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Chartio shut down in March 2022 after its acquisition by Atlassian. Teams that relied on Chartio's cloud-based BI platform had to migrate—fast.
The challenge wasn't just finding a tool that could visualize data. Marketing analysts needed connectors that actually understood marketing metrics, transformation layers that didn't require SQL for every campaign report, and dashboards that stakeholders could trust without constant verification. Most generic BI tools fail at least one of these requirements.
This guide evaluates 10 Chartio alternatives built for marketing analytics. You'll see what each platform does well, where it falls short, and which use cases it's actually designed to solve. By the end, you'll know exactly which tools to demo based on your team size, technical resources, and reporting complexity.
✓ Chartio users need platforms that centralize marketing data sources without requiring engineering support for every new connector or schema change.
✓ The best alternatives combine pre-built marketing integrations, automated data transformation, and flexible visualization layers that work with your existing BI stack.
✓ Enterprise teams should prioritize platforms with built-in data governance, historical data preservation during API migrations, and dedicated customer success resources.
✓ No-code tools work well for standardized reporting, but fall apart when you need custom attribution models, cross-channel analysis, or API-level control.
✓ Migration speed matters—look for platforms that offer professional services, pre-built data models, and compatibility with your current warehouse and dashboard tools.
What Was Chartio?
Chartio was a cloud-based business intelligence platform that allowed teams to connect data sources, build SQL queries through a visual interface, and create dashboards without writing code. It became popular with mid-market companies because it balanced accessibility for non-technical users with enough flexibility for analysts who needed custom queries.
After Atlassian acquired Chartio in 2021, the platform was sunset in March 2022. Atlassian chose not to integrate Chartio's features into its own product suite, leaving thousands of users searching for replacements. For marketing teams specifically, this created an urgent need: most generic BI tools lacked the marketing-specific connectors, attribution logic, and campaign-level granularity that Chartio users had built their reporting stack around.
How to Choose a Chartio Alternative: Evaluation Criteria
Not every BI platform is built for marketing analytics. When evaluating Chartio alternatives, focus on these criteria:
Marketing-native data connectors. Generic BI tools offer 50–100 connectors. Marketing platforms generate new metrics every quarter—TikTok Ads, Reddit Ads, Performance Max campaigns. Your replacement needs either a massive connector library (500+) or a guarantee that new sources get added within weeks, not months.
Transformation logic that understands marketing data. UTM parameters, multi-touch attribution, campaign hierarchies, cost-per-action calculations—these require more than raw SQL. Look for platforms with pre-built marketing data models or transformation templates that don't force you to reinvent attribution logic from scratch.
Warehouse compatibility and BI flexibility. If you've already invested in Snowflake, BigQuery, or Redshift, your alternative should write directly to your warehouse in your schema. If you use Looker, Tableau, or Power BI for visualization, the platform should integrate natively—not force you into a proprietary dashboarding layer.
Historical data preservation during API changes. Ad platforms change their APIs constantly. Facebook deprecates fields, Google Ads restructures campaign types, LinkedIn shifts metrics. Your tool should either maintain historical mappings automatically or give you enough notice and migration support to avoid data gaps.
Support model and implementation speed. Chartio users valued quick onboarding. Some alternatives assign a customer success manager and include professional services in the base contract. Others charge separately for implementation or leave you with documentation and a Slack channel. Know which model you're buying into before signing.
Improvado: Marketing Data Platform Built for Multi-Channel Attribution
Improvado is a marketing-specific data platform that centralizes over 500 data sources, transforms marketing data using pre-built models, and delivers clean datasets to any BI tool or data warehouse. It's designed for marketing teams at mid-market and enterprise companies who need reliable, attribution-ready data without building a custom ETL stack.
Why Marketing Teams Choose Improvado
Improvado solves the connector problem that generic BI tools ignore. With 500+ pre-built integrations—Google Ads, Meta, LinkedIn, Salesforce, HubSpot, TikTok, Reddit, and dozens of niche ad platforms—you don't wait months for new sources. Custom connectors are delivered in 2–4 weeks under SLA.
