The Ultimate Guide to
Supermetrics Alternatives
It is Monday morning. Your client reports are due in an hour, and your Supermetrics for Google Sheets refresh just timed out—again. You are not alone. Here is the definitive, fluff-free breakdown of the 8 best marketing data connectors on the market today.
The Top 8 Supermetrics Alternatives at a Glance
| Platform | Best For | Pricing Model | Query Speed | Starting Price |
|---|---|---|---|---|
| Metric Might | Agencies & Sheets Power Users | Flat Fee (Unlimited Accounts) | Sub-3 seconds | $0 (Free Tier) / $99 Agency |
| Dataslayer | Mid-market Agencies | Tiered (Unlimited Users) | Standard / Queue | €25/mo |
| Windsor.ai | Attribution Modeling | Tiered (By features) | Standard / Queue | $19/mo |
| Funnel.io | Enterprise Data Hubs | Flexpoints (Credit-based) | Batch Processing | ~$400/mo |
| Fivetran | Data Engineering Teams | MARs (Monthly Active Rows) | Warehouse Sync | $500/mo |
| Improvado | Massive Scale (100M+ rows) | Custom Enterprise | Batch Processing | Contact Sales |
| Whatagraph | Visual Reporting | Tiered | In-app only | $223/mo |
| Porter Metrics | Looker Studio Beginners | Pay Per Connection | Standard / Queue | $15/mo |
Why Everyone is Looking for a Supermetrics Alternative in 2026
If you are reading this, you likely fall into one of two camps: you are tired of your Google Sheets dashboards timing out, or you just received your annual renewal invoice and realized how much Supermetrics pricing has skyrocketed.
The reality is that Supermetrics is no longer the scrappy Google Sheets add-on it was in 2018. Having raised substantial venture capital and grown to over $50M in ARR, they have aggressively pivoted upmarket. Their target demographic is no longer the freelance marketer or the mid-sized agency; it is the enterprise data engineering team moving massive datasets into Snowflake and BigQuery.
Based on our conversations with hundreds of marketing operators, three critical failures are driving the mass exodus to alternative marketing data connectors:
1. Punitive Pricing
Supermetrics pricing scales aggressively. Their entry plan restricts you to just 3 basic data sources. Adding premium connectors, additional team seats, or scaling past 10 ad accounts per source requires massive tier jumps—often turning an affordable tool into a $5,000/year line item.
2. Architectural Timeouts
When you request data, it sits in a global server queue. During peak hours, your query waits behind thousands of other users, causing Google Sheets to hang and ultimately return API timeout errors.
3. Enterprise Bloat
As they added features for data lakes and complex ELT pipelines, the core experience degraded. Marketers who just want to pull Facebook Ads data into a pivot table are forced to navigate UI bloat meant for database administrators.
The Technical Truth: Why Does Supermetrics for Google Sheets Time Out?
Most alternative lists simply state that Supermetrics is "slow" without explaining why. The issue is deeply architectural. Supermetrics relies on a centralized, queue-based server architecture.
When you click "Refresh" in your Supermetrics for Google Sheets sidebar, your browser does not talk directly to Facebook or Google. Instead, your request is sent to Supermetrics' central servers. Because they process millions of queries daily, your specific request is placed into a global queue. It waits in line behind every other user globally until a server thread becomes available.
Once a thread is free, their server makes the API call to Facebook, waits for the payload, processes it, and then sends it back to your Google Sheet. If this entire round-trip takes longer than Google Apps Script's strict execution time limits for add-ons, the script dies. You get an "Error: Timeout" message, and your report remains blank. This is why modern tools are moving to front-end execution, bypassing the server queue entirely.
The Pre-Purchase Checklist: What to Check Before You Buy
It is easy to look at a marketing data connector's pricing page and think, "Wow, $39 a month is a steal!" But SaaS pricing pages are famously opaque. Before committing to any tool or migrating your client reports, you must verify these five hidden constraints:
1. Connector Tiering
Almost every legacy provider places Meta, Google Ads, and GA4 in their basic tier. But what happens when you land an e-commerce client who runs TikTok Ads or Pinterest Ads? Or a B2B client using LinkedIn Ads? Many competitors lock these "premium" connectors behind their $200+/month plans. Check the tier for your specific data sources before buying.
2. Refresh Frequency Limits
If you are running real-time Black Friday campaigns, a "daily" refresh isn't enough. Many entry-level plans strictly limit automated refreshes to once every 24 hours. If you need hourly data pulls or the ability to manually refresh a Google Sheet 50 times in a single afternoon during troubleshooting, ensure your plan doesn't throttle API calls.
