We pull the data from all your performance channels into one place and analyze it with OpenAI and Claude models, keeping a constant watch on competitors, seasonal demand and creative performance. AI does the heavy lifting on analysis; our specialists interpret the findings and turn them into a marketing plan.
Done by hand, competitor, seasonal and creative analyses take weeks, so most teams run them only a few times a year. With AI, they become continuous.
Manual analysis
AI-powered analysis
AI is only as good as the data you feed it. That is why the workflow starts with a verified measurement setup and ends with expert approval.
We pull data from your ad platforms and analytics on a regular schedule.
All sources land in a single table with shared definitions, so every metric means the same thing to everyone.
The models run competitor, seasonal, ad and creative analyses, and we cross-check critical findings between the two models.
Our team interprets and prioritizes the findings, then adds them to the 90-day plan.
We track competitors' search visibility, pricing and campaign periods on a regular basis, and find the opportunities where you are not yet visible.
The question we answer: Which searches do competitors show up for while we do not?
We build a seasonal curve for your brand from past years' demand, traffic and conversion data, so budget is in place before demand rises.
The question we answer: When does demand start to rise, and how many weeks in advance should we increase the budget?
Using public ad libraries, we map where competitors advertise and which messages, offers and formats they use, then look for positioning gaps.
The question we answer: What promises do competitors advertise with, and which message can set us apart?
We tag the visual, headline, message and format of each creative, match them to performance data and identify the elements that work.
The question we answer: Which visual, headline and format elements drive conversions?
Each week you receive a short summary that pairs the AI findings with our team's interpretation. No long reports, just clear points on what to do next.
A competitor has started bidding on your brand searches. Review bids and ad copy in the brand campaign.
In past years, demand started rising two weeks after this period. Plan the budget increase now.
Competitors are highlighting free shipping. We recommend a test that stands out with a fast delivery message.
Videos that show the product in the first second perform better. Build the new brief around this.
Only aggregated performance data goes to the models. Names, email addresses and phone numbers never enter the workflow.
By default, data sent through the enterprise API is not used for model training.
Your raw data lives in your own BigQuery project, and access stays under your control when the engagement ends.
We compare critical findings across OpenAI and Claude models and check any inconsistencies by hand.
No recommendation reaches your campaigns without expert approval.
The report notes the data behind every finding. No decision is made just because "the AI said so".
No. AI scans the data, finds patterns and drafts recommendations. Our specialists decide what gets implemented, and nothing is applied to your campaigns without their approval.
We use OpenAI models and Anthropic's Claude models through their enterprise APIs. The model is chosen by task type, and critical outputs are verified by comparing the two.
Only aggregated performance data is sent to the models. Personal data such as names, email addresses and phone numbers is never shared. By default, data sent through the API is not used for model training, and your raw data stays in your own BigQuery project.
Yes. Competitor and seasonal analyses add value at any budget. Creative analysis becomes more reliable once there is enough ad data, so we set the scope based on your data volume.
In a free 30-minute call, we look at your data and show you, with concrete examples, what AI-powered analysis can do for your brand.