The platform extracts 46,000+ marketing metrics and dimensions, then applies transformation logic through its Marketing Cloud Data Model (MCDM). This means UTM normalization, campaign hierarchy mapping, and multi-touch attribution calculations happen automatically, not in 300 lines of SQL you have to maintain.
Improvado preserves 2 years of historical data even when ad platforms change their APIs. When Facebook deprecates a metric or Google Ads restructures campaign types, your historical reports don't break—Improvado maintains backward-compatible mappings and alerts you to schema changes before they affect dashboards.
Unlike platforms that lock you into proprietary dashboards, Improvado writes to your existing warehouse (Snowflake, BigQuery, Redshift) and works with any BI tool (Looker, Tableau, Power BI, custom dashboards). You keep full SQL access while non-technical users interact through a no-code interface.
“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.”
Every contract includes a dedicated customer success manager and professional services—not as an add-on, but as part of the implementation. Most teams connect their first data sources within two weeks.
When Improvado Isn't the Right Fit
Improvado is built for marketing analytics at scale. If you're a five-person startup running two ad platforms and need basic dashboards, the platform's enterprise feature set and pricing model will exceed what you need. Teams with fewer than 10 marketing data sources and no plans to scale into multi-touch attribution or cross-channel analysis should consider lighter-weight BI tools first.
The platform also assumes you want centralized marketing data in a warehouse or BI tool. If your team prefers to work directly inside spreadsheets and has no interest in SQL access, data governance, or historical schema management, Improvado's architecture may feel like overhead.
Looker: Enterprise BI with Strong Data Modeling
Looker is a business intelligence platform owned by Google Cloud that uses a semantic layer (LookML) to define metrics once and reuse them across dashboards. It's popular with data teams that want centralized metric definitions and version-controlled reporting logic.
Why Data Teams Choose Looker
Looker's LookML layer allows analysts to define metrics, joins, and business logic in code, then expose those definitions to non-technical users through a visual interface. This prevents the "ten different versions of CAC" problem—everyone queries the same metric because it's defined centrally.
For teams already on Google Cloud, Looker integrates natively with BigQuery and benefits from Google's infrastructure. Version control for LookML models means changes to reporting logic are tracked, reviewed, and deployed like software code.
Where Looker Falls Short for Marketing Analytics
Looker is a visualization and semantic layer, not a data integration platform. You still need to build or buy connectors to get marketing data into your warehouse. If you're migrating from Chartio, Looker doesn't solve the "how do I get Facebook Ads, LinkedIn, Salesforce, and Google Analytics into one place" problem—it assumes that data is already there.
LookML requires SQL knowledge and a mindset shift. Marketing analysts who were comfortable in Chartio's visual query builder often find Looker's code-first approach steep. Setting up a new data source means writing or modifying LookML, not clicking through a UI.
Pricing is per-user and scales quickly. For agencies or companies with dozens of stakeholders who need view-only access, costs add up fast compared to platforms that charge by data volume or席connector count.
Tableau: Market-Leading Visualization with Broad Adoption
Tableau is one of the most widely deployed BI tools globally, known for its powerful visualization engine and drag-and-drop interface. It's used across industries for everything from financial reporting to operational dashboards.
Why Tableau Remains Popular
Tableau's visualization flexibility is unmatched. If you need custom chart types, interactive filters, or pixel-perfect executive dashboards, Tableau delivers. The platform supports dozens of data sources natively and allows analysts to blend data from multiple connections in a single workbook.
Tableau's user base is enormous, which means extensive community support, third-party training, and a mature ecosystem of consultants. If you hire a BI analyst, they likely already know Tableau.
Why Marketing Teams Outgrow Tableau
Like Looker, Tableau is a visualization tool, not a data pipeline. It doesn't extract data from marketing APIs—you need separate ETL tools or custom scripts to populate your warehouse. For ex-Chartio users, this means adding another vendor or building in-house connectors.
