Skill: HG Momentum Signals
Detect which companies are growing into or fading out of a product — not just who has it today, but where the trajectory is heading.
Overview
Teach Claude to query and interpret HG's momentum, trending, and time-series tables so it can detect companies where product usage is growing or declining — the signal behind 'companies using Workday but less and less.'
Use cases
Target accounts in a platform transition window
When intensity_momentum goes negative, the company is pulling back from a product. That's a displacement window — and the workflow catches it automatically by querying install_intensity_momentum_global and ranking by the steepest decline.
Find companies doubling down on a technology bet
Positive momentum + rising trending = a company investing more in a platform. Perfect for cross-sell or expansion plays — and the skill teaches Claude exactly how to query and interpret the signal.
View full skill
HG Momentum Signals
When to use
- Detecting companies where product usage is growing or declining
- Queries that need "companies using X but less and less" or "companies ramping up on Y"
- Time-series analysis for trend validation
Three tables, three granularities
| Table | Field | Granularity | Use |
|---|---|---|---|
install_intensity_momentum_global | intensity_momentum | Single score per product×company | Quick filter: declining vs. growing |
install_intensity_trending_global | intensity_trending | Trending direction | Confirm direction when momentum is ambiguous |
install_time_series_global | weighted_score × date_verified | Monthly snapshots | Granular trend analysis and charting |
Momentum interpretation bands
intensity_momentum value | Interpretation |
|---|---|
| < −20 | Significant decline — active pullback, displacement window |
| −20 to 0 | Slight decline — worth monitoring |
| 0 to 20 | Stable — no clear directional signal |
| > 20 | Growing — company investing more in this product |
Query pattern: declining usage
SELECT cl.name, cl.country_name, cl.revenue_min,
m.intensity_momentum, ig.intensity
FROM install_intensity_momentum_global m
JOIN install_global ig ON m.url_id = ig.url_id AND m.product_id = ig.product_id
JOIN company_locations cl ON m.url_id = cl.url_id
WHERE ig.vendor_name = 'Workday, Inc.'
AND cl.is_ghq = true
AND m.intensity_momentum < -20
ORDER BY m.intensity_momentum ASC
LIMIT 100
Query pattern: growing usage
SELECT cl.name, cl.country_name, cl.revenue_min,
m.intensity_momentum, ig.intensity
FROM install_intensity_momentum_global m
JOIN install_global ig ON m.url_id = ig.url_id AND m.product_id = ig.product_id
JOIN company_locations cl ON m.url_id = cl.url_id
WHERE ig.category_leaf_name = 'Cloud Security'
AND cl.is_ghq = true
AND m.intensity_momentum > 20
ORDER BY m.intensity_momentum DESC
LIMIT 100
When to use each table
| Need | Table | Why |
|---|---|---|
| Filter a list by "declining" or "growing" | install_intensity_momentum_global | Single score, fast filter |
| Confirm an ambiguous momentum score | install_intensity_trending_global | Trending direction adds a second signal |
| Deep dive on one account's product trajectory | install_time_series_global via company_install_time_series tool | Monthly datapoints for trend analysis |
Credit implications
- Momentum and trending table queries via
hg_data_query: dynamic credits (varies by query complexity) company_install_time_series(per-account): 3 credits per product returned (default up to 10 products; can exceed 30 credits at max)- Time-series table has 5.5B rows — always filter by
product_idfirst to avoid expensive full-table scans
Reference
hg-insights-api.md#company_install_time_series— per-account time-series toolhg-data-query-discipline— safe ClickHouse query patternshg-recent-signals— recency (fresh vs. stale), distinct from momentum (growing vs. declining)