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Looker excels at semantic modeling for enterprise BI — building a governed single source of truth with LookML. Improvado specializes in marketing data aggregation, transformation, and governance across 500+ advertising and analytics platforms. Both tools appear in marketing tech stacks, but they solve fundamentally different problems: Looker provides the visualization and exploration layer, while Improvado handles the extraction, normalization, and preparation of marketing data upstream. The decision isn't which is "better" — it's whether your team needs a BI tool that assumes clean data already exists, or a marketing-specific pipeline that delivers ready-to-analyze data to any BI platform.
Quick Verdict
Full disclosure: we're Improvado, and this comparison reflects our perspective. We've represented Looker's capabilities based on public documentation, G2 reviews, and customer migration stories. Where we've missed nuance or gotten details wrong, email us and we'll correct it. Our goal is to help you choose the right tool for your team — even if that's Looker.
Feature Comparison: Improvado vs Looker
| Feature | Improvado | Looker |
|---|---|---|
| Platform Type | End-to-end marketing data platform (ETL + transformation + governance) | BI and semantic modeling layer (post-ETL visualization) |
| Data Connectors | 500+ pre-built marketing connectors; custom builds in 2–4 weeks (SLA) | 1,050+ connectors (primarily databases, Google ecosystem); no marketing-specific maintenance |
| Data Transformation | No-code UI + SQL; Marketing Cloud Data Model (MCDM) pre-built; normalization automated | LookML semantic layer; requires upstream ETL (DBT, Fivetran, custom scripts) |
| Marketing Data Governance | 250+ pre-built rules; pre-launch budget validation; UTM enforcement | General data governance (row-level security, permissions); no marketing-specific rules |
| AI Capabilities | AI Agent for natural-language queries; automated mapping; anomaly detection | Emerging AI features (preview); natural-language exploration in roadmap |
| Data Destinations | Any warehouse (BigQuery, Snowflake, Redshift) + BI tools (Looker, Tableau, Power BI) | Connects to 50+ SQL databases; visualizes data in place (no ETL) |
| Attribution & MMM | Built-in multi-touch attribution; integrates with MMM tools; unified customer journey | Custom LookML models required; no native attribution |
| Implementation | 2–4 weeks typical; dedicated CSM + professional services included | Multi-month for complex deployments; LookML requires developer training |
| Pricing Model | Outcome-based (connectors + data volume); predictable annual contract | Enterprise subscription (user-based + API calls); pricing not public |
| Enterprise Compliance | SOC 2 Type II, HIPAA, GDPR certified | Enterprise-grade security; role-based access; data lineage |
The Architecture Difference: BI Tool vs. Marketing Data Platform
Looker and Improvado sit in different layers of the data stack. Looker is a BI platform — it visualizes, models, and explores data that already lives in a warehouse or database. Improvado is a marketing data platform — it extracts raw data from advertising APIs, normalizes it into a unified schema, applies marketing-specific governance, and delivers it to warehouses or BI tools.
Teams choose Looker when they need governed, self-service reporting with a reusable semantic layer. LookML standardizes how metrics are calculated — everyone sees the same "customer acquisition cost" definition, no spreadsheet discrepancies. But Looker doesn't pull data from Facebook Ads, Google Analytics, or Salesforce on its own. You need an upstream ETL tool (Fivetran, Stitch, custom scripts) to land that data in your warehouse first.
Improvado starts earlier in the pipeline. It connects directly to 500+ marketing platforms, extracts campaign-level data, normalizes naming conventions (Facebook's "campaign_name" becomes the same field as Google Ads' "campaign"), applies governance rules (flags budget overruns, enforces UTM parameters), and outputs clean, analysis-ready data. From there, the data flows to any BI tool — including Looker.
Connector Breadth: Marketing APIs vs. Databases
Looker connects to over 1,050 data sources — primarily SQL databases (BigQuery, PostgreSQL, MySQL), Google services (Analytics, Ads, Sheets), and a handful of SaaS tools via partner connectors. It's designed to query data in place, not to extract and move it.
Improvado maintains 500+ pre-built connectors for advertising platforms, analytics tools, CRMs, and marketing automation systems. The library includes niche sources like The Trade Desk, AppsFlyer, Adjust, and Kochava — platforms that don't have native Looker connectors. When a platform isn't covered, Improvado builds custom connectors under a 2–4 week SLA, maintains them through API changes, and preserves 2 years of historical data during migrations.
