Connect Brevo (ex SendInBlue) to ChatGPT

Multi-Client Messaging Health Radar

Using the Catchr MCP, pull Brevo data for [List of Client Accounts] over [Period] and compare it with [Comparison Period]. For each account, summarize Sent, Delivered, Delivery Rate, Open Rate, Click Rate, Click-to-Open Rate, Hard Bounces, Soft Bounces, Complaints Rate, and Unsubscribe Rate, split by Campaign Type where available. Classify every account as Healthy, Watch, or Critical against [Client Targets or Historical Baseline], explain the main evidence behind each label, and rank the accounts that need the consultant's attention today with one specific next action per account.

Client Campaign Review Brief

Using the Catchr MCP, analyze Brevo performance for [Client Account Name/ID] over [Period] and compare it with [Comparison Period]. Break down Sent, Delivered, Open Rate, Click Rate, Click-to-Open Rate, Complaints Rate, Unsubscribe Rate, Hard Bounces, and Soft Bounces by Campaign Name, Campaign Type, Campaign Tags, Campaign Subject, Campaign Preview Text, and Campaign Sent Date. Identify the three strongest and three weakest campaigns, support every conclusion with the observed metrics, and produce a concise client-ready brief covering wins, risks, likely causes, and the recommended next test or correction.

Cross-Client Deliverability Watchlist

Using the Catchr MCP, review Brevo deliverability across [List of Client Accounts] for [Period]. At campaign level, use Campaign Name, Campaign Type, Campaign Sender Email, Campaign Sent Date, Sent, Delivered, Delivery Rate, Non-Delivery Rate, Hard Bounces, Soft Bounces, Complaints Rate, and Unsubscribe Rate. Compare results with [Thresholds] and [Previous Period], distinguish isolated spikes from sustained deterioration, and return a prioritized watchlist showing the client, affected campaign or sender, evidence, business risk, and a specific action such as list cleanup, sender review, audience refinement, or cadence adjustment.

Morning Client Priority Queue

Using the Catchr MCP, pull Brevo performance for [List of Client Accounts] for [Today or Recent Period] and compare it with [Baseline Period]. For each client, review Sent, Delivery Rate, Open Rate, Click Rate, Click-to-Open Rate, Hard Bounces, Soft Bounces, Complaints Rate, and Unsubscribe Rate, with Campaign Name and Campaign Type for context. Flag unusual drops or spikes against [Client KPI Targets or Historical Baseline], then give me a ranked morning priority queue with one sentence on what changed, why it matters, and the first action I should take for each client.

Monthly Client Messaging Report

Using the Catchr MCP, pull Brevo data for [Client Account Name/ID] for [Reporting Period] and [Previous Period]. Summarize Sent, Delivered, Delivery Rate, Open Rate, Click Rate, Click-to-Open Rate, Hard Bounces, Soft Bounces, Complaints Rate, and Unsubscribe Rate, then explain the most important changes by Campaign Name, Campaign Type, Campaign Subject, and Campaign Sent Date. Write a concise, client-ready report in plain English covering what improved, what declined, the evidence for each conclusion, and the three priorities for [Next Period].

Campaign Optimization Sprint Plan

Using the Catchr MCP, analyze Brevo campaigns for [Client Account Name/ID] over [Period]. For every Campaign Name above [Minimum Sent Volume], compare Campaign Subject, Campaign Preview Text, Campaign Type, Campaign Tags, Delivery Rate, Open Rate, Click Rate, Click-to-Open Rate, Complaints Rate, and Unsubscribe Rate against [Performance Targets]. Diagnose whether the main constraint is delivery, opens, clicks, complaints, or subscriber loss, then create a freelancer-friendly sprint plan ranked by expected impact and effort, with one test, owner, success metric, guardrail, and review date for each task.

Lifecycle Messaging Scorecard

Using the Catchr MCP, evaluate Brevo lifecycle messaging for [Account Name/ID] over [Period]. Use Campaign Name, Campaign Type, Campaign Tags, Campaign Sent Date, Sent, Delivered, Open Rate, Click Rate, Click-to-Open Rate, Complaints Rate, and Unsubscribe Rate to compare [Welcome, Promotional, Abandoned-Cart, Post-Purchase, Win-Back, or Other Campaign Name/Tag Patterns]. Rank the lifecycle stages by engagement quality, identify where attention is lost between delivery, open, and click, and recommend three prioritized optimizations without claiming revenue or order impact that is not present in the Brevo data.

Subject and Preview Text Winner Finder

Using the Catchr MCP, analyze Brevo campaigns for [Account Name/ID] over [Period] to find the messages that best turn delivery into engagement. For each Campaign Name with at least [Minimum Sent Volume], compare Campaign Subject, Campaign Preview Text, Campaign Type, Campaign Sent Date, Delivery Rate, Open Rate, Click Rate, Click-to-Open Rate, Complaints Rate, and Unsubscribe Rate. Rank winners and underperformers, identify repeatable subject-line, preview-text, timing, and channel patterns supported by the data, and propose three concrete A/B tests with a primary metric, guardrail metric, and success threshold.