3. The Multiple Destination Tax
Do you build internal diagnostic dashboards in Google Sheets, but present polished deliverables to clients in Looker Studio? Supermetrics and several others charge per destination. Pushing the exact same Facebook data to two different places could require purchasing two entirely separate licenses.
4. The "Seat Tax" for Analysts
As your agency grows, you will hire account managers, junior analysts, and media buyers. If your software charges per user, your overhead scales exponentially. Look for providers that offer unlimited users at the agency tier so you aren't penalized for hiring.
5. Historical Data Backfill Fees
When onboarding a new client, you typically want to pull their last 12-24 months of performance data to establish baselines. Many connectors limit historical data pulls on their entry-level tiers. For example, a basic plan might only allow you to pull the last 6 months of data. To pull 2 years of data, you often have to upgrade to an enterprise tier or pay a one-time historical backfill fee. Always check the "Lookback Window" limits before buying to avoid expensive surprises during client onboarding.
Understanding Data Pipeline Architectures
Before diving into the specific Supermetrics alternatives, you must understand the technical architecture you are buying. Marketing data tools fall into three distinct categories. Choosing the wrong one guarantees you will overpay or overwhelm your team.
Fast, Lightweight, Sheets-First
These tools are built for speed and agility. Instead of routing your query through a central server, tools like Metric Might execute the API call directly from your front-end browser logic.
- Pros: Lightning fast (sub-3 seconds), highly affordable, impossible to get stuck in a server queue.
- Cons: Cannot push data to enterprise data warehouses; limited to spreadsheets.
Extract, Transform, Load
These platforms act as a middleman database. They pull your data from the ad networks, store it on their servers, clean it, map currencies, harmonize naming conventions, and then push it to your dashboard.
- Pros: Incredible data cleanliness; perfect for massive enterprise budgets across 50+ ad networks.
- Cons: Extremely expensive (often $1,000+/mo), high learning curve, vendor lock-in.
Extract, Load, Transform (via SQL)
Built for data engineers. These tools extract raw data and dump it into BigQuery or Snowflake. All transformations (cleaning, merging) must be done manually by your engineers using SQL and tools like dbt.
- Pros: Ultimate control; highly scalable for technical teams.
- Cons: Useless for marketers who cannot write SQL. Pricing scales aggressively based on data volume.
1. Best Supermetrics Alternative for Agencies: Metric Might
The fast, flat-priced alternative built explicitly for Google Sheets.
Metric Might was designed by marketing operators to fix the two most glaring flaws of legacy connectors: punitive pricing multipliers and glacial execution speeds.
When you build a report in Supermetrics, your query is sent to a central server queue. If thousands of other marketers are running reports at the same time, you wait. Metric Might changes this paradigm entirely. Manual executions are handled directly by the front-end. By bypassing the central server queue, Metric Might delivers data directly into your spreadsheet in sub-3 seconds. It fully supports the most critical performance channels: Meta, Google Ads, GA4, TikTok Ads, LinkedIn Ads, Microsoft Ads, and Pinterest Ads.
When it comes to automation, scheduled refreshes are handled by highly efficient AWS Lambda functions, ensuring rock-solid daily and hourly updates without the massive overhead costs of running legacy server farms.
Pricing Implications in the Real World
Metric Might outright rejects the SaaS industry's obsession with "seat licenses" and "per-account limits." The Agency tier is a flat $99/month. In practice, this means an agency managing 30 Meta Ad accounts and 20 Google Ad accounts across 15 clients pays exactly $99. If they hire 5 new media buyers tomorrow and give them all access, the price remains $99. Your data pipeline cost is fixed, allowing your agency's profit margins to scale cleanly with every new client you onboard. Additionally, unlike Supermetrics, Metric Might offers a permanent Free tier (1 user, 1 account) for solo operators or extended testing.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Mid-sized to large marketing agencies (manage 5 to 50+ clients) whose primary system of record is Google Sheets. If you have multiple analysts pulling data, the unlimited users/accounts on the $99 flat-fee plan will save you thousands of dollars a year compared to Supermetrics pricing.
Who should skip it: Enterprise data engineering teams. Metric Might treats Google Sheets as a first-class citizen and does not export to Snowflake, BigQuery, or Amazon Redshift. If you strictly use Tableau or Power BI, you need a different tool.