The difference: Looker connectors assume someone else is managing the API relationship. Improvado owns it end-to-end. When Facebook deprecates an API endpoint or LinkedIn changes its rate limits, Improvado updates the connector automatically. Looker users relying on partner-built connectors often face breakages with no clear owner to fix them.
Transformation: LookML Modeling vs. Marketing Normalization
Looker's transformation layer is LookML — a code-based modeling language that defines metrics, dimensions, joins, and business logic in version-controlled files. It's powerful for analysts who think in SQL and want a single source of truth for KPIs. But LookML doesn't transform raw API data into a usable schema — it models data that's already been cleaned and structured upstream.
Improvado automates the transformation step most marketing teams struggle with: normalizing inconsistent field names, handling schema changes across platforms, and unifying metrics into a common taxonomy. The Marketing Cloud Data Model (MCDM) pre-defines standard dimensions (campaign, ad group, creative) and metrics (impressions, clicks, conversions) so teams don't rebuild the same transformations for every new data source.
For marketers without SQL skills, Improvado provides a no-code interface to map fields, create calculated metrics, and apply transformations. For engineers who want control, full SQL access is available. Looker requires LookML proficiency — there's no drag-and-drop escape hatch for non-technical users.
Marketing Data Governance: Pre-Built Rules vs. Custom Configuration
Looker provides enterprise data governance — row-level security, permissions by role, data lineage tracking. It's designed for IT and data teams managing access to sensitive information across departments. What it doesn't include: marketing-specific validation.
Improvado's Marketing Data Governance layer includes 250+ pre-built rules that catch errors before they corrupt dashboards. Budget pacing alerts notify teams when spend deviates from plan. UTM parameter enforcement flags campaigns missing required tracking codes. Schema validation prevents API changes from breaking downstream reports. Pre-launch checks verify that new campaigns include all necessary metadata.
The difference matters when a campaign launches with a typo in the UTM source parameter, or when a platform's API silently changes how it reports conversions. Looker will visualize whatever data arrives — garbage in, visualized garbage out. Improvado stops the bad data at ingestion and alerts the team to fix it.
“If we don't trust the data, the agency won’t trust the reports and won't give them to the client. They’ll start pulling data manually to Excel and spend a lot of time comparing platform numbers to reports. With Improvado, we now trust the data. If anything is wrong, it’s how someone on the team is viewing it, not the data itself. It’s 99.9% accurate.”
When to Choose Looker
Looker is the right choice in specific scenarios where its strengths align with your team's structure and data maturity.
- Your data engineering team owns the marketing data pipeline. If you have dedicated engineers managing DBT transformations, maintaining API connectors, and ensuring data quality before it hits the warehouse, Looker adds a governed visualization layer on top of that foundation.
- You need cross-functional BI, not just marketing analytics. Looker serves finance, product, sales, and operations teams equally well. If marketing is one of many departments using the platform, Looker's general-purpose design is an advantage.
- Your analysts are SQL-literate and want modeling control. LookML gives technical users precise control over metric definitions, join logic, and aggregation rules. Teams with strong analytics engineering practices benefit from the reusability and version control.
- You're deeply embedded in the Google Cloud ecosystem. Looker integrates natively with BigQuery, Google Analytics 4, and Google Ads. If your entire stack runs on GCP, the friction is lower than introducing a third-party ETL tool.
- You need embedded analytics in customer-facing applications. Looker's embedding capabilities and API-first design support operational workflows and white-labeled dashboards better than Improvado's analyst-focused interface.
What Customers Say
Marketing teams that have migrated from BI-only setups to Improvado cite time savings, data quality improvements, and the elimination of engineering bottlenecks as primary drivers.
At the University of San Francisco, the Digital Marketing team was responsible for reporting performance across 11+ marketing channels used by six different schools within the university. However, this process, at some point, turned into a significant operational burden. Read full case study →
“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.”
At Signal Theory, for most clients, the reporting process is now fully automated, taking 30 minutes to an hour at most. For clients with unique data sources requiring manual input, the system is flexible enough to accommodate specific needs without compromising overall efficiency. Read full case study →
“Reports that used to take hours now only take about 30 minutes. We're reporting for significantly more clients, even though it is only being handled by a single person. That's been huge for us.”
Improvado maintains a 9.0/10 quality-of-support rating on G2, compared to Looker's 8.6/10. The difference reflects the service model: Improvado includes a dedicated customer success manager and professional services in the base contract. Looker's enterprise support is available, but often requires escalation through ticketing systems for technical issues.
