Every marketing agency and in-house team hits the same wall. Your data is spread across Meta, Google Ads, GA4, Search Console, TikTok, LinkedIn, Shopify, and a dozen other platforms. Getting all of it into one place where you can actually understand what's happening — let alone act on it — requires stitching together multiple tools, each with its own pricing model, its own limitations, and its own maintenance overhead.
The market for solving this problem is crowded. Supermetrics handles extraction. AgencyAnalytics and DashThis build client reports. Funnel.io and Whatagraph sit somewhere in between. Looker Studio, Tableau, and Power BI provide visualization if you've already solved the data infrastructure problem. And increasingly, AI-native platforms like Hyper are replacing the entire stack with managed databases, real-time pipelines, and agents that analyze and act on the data.
This guide breaks down the major tools in the space — what each one actually does, what it costs, where it falls short, and how they compare for agencies, in-house teams, and founders in 2026.
How we structured this guide
Marketing data and reporting tools generally solve some combination of four problems:
- Data extraction — Getting data out of ad platforms and analytics tools
- Data storage — Putting it somewhere structured and queryable
- Visualization — Building dashboards and reports
- Analysis — Understanding what the data means and what to do about it
Most tools in this space solve one or two of these well and punt on the rest. That's the fundamental issue — you end up needing 3-5 tools to cover all four, and the gaps between them are where intelligence gets lost.
We'll evaluate each tool against all four dimensions, plus pricing, agency-specific features, AI capabilities, and scalability.
Supermetrics — The extraction standard
What it is: The most widely used marketing data extraction tool. Supermetrics pulls data from 100+ ad platforms and analytics tools into destinations like Google Sheets, Looker Studio, BigQuery, Snowflake, and Excel.
Pricing:
- Starter: $37/month (annual) — 1 destination, 3 data sources, weekly refreshes
- Growth: $177/month (annual) — 1 destination, 6 data sources, daily refreshes
- Pro: $399/month (annual) — 1 destination, 10 data sources, hourly refreshes
- Enterprise: Custom pricing — unlimited sources, data warehousing
What it does well:
Supermetrics is plumbing, and it's good plumbing. It connects to virtually every marketing platform, handles the API complexity behind the scenes, and delivers clean data to your destination of choice. The Google Sheets integration is particularly popular — you set up a query, schedule refreshes, and your spreadsheet stays current. For teams that already have a BI tool and just need data to flow into it, Supermetrics is the standard.
The connector library is genuinely broad. If a marketing platform has an API, Supermetrics probably connects to it. That matters when you're running campaigns across less common platforms or need data from niche analytics tools.
Where it falls short:
The per-destination pricing model is the first friction point. Supermetrics charges separately for each destination. Need data in both Google Sheets and Looker Studio? Two subscriptions. Need it in BigQuery too? Three. An agency that needs data flowing to multiple destinations for different use cases can easily be paying $500–$1,000/month just for extraction.
More fundamentally, Supermetrics only solves problem #1 — extraction. It doesn't store, visualize, or analyze your data. You still need a data warehouse (BigQuery, Snowflake, or Redshift — each with their own costs and setup), a transformation layer (dbt or similar — requiring engineering knowledge), and a BI tool (Looker Studio, Tableau, or Power BI — each with their own learning curve and pricing). Supermetrics is the first domino in a 4-5 tool chain.
For agencies specifically, Supermetrics doesn't offer client-facing features. There's no way to share a dashboard, generate a client report, or manage multiple client accounts from one interface. You're building all of that downstream.
Best for: Technical teams that already have a data warehouse and BI tool and just need reliable extraction from marketing platforms.
AgencyAnalytics — Built for client reporting
What it is: A reporting platform designed specifically for marketing agencies. AgencyAnalytics connects to 80+ marketing platforms and builds automated client dashboards and reports.
Pricing:
- Freelancer: $79/month — 5 client campaigns
- Agency: $179/month — 10 client campaigns
- Enterprise: Custom pricing — 100+ campaigns, custom onboarding
Per-client pricing applies beyond plan limits. White-labeling and custom domains are available on higher tiers.
What it does well:
AgencyAnalytics is the most agency-focused tool in this comparison. The entire product is designed around the agency-client relationship — white-labeled dashboards, automated report delivery, client user logins, and campaign-level data organization.
Setup is fast. Connect a client's platforms, pick a dashboard template, and you have a presentable report within minutes. The drag-and-drop report builder is intuitive, and Smart Reports can generate a comprehensive multi-platform report in under 15 seconds. For agencies that need to get client reporting off the ground quickly, it removes a lot of friction.
