Supermetrics Alternatives 2026 — 7 Tools Compared.
Supermetrics popularized marketing data integration — pulling Google Ads, Meta, TikTok and 100+ sources into Sheets, Looker Studio or BigQuery. But pricing scales aggressively per-connector, the Sheets-first model isn't for warehouse-native teams, and the tool stays at "data pipe" — leaving the analysis and action work to you. We compare seven production alternatives, including warehouse-grade ETL (Funnel.io, Improvado, Fivetran), Shopify-native BI (Polar Analytics) and an agentic option (d-lens) that flips the model: instead of moving data, it audits accounts and writes the next action.
For Sheets/Looker Studio reports on a budget → Supermetrics still wins. For warehouse-grade marketing ETL → Funnel.io or Fivetran. For mid-market multi-source ETL → Improvado or Adverity. For Shopify-native BI → Polar Analytics. For "skip the pipe, get the action" → d-lens (agentic ad audit + concrete next action per finding). Don't pick one without first asking: do you actually need a data pipe, or do you need someone to tell you what to fix?
Side-by-side comparison.
| Tool | Platform scope | Approach | Starting price | Best for |
|---|---|---|---|---|
| Supermetrics | 100+ sources to Sheets/Looker/BQ | ETL/data pipe | $39-$1,099/mo | Sheets/Looker reporting |
| Funnel.io | 500+ sources to warehouse | Marketing-specific ETL | $400-$2,500+/mo | Warehouse-native teams |
| Improvado | 500+ sources, mid-enterprise | ETL + data modeling | $1,500-$5,000+/mo | Agencies, mid-market |
| Adverity | 600+ sources, enterprise | ETL + data quality | Custom (~$2,000+/mo) | Enterprise compliance |
| Fivetran | Generic ELT (300+ sources) | Schema-managed ELT | Volume-based ($120-$5k+) | Modern data stack |
| Polar Analytics | Shopify-first BI | BI dashboards | $300-$1,000/mo | Shopify DTC operators |
| d-lens | Google + Meta + TikTok + GA4 + Shopify | Agentic audit + action | $199/mo flat | Cross-platform teams wanting next-action recommendations |
// 01What Supermetrics is, and what it isn't
Supermetrics is a marketing data integration tool — a pipe that pulls metrics from 100+ ad/analytics sources (Google Ads, Meta, TikTok, GA4, LinkedIn, Klaviyo, etc.) into Google Sheets, Looker Studio, BigQuery, Snowflake, or Excel. Founded in 2013, it became the default for SMB marketing teams that wanted "all my numbers in one Sheet."
Where it shines
- Google Workspace native — Sheets and Looker Studio integrations are mature and friction-free.
- Wide source library — 100+ connectors across ad, analytics, CRM, e-commerce, social.
- SMB pricing — Sheets-only plan starts at $39/mo, accessible for small marketing teams.
- Pre-built templates — Looker Studio templates for common dashboards (Google Ads overview, Meta performance) save setup time.
Where it falls short
- Pricing scales by connector + destination. A team needing Google Ads + Meta + TikTok + GA4 + Shopify into BigQuery can hit $500-1,200/mo fast.
- Schema is per-connector. Combining sources requires manual SQL/Sheets work; no unified marketing schema.
- It's a pipe, not insight. The data lands; you still have to clean it, model it and decide what to do. That's what 80% of Supermetrics work actually is.
- Sheets first. If your team works in Snowflake or Databricks-native, the warehouse-side tooling is less mature than competitors.
- Sampling on large queries. Heavy GA4 / Google Ads queries can hit row limits or sampling.
// 02The three categories of "Supermetrics alternative"
Before picking a tool, identify which of three problems you're solving:
- "I want a cheaper / more reliable Sheets pipe." Stay in the ETL category — Funnel.io free tier, lighter Improvado plans, or stay with Supermetrics on a tighter plan.
- "I want a real warehouse-grade marketing data layer." Move up to Funnel.io, Improvado, Adverity, or generic Fivetran with marketing schemas.
- "I don't actually need a pipe — I need someone (or something) to tell me what to fix in my ad accounts." Skip the ETL category entirely and use an audit tool like d-lens that pulls data, scores accounts and writes action recommendations instead of dumping rows.
Many teams spend $500-2,000/mo on a Supermetrics-class tool then never build the dashboards they envisioned. If that's you, option 3 is more honest.
// 03The seven alternatives, in detail
Below: each alternative with what it does well, where it falls short, real pricing tiers, and which kind of team it fits.
Funnel.io
$400-$2,500+/moMarketing-data ETL with a unified schema. 500+ sources cleaned and joined into a single "Funnel data model" you query in BigQuery, Snowflake, or their own UI. Better than Supermetrics if you're building a real marketing data warehouse and need cross-source attribution.
// pros
- Unified schema across sources (huge time saver)
- Strong warehouse integrations
- Better data quality than ad-hoc Supermetrics extracts
- Active enterprise support
// cons
- ~3-5x Supermetrics pricing at the entry tier
- Implementation takes 2-4 weeks
- Overkill for Sheets-only teams
- Less template library than Supermetrics for Looker Studio
Improvado
$1,500-$5,000+/moAgency-favorite mid-market ETL platform. 500+ connectors plus AI-assisted data modeling and a layer of pre-built reports. Strong if you manage multiple client accounts and need cross-client benchmarking.