Pricing: Subscription Model vs. Outcome-Based
Looker operates on an enterprise subscription model with pricing based on user count, API call volume, and deployment type. Public pricing isn't available — quotes vary by organization size and negotiation. G2 reviews mention high costs and steep user-based fees that escalate as teams grow.
Improvado uses outcome-based pricing tied to the number of data sources, data volume, and required connectors. The model is designed for predictable annual budgets — no surprise overages when query volume spikes or a new analyst joins the team. Professional services, dedicated CSMs, and ongoing connector maintenance are included, not billed separately.
Total Cost of Ownership
Looker's sticker price doesn't include the upstream ETL infrastructure. Teams need to budget for:
- An ETL tool (Fivetran, Stitch, or custom engineering time) to extract marketing data
- DBT Cloud or equivalent for transformation logic
- Data engineering time to build and maintain LookML models
- Warehouse costs (BigQuery, Snowflake) scaled to marketing data volume
- Training and onboarding for LookML (steep learning curve for non-technical marketers)
Improvado consolidates those line items into a single platform fee. The engineering effort to maintain connectors, normalize schemas, and apply governance is handled by Improvado's team, not yours.
Frequently Asked Questions
What is the main difference between Improvado and Looker?
Improvado is a marketing data platform that extracts, transforms, and governs data from 500+ advertising and analytics sources before delivering it to warehouses or BI tools. Looker is a BI platform that visualizes and models data that already exists in databases — it doesn't handle extraction or normalization. Teams often use both: Improvado for the upstream pipeline, Looker for governed self-service reporting.
Can Improvado replace Looker?
No. Improvado handles data aggregation, transformation, and governance — the ETL layer. Looker provides visualization, semantic modeling, and exploration — the BI layer. Improvado is compatible with Looker and can deliver data to it. If your team only needs dashboards and your data pipeline is already managed elsewhere, Looker alone may suffice. If you need to extract and normalize marketing data, you'll need a tool like Improvado upstream.
Does Looker integrate with marketing platforms like Facebook Ads and Google Ads?
Looker connects to Google Ads natively and to other platforms through partner-built connectors. However, these connectors often break during API updates and require manual fixes. Looker doesn't maintain them the way a dedicated marketing ETL tool does. For reliable, continuous data from 500+ marketing sources, a purpose-built integration platform is required.
How long does it take to migrate from Looker to Improvado?
Migration isn't the right framing — the tools solve different problems. If you're currently using Looker to visualize marketing data that's manually aggregated or pulled from fragmented sources, adding Improvado upstream typically takes 2–4 weeks. Improvado handles extraction and transformation; Looker continues to handle visualization. Most teams keep both in their stack.
Is Improvado harder to use than Looker?
For non-technical marketers, Improvado is easier. It provides a no-code UI for mapping data sources, creating metrics, and setting up dashboards. Looker requires LookML proficiency — a code-based modeling language that has a steep learning curve for users without SQL backgrounds. Improvado is designed for marketing ops teams; Looker is designed for analytics engineers.
What does Improvado cost compared to Looker?
Looker pricing is enterprise-only and not publicly listed. Costs scale with user count and API call volume. Improvado uses outcome-based pricing tied to data sources, volume, and connectors — designed for predictable annual budgets. When comparing total cost of ownership, include the ETL tools, DBT subscriptions, and engineering time required to support Looker's upstream pipeline.
Does Improvado offer the same level of data governance as Looker?
Improvado and Looker govern different parts of the data pipeline. Looker provides row-level security, permissions management, and semantic consistency for BI consumers. Improvado provides marketing-specific governance at ingestion — budget pacing alerts, UTM enforcement, schema validation, and pre-launch checks. Both are necessary for a complete governance framework; neither replaces the other.
Can I use Improvado with Looker?
Yes. This is a common architecture. Improvado extracts and transforms marketing data from 500+ sources, applies governance, and delivers it to your data warehouse (BigQuery, Snowflake, Redshift). Looker connects to that warehouse and provides the visualization, exploration, and semantic modeling layer. The combination eliminates the need for custom ETL scripts or fragile third-party connectors.
Ready to See the Difference?
If your marketing team spends more time fixing data pipelines than analyzing performance, it's time to evaluate a purpose-built solution. Improvado handles the extraction, transformation, and governance that general BI tools assume someone else has solved.
FAQ
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