Tableau's refresh schedules and extract limitations frustrate teams that need real-time or hourly campaign data. Extracts can be slow to update, and live connections to cloud warehouses often hit performance issues when querying large marketing datasets.
Marketing-specific features—UTM parsing, attribution modeling, campaign hierarchy rollups—don't exist out of the box. You either build these in SQL before Tableau touches the data, or you recreate them as calculated fields in every workbook, leading to inconsistency across reports.
Power BI: Microsoft-Native BI for Office 365 Teams
Power BI is Microsoft's business intelligence platform, tightly integrated with Excel, Azure, and the broader Office 365 ecosystem. It's a natural choice for companies already invested in Microsoft infrastructure.
Why Microsoft Shops Choose Power BI
If your organization runs on Office 365, Power BI's integration with Excel, Teams, and SharePoint makes adoption frictionless. Reports embed directly into Teams channels, and users can start building dashboards using familiar Excel-like formulas (DAX).
Pricing is significantly lower than Tableau or Looker for teams that only need basic dashboarding. Power BI Pro licenses cost a fraction of enterprise BI seats, making it accessible for mid-market budgets.
Where Power BI Struggles with Marketing Data
Power BI's connector library lags behind competitors for marketing platforms. While it supports Google Analytics and Facebook Ads, niche ad platforms—TikTok Ads, Reddit Ads, Bing Ads API v13—often require custom connectors or third-party tools.
DAX (Power BI's formula language) has a steep learning curve for analysts coming from SQL-based tools like Chartio. Marketing attribution logic, multi-touch modeling, and UTM normalization require DAX expertise that most marketing analysts don't have.
Performance degrades quickly with large datasets. Marketing data—especially raw event logs or hourly ad performance snapshots—can exceed Power BI's optimal dataset size, leading to slow refreshes and timeout errors.
Sisense: Embedded Analytics for Product Teams
Sisense is a BI platform designed for embedding analytics into SaaS products and building custom dashboards for external users. It's popular with software companies that want to offer analytics as a product feature.
When Sisense Makes Sense
Sisense excels at white-labeled, customer-facing analytics. If you're a SaaS company that needs to embed dashboards into your product—showing customers their campaign performance, usage analytics, or ROI metrics—Sisense provides the infrastructure and APIs to do that at scale.
The platform's ElastiCube technology allows in-memory data processing, which can speed up queries for moderate datasets without requiring a separate data warehouse.
Why Marketing Teams Avoid Sisense
ElastiCubes are resource-intensive and expensive. For internal marketing analytics—where you're not monetizing dashboards—the infrastructure cost often exceeds the value delivered. Multiple reviews cite Sisense as too expensive for what it provides.
Marketing connector coverage is weak. Sisense focuses on embedded use cases, not on maintaining hundreds of ad platform integrations. If you're replacing Chartio, you'll need a separate ETL tool to get campaign data into Sisense.
The platform is overkill for teams that just need internal dashboards. Unless you're embedding analytics into a customer-facing product, Sisense's feature set and pricing model won't align with a straightforward "replace Chartio" migration.
Domo: Cloud-Native BI with Built-In ETL
Domo is a cloud BI platform that combines data integration, transformation, and visualization in one tool. It's marketed as an all-in-one solution for companies that want to avoid managing separate ETL and BI vendors.
What Domo Does Well
Domo includes native connectors for hundreds of data sources, including major marketing platforms. Unlike pure BI tools, it handles extraction and transformation, reducing the need for separate ETL infrastructure.
The platform's "Magic ETL" feature provides a visual interface for building data pipelines, making it accessible to analysts who don't write SQL. For teams that need quick dashboard deployment without engineering support, Domo's all-in-one approach can accelerate time-to-value.
Where Domo Falls Short
Domo's proprietary data layer locks you in. Data lives inside Domo's cloud environment—you can't write to your own Snowflake or BigQuery warehouse and use Domo purely as a visualization layer. This creates vendor lock-in and limits interoperability with other tools in your stack.