Campaign Deliverability Leak Detector

Using the Catchr MCP, pull Brevo data for [Account Name/ID] over [Period] and compare it with [Comparison Period]. Break down Sent, Delivered, Non Delivered, Delivery Rate, Non-Delivery Rate, Hard Bounces, Soft Bounces, Complaints Rate, and Unsubscribe Rate by Campaign Name, Campaign Type, Campaign Sender Email, Campaign Sent Date, and Campaign Tags. Identify the campaigns responsible for the largest deliverability or subscriber-loss deterioration, separate low-volume noise from material issues using [Minimum Sent Volume], and recommend whether to clean the audience, adjust targeting or cadence, review the sender, or revise the message.

Campaign Data Integrity Audit

Using the Catchr MCP, audit Brevo campaign data for [Account Name/ID or All Connected Accounts] over [Period]. Check completeness and consistency for Campaign Id, Campaign Name, Campaign Type, Campaign Status, Campaign Sent Date, Campaign Sender Email, Sent, Delivered, Viewed, Unique Views, Clicks, Unique Clicks, Hard Bounces, Soft Bounces, Complaints, and Unsubscriptions. Flag missing identifiers or dates, duplicate campaign records, negative values, Delivered above Sent, unique activity above its logical parent total, and impossible component totals. Return an exception table with account, campaign, failed rule, observed values, severity, and recommended validation step.

Engagement Metric Reconciliation

Using the Catchr MCP, pull Brevo data for [Account Name/ID or All Connected Accounts] over [Period], grouped by Date and Campaign Name. Recalculate Delivery Rate as Delivered divided by Sent, Non-Delivery Rate as Non Delivered divided by Sent, Open Rate as Viewed divided by Delivered, Click Rate as Unique Clicks divided by Delivered, Click-to-Open Rate as Unique Clicks divided by Viewed, Complaints Rate as Complaints divided by Delivered, and Unsubscribe Rate as Unsubscriptions divided by Delivered. Compare each recalculated value with the corresponding Brevo field using [Tolerance], flag mismatches and zero-denominator cases, and return a reconciliation table with likely causes and the next diagnostic check.

Audience and CRM Hygiene Monitor

Using the Catchr MCP, inspect Brevo audience and CRM hygiene for [Account Name/ID] as of [Snapshot Date] and compare it with [Previous Snapshot Date] when available. Use Contact ID, Contact Created At, Contact Modified At, Contact Has Email Blacklisted, Contact Has SMS Blacklisted, List ID, List Name, List Total Subscriber, List Unique Subscribers, List Total Blacklisted, Segment ID, Segment Name, Segment Category Name, Segment Updated At, and Extracted Date. Flag duplicate or missing IDs, stale contacts and segments based on [Stale-Day Threshold], unusual gaps between total and unique subscribers, rising blacklist counts, and extraction-freshness issues; aggregate sensitive contact details rather than exposing Contact Email, and return a prioritized remediation table with rule, scope, severity, owner, and action.

Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Connect Brevo (ex SendInBlue) to ChatGPT

How to connect Brevo (ex SendInBlue) to ChatGPT

Authorize the Brevo (ex SendInBlue) account in Catchr

Install the Catchr app in ChatGPT

Choose, adapt, and run a prompt.

A simple client question should not trigger an hour of data prep.

Pull another CSV

Rebuild the context

Summarize it by hand

Ask the account. Get to the explanation.

Prepare data before every question.

Connect once. Keep asking.

See it in ChatGPT

Twelve Brevo (ex SendInBlue) prompts for analyzing real account data.

Multi-Client Messaging Health Radar

Client Campaign Review Brief

Cross-Client Deliverability Watchlist

Multi-Client Messaging Health Radar

Brevo (ex SendInBlue) to ChatGPT pricing

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Brevo (ex SendInBlue) to ChatGPT: FAQ

What Brevo (ex SendInBlue) data can ChatGPT analyze through Catchr?

How granular can Brevo (ex SendInBlue) analysis be in ChatGPT?

Can ChatGPT analyze engagement and deliverability in Brevo (ex SendInBlue)?

Can ChatGPT compare campaigns, automations, or audience segments in Brevo (ex SendInBlue)?

What types of prompts work best for Brevo (ex SendInBlue) analysis?

Can I combine Brevo (ex SendInBlue) with other data sources in ChatGPT?

Can I analyze multiple accounts, workspaces, lists, or campaigns together?

What do I need to connect Brevo (ex SendInBlue) to ChatGPT with Catchr?

How recent is the Brevo (ex SendInBlue) data, and how much history can I analyze?

Can ChatGPT change anything in Brevo (ex SendInBlue) through Catchr?

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