The integration library covers the essentials — Google Ads, Meta, GA4, Search Console, Shopify, HubSpot, Mailchimp, and most major platforms. They add new integrations regularly. White-labeling is solid — custom domains, branded login pages, agency logos throughout.
Their Ask AI feature provides surface-level insights and recommendations based on connected data, which can speed up the process of identifying talking points for client calls.
Where it falls short:
AgencyAnalytics solves problem #3 (visualization) and parts of problem #1 (extraction, but limited to what their integrations support). It doesn't provide a managed database, doesn't support custom SQL queries, and the "analysis" is limited to pre-built widgets and AI summaries.
The dashboards are template-based. You can customize them with widgets, but you're working within the constraints of what AgencyAnalytics has built. If you need a custom metric that combines data from multiple platforms in a non-standard way — say, blended CAC across paid and organic channels with custom attribution weighting — you're probably out of luck. There's no underlying database to query, no code execution, no way to build custom calculations beyond what the UI offers.
Per-client pricing means costs scale linearly with your client count. An agency with 50 clients is paying significantly more than the base price, and at that scale, the cost often exceeds what a more comprehensive platform would charge. The economics get worse as you grow, which is exactly backwards from how pricing should work for a scaling agency.
The AI features are thin compared to what's possible in 2026. "Ask AI" provides summaries and recommendations, but it can't run custom analysis, write SQL, generate Python-based statistical models, or take action based on what it finds. It's a layer on top of dashboards, not a replacement for analytical thinking.
Best for: Small to mid-size agencies (5-25 clients) that need fast, presentable client reporting and don't require deep custom analysis.
Funnel.io — Enterprise data normalization
What it is: A marketing data hub that connects to 500+ platforms, normalizes cross-channel data, and exports it to warehouses and BI tools. Funnel positions itself as a "marketing intelligence platform" rather than just an extraction tool.
Pricing:
- Usage-based through "flexpoints" — pricing depends on data volume, number of connectors, and destinations
- Typically $500+/month for mid-size teams, scaling well into thousands for enterprise
- Free tier available with limited functionality
What it does well:
Funnel.io's connector library is the largest in the space — 500+ marketing and advertising platforms. If you run campaigns on obscure or regional platforms, Funnel probably has a connector. The data normalization capabilities are genuinely strong — Funnel automatically maps metrics across platforms so that "cost per result" from Meta and "cost/conv." from Google become comparable, standardized metrics.
The data transformation features are more sophisticated than Supermetrics. You can create custom metrics, apply business rules, and clean data before it hits your warehouse. For enterprise teams with complex data requirements and existing BI infrastructure, this is valuable.
Funnel also supports multiple export destinations and can push data to BigQuery, Snowflake, Google Sheets, and various BI tools simultaneously. The pipeline reliability is enterprise-grade.
Where it falls short:
Funnel.io is expensive. The usage-based pricing model means costs are hard to predict and tend to increase as you connect more platforms and pull more data. An agency connecting 10+ platforms across 30+ client accounts can easily be spending $1,000–$2,000/month on Funnel alone — and that's before the warehouse and BI tool costs.
Like Supermetrics, Funnel.io is infrastructure. It handles extraction and transformation, but it doesn't visualize or analyze. You still need Looker Studio, Tableau, or Power BI on top. And you still need someone who understands data modeling to set up the warehouse and transformations correctly. Funnel reduces the ETL complexity, but it doesn't eliminate the need for technical expertise.
No client-facing features. No built-in dashboards. No report delivery. An agency using Funnel.io for data still needs AgencyAnalytics, Whatagraph, or a BI tool for the client-facing layer.
Best for: Enterprise marketing teams with existing data infrastructure that need robust, high-volume data extraction and normalization across many platforms.
Whatagraph — Visual reporting with better design
What it is: A marketing reporting and analytics platform that competes with AgencyAnalytics and DashThis. Stronger on visual presentation, with drag-and-drop branded reports and templates.
Pricing:
- Professional: $199/month — for small teams
- Premium: $299/month — for growing agencies
- Enterprise: Custom pricing
What it does well:
Whatagraph's strength is presentation. The reports and dashboards are genuinely well-designed — better looking out of the box than AgencyAnalytics or DashThis. The drag-and-drop builder offers more layout flexibility, and the branded templates are polished enough to impress clients.