Pricing is opaque and scales unpredictably. Domo charges based on data volume, user count, and feature tiers in ways that aren't transparent upfront. Teams often report surprise cost increases as usage grows.
Marketing-specific transformation logic is limited. While Domo can connect to ad platforms, it doesn't include pre-built attribution models, UTM normalization rules, or campaign hierarchy mappings. You'll rebuild these manually in Magic ETL, which reintroduces the maintenance burden Chartio users were trying to avoid.
- →Your data team spends more time fixing broken connectors than analyzing campaigns—every API change becomes a two-week firefight
- →Reports show different CAC numbers depending on who built the dashboard, and no one trusts the attribution model anymore
- →New ad platforms (TikTok, Reddit, Performance Max) take 6+ months to integrate because your BI vendor doesn't prioritize marketing sources
- →Historical data disappears every time Facebook or Google deprecates a metric, forcing you to rebuild reports from scratch
- →You're paying for three separate tools—one for ETL, one for transformation, one for visualization—and none of them talk to each other cleanly
GoodData: Embedded Analytics for High-Security Environments
GoodData is an analytics platform focused on embedded use cases and industries with strict data governance requirements, such as healthcare and financial services. It's SOC 2 and HIPAA certified, making it suitable for regulated environments.
When GoodData Is the Right Choice
For companies that need to embed analytics into customer-facing applications while maintaining strict security and compliance standards, GoodData provides the infrastructure and certifications required. Its multi-tenant architecture allows SaaS companies to isolate customer data while serving analytics at scale.
Why Ex-Chartio Users Struggle with GoodData
GoodData demands high technicality, hiding data and insights from non-technical users and making adaptation extremely difficult for ex-Chartio users. Marketing analysts who were comfortable in Chartio's visual interface find GoodData's learning curve steep and its workflows unintuitive.
The platform's focus on embedded analytics means it under-invests in internal-use features like ad-hoc querying, collaborative dashboarding, and self-service exploration. If you're not embedding analytics into a product, much of GoodData's feature set is irrelevant.
Marketing connector support is weak. GoodData prioritizes transactional and operational data sources over advertising APIs, leaving teams to build custom integrations or rely on third-party ETL tools.
Metabase: Open-Source BI for Startups and Small Teams
Metabase is an open-source business intelligence tool that provides a simple query builder and dashboarding interface. It's popular with startups and small companies that need basic analytics without enterprise licensing costs.
Why Small Teams Choose Metabase
Metabase is free to self-host, making it the most budget-friendly option on this list. For early-stage companies with one or two analysts and straightforward reporting needs, Metabase delivers dashboards without vendor lock-in or subscription fees.
The interface is clean and intuitive. Non-technical users can build simple queries using a visual question builder, while analysts can drop into SQL for custom logic. Setup takes hours, not weeks.
When Teams Outgrow Metabase
Metabase has minimal built-in ETL. You need separate tools to get marketing data into your database—it only visualizes what's already there. For ex-Chartio users, this means adding another layer to your stack or writing custom scripts to pull from ad platform APIs.
As teams scale past 10–15 users, Metabase's lack of enterprise features becomes painful. No role-based access control, limited version control for dashboards, and weak collaboration tools mean governance becomes manual and error-prone.
Support is community-based unless you pay for Metabase Cloud. If a connector breaks or a query fails, you're troubleshooting in GitHub issues, not escalating to a support team with SLAs.
InsightSquared: Revenue Analytics for Sales and Marketing Alignment
InsightSquared is a revenue intelligence platform designed to align sales and marketing teams around pipeline data, campaign attribution, and forecasting. It integrates directly with CRMs like Salesforce and HubSpot.
What InsightSquared Does Well
InsightSquared specializes in closed-loop marketing attribution—tracking how campaigns influence pipeline and revenue. For B2B teams that need to connect ad spend to won deals, InsightSquared provides pre-built reports and models that sales and marketing teams both understand.
The platform's Salesforce integration is deep and reliable. If your reporting revolves around opportunity stages, lead sources, and sales cycle metrics, InsightSquared offers more context than generic BI tools.
