Comps

Comps is the peer-comparison and relative-valuation workspace inside a company’s Data Viewer. You build a curated peer set — the company you are viewing plus the comparable companies you choose — pick the standard financial metrics and ratios you want to line them up on, set a year range and quarterly or annual periods, and read every peer side by side in a sortable comparison table with a clean trend chart for each metric. Peer sets and metric selections can be saved as named configurations that sync to the cloud, so the same comp set follows you across sessions and devices. Find it under Equities → Comps for any company. Users also call it “Comparables,” “Peer comparison,” “Relative valuation,” or “Comp tables & graphs.”

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What it is

Comps lets you compare one company against the peers you pick, on the financial metrics and ratios you choose, over the time window you set. The current company is always pinned into the set; you add the rest by ticker or name (or with one click from its suggested peer group), then choose any number of income statement, balance sheet, cash flow, and ratio line items. The results come back two ways at once:

• A trend chart for each selected metric, with every company plotted as its own series, so you can see how the group’s revenue, margins, leverage, returns, or valuation diverge over time.
• A synchronized comparison table underneath, grouped by year and period, with each company’s exact figures side by side for sorting, filtering, and cell-level selection.

The fundamentals and ratios behind the comparison are sourced from FactSet and standardized by AllMind AI, so the line items and ratios are apples-to-apples across the group.

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When to use it

Reach for Comps when you want to compare one company against its peers on the same financial metrics and ratios over time — relative-valuation and benchmarking work where you already know (or want to hand-pick) the companies in the group:

• Build a comp set for a sector or thesis — semis, large-cap pharma, regional banks — and line them up on the metrics that matter.
• Compare revenue, margins, leverage, returns, or valuation ratios across the group on a common basis.
• Watch how a peer group’s metric trends diverge over several years.
• Save the comp set to reuse each quarter so you are not rebuilding the group every reporting cycle.
• Hand off the comparison to Excel, a chart image, a bookmark, or the AI assistant.

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When to use something else instead

Comps is a curated peer set measured on standardized financial metrics and ratios with time-series charts, saved configurations, and exports. Grids runs many companies against your own questions at scale; Comps covers reported, historical actuals and ratios — not forward estimates.

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How to use it

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What you get

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Working areas

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Key capabilities

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What you can take away

• Excel (.xlsx) export of the comparison table, AllMind authored, with header freeze and financial formatting.
• CSV export of the comparison table.
• Branded PNG of any individual metric chart, including per-series total change and CAGR.
• Bookmarked table saved to your bookmarks / Insights.
• Full comparison table pushed into AI Chat as structured context for follow-up questions.
• Named, cloud-synced saved configurations — reusable comp sets.

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Data & sources

• Company fundamentals and standardized ratios — income statement, balance sheet, and cash flow line items plus computed financial ratios — are sourced from FactSet and standardized by AllMind.
• The suggested peer group behind Add Relevant Comps comes from the company’s profile peer list.
• The searchable company universe for the peer-set builder covers US and Canadian listed securities.
• Saved configurations are stored in your AllMind account so peer sets persist across sessions and devices.

The table footer also credits the platform’s wider data sources — Estimates via LSEG IBES & Broker Estimates and ESG via MSCI — which power other tabs rather than the Comps comparison itself.

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Tips & best practices

• Seed with Add Relevant Comps, then refine. Start from the suggested peer group in one click, then add or remove names to match your exact thesis rather than building the set from scratch.
• Add the ratios, not just the line items. Margins, returns, leverage, and valuation multiples line up the group on a common basis even when absolute sizes differ; they carry the right %, x, and days formatting automatically.
• Use the trend stats to read divergence fast. Each chart’s per-series CAGR and total change tell you at a glance which peers are pulling ahead or falling behind over the window.
• Save the set you will revisit. Store the comp set under a name so it is ready next quarter; the cloud sync makes the same set available on any device.
• Send the table to the AI assistant for the “why.” Push the full comparison into AI Chat and ask which peer is cheapest on EV/EBITDA, or what is driving a margin gap across the group.
• Flip Quarterly / Annual to match the question. Use quarterly for near-term momentum across peers, annual for the longer arc and cleaner multi-year trend lines.

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Limits & things to know

• Up to 10 saved configurations are retained per user; saving more drops the oldest.
• The current company is always forced into the peer set and cannot be removed.
• Both metric search and company/ticker search return up to 100 matches at a time.
• Coverage is US and Canadian listed securities — the searchable ticker universe.
• The year range defaults to the last four years. The selector spans a wide historical range, but actual depth depends on the company’s reported history available from the data provider.
• Charts and table show reported, historical actuals and ratios — not forward estimates or forecasts. For the forward view, use Estimates.
• Companies with no fundamental data in the chosen window simply show blank, dash (—) cells for the affected metrics rather than dropping out of the comparison.
• Data is cached briefly for performance (roughly six hours per company and year range), so very recent restatements may take time to refresh.
• Saved configurations capture companies, metrics, and year range — not chart styling choices.

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Availability

Comps is available to signed-in users within a company’s Data Viewer, and saved-configuration cloud sync is tied to your account. There is no separate entitlement or paywall on the Comps surface beyond being signed in — it relies on fundamentals, so unlike the Price Analysis tab it is not gated to full-market-data US tickers.

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Works with other features

Because saved comp sets are cloud-synced, the same group is ready across your sessions and devices.

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Example workflow

Goal: build a peer group for a thesis, benchmark valuation and margins across it, then package and reuse the work.

1. Open the lead company in the Data Viewer and go to Comps. Click Add Relevant Comps to seed the suggested peer group, then add or remove names by ticker until the set matches your thesis.
2. Add the metrics that matter — say Revenue, Gross Margin, EBIT Margin, Net Debt / EBITDA, and EV/EBITDA — and set the Years range to the last five years on the Annual view.
3. Read the per-metric charts: use the CAGR and total-change stats to see which peers are compounding fastest and which are re-rating, then export the EV/EBITDA chart as a PNG for your memo.
4. Press Add to AI Chat and ask the assistant, “Which peer looks cheapest relative to its margin and growth?” — answered against the exact comparison table.
5. Save the comp set under a name so it is ready next quarter; it syncs to the cloud and appears on any device. Bookmark the table and export it to Excel for your model.
6. To extend the work, run a Grid that asks each peer your own custom questions at scale, check Estimates for where consensus expects the group to land next, and generate a Report on the lead name grounded in the same numbers.

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FAQ

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Getting help

For help using Comps or to talk through a relative-valuation workflow, reach AllMind support through the in-app support option or your account team. For a guided walkthrough, book a session from the Help link in the top navigation.