Data blending capabilities are stronger than DashThis, allowing you to combine data from multiple platforms into unified widgets. Cross-channel performance views are easy to set up without technical knowledge.
AI-powered insights provide automatic recommendations and trend identification, and the platform has been investing more in this area recently.
Where it falls short:
Similar structural limitations as AgencyAnalytics — template-based dashboards, no underlying database, no custom SQL, no ability to take action on insights. The AI features are summaries and recommendations, not analytical capabilities.
At $199/month for the base plan, Whatagraph is more expensive than AgencyAnalytics for comparable functionality. The visual quality is better, but the data capabilities are roughly equivalent.
Limited integrations compared to Supermetrics or Funnel.io — you may find gaps if you work with less common platforms.
Best for: Agencies where report presentation quality is a key differentiator and clients expect polished, branded deliverables.
DashThis — Simple, fast, limited
What it is: The simplest reporting tool in this space. Connect platforms, pick a template, generate a dashboard. DashThis focuses on making basic reporting as frictionless as possible.
Pricing:
- Individual: $49/month — 3 dashboards
- Professional: $149/month — 10 dashboards
- Business: $209/month — 25 dashboards
- Standard: $399/month — 50 dashboards
What it does well:
Speed and simplicity. DashThis is the fastest way to get a basic client dashboard up and running. The template library covers most common reporting scenarios, and the setup process is deliberately minimal. For freelancers or small agencies that need "good enough" reporting without complexity, it works.
Where it falls short:
Limited in almost every dimension beyond basic reporting. Only 30+ native integrations — missing major platforms like Salesforce, Shopify, and Google DV360. Minimal data transformation capabilities. No custom metrics beyond basic calculations. No AI features. No underlying database. Limited customization compared to AgencyAnalytics or Whatagraph.
Per-dashboard pricing means costs scale linearly. An agency with 50 clients needing 2-3 dashboards each is looking at the $399/month tier or higher.
Best for: Freelancers and very small agencies (under 10 clients) that need basic reporting with minimal setup.
The BI tool layer — Looker Studio, Tableau, Power BI
These aren't direct competitors to the tools above — they're the visualization layer that sits on top of whatever data infrastructure you've built. But they're worth mentioning because they're often part of the stack.
Looker Studio (free) — Google's BI tool. Free, which is why it's popular, but the learning curve is steep, the interface is clunky, and performance degrades with large datasets. Requires data to already be in a queryable format — usually via Supermetrics or Funnel.io.
Tableau ($75+/user/month) — The enterprise standard. Powerful, flexible, expensive. Requires significant technical expertise to use effectively. Overkill for most marketing teams and agencies.
Power BI ($10+/user/month) — Microsoft's option. More affordable than Tableau, deeply integrated with the Microsoft ecosystem. Good for teams already on Azure. Similar technical requirements.
All three assume you've already solved data extraction, storage, and transformation. They're the top of a stack, not a solution by themselves.
Hyper — Managed databases, AI agents, and Interfaces
What it is: An AI agent platform for marketing. Agents operate across the entire marketing workflow — ads, SEO, analytics, reporting, content, and operations. Managed databases, real-time data pipelines, and Interfaces (customizable dashboards) are the data and visualization layer built into the platform.
Pricing: Included in the Hyper platform. No separate data extraction subscription, no per-client reporting charges, no warehouse costs.
Data extraction and storage — built in
Connect Meta, Google Analytics, Search Console, Google Ads, and more through standard OAuth. The moment you connect, Hyper creates managed database tables, configures the schema, and starts syncing data automatically. Real-time pipelines pull data on an hourly cadence across all connected platforms.
No Supermetrics. No Funnel.io. No warehouse setup. No ETL configuration. No dbt. No schema mapping. The entire extraction → storage → normalization chain happens behind the scenes.
Each workspace gets its own managed database with isolated data. For agencies, each client workspace is completely separated — connect their accounts and the pipeline starts automatically. No per-client connector setup, no maintaining separate extraction instances.
You can open the database and look at the tables directly. What you see is the same data agents query. There's no ETL pipeline introducing drift, no caching layer serving stale results. The source of truth is the same for humans, agents, and dashboards.
AI agents that analyze — not just report
This is the fundamental difference between Hyper and every other tool in this comparison. The other tools show you data. Hyper agents analyze it, explain it, and act on it.