2. Dataslayer
The closest direct clone to Supermetrics, but with fairer user limits.
Launched in 2018, Dataslayer was built specifically to absorb frustrated Supermetrics customers. Their entire pitch revolves around offering a very similar UI and feature set, but without charging you for every single team member you add.
They support over 50 of the most common marketing platforms (Google, Meta, LinkedIn, TikTok) and can pipe data into Google Sheets, Looker Studio, and BigQuery.
Pricing Implications in the Real World
Their entry-level plan starts at a highly competitive €25/month, and crucially, they offer unlimited users on all plans. However, you must read the fine print regarding API calls and row limits. While the €25/mo plan allows unlimited users, it caps API calls. In the real world, if you have 8 analysts refreshing dashboards multiple times a day for client meetings, or if you pull large granular datasets (like daily keyword-level performance), you will blow past the API limit by the 15th of the month. Heavy users are quickly pushed into their Large Agency plans (€200+/month). Furthermore, they use the same queue-based extraction architecture as Supermetrics, meaning you will still encounter slow load times.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Traditional agencies managing small to mid-sized budgets who use Looker Studio as their primary dashboarding tool. If you have an 8-person team and you want everyone to have login access without paying per-seat, Dataslayer is a solid, economical choice.
Who should skip it: Solo operators who just want fast, reliable queries. Because Dataslayer still uses queue-based architecture, you are still vulnerable to the same timeout frustrations you experience with Supermetrics.
3. Funnel.io
The massive, enterprise-grade Data Hub for complex marketing operations.
Funnel is fundamentally different from typical marketing data connectors. It is a full ETL platform. When you connect a source to Funnel, the data doesn't go straight to your spreadsheet. It goes to Funnel's secure cloud servers, known as the "Data Hub."
Inside the Data Hub, you can build complex, no-code transformation rules. You can align "Spend" from Google Ads and "Amount Spent" from Facebook into one unified column. With an incredible 590+ connectors, Funnel is the ultimate choice if your enterprise runs ads on obscure programmatic networks, local affiliates, and niche platforms.
Pricing Implications in the Real World
Funnel utilizes a credit system called "Flexpoints." What do Flexpoints mean in practice? Let's say you want to pull Google Ads data. Connecting the source costs points. Want to add a new destination like BigQuery? That's more points. If you take on a new enterprise client mid-month and need to connect 5 new regional ad accounts across 3 platforms, your point consumption spikes immediately. It becomes incredibly difficult to forecast your monthly software bill. Verified G2 reviews indicate that most mid-sized businesses pay between $6,000 and $8,000 annually for Funnel.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Massive, multi-national brands running ads across 50+ different platforms (from standard Meta ads to obscure Japanese programmatic networks). The Data Hub is incredible for normalizing messy, disparate data sets before sending them to a BI tool.
Who should skip it: Basically any standard agency. If 90% of your spend goes through Meta, Google Ads, LinkedIn, and TikTok, paying $8,000 a year for 500+ connectors you will never use is terrible resource allocation.
4. Windsor.ai
The point-solution for multi-touch attribution modeling.
While Windsor.ai operates as a data connector (boasting an impressive 325+ integrations), their true differentiator lies in marketing attribution. If your primary struggle is answering the question, "Did that LinkedIn ad assist the Google Search conversion that happened two weeks later?", Windsor is built to help solve that.
They pull campaign data from top-of-funnel platforms and connect it with downstream CRM data (like Salesforce or HubSpot) to model how different touchpoints contribute to a final sale.
Pricing Implications in the Real World
Pricing starts very affordably at $19/month for 3 users. However, in reality, the $19/mo plan is just a basic connector. If you actually want the multi-touch attribution modeling—which is the main reason to buy the tool—you need the $99/mo plan. Furthermore, if you are an agency managing multiple clients and you need API access to build custom models or export data outside their ecosystem, you are forced to upgrade to the Professional tier at $499/mo. An agency hoping for a cheap $99 attribution tool will suddenly find their software bill 5x higher just to unlock standard API functionality.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Growth teams with long, complex B2B sales cycles or multi-channel e-commerce plays where proving cross-channel attribution is the primary goal of the reporting setup.
Who should skip it: Marketers who just need raw performance metrics. If you just need a fast, reliable pipe to dump raw Facebook Ads metrics (clicks, spend, ROAS) into a Google Sheet for your weekly client sync, Windsor's interface and attribution focus add unnecessary complexity.
5. Fivetran
The gold standard for Data Engineers and the Modern Data Stack.
