1 min lesson
Cost vs. coverage
Pick two rows from the table in "Cost vs. coverage" and explain the choice each one supports.
Step 1 of 3
Cost vs. coverage
Every provider call costs money and latency. The whole design is a dial between filling more fields and spending less.
- Lever
- Chain depth
- Push toward coverage
- More providers per field
- Push toward cost
- Stop after 2-3; accept some blanks
- Lever
- Confidence bar
- Push toward coverage
- Accept lower-confidence values
- Push toward cost
- Only accept verified values
- Lever
- Field set
- Push toward coverage
- Enrich 30+ data points
- Push toward cost
- Enrich the handful scoring actually uses
- Lever
- Trigger
- Push toward coverage
- Enrich every record
- Push toward cost
- Enrich only records that pass a cheap pre-filter
| Lever | Push toward coverage | Push toward cost |
|---|---|---|
| Chain depth | More providers per field | Stop after 2-3; accept some blanks |
| Confidence bar | Accept lower-confidence values | Only accept verified values |
| Field set | Enrich 30+ data points | Enrich the handful scoring actually uses |
| Trigger | Enrich every record | Enrich only records that pass a cheap pre-filter |
Interviewers love "enrich only what scoring needs." Spending to fill a field no decision reads is pure waste.
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Full explanation
Caching and freshness
Caching and freshness
Re-enriching a record you already have is the most common way GTM bills balloon. Cache aggressively, but give cached values a shelf life.
- Key the cache by normalized domain or email plus field name, so a hit skips the entire chain for that field.
- Attach a TTL per field group: a company's headcount can be weeks stale, a person's current employer should expire sooner.
- On a stale read, re-enrich in the background and serve the old value now - don't block the pipeline waiting for freshness.
- Track a per-provider hit-rate over time; a vendor whose coverage quietly drops should fall in the order.