Blog
Read third i articles on AI marketing operations, creative analysis, reporting, growth systems, and performance workflows.
A step-by-step guide to connecting Claude to your Google and Meta Ads data using MCP - with 5 copy-paste prompts for cross-channel insights.
Abhinav Krishna
This article breaks down how we teach AI to scan ad accounts for “money pits” — the creatives and keywords that quietly burn budget without moving real outcomes. It explains how our analyzers focus on real patterns, not random spikes, so you get a short, actionable list of leaks to fix instead of m…
Vimal Babu
If you run performance marketing today, you hear the same question every time AI agents come up: “So, which model are you using?” For real-world results, that is the least useful place to focus. The teams that are quietly getting better ROAS, lower waste, and fewer surprises from AI agents are not…
Abhinav Krishna
This post explains that AI agents are not magic robots, but tools built on one simple trick: predicting the next word very well, then wrapping that prediction engine with rules, tools, and memory so it can actually do jobs for you. It shows how this setup lets you talk to software in plain language…
Aravindhan
MCP gives you a powerful AI layer inside Meta, but the risk is simple: it can move faster than your brand is ready for.
Anand Kumar
We rebuilt our AI marketing analyst four times. Each iteration taught us something about the hardest problem in agentic systems: giving the model the right information at the right moment. Here's the full story — what broke, what worked, and the architecture pattern we landed on.
Aravind Nair
Neeraj Kushwaha
Neeraj Kushwaha
A key challenge in fintech marketing is optimizing campaigns based on the wrong metrics, treating platform-reported "approvals" as success when the true measure of performance is the "dispersal" of actual loans. Since ad platforms like Meta and Google only see up to the approval stage, campaigns ca…
Neeraj Kushwaha
