ImprovadoAgentic marketing data pipeline/OS
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Improvado

Agentic marketing data pipeline/OS

Last updated August 23, 2026
The take

A governed marketing data pipeline with an AI agent on top, worth it when your ad spend is big enough that a managed data layer pays for itself.

Great for

Enterprise marketing teams and agencies who need one governed data layer across dozens of ad platforms, and who want their AI agents to query real campaign numbers instead of estimates.

The catch

Advanced and Enterprise are custom-quoted only, implementation runs about two months, and most changes go through a sales or support touchpoint. This is not a self-serve tool.

Bottom line

Reach for it when your ad spend justifies the pipeline and you have the patience for a 2-month onboarding. If you just need to pull Facebook Ads into a spreadsheet, this is a tank when you need a bicycle.

At a glance
Starting price$0/mo (Free Limited), $100/mo (MCP Only)
Free tierYes (50 MCP actions/week, no data rows)
Pricing modelVolume-based (rows/yr + MCP actions/week)
Best forEnterprise marketing teams and agencies
Key integrations500+ marketing sources, MCP for Claude/ChatGPT/Gemini, Snowflake, BigQuery, Tableau, Power BI
Watch out forAdvanced/Enterprise custom-quoted; $5K-$50K+/mo typical; 2-month onboarding
Feature checklist
Marketing source connectors500+ ad, CRM, analytics sources
Unified governed data schemaone marketing common data model
Plain-English AI analystanswers campaign questions
AI agent access via MCP84 tools for Claude, ChatGPT
BI and warehouse deliverySnowflake, BigQuery, Tableau, Power BI
Campaign writeback to platformsagent acts on platforms
Free tierongoing; 50 MCP actions/week
Self-serve top tiersAdvanced and Enterprise quoted
Per-seat pricingvolume-priced by rows, actions
Multi-client workspacesup to 50; enterprise unlimited
Fast implementationabout two months typical
What 5 real users said
4 positive1 mixed

What you're actually getting

Improvado is a marketing data pipeline with an AI agent on top. It pulls data from 500-plus ad platforms, CRMs, and analytics tools, normalizes everything into a single schema, and lets you query it in plain English.

The 2026 repositioning centers on the MCP server: connect Claude, ChatGPT, or any MCP-compatible client, and your AI agent gets governed access to your actual campaign numbers, queried in plain English.

The pipeline underneath handles extraction, transformation, governance rules, and warehouse delivery. The AI Agent and MCP layer sit on top, turning that governed data into answers, reports, and platform actions.

As a Principle Software Engineer in the healthcare sector I rely & work on the systems which involves timely data flow from the Clinical, Operational & marketing systems. For this Improvado has helped to streamline the analytics ingestion process & finally giving Standardized & consumable data sets. Our primary use case revolves around reducing the manual data preparation for Dashboards. Pros: 1. It automated data pipelines which significantly reduced the ETL work that we used to do manually. 2. Mapping & transformation workflows are intuitive & integrate well with BI tools. Cons: 1. Some connectors still require manual intervention (which is expected, as this will improve over time & behavior) 2. Some deeper technical documentation would speed up adoption for engineering heavy teams like us.
Anonymous, Principal Software Engineer, Healthcare and Biotech (50M-1B USD)Gartner Peer Insights · March 10, 2026 ↗

Where it earns its keep

It shines when you are running campaigns across so many platforms that manual reconciliation is a full-time job. One governed data layer feeding every dashboard and every AI query beats 30 browser tabs and a pivot table.

The MCP angle is genuinely useful if your team already works inside Claude or Cursor. Ask a question, get real numbers back from the same data source your dashboards use, without building a custom integration for each platform.

Agencies get a second win: multi-client workspaces with per-workspace governance, up to 50 on Advanced and unlimited on Enterprise. Dashboards and BI delivery cover Tableau, Power BI, and Looker Studio, backed by Snowflake, BigQuery, and Redshift in the warehouse.

Now, we don't have to involve our technical team in the reporting part at all. Improvado saves about 90 hours per week and allows us to focus on data analysis rather than routine data aggregation, normalization, and formatting.
Jeff Lee, Improvado customerImprovado Blog (customer testimonial) · March 27, 2026 ↗

Where it'll bite you

Cost is the first and loudest complaint. Advanced and Enterprise are custom-quoted only. Third-party sources report $5K to $50K-plus per month, and annual contracts are the norm. The Free Limited tier is a sampler: 50 MCP actions a week and no stored data rows.

Implementation takes about two months. That rules out teams that need results this quarter. Plan changes and data tweaks route through sales or support, so expect a managed-service relationship with few self-serve knobs.

Connector coverage is Western-platform-heavy. Google, Meta, LinkedIn, Salesforce, HubSpot are well covered. Regional ad networks in APAC, local e-commerce platforms, and niche DSPs may not be. Teams outside North America and Europe should request a connector audit before signing.

I use Improvado AI Agent to get basic analytics and quick solves. I just enter the question, and it gives me the answer I need.
Beau Payne, Improvado customerImprovado Blog (customer testimonial) · March 27, 2026 ↗

What it costs, really

There is a free tier at $0/mo with 50 MCP actions a week and no data rows. The MCP Only plan at $100/mo adds 2M rows a year, daily sync, and 300 MCP actions a week. Both are self-serve.

Advanced and Enterprise are custom-quoted. Annual contracts typically run $5K to $50K-plus per month, scoped to your data volume, connector count, and support needs. White-glove service is part of the Enterprise package, which softens the sticker but does not erase it.

On the reporting side, we saw a significant amount of time saved! Some of our data sources required lots of manipulation, and now it's automated and done very quickly. Now we save about 80% of time for the team.
Kasia Pasich, Data AnalystImprovado Blog (customer testimonial) · March 27, 2026 ↗
Every Monday, we would spend 4 hours on average logging in to each platform and downloading the data we needed, clean the files before we were able to upload them to our database and visualize them in Tableau.
Peter Sahaidachny, Digital Marketing Manager, USFImprovado Blog (customer testimonial) · March 18, 2026 ↗

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