Agents query your managed database directly using SQL — and they're exceptionally good at writing SQL. When you ask "how did our Meta campaigns perform this week compared to last week," the agent writes a query, gets the answer in seconds, and explains the implications. When you ask "which Google Ads campaigns should we pause," it runs the analysis across CPA, ROAS, conversion volume, and trend data, then gives you a recommendation.
This is a 100x cost reduction compared to having agents call platform APIs in real time. The data is already synced, structured, and queryable. No rate limits, no API latency, no token waste pulling data that's already available locally.
But agents go beyond what any dashboard can show. They run the kind of cross-platform analysis that normally requires a data team or a senior analyst:
- Creative fatigue modeling — identifying when ad creative is hitting diminishing returns before it shows up in headline metrics
- Spend pacing anomalies — catching budget overspends or underspends across platforms before they become problems
- Cross-channel attribution analysis — understanding how organic and paid channels interact, not just how each performs in isolation
- Trend prediction — identifying patterns in your data that suggest upcoming performance changes
- Competitive analysis — agents can scrape Meta Ad Library, monitor competitor strategies, and benchmark your performance
Agents write Python, run SQL, generate statistical analysis, and produce the kind of insights that normally require a data analyst on staff. And they do this automatically — on schedules, on triggers, or on demand.
Interfaces — live dashboards your clients can access
Interfaces are customizable dashboards that agents build from natural language. This is where Hyper replaces AgencyAnalytics, DashThis, Whatagraph, and Looker Studio.
Tell an agent: "Create a dashboard for Client X showing weekly ad spend, CPA, and ROAS across Meta and Google, with a 30-day trendline and a channel breakdown." The agent builds it. The dashboard connects to the client's managed database and updates with real-time data automatically.
Here's what makes Interfaces different from template-based reporting tools:
Live, shareable links. Every Interface automatically gets a live URL. Send it to a client and they see a real-time dashboard — not a static PDF, not a screenshot, not a stale report from last Tuesday. The data updates because it's connected to a managed database that syncs hourly.
Password protection. You can password-protect any Interface. Share a link with a client, set a password, and they have secure access to their live dashboard. No client login system to set up, no user management overhead.
Template-based creation at scale. This is the agency unlock. You can ask an agent to create a dashboard for each of your clients based on a template or specific set of metrics. "Create a performance dashboard for each client showing weekly spend, CPA, ROAS, and top-performing creatives across all their connected ad platforms." The agent generates individual dashboards for every client workspace, each connected to that client's isolated database. What would take days of manual setup in AgencyAnalytics happens in minutes.
No widget constraints. Because Interfaces are backed by a real database and built by agents, they aren't limited to pre-built widgets. If you can describe the visualization — multi-dimensional cohort analysis, custom attribution models, blended metrics with weighted formulas — agents can build it. The dashboards are as flexible as the underlying data.
Beyond dashboards. Interfaces can be multi-page analytics apps, performance scorecards, competitive benchmarks, or custom reporting tools. Because agents can write code and query databases, the ceiling on what an Interface can display is much higher than any template-based tool.
The action layer — what no reporting tool does
Every tool in this comparison stops at showing you data. Hyper's agents act on it.
An agent that spots declining ROAS on a Google Ads campaign can pause underperforming ad groups, reallocate budget to what's working, adjust bids, and message you in Slack — all before you've seen the report. An agent that identifies creative fatigue can generate new ad variations, test them, and scale the winners. An agent that notices a conversion tracking issue can flag it immediately rather than letting it corrupt weeks of data.
This is possible because the data layer (managed databases), the visualization layer (Interfaces), and the action layer (agents that manage campaigns, optimize ads, publish content, run SEO) all share the same environment. There's no gap between insight and action. The same platform that shows you the problem can fix it.
No other tool in this comparison does this. Supermetrics extracts data. AgencyAnalytics displays it. Funnel.io normalizes it. But none of them can do anything about what the data shows.
