different platforms and cleaning it up. It's not just the time cost; it's the mental drain and the worry that a small error could impact client decisions. I've tried building more robust spreadsheets and using Looker Studio, but it's still incredibly time-consuming. The idea of an autonomous platform sounds appealing, but I'm highly skeptical about 'black box' solutions. How does it handle nuanced budget allocation or unexpected performance drops without human oversight? And what's the true cost beyond the advertised price?

Simulated interest: 30/100

Prem Namboothirineutral

An autonomous AI advertising platform? That sounds interesting. My biggest problem right now is the sheer amount of time my team and I spend manually cleaning data exports from Google, Meta, and LinkedIn, and then reconciling that spend for our leadership reports. It's easily 10-15 hours a week, prone to errors, and takes away from actual strategy. We've tried VLOOKUPs and some custom scripts, but it's still a bottleneck. I'm not sure how 'autonomous' this platform is – does it truly handle campaign management from planning to optimization, or is it just another layer of reporting?

Simulated interest: 70/100

Rebecca Lopeznegative

The biggest problem is attribution accuracy, especially with the new agentic AI campaigns. It's costing us significant time trying to untangle what's *actually* driving sign-ups versus what looks good on paper. We're using a mix of platform data and an agency layer, but validating ROI within the quarter is tough. I've tried building custom dashboards, but the granularity for these new AI models is still a blind spot. It's a drain on my team's engineering resources and my own sanity trying to reconcile spend with genuine growth.

Simulated interest: 60/100