Digimetrics — Per-Tool Market Pricing Research & Recommendation

Does this cover every tool?

Yes — 32 of 32 AI tools, plus the 5 free data connectors listed individually below. Two rows are marked (est.) rather than ledger-confirmed — Time to Rank and Anchor Text Cleaner — because their exact credit cost wasn't isolated via a clean before/after balance check during testing. Everything else in the table is a directly observed number, either from a live run's balance delta or the Projects & Runs ledger.

Methodology

For each tool, three reference points:

1. Digimetrics today — the exact credit cost pulled from the Projects & Runs ledger, converted to USD at the Expert plan's effective rate of $0.0332/credit ($199 ÷ 6,000 credits/month).
2. SaaS subscription equivalent — what the closest standalone tool charges, amortized. A soft comparison (subscriptions bundle many lookups), included to show the floor a customer would otherwise pay just to access the capability at all.
3. Fiverr / freelancer market rate — what a human freelancer charges for the same single deliverable, researched live (August 2026). The more relevant comparison for a per-run, pay-as-you-go model like Digimetrics', since it's priced the same way: one deliverable, one price, no subscription required.

This isn't "our tool should cost what a human costs" — it's "how much of a gap exists, and is the product leaving obvious money on the table by pricing an automated, instant deliverable at 1–2% of what a human charges for a slower, less consistent version of the same thing."

Per-tool pricing table

USD values use the Expert plan's effective rate, $0.0332/credit ($199 ÷ 6,000 credits/month) — the same rate applied to "today" prices, so the × increase column is an apples-to-apples comparison. All five connectors confirmed "free of credits, and queryable by the assistant" on the Connect Data page. They're data pipes, not AI-generated deliverables — folding them into the platform's advertised "36 tools" count somewhat overstates the AI-tool catalogue to a prospective buyer. That's a labeling fix, not a price fix.

Where the leverage actually is

Sorted by multiplier — the highest-confidence, lowest-risk increases first. All of these have no open bugs blocking a price change today.

The pattern: the highest-multiplier moves are all currently-clean 1-credit tools (Content Pillar Framework, Competitors Identifier, Keyword Analysis, Caption Generator, llms.txt Generator) — no bug fixes required, no trust risk, purely a "this was priced as a lookup but delivers strategy-consultant-tier output" correction. The tools with the largest absolute dollar increase (AI Page Rewrite, Media Plan Generator, AI Mentions Tracker) either need a bug fixed first or carry a COGS question — sequence those after the clean wins above.

What this table adds up to

1. The catalogue is systematically underpriced relative to the freelance market — often by 10–50x, sometimes 100x+. The widest gaps: On-Page Optimisation (108 headings for 17¢ vs. a $100+ Fiverr audit), Persona Generator (10 personas for 17¢ vs. one for $15–25), Content Pillar Framework (a full strategy for 3¢ vs. $100–400), and AI Mentions Tracker (up to 15 live LLM calls for 33¢ vs. $29–499/month standalone). These four are the clearest, lowest-risk places to raise price — output quality already clears the bar a higher price implies.
2. Some underpriced tools have open bugs that should be fixed before the price goes up, not after — AI Content Optimiser (incomplete rewrite), AI Page Rewrite (fabricated review schema), Media Plan Generator (generic funnel section), Backlinks Explorer (broken-backlink count mismatch), SEM Ad Copy Generator (truncated copy), Persona Generator (undercounting summary). Full detail on all of these is in the fix report.
3. A few tools are already correctly priced and shouldn't move: Rank Checker, Schema Generator, Content Checker, Full Site Audit — either already matching their Fiverr-equivalent tier, or cheap-and-simple-by-design tools meant to be run constantly.
4. AI Mentions Tracker is the single highest-priority pricing action — the most underpriced relative to the freelance/SaaS market and a possible COGS risk (up to 15 live LLM API calls for $0.33). This is likely a margin question, not just a revenue one.
5. None of these increases threaten the "radically cheaper than alternatives" story. Even after every recommended increase, every tool remains at least 90% cheaper than its Fiverr equivalent, and the bundling argument — replacing $350–1,800+/month in stacked subscriptions with one $199/month plan — is untouched. This is "capture some of the value you're clearly already delivering," not "charge what the market would bear."

What this analysis can't tell you

The multiplier and USD columns above answer "is this fair relative to the market." They don't answer "what will this actually do to revenue" — that needs data this research doesn't have access to. In order of how much they'd change the recommendation:

1. Usage volume per tool — the biggest gap. Every number above is a per-run price change; none of it is weighted by how often each tool is actually run. A 6–8× increase on a rarely-used tool moves revenue less than a 1.6× increase on your most-run tool. The Admin console's "Tool Runs" data and each tool's run count in Projects & Runs should let you build a real $ revenue-impact model in about an hour — multiply each tool's monthly run count by its price delta. Worth doing before finalizing any number here.
2. New customers vs. existing customers. This research doesn't address whether increases apply going forward only, or retroactively to existing subscribers — the latter needs advance notice under most terms of service and risks churn that a pure market-rate comparison can't predict.
3. Credit-pack and plan-allowance consistency. If per-tool credit costs go up, the included monthly allowance (6,000cr on Expert) effectively buys fewer total runs than before, and the top-up pack prices ($15/300cr, $45/1,000cr, $99/2,500cr) weren't re-examined against the new per-tool economics. Worth a pass to confirm the whole credit system still feels coherent after these changes, not just each row in isolation.
4. Elasticity and churn risk. "This is underpriced relative to Fiverr" is a fairness argument, not a revenue-maximization one — some price-sensitive customers may churn even off a fair increase, and this research has no A/B data or churn model to weigh against the upside. Recommend piloting the highest-confidence movers (see "Where the leverage actually is," §07) on a subset of accounts before a blanket rollout.
5. COGS validation, still pending. The report flags AI Mentions Tracker, AI Content Optimiser, Full Site Audit, and AI Video Generator as possible margin risks based on the compute/API load each run implies — but real COGS numbers live in your billing dashboards, not anywhere this research could reach. This should happen before, or at least alongside, any of these four getting repriced.
6. Enterprise/custom pricing isn't covered. This table is entirely about the public self-serve credit price. Larger agency accounts negotiating custom rates are a separate conversation this research doesn't touch.