Digraph vs Rankscale pricing
| Plan detail | Digraph | Rankscale |
|---|---|---|
| Lowest published price | Free for 14 days, then $99/mo | From $20/mo |
| Plan and billing | Standard, billed monthly | Essentials |
| Allowance | 30 prompts, 1 brand | Credit-based usage |
| AI coverage | Supported AI models | Varies by credits |
| Next plan | Pro $249/mo: 300 prompts, 3 brands | See Rankscale’s pricing page |
Lowest published plan for each vendor; billing terms differ. See which AI systems Digraph checks and how.
Features compared
| Capability | Digraph | Rankscale |
|---|---|---|
| Published entry pricing | Standard: $99/month for 30 tracked prompts and 1 brand. | Rankscale lists Essentials from $20/month with limited included usage and Pro at $99/month with 1,200 credits. |
| Mid-tier agency capacity | Pro: $249/month for 300 prompts, 3 brands, with supported model APIs. | Growth: $385/month with 5,500 credits, up to 22,000 answers, 50 brand dashboards, white-label dashboard links via API, and REST API access. |
| Measurement unit and engines | Plans publish prompt and brand limits across supported model APIs. | Rankscale uses credits; its pricing page says each engine query typically costs 0.25 credits and lists ChatGPT, Gemini, Perplexity, Claude, DeepSeek, Mistral, Grok, Copilot, and more. |
| Citations and competitor context | Inspect full answers, recommendations, competitor mentions, cited URLs, source domains, and changes over time. | Rankscale describes visibility scores, competitor benchmarking, citation analysis, sentiment, query fan-out, sources-box analysis, and citation-gap workflows; verify full answer and source exports. |
| Audits and optimization | Route observed visibility gaps into audits, analysis, Signal, and agent workflows tied to evidence. | Rankscale includes page audits, Rankscale Scout recommendations, prompt research, shopping analysis, sources-box analysis, and prioritized citation-gap action lists. |
| Agency reporting and access | Reports and exports are public-plan capabilities; API access is listed for Enterprise. | Rankscale lists shareable dashboards, unlimited-seat team workspaces, CSV/Sheets or Looker Studio exports, white-labeled dashboard links through API on higher plans, and REST API access. |
Key differences between Digraph and Rankscale
Rankscale and Digraph both measure AI visibility, competitors, citations, and sentiment. Rankscale emphasizes credit-based scaling, many engine options, high answer volume, scheduling from hourly to monthly, page audits, query fan-out, shopping analysis, and agency exports or API access. Digraph emphasizes a defined prompt portfolio, full answer evidence, cited URLs, source domains, competitor framing, and connected audit or analysis workflows across supported model APIs. Their units and workflow boundaries differ, so a controlled evidence-level pilot matters more than headline answer counts.
Credits, answers, and prompts are different workloads
Rankscale publishes credits and estimated answer counts: Pro has 1,200 credits and up to 4,800 answers, while Growth has 5,500 credits and up to 22,000 answers. Digraph publishes 30 or 300 tracked prompts and brand limits. Because engine costs vary, model the exact prompts, engines, schedules, regions, and stored answers your team needs before treating the monthly quotas as equivalent.
Compare breadth with traceable evidence
Rankscale emphasizes many engines, visibility trends, competitor benchmarks, citation share, query fan-out, and source-box analysis. Digraph emphasizes the prompt, full answer, recommendation context, cited URL, source domain, competitor framing, and follow-up analysis behind a finding. Use the same citation-gap example and record whether each product exposes the evidence needed to choose and verify an action.
Test cadence and credit consumption with real prompts
Rankscale lists hourly, daily, weekly, monthly, and optional bi-cadence schedules, with each engine query consuming a fraction of a credit. Digraph uses tracked prompts and selected AI systems as the planning unit. Run the same prompt set at the same cadence for a defined window and record credit consumption, model modes, answer retention, and result stability.
Evaluate page audits and client delivery separately
Rankscale bundles URL page audits, shareable dashboards, exports, Looker Studio, and higher-tier white-label or API access. Digraph lists reports and exports on public plans and Enterprise API access, with evidence connected to audit and analysis workflows. Test technical audit depth, permissions, client separation, branded delivery, export fields, archive retention, and the effort to turn a citation gap into a verified change.
Run a controlled side-by-side pilot
Use the same brand, competitors, categories, markets, language, buyer questions, active engines, collection window, and reporting format. Record full answers, prompt and engine context, brand position, competitor mentions, sentiment, citations, cited URLs, source domains, page-audit findings, proposed actions, refresh time, and credits or prompts consumed. Compare one recurring report and one verified follow-up action before choosing the operating model.
Need the work done, not another tool?
A tracking tool tells you where you stand in AI answers; it does not write the content, fix the site or earn the mentions that change them. Digraph is an AI marketing agency: we measure on our own platform and do that work for you, starting with a one-off audit.
See our AEO agency servicesHow to evaluate both
This documentation-based comparison was reviewed September 21, 2026; it is not a hands-on benchmark. Rankscale publishes Pro at $99/month with 1,200 credits, up to 4,800 AI answers, 10 brand dashboards, and 50 page audits; Growth at $385/month with 5,500 credits, up to 22,000 answers, 50 dashboards, and white-label or API capabilities; and Enterprise at $780/month with 12,000 credits, up to 48,000 answers, and 100 dashboards. Its pricing page also lists an Essentials entry point at $20/month with limited included usage. Digraph lists Standard at $99/month for 30 prompts and 1 brand and Pro at $249/month for 300 prompts and 3 brands across supported model APIs. Rankscale’s credit and answer model differs from Digraph’s prompt and brand model. Normalize engines, credit costs, schedules, answers, evidence, audits, and client delivery before comparing value.
Sources reviewed
Rankscale’s capabilities are summarized from the official sources below. This is a documentation-based comparison published by Digraph, not a hands-on benchmark.
Common questions
How does Digraph compare with Rankscale?
Rankscale and Digraph both measure AI visibility, competitors, citations, and sentiment. Rankscale emphasizes credit-based scaling, many engine options, high answer volume, scheduling from hourly to monthly, page audits, query fan-out, shopping analysis, and agency exports or API access. Digraph emphasizes a defined prompt portfolio, full answer evidence, cited URLs, source domains, competitor framing, and connected audit or analysis workflows across supported model APIs. Their units and workflow boundaries differ, so a controlled evidence-level pilot matters more than headline answer counts.
How does Rankscale pricing compare with Digraph?
Rankscale’s lowest published plan is From $20/mo (Essentials) with credit-based usage and varies by credits. Digraph starts with a 14-day free trial; Standard is then $99/mo billed monthly for 30 prompts, 1 brand across supported model APIs, and Pro is $249/mo for 300 prompts, 3 brands. Billing basis, collection surfaces, and plan units differ, so confirm current terms with both vendors.
Is Digraph a good Rankscale alternative?
Digraph is a fit for teams and agencies comparing high-volume, credit-based AI visibility monitoring and page auditing with a prompt-centered evidence and investigation platform. Run the same buyer prompts in both products and compare the full answers, citations, and next actions before deciding.
Can Digraph complement an existing Rankscale workflow?
Yes. Many teams use more than one research or measurement system. Digraph adds an evidence-led view of AI answers, prompts, citations, competitors, and follow-up work alongside the tools SEO, brand, and content teams already use.
How should I run a fair AI visibility evaluation?
Use the same prompt portfolio, competitors, markets, AI systems, and reporting period in each tool. Review the underlying answers and sources, not only aggregate scores, before choosing a workflow.