Side-by-side comparison
| Capability | Supermetrics | AgencyAnalytics | Funnel.io | Whatagraph | DashThis | Hyper |
|---|---|---|---|---|---|---|
| Data extraction | 100+ connectors | 80+ connectors | 500+ connectors | 45+ connectors | 30+ connectors | Built-in (automatic) |
| Managed database | No | No | No | No | No | Yes (per workspace) |
| Data normalization | Basic | Basic | Advanced | Basic | Minimal | Automatic |
| Real-time pipelines | Weekly–hourly ($399/mo) | Via integrations | Yes | Via integrations | Via integrations | Hourly (included) |
| Custom SQL queries | No | No | No | No | No | Yes (agents write SQL) |
| Custom code / Python | No | No | No | No | No | Yes |
| Client dashboards | No | Yes (templates) | No | Yes (templates) | Yes (templates) | Yes (AI-generated) |
| Shareable live links | No | Limited | No | Yes | Yes | Yes (password-protected) |
| Dashboard from natural language | No | No | No | No | No | Yes |
| Bulk dashboard creation | No | Manual per client | No | Manual per client | Manual per client | Yes (agent creates per client) |
| AI analysis | No | Basic summaries | No | Basic summaries | No | Full analysis + code |
| Takes action on insights | No | No | No | No | No | Yes |
| White-label / branding | No | Yes | No | Yes | Yes | Yes |
| Per-client pricing | No | Yes | No | Yes | Per dashboard | No |
| Requires warehouse | Yes (downstream) | No | Yes (downstream) | No | No | No (built in) |
| Requires BI tool | Yes | No | Yes | No | No | No (Interfaces) |
| Starting price | $37/mo | $79/mo | ~$500/mo | $199/mo | $49/mo | Included in platform |
What the typical agency is actually paying
Let's do the math for a mid-size agency with 30 clients, running campaigns across Meta, Google Ads, GA4, and Search Console.
Option A: Supermetrics + Looker Studio
- Supermetrics Pro (hourly refreshes, 10 sources): $399/month
- Additional destination for BigQuery: ~$177/month
- BigQuery storage and compute: ~$50–$200/month
- Looker Studio: Free, but 10+ hours/week of manual dashboard building and maintenance
- No client-facing features — you're screen-sharing or exporting PDFs
- Total: ~$626–$776/month + significant time
Option B: AgencyAnalytics
- Agency plan (10 campaigns): $179/month
- 30 clients × overage pricing: likely $300–$500+/month total
- Limited custom analysis — you're constrained to template widgets
- AI summaries but no deep analysis
- Total: ~$300–$500/month + limited capabilities
Option C: Funnel.io + Whatagraph
- Funnel.io (30 client accounts, multiple sources): $800–$1,500/month
- Whatagraph for client-facing reports: $199–$299/month
- Total: ~$1,000–$1,800/month
Option D: Hyper
- Managed databases, real-time pipelines, AI agents, and Interfaces all included in the platform
- Each client gets an isolated workspace with automatic data sync
- Agents create dashboards from templates in minutes
- Agents analyze data, surface insights, and take action
- Same platform also manages ad campaigns, SEO, content, and operations
- Total: Included in Hyper subscription — no separate data/reporting stack
The agency paying $1,000+/month across 3-4 tools — plus 15-20 hours per week on pipeline maintenance and report building — replaces all of it with one platform. The cost savings are significant, but the time savings are transformational. Hours per week spent on data plumbing become hours spent on strategy and client relationships.
For agencies: the Interfaces workflow
Here's what the reporting workflow actually looks like for an agency on Hyper:
Day 1 — Client onboarding: Connect the client's Meta, Google Ads, GA4, and Search Console accounts via OAuth. Takes about 2 minutes. Managed database tables are created automatically. Data starts syncing immediately.
Day 1 — Dashboard creation: Tell an agent: "Create a performance dashboard for this client showing weekly ad spend and ROAS by platform, CPA trend over 30 days, top 5 performing campaigns, and a channel-level breakdown." The agent builds the Interface. You review it, adjust if needed, and generate a shareable link.
Day 1 — Client access: Send the client the dashboard URL. Set a password. They now have a live, auto-updating dashboard they can check anytime. No login system to configure, no user management.
Ongoing — Automated insights: Set up an agent to run weekly analysis on the client's data. "Every Monday, analyze this client's ad performance, identify any campaigns with declining ROAS or rising CPA, check for creative fatigue, and send a summary to Slack with recommendations." The agent queries the managed database, runs the analysis, and delivers it on schedule.
Ongoing — Action: When agents find issues, they can act. Pause underperforming campaigns. Reallocate budget. Flag creative that needs refreshing. Send the client a summary of what changed and why.
Scaling to 30+ clients: "Create the same dashboard template for all client workspaces." The agent generates dashboards across every workspace. Each one is connected to that client's isolated database. Total time: minutes, not days.
This replaces the entire AgencyAnalytics or DashThis workflow — the manual dashboard building, the template configuration per client, the weekly report generation, the PDF exports. It also replaces the Supermetrics pipeline, the warehouse management, and the BI tool maintenance.