// pros
- Multi-client / multi-tenant management
- Pre-built reports save weeks
- Good professional services for setup
- Strong Microsoft Power BI fit
// cons
- Enterprise pricing, no entry tier
- Implementation overhead
- UI feels heavier than competitors
- Not for SMB / single-brand teams
Adverity
Custom (~$2,000+/mo)European enterprise marketing data platform. 600+ sources, strong data quality / governance features, GDPR-friendly architecture. The pick if you're a large brand or holding-co with audit / compliance needs.
// pros
- Enterprise governance + data quality
- GDPR-aware architecture
- Multi-brand / multi-region setups
- Strong support and SLAs
// cons
- Heavy implementation (4-8 weeks)
- Sales-led only, no self-serve
- Annual contracts
- Pricing opaque without quote
Fivetran
Volume-based ($120-$5k+/mo)Not marketing-specific — Fivetran is the gold-standard generic ELT for the modern data stack. 300+ connectors land raw data in your warehouse with managed schema; you do the modeling in dbt. Best if you already run a warehouse + dbt and want marketing data alongside transactional data.
// pros
- Best-in-class warehouse delivery
- Managed schema (auto-handles source changes)
- Pairs well with dbt + Looker
- Pay only for active rows synced
// cons
- Not marketing-specific (no pre-modeled metrics)
- MAR (monthly active rows) pricing can spike
- Marketing connector depth lighter than Funnel.io
- Requires data-engineer skill to use well
Polar Analytics
$300-$1,000/moShopify-first BI tool — pulls Shopify, Klaviyo, Meta, Google, TikTok into pre-built D2C dashboards. Not really an ETL competitor; more a Triple Whale / Polar lookalike. The pick if you're Shopify DTC and want operator-friendly dashboards out of the box.
// pros
- Shopify-native, fast setup
- Pre-built D2C dashboards
- Affordable mid-tier pricing
- Active product velocity
// cons
- Shopify-only ecosystem
- Less depth than Triple Whale at high tiers
- Limited customization beyond defaults
- Not a true data-pipe replacement
d-lens
$199/mo flatDifferent category from the rest. d-lens doesn't move data into a warehouse — it scans your Google Ads, Meta, TikTok, GA4 and Shopify accounts directly via read-only OAuth, runs 46+ audit modules across them, and writes a concrete "do this" action recommendation for every finding. The output isn't a dashboard; it's a prioritized to-do list.
If your real question is "what should I fix in my ad accounts?" rather than "how do I move data around?", an audit agent is more useful than an ETL pipe. Many teams pair d-lens with a separate data layer (Funnel.io, BigQuery + dbt) and get the best of both.
// pros
- Concrete action per finding (not raw data)
- Read-only OAuth — never modifies your accounts
- Flat $199/mo regardless of spend or accounts
- 7-day free trial, no credit card
// cons
- Not a data pipe — won't replace Supermetrics if you need Sheets reports
- Cross-platform but doesn't integrate every source Supermetrics does
- New entrant — less ecosystem mindshare than incumbents
- Best as complement to a data layer, not full replacement
// faqFAQ.
What is the best Supermetrics alternative in 2026?
It depends on the actual problem. For warehouse-grade marketing ETL, Funnel.io. For agency / mid-market with modeling needs, Improvado. For modern-data-stack teams using dbt, Fivetran. For Shopify-native dashboards, Polar Analytics. For audit + action recommendations rather than data piping, d-lens.
Why are people looking for Supermetrics alternatives?
Three common reasons: (1) pricing scales aggressively per connector + destination once you go beyond a couple of sources; (2) the Sheets-first model doesn't fit warehouse-native teams; (3) ETL is just plumbing — many teams realize after months of Supermetrics that they still don't have insight, only data.
Is Supermetrics worth it for SMB marketing teams?
If your endpoint is Google Sheets / Looker Studio reports and you have under 5 sources, yes — at $39-99/mo it's the simplest path. Beyond that, costs and complexity scale faster than Supermetrics' value.
How does d-lens compare to Supermetrics?
Different category. Supermetrics moves marketing data into your tools (Sheets, Looker, BigQuery). d-lens reads your ad accounts and tells you what to fix. They're complementary — many teams use Funnel.io or Supermetrics for the data layer plus d-lens for actionable audits.
Can I replace Supermetrics with Fivetran?
Yes, if you're already on a modern data stack (warehouse + dbt + BI). Fivetran lands raw data; you model it in dbt; you query in Looker / Hex / Mode. Marketing connector depth is lighter than Funnel.io but generally sufficient for major sources.
Stop moving data. Start acting on it.
If your real bottleneck is "what should I fix in my ad accounts" rather than "where do I put my data", an agentic audit is faster than building a warehouse. d-lens scans your accounts, finds the leaks, writes the actions — 90 seconds, free.