Team
AI automation for marketing teams that builds the weekly report for you, drafts on-brand copy variations and turns reviews and survey answers into insights you can act on.
Sound familiar?
Marketing teams produce a lot, measure a lot and report a lot, usually with fewer people than the plan assumed. The creative and strategic work is what moves results, but it gets squeezed by reporting, versioning copy and cleaning up data so the numbers make sense.
AI automation for marketing teams is most useful on that supporting work. We build automations that pull performance data from GA4, Meta, Google Ads and Klaviyo into one report every week, generate copy variations within your brand rules for a person to approve, and read through reviews, survey responses and support tickets to tell you what customers keep saying.
Reporting is a common first step, and reporting automation works because the numbers come straight from each platform's API. The model only writes the commentary, so it can't invent a conversion rate. For content, we use LLM integration to put generation inside the tools your team already uses, with your tone, product facts and banned phrases built in.
We're honest about the limits. AI drafts are a starting point, not finished work. Mass-produced pages with nothing new to say rarely help search rankings, and they can hurt your brand. We aim for less busywork and better inputs, not more content for its own sake. If you sell online, this connects closely with our work for ecommerce brands.
The problem
Ask a marketer what they'd do with an extra day a week and the answer is usually strategy, testing or creative. Then look at where that day currently goes.
Every platform reports differently. GA4 says one thing, Meta claims another, Shopify has the actual revenue. Someone exports from each, lines up date ranges, fixes currency and writes a summary for leadership. It's important and repetitive, which makes it a strong candidate for automation.
One campaign needs headlines for three ad formats, email subject lines for A/B tests, product descriptions for a new range and posts for four channels. The idea takes an hour. The versions take a day.
Reviews, post-purchase surveys, support tickets and sales call notes are full of useful language and objections. Reading them properly takes time nobody has, so they go unread or get skimmed.
Leads arrive without UTM data, duplicates pile up in the CRM, and segments in Klaviyo or HubSpot drift out of date. Attribution arguments start because the underlying data was never clean.
Briefs, approvals and asset requests bounce between Slack threads and email, and status lives in someone's head.
For example, an ecommerce brand spending across Meta, Google and email might have one marketer who spends most of Monday building the weekly report. Automating that report doesn't need anything clever: scheduled API pulls, a few calculations in code and a short summary written by a model from the finished numbers. It's often one of the cheapest automations to run and one of the quickest to show value, which makes it a good way to test how your team likes working with AI before moving on to content.
Automation won't come up with your positioning or your best campaign idea. It can take the reporting, versioning and sorting off the team so there's time left for that work.
Where to start
Spend, revenue, conversions and key metrics are pulled from GA4, Meta, Google Ads, Klaviyo and Shopify into one Google Sheet or Looker Studio dashboard, with a short written summary of what changed and why it might matter, posted to Slack every Monday.
From one approved brief, the automation drafts ad headlines, email subject lines and product descriptions that follow your tone guide, product facts and banned claims. A marketer picks, edits and approves before anything is published.
Reviews from Trustpilot, Okendo or Yotpo and open survey answers are grouped into themes each month, with real customer quotes for each, so you know which benefits to lead with and which complaints product needs to hear.
New contacts are checked for missing UTM and source data, matched against existing records to prevent duplicates and tagged consistently in HubSpot or your CRM, which makes attribution reports something people can trust.
A webinar recording, podcast or long article is turned into draft social posts, an email and a short summary page, each linked back to the original. An editor reviews and adjusts the drafts before they go anywhere.
Requests from Slack or a simple form are turned into structured briefs with audience, channel, deadline and assets needed, then created as tasks in Asana, Trello or Notion. Missing details are asked for up front instead of discovered the day before launch.
Integrations
GA4, Looker Studio, BigQuery and Shopify analytics, with numbers always pulled from source rather than generated by a model.
Meta, Google Ads, LinkedIn Ads and TikTok Ads for spend, performance and creative-level reporting.
Klaviyo, Mailchimp and HubSpot for campaign data, segments, flows and draft content.
Shopify, WooCommerce, WordPress and Webflow for product content, landing pages and revenue data.
Trustpilot, Okendo, Yotpo, Typeform and Google Forms as the raw material for customer insight reports.
Claude or OpenAI models through n8n, Make, Zapier or custom code, with approvals in Slack, Teams or Notion.
FAQ
It gets close when we give the model good material: your tone guide, approved past copy, product facts and a list of things you never say. It still needs an editor. We treat drafts as a strong first pass that saves time, not finished work.
Only if you want it to. By default every customer-facing piece is a draft that someone on your team approves. Internal outputs like reports usually run on their own once you trust them.
The numbers are pulled directly from each platform's API and calculated in code, not produced by the model. The model writes commentary around those numbers, and we show the underlying figures beside it so anyone can check.
Thin, mass-produced pages can. Pages that are useful, accurate and reviewed by someone who knows the subject are judged on their quality. We help with research, outlines and drafts, and recommend a person adds the expertise and edits before publishing.
Most marketing automations don't need personal data in the model at all, since reports work on aggregates. Where customer text is analyzed, such as reviews, we can strip names and emails first and use providers' business terms that exclude training.
Tell us which tasks eat your team's time. We'll suggest where AI automation for marketing teams fits, and which parts are better left to your people.
A short call is usually enough to spot the first workflow worth automating. Bring a recent weekly report or a campaign checklist and we'll look at where the manual steps are, what it would take to automate them and what it would cost to run each month.
Each solution is built from one or more of these. Follow a link for the detail on scope, stack and process.
We turn multi-step business processes into automated workflows across your apps, with approvals in Slack or Teams, clear ownership and a log of every step.
ExploreWe build sales agents for web chat, forms and email that qualify inbound leads against your criteria, enrich and update your CRM, and route or book meetings without leaving good leads waiting.
ExploreWe build first versions of AI-powered SaaS products: a narrow, well-tested core feature, user accounts, subscriptions and the admin tools you need to run it.
ExploreWe automate lead capture, enrichment, routing, activity logging and pipeline hygiene in your CRM, so sales spends its time selling and managers can trust the numbers.
ExploreWe build Shopify automations and integrations with ERPs, 3PLs, supplier feeds, accounting and Slack, using webhooks, the Admin GraphQL API and well-monitored background jobs.
ExploreWe add large language model features to existing web apps and platforms, with evaluation, guardrails, cost controls and a design that lets you swap models later.
ExploreWe build custom WordPress plugins: custom post types, integrations, REST API endpoints, admin tools and commercial plugins with licensing and automatic updates.
ExploreWe automate the data collection, cleanup, reconciliation and delivery behind your recurring reports and dashboards, plus the data feeds that keep your systems in sync.
ExploreHow we designed a Shopify app that syncs supplier stock and prices from any file or API, shows a diff before writing, and refuses to import files it doesn't trust.
Read the storyHow we turned a Google Form, a serial-number spreadsheet and a claims inbox into one Shopify app that registers units, issues coverage and resolves claims with real Shopify objects.
Read the storyHow we built a deterministic, explainable rules engine that scores Shopify return and refund requests, shows the reasons behind every score, and never declines a customer automatically.
Read the storyTell us how it works today. We'll tell you honestly what's worth automating, what it would take, and what it would cost.