Automate Marketing Reports with Claude Code: Never Build the Monday Deck Again

By Jonah, Founder of FindClout — July 2026

The Monday marketing report is a ritual with no upside. Someone spends an hour pulling numbers from four platforms, writes three bullet points that say roughly the same thing every week, and pastes it into a slide nobody will remember by Wednesday. That hour is pure overhead — the numbers were already sitting in an API somewhere, waiting to be read.

This build replaces the whole ritual with a pipeline: a script pulls the real numbers, a cheap LLM turns them into a readable summary, and it lands in Slack, Telegram, or your inbox before you've had coffee. You never touch it again unless the metrics you care about change. Here's the exact build with Claude Code.

If you haven't already, get Claude Code installed — this guide takes 20 minutes — and it helps a lot to have already built the marketing dashboard, since this pipeline reuses the exact same data connections.

The three-part pipeline

Keep these strictly separate — it's the difference between a report you trust and one you have to double-check every week:

1. Fetch — a script pulls real numbers directly from your APIs or database. No LLM involved. No room for a model to invent a number.
2. Summarize — the real numbers get handed to a cheap, fast LLM via OpenRouter, which writes the plain-English recap.
3. Deliver — the summary (plus the raw numbers) gets pushed to wherever your team actually reads things.

Describe this structure to Claude Code up front so it builds the separation in, not as an afterthought:

tell cc: "Build a weekly marketing report pipeline in three clean
steps: 1) a fetch script that pulls this week's numbers from
[your APIs/database], 2) a summarize step that sends those numbers
to an LLM via OpenRouter and gets back a short written recap,
3) a delivery step that sends both the recap and the raw numbers
to a Slack webhook. Keep these as separate functions I can test
independently."

Step 1: The fetch — reuse what you already built

If you already built the marketing dashboard, this step is nearly free — the same D1 table storing daily snapshots is exactly what a weekly report needs to summarize. If you're starting fresh, describe the pull directly:

tell cc: "Pull ad spend, ROAS, and conversion rate from [platform] for
the last 7 days, plus the same 7 days from the prior week for
comparison. Print it as a clean JSON object so I can see exactly what
data we're working with before we summarize it."

Verify the raw numbers look right before moving to the next step. This is the step where accuracy actually matters, and it's pure code with no model involved — so if a number's wrong, it's a straightforward bug, not a hallucination.

Step 2: The summary, via OpenRouter

This is the step people over-think. You do not need your most expensive model to turn a table of numbers into three sentences of prose — a cheap, fast model does this well, and OpenRouter gives you one API key and one bill across dozens of model providers, so you can route this specific job to whichever cheap model handles it best without juggling separate accounts. This is the pattern covered in full in OpenRouter for agent workflows.

tell cc: "Add a summarize step that sends the JSON numbers to OpenRouter
using a cheap, fast model. The prompt should tell it: write a 3-4
sentence marketing recap, lead with the single most important number,
mention anything that changed more than 15% week over week, and keep
the tone direct with no fluff or hedging language."

Run it a few times and read the output critically. If it's too generic, that's a prompt problem, not a model problem — get specific about tone, what "important" means for your business, and feed it a couple of examples of summaries you've actually liked in the past. Claude Code will happily iterate on the prompt template itself, the same way it iterates on code.

Step 3: Delivery — Slack, Telegram, or email

Pick wherever your team actually reads things, and it's a single well-documented API call either way:

tell cc: "Send the final report to a Slack channel using an incoming
webhook, formatted with the recap paragraph up top and the raw numbers
in a small table underneath."

If your team lives in Telegram instead, the same delivery step reuses everything from the Telegram bot build — the same bot token, the same sendMessage call, just triggered by the report pipeline instead of a chat message. Email works the same way through a transactional email API. You can wire up all three in parallel if different stakeholders check different places.

Step 4: Put it on a schedule

tell cc: "Schedule this whole pipeline to run automatically every
Monday at 8am. If any step fails, send me an error message directly
instead of failing silently."

A Cloudflare Worker on a Cron Trigger handles this cleanly for a job that runs once a week and finishes quickly — no server to babysit, and it's within the free tier as of 2026 for a job this infrequent. Claude Code sets up the trigger, deploys it, and from that point forward the report simply exists every Monday without anyone touching it.

Trust it gradually, not immediately

The first few weeks, keep a human glancing at the raw numbers alongside the AI summary before it goes out — ask Claude Code to send you a preview an hour before the scheduled send, or just watch the first few runs manually. Once you've confirmed the fetch step is solid and the summary tone is consistently right, let it run fully unattended. This staged-trust approach is the same one worth applying to any automation you didn't build by hand line by line — the vibe coding guide covers the broader version of this instinct.

Where this compounds

Once the pipeline exists, extending it is cheap. Add a monthly rollup that compares four weekly reports. Add a per-channel breakdown that only gets sent to that channel's owner. Add a "here's what changed" diff against last quarter. Every one of these is a small addition to a system that already runs itself — which is the entire promise behind Claude Code for growth teams: build the pipeline once, keep asking it to do more.

FAQ

What is OpenRouter and why use it for report writing?

OpenRouter is a single API giving access to dozens of LLMs from different providers through one key and one bill. For turning a table of numbers into a paragraph, you don't need the most expensive model — a cheap, fast one handles it well and costs a fraction as much.

Will the AI-written summary actually sound right, or generic?

It sounds as good as the prompt you give it. Feed the model your real numbers plus examples of past summaries you've liked, and state your tone explicitly. Claude Code can wire in a persistent prompt template so every report reads consistently.

Where does the report get delivered?

Wherever your team actually reads things — a Slack channel via webhook, a Telegram group via bot, or email via a transactional API. All three are a small API call, and Claude Code can wire up any or all of them.

How do I make sure the numbers in the report are actually correct?

Separate the two jobs: a script pulls the real numbers with no LLM involved, and only afterward does an LLM turn them into prose. Have Claude Code print the raw numbers alongside the generated summary the first few times so you can sanity-check before trusting it fully.

Can this replace an analyst?

It replaces the repetitive part — pulling numbers and writing the same weekly recap — not the judgment part. Most teams that build this free up an analyst's time for actual strategic thinking instead of copy-pasting numbers into a slide.

Jonah is the founder of FindClout, a curated creator distribution network that has generated 3.3B+ views for brands across sports, prediction markets, AI, and more, built on verified American audiences. He builds most of FindClout's internal tooling himself, in a terminal, with zero formal coding background. Reach him at [email protected] or book a call.