Fivetran is an ELT (Extract, Load, Transform) platform designed strictly for data engineers. It does not export to Google Sheets, Excel, or Looker Studio. Instead, its sole purpose is to reliably replicate data from over 600 sources and dump it into cloud data warehouses like Snowflake, BigQuery, or Amazon Redshift.
Because it is an ELT tool, the "Transform" step happens *after* the data reaches the warehouse. Fivetran relies heavily on open-source frameworks like dbt (Data Build Tool), meaning you must write SQL to clean, merge, and model your data.
Pricing Implications in the Real World
Fivetran prices entirely on data volume using a metric called MARs (Monthly Active Rows). Plans start at $500/month, but here is what MARs pricing actually means in practice: If you run a high-frequency sync for an e-commerce client pulling 500,000 product catalog updates per day, those updates count as active rows. If a client runs a massive Black Friday campaign generating millions of new ad impressions and click rows, you are billed for that volume. A client who had a remarkably good month can accidentally spike your Fivetran bill by thousands of dollars, making budget forecasting a nightmare.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Organizations with dedicated data engineering teams who are comfortable writing SQL and managing dbt models inside a Snowflake or BigQuery environment.
Who should skip it: Marketers. Period. If you do not know how to write SQL queries to transform raw JSON payloads inside a data lake, you cannot use this product.
6. Improvado
The white-glove managed service for massive marketing budgets.
Improvado targets companies that spend upwards of $10 million a year on advertising. They offer 500+ connectors, AI-powered data mapping, and automated governance to ensure strict compliance.
Unlike self-serve platforms like Supermetrics or Metric Might, Improvado is heavily managed. You are assigned dedicated data engineers and success managers who help build custom connectors and pipelines to your exact specifications.
Pricing Implications in the Real World
They do not list pricing publicly, operating strictly on a "Contact Sales" model. Based on industry reports, organizations processing up to 200 million rows per year can expect to pay over $1,200 to $3,000+ per month. In the real world, 'Contact Sales' pricing also means you are entering a multi-week procurement cycle. If your agency lands a client tomorrow and needs to connect a niche ad platform immediately, you aren't just clicking a self-serve button—you are submitting a ticket to an engineering team and waiting for a custom build.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Fortune 500 brands and massive holding-company agencies that require SOC-2 compliance, custom SLAs, and dedicated data engineering support to handle hundreds of millions of rows of data.
Who should skip it: Any agile, independent agency or solo performance marketer. The onboarding is long, the pricing is highly restrictive, and the platform is vast overkill for 95% of standard reporting needs.
7. Whatagraph
The all-in-one visual reporting and dashboarding tool.
Whatagraph circumvents Google Sheets and BI tools entirely. It acts as both the data connector and the visualization layer. You connect your ad platforms directly to Whatagraph, and then use their drag-and-drop widget builder to create beautiful, white-labeled PDF and web reports for your clients.
Pricing Implications in the Real World
It is highly convenient, offering over 45 native integrations and dozens of pre-built templates. However, this convenience comes at a steep price, starting at $223/month for just 3 users. The real-world implication of this all-in-one pricing is lock-in: you are paying for their visualization engine, not just the data pipe. If your client decides they want their data in Looker Studio instead, or if your CFO wants to run complex pivot tables in Google Sheets, you are stuck. You cannot extract the data out of Whatagraph to use elsewhere.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: Small boutique agencies whose clients only care about seeing a pretty, high-level PDF summary of their Facebook and Google Ads performance once a month, and who do not want to learn how to build dashboards in Looker Studio.
Who should skip it: Analytical marketers. Because you are locked into their proprietary dashboarding system, you lose the mathematical flexibility, VLOOKUPs, pivot tables, and deep diagnostic power of Google Sheets.
8. Porter Metrics
The pay-per-connection tool for Looker Studio beginners.
Porter Metrics has carved out a niche by offering extremely low entry points, starting at just $15/month. They are highly optimized for Looker Studio, offering dozens of free, copy-and-paste templates that allow beginners to set up a dashboard in minutes.
Pricing Implications in the Real World
Their unique pricing model is "Pay-Per-Connection." Let's do the math on Pay-Per-Connection in the real world. If you are a freelancer with exactly one client, paying $15 for a single connection is a fantastic deal. But if you are an agency with 15 clients, and each client runs Google Ads and Facebook Ads, that is 30 connections. At $8 to $15 per connection, you are suddenly paying $240 to $450/month for a tool that was advertised as $15/month. Furthermore, because they are built on a similar backend architecture to legacy tools, they suffer from the same queue-based timeout limitations as Supermetrics.