For in-house teams and founders
You don't need to run an agency to benefit from this. If you're a founder, a solo marketer, or a small team running your own campaigns, the same pain applies — it's just concentrated in one person instead of spread across a team.
You're logging into Meta Ads Manager. Then Google Ads. Then GA4. Then Search Console. Each platform shows you a different slice of reality with different time ranges, different attribution models, and different definitions of what counts as a conversion. Pulling it all together into a coherent picture requires either spending 2-3 hours per week in spreadsheets or paying for Supermetrics + a BI tool.
With Hyper, you connect your accounts once. Your managed database populates automatically. From that point forward, you can ask an agent anything about your marketing performance in plain English:
- "What's my blended CAC this month across all channels?"
- "Which campaigns should I pause based on the last 14 days?"
- "Create a weekly performance dashboard I can check every Monday"
- "Compare my organic traffic growth to paid traffic costs over the last 90 days"
- "Which ad creatives are showing signs of fatigue?"
The agent queries your database and gives you the answer — or builds you an Interface that updates automatically. No SQL knowledge required. No BI tool learning curve. No $200/month extraction subscription. No configuring data connectors.
For founders specifically, this changes the economics of marketing intelligence. Tools like Supermetrics + Looker Studio were designed for teams with a data person. AgencyAnalytics was designed for agencies with dedicated report builders. Hyper is designed for anyone who can describe what they want to know.
What about data accuracy?
A common concern with any data tool: is the data correct?
With Supermetrics and Funnel.io, you're trusting their API connectors to pull the right data, but you're also introducing potential drift through the ETL pipeline, the warehouse, and the BI tool. Each layer can introduce discrepancies — timezone mismatches, currency conversion issues, metric definition differences, caching delays. Debugging where a number went wrong often requires tracing through 3-4 systems.
With AgencyAnalytics and DashThis, the data flows through their integrations directly into dashboards. Simpler pipeline, fewer places for things to break, but also fewer tools to diagnose issues when they do. And since there's no underlying database you can inspect, you're trusting the dashboard number without the ability to verify the source.
With Hyper, you can open the managed database and look at the raw tables. The data agents query is the same data you see in the database. When something looks off, you can inspect the actual rows — not a cached aggregation, not a widget calculation, the source data. And because agents write SQL against these tables, their analysis is reproducible and auditable.
The bigger picture: reporting vs. operating
Here's the distinction that matters most in 2026.
Every other tool in this comparison is a reporting tool. They show you what happened. Some do it faster. Some do it prettier. Some do it across more platforms. But they all end at the same place: a dashboard or report that a human reads and then goes somewhere else to take action.
Hyper is an operating platform. It doesn't just show you what happened — it understands why, recommends what to do, and can execute the fix. The managed database isn't just for reporting. It's the foundation that makes intelligent, automated action possible. The Interfaces aren't just dashboards. They're live windows into a system that's actively managing your marketing.
The question isn't whether Supermetrics or AgencyAnalytics or Funnel.io are good tools. They are, within their scope. The question is whether managing 3-5 of them, paying for all of them, and manually connecting the intelligence between them is the right architecture for marketing in 2026 — or whether a platform that handles data, analysis, visualization, and action in one environment is a better foundation.
Summary: which tool should you pick?
Pick Supermetrics if you already have a data warehouse and BI tool, you have someone technical to maintain the pipeline, and you just need reliable data extraction from marketing platforms.
Pick AgencyAnalytics if you're a small agency (under 25 clients) that needs fast, presentable client reporting, you don't need deep custom analysis, and per-client pricing doesn't concern you at your current scale.
Pick Funnel.io if you're an enterprise marketing team with an existing data infrastructure, you need extraction from 500+ platforms, and you have the budget and technical resources to manage a warehouse + BI layer on top.
Pick Whatagraph if report presentation quality is a key differentiator for your agency and you want better-designed client deliverables than AgencyAnalytics provides.
Pick DashThis if you're a freelancer or very small agency that needs basic reporting with minimal setup and complexity.
Pick Hyper if you want to replace the entire stack — extraction, warehousing, ETL, BI tools, and reporting — with one platform. Managed databases with real-time pipelines, AI agents that analyze and act on your data, and Interfaces with live, shareable, password-protected dashboards. For agencies that want to stop spending hours on data plumbing and start spending that time on strategy. For in-house teams and founders that want marketing intelligence without a 4-tool stack.
Try Hyper at hyperfx.ai. Connect your accounts and see your marketing data in one place — with agents that understand it.