Where InsightSquared Falls Short
InsightSquared produces static and non-customizable charts that can't be embedded or white-labeled. Marketing analysts used to Chartio's flexibility will find InsightSquared's reporting rigid and hard to adapt to unique campaign structures or attribution models.
The platform is CRM-first, not marketing-platform-first. While it connects to Google Ads and LinkedIn, its connector library is narrow compared to Improvado, Domo, or even Power BI. If you run campaigns on TikTok, Reddit, or niche B2B ad networks, you'll need a separate ETL layer.
Pricing is high relative to functionality. InsightSquared targets mid-market and enterprise sales teams, and its licensing reflects that positioning. For marketing teams that don't need revenue forecasting or sales pipeline analysis, the cost often exceeds the value delivered.
Toucan Toco: Storytelling-Focused BI for Executive Reporting
Toucan Toco is a BI platform built around data storytelling and narrative-driven dashboards. It's designed for executive reporting and stakeholder communication, emphasizing visual clarity over ad-hoc analysis.
When Toucan Toco Excels
Toucan's interface prioritizes readability and narrative flow. If your primary use case is monthly executive dashboards or board-level reporting, Toucan's templates and design system produce polished, presentation-ready outputs faster than tools like Tableau or Looker.
Quick onboarding, often two weeks or less, gets teams from contract signature to live dashboards quickly. Toucan's customer success model includes a 2-week process with Trello boards, videos, and customer success support, reducing time-to-value compared to platforms that leave you with documentation.
Why Analysts Avoid Toucan Toco
Toucan's focus on storytelling limits flexibility for ad-hoc analysis. Marketing analysts who need to slice data by custom dimensions, run exploratory queries, or build one-off reports will find Toucan's template-driven approach restrictive.
The platform's connector library is small. Toucan integrates with major data warehouses but doesn't maintain direct connections to hundreds of marketing platforms. You'll need a separate ETL tool to centralize campaign data before Toucan can visualize it.
Toucan is overkill if your team needs operational dashboards refreshed hourly or daily. The platform is optimized for periodic, high-level reporting—not real-time campaign monitoring or performance alerting.
Zoho Analytics: Budget-Friendly BI for Zoho Ecosystem Users
Zoho Analytics is a self-service BI tool from Zoho Corporation, designed to integrate seamlessly with Zoho's suite of business applications (CRM, Campaigns, Social, etc.). It's a cost-effective option for small businesses already using Zoho products.
Why Zoho Users Choose Zoho Analytics
If your team already uses Zoho CRM, Zoho Campaigns, or Zoho Social, Zoho Analytics connects natively with zero configuration. Data flows automatically from Zoho apps into dashboards, eliminating the need for custom integrations.
Pricing is significantly lower than enterprise BI tools. For small teams with basic reporting needs, Zoho Analytics delivers dashboards at a fraction of the cost of Looker, Tableau, or Domo.
When Zoho Analytics Isn't Enough
Zoho Analytics is built for the Zoho ecosystem. While it supports some third-party connectors, coverage for major advertising platforms—Google Ads, Meta, LinkedIn, TikTok—is incomplete or requires manual CSV uploads. Ex-Chartio users expecting seamless API-based integrations will be disappointed.
The platform lacks advanced features like version control, role-based governance, or SQL-level transformation logic. For marketing teams that need attribution modeling, custom metrics, or complex joins across data sources, Zoho Analytics quickly hits functional limits.
Performance degrades with larger datasets. Zoho Analytics is optimized for small business use cases—thousands of rows, not millions. Marketing event data or granular ad performance logs will slow queries and exceed the platform's practical limits.