The Verdict: Who Should Buy / Who Should Skip
Who it is for: A freelancer with exactly 1 or 2 clients who wants a cheap ($15 to $30) way to populate a basic Looker Studio template without any complex setups.
Who should skip it: Any growing agency. The pay-per-connection model scales terribly, making flat-fee tools like Metric Might dramatically more economical once you pass 5 accounts.
How to Migrate Away from Supermetrics Without Breaking Reports
The fear of broken dashboards keeps many agencies chained to overpriced software. Migrating your data pipeline does not have to be painful if you follow a structured, three-step parallel run process.
Audit and Consolidate
Do not blindly recreate every query. Agencies often have dozens of "zombie sheets" updating daily that nobody has looked at in six months. Audit your active clients and list the exact metrics, dimensions, and date ranges required for their deliverables. This cleans up your Google Drive and reduces API bloat.
The 14-Day Parallel Run & Discrepancy Check
Never hard-switch your tools on the 1st of the month. Sign up for a free trial of your new tool. Build your new queries in a separate tab within your existing Google Sheet. Run both Supermetrics and the new tool side-by-side for 14 days to ensure the numbers match.
Pro Tip on Data Discrepancies: If the data does not match exactly, do not panic. The most common legitimate mismatch you will see is Spend figures being off by 1–3% — this is almost always a timezone issue, not a connector problem. Check that your new tool's query timezone matches your ad account's billing timezone before assuming the data is wrong. Secondly, check your attribution windows. Supermetrics might be pulling Facebook's default "7-day click, 1-day view", while your new tool might be pulling "28-day click".
Historical Data Preservation
Before canceling your Supermetrics subscription, do a massive static export of your historical data. Export your last 2 years of performance into a static CSV or a locked Google Sheet tab. You can seamlessly blend this static history with your new, live data pipelines via simple VLOOKUPs or SUMIFS without paying to continuously query old data.
Frequently Asked Questions (2026 Updates)
What is the difference between ETL and ELT for marketing teams?
ETL (Extract, Transform, Load) platforms pull data, clean it, and standardize it *before* sending it to your dashboard, making them marketer-friendly. ELT (Extract, Load, Transform) tools like Fivetran dump raw, messy data into a warehouse (like BigQuery), requiring a data engineer to write SQL code to clean it *after* it lands.
Is Supermetrics still worth it in 2026?
If you are an enterprise data engineering team moving massive datasets into a Snowflake or BigQuery data warehouse, Supermetrics is still a highly reliable, mature choice. However, if you are a marketing agency that primarily uses Google Sheets or Looker Studio, Supermetrics is now largely considered overpriced and unnecessarily complex compared to modern alternatives.
What happened to Supermetrics pricing?
Over the last few years, Supermetrics pivoted toward enterprise clients. They restructured their pricing to charge heavily for adding new data sources, ad accounts, and team members. This seat-and-source tax has caused many mid-market agencies to see their annual software bills double or triple upon renewal.
Can I use Supermetrics for free?
No. Supermetrics offers a 14-day free trial, but there is no permanent free tier. However, alternatives like Metric Might offer a permanent Free tier (1 user, 1 account) which is perfect for freelancers or testing the platform thoroughly before upgrading to a paid agency plan.
Does Supermetrics work with TikTok Ads?
Yes, but it is often gated behind their higher, more expensive pricing tiers as a "premium connector." Alternative platforms like Metric Might include TikTok Ads in their standard flat-fee plans, making it much cheaper to extract data from newer social platforms.
What is the best Supermetrics alternative for agencies?
The best alternatives for agencies are Metric Might or Dataslayer. Both tools offer plans that allow for unlimited users and unlimited ad accounts. Metric Might specifically excels for Google Sheets power users due to its front-end execution, which eliminates the queue-based timeouts common in legacy tools.
Why does Supermetrics time out in Google Sheets?
Supermetrics relies on a central server queue. When you request data, your query waits in line behind thousands of other users. If this server round-trip exceeds Google Apps Script's strict execution time limits for add-ons, the script is killed automatically by Google, resulting in a frustrating timeout error and a blank spreadsheet.
Stop paying the enterprise tax.
If you want lightning-fast queries, deep Google Sheets integration, and flat-rate pricing that scales with your agency—it's time to switch to Metric Might.
Try Metric Might freePermanent free tier available. No credit card required.
