Explanation:

✅ A. The total number of records on the lookup object. → Correct
Lookup queries run against the lookup object (e.g. a custom object you’ve created for pricing rules). The more records exist on that object, the more rows are scanned and potentially returned. Salesforce has limits on total rows returned across all queries, so larger datasets increase row counts quickly.

B. The total number of lookup objects. → Incorrect
Having multiple lookup objects doesn’t itself directly increase query rows. It may increase the number of queries, but the count of rows depends on records in each object and how often those objects are queried. Merely having many objects is not a direct multiplier of row count.

✅ C. The total number of quote lines on the quote. → Correct
Lookup rules often run once per quote line. So if you have 100 quote lines, and one lookup rule, that’s potentially 100 queries. Each of those queries might return multiple rows, multiplying the row count.

D. The total number of fields on the lookup object. → Incorrect
Fields don’t impact row count. More fields only affect query width (number of columns), not number of rows returned.

✅ E. The total number of lookup queries. → Correct
Each lookup rule equals at least one query. Multiple rules, or multiple lookups in a single rule, multiply the total rows returned. For example:
2 Lookup Queries × 100 Quote Lines × 50 records in the lookup object = potentially 10,000 rows considered.

✅ How Lookup Row Limits Work

Salesforce CPQ limits the number of rows retrieved across all Lookup Queries for a quote. Each lookup query multiplies by the number of quote lines. Hence, three factors directly impact row volume:
- How many records exist in the lookup object → A
- How many times lookup runs (e.g. per quote line) → C
- How many lookup queries fire → E