Chartio Alternatives Comparison Table
| Platform | Best For | Marketing Connectors | ETL Included | Pricing Model | Key Limitation |
|---|---|---|---|---|---|
| Improvado | Mid-market & enterprise marketing teams | 500+ pre-built, custom in 2–4 weeks | Yes, with MCDM transformation | Custom (volume + sources) | Overkill for teams under 10 sources |
| Looker | Data teams needing centralized metrics | None (visualization layer only) | No | Per-user | Requires LookML expertise, no ETL |
| Tableau | Analysts needing flexible visualizations | Limited, requires separate ETL | No | Per-user | No marketing-specific features |
| Power BI | Microsoft-native organizations | Limited, gaps in niche platforms | Basic | Per-user | DAX learning curve, performance issues |
| Sisense | SaaS companies embedding analytics | Limited | Yes (ElastiCube) | Custom (infrastructure + users) | Expensive, weak marketing connectors |
| Domo | All-in-one BI for mid-market | Moderate | Yes (Magic ETL) | Opaque (volume + users) | Vendor lock-in, limited attribution logic |
| GoodData | Regulated industries, embedded analytics | Minimal | No | Custom | High technicality, weak marketing support |
| Metabase | Startups, small teams | None (connects to databases) | No | Free (self-hosted) or per-user (cloud) | No ETL, limited governance |
| InsightSquared | B2B sales & marketing alignment | CRM-focused, limited ad platforms | Partial | Per-user | Static reports, narrow connector library |
| Toucan Toco | Executive reporting, data storytelling | Minimal | No | Custom | Limited ad-hoc analysis, small connector library |
| Zoho Analytics | Zoho ecosystem users | Zoho apps only, limited external | No | Per-user | Weak third-party connectors, performance limits |
How to Get Started with a Chartio Alternative
Migrating from Chartio requires more than picking a new dashboard tool. Follow this process to ensure your replacement actually solves the problems Chartio left behind:
Step 1: Audit your current data sources and reporting requirements. List every platform you connect to—ad networks, CRMs, analytics tools, attribution platforms. Note which reports are business-critical and which metrics you can't afford to lose during migration. This inventory becomes your vendor evaluation checklist.
Step 2: Decide whether you need ETL, BI, or both. If you already have a data warehouse and just need visualization, pure BI tools like Looker or Tableau work. If you need to centralize marketing data first, prioritize platforms with built-in ETL (Improvado, Domo) or plan to add a separate integration layer.
Step 3: Test with your most complex use case, not your simplest. Vendors demo their best features. Instead, give them your messiest report—the one with five data sources, custom attribution, and UTM normalization logic. See how much of that complexity their platform handles natively versus how much you'll rebuild manually.
Step 4: Verify historical data handling and API change management. Ask vendors: "What happens when Facebook deprecates a metric I use in 30 dashboards?" Platforms that preserve historical mappings and alert you to schema changes prevent data gaps. Those that don't will leave you fixing broken reports every quarter.
Step 5: Negotiate implementation support into your contract. Professional services, dedicated CSMs, and custom connector builds shouldn't be add-ons—they should be part of the deal. Clarify upfront what's included in onboarding, how quickly new connectors get built, and what ongoing support looks like.
Conclusion
Chartio's shutdown forced marketing teams to confront a reality most had deferred: generic BI tools weren't built for the complexity of modern marketing data. The alternatives that work best—Improvado, Looker, Tableau, Power BI—solve different parts of the problem. Some centralize data but limit visualization flexibility. Others offer powerful dashboards but assume your data is already clean and connected.
The right replacement depends on what you need most. If you're a data team with engineering resources and an existing warehouse, Looker or Tableau might suffice. If you're a marketing team drowning in connector maintenance, attribution modeling, and schema changes, you need a platform that treats marketing data as a first-class problem—not an afterthought.
Don't optimize for the easiest demo. Optimize for the problem you'll face six months from now: when TikTok changes its API, when your CFO asks for multi-touch attribution, when your agency needs white-labeled reports for 15 clients. The platform that handles those scenarios without escalating to engineering is the one worth migrating to.
Frequently Asked Questions
Why did Chartio shut down?
Chartio shut down in March 2022 following its acquisition by Atlassian in 2021. Atlassian chose not to integrate Chartio's BI capabilities into its own product suite and instead discontinued the platform entirely. This left existing Chartio users with a migration deadline and no direct replacement from Atlassian. The shutdown reflected Atlassian's strategic focus on collaboration and project management tools rather than standalone business intelligence platforms.
Are there free Chartio alternatives?
Metabase is the most viable free alternative for teams willing to self-host. It provides basic dashboarding and SQL querying without licensing fees, though you'll need to manage server infrastructure and handle updates yourself. However, free tools lack enterprise features like advanced governance, dedicated support, and automated marketing data integrations. For production marketing analytics, most teams find that free tools introduce hidden costs in engineering time, maintenance, and data quality issues that exceed the cost of a paid platform.
How long does it take to migrate from Chartio?
Migration timelines vary based on the complexity of your reporting stack and the platform you choose. Teams with fewer than 10 data sources and standard dashboards often complete migration in 2–4 weeks. Enterprise teams with custom attribution models, dozens of connectors, and complex transformation logic typically require 6–12 weeks. Platforms that offer professional services and pre-built marketing data models (like Improvado) accelerate timelines by handling connector setup and schema mapping upfront, while self-service tools push those tasks onto your team.
Can I preserve my existing Chartio dashboards?
You cannot directly import Chartio dashboards into most alternatives—each platform uses different data models and visualization APIs. However, you can recreate reports by exporting your underlying data schemas and query logic from Chartio before the shutdown deadline. Document which data sources feed each dashboard, what transformations are applied, and which metrics are calculated versus raw. Most modern BI tools offer visual query builders or SQL interfaces that can replicate Chartio's functionality, though you'll rebuild the dashboards manually in the new platform's interface.
What's the best Chartio alternative for small marketing teams?
For teams under 10 people with limited technical resources, Power BI offers the best balance of cost, ease of use, and Microsoft ecosystem integration. If your organization doesn't use Office 365, Metabase (self-hosted) or Zoho Analytics (if you're in the Zoho ecosystem) provide budget-friendly options. However, all three require separate ETL tools to centralize marketing data—they only visualize what's already in your database. If your team needs automated data pipelines and marketing-specific connectors without hiring engineers, a platform like Improvado delivers faster time-to-value despite higher upfront cost.
Which Chartio alternative is best for enterprise marketing teams?
Enterprise teams should prioritize platforms that combine robust ETL, governance features, and dedicated support. Improvado leads this category with 500+ marketing connectors, SOC 2 Type II compliance, historical data preservation during API changes, and included professional services. Looker is a strong choice if you already have engineering resources managing data pipelines and need centralized metric definitions across business units. Tableau works for organizations that require pixel-perfect executive dashboards and have existing data infrastructure. Avoid platforms that lack SLA-backed support, custom connector guarantees, or enterprise security certifications—those gaps become critical pain points at scale.
How do I preserve historical data when switching from Chartio?
Before Chartio's shutdown, export all raw data tables from your connected sources to a data warehouse (Snowflake, BigQuery, or Redshift) or to CSV backups. Most alternatives won't backfill historical data beyond API rate limits—if a platform can only pull 90 days of Facebook Ads history via API, data older than that must come from your archives. When evaluating alternatives, ask vendors how far back they can extract historical data and whether they preserve old schema versions when ad platforms change APIs. Platforms like Improvado maintain 2-year historical mappings automatically, preventing data loss during platform migrations or API deprecations.
Do Chartio alternatives support multi-touch attribution modeling?
Most generic BI tools (Looker, Tableau, Power BI) do not include pre-built attribution models—you must build attribution logic in SQL or using calculated fields, then maintain it as your campaign structure evolves. Marketing-specific platforms like Improvado include attribution frameworks as part of their Marketing Cloud Data Model, allowing teams to configure first-touch, last-touch, linear, time-decay, or custom attribution without writing code. InsightSquared offers CRM-based attribution for B2B pipeline tracking but lacks support for upper-funnel ad platforms. If attribution is central to your reporting, choose a platform that treats it as a core feature, not a custom project.
FAQ
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