This article answers common questions about custom indexes that appear on Salesforce custom fields without any admin or support request. Salesforce administrators may notice a field has been indexed and wonder what triggered it, whether it improves performance, and what happens if the index is removed.
Salesforce includes an automated custom index recommender process that monitors query performance across the platform. When the process identifies slow, selective queries that could benefit from an index, it creates one automatically — no manual request is needed. This article explains the selection criteria, the performance value these indexes provide, and the behavior of the recommender after an index is deleted.
The following answers address the three most common questions about Salesforce auto-created custom indexes.
**What performance value do auto-created indexes provide?**
These indexes are built to tune queries that the automated custom index recommender process identified as both slow and selective. Adding an index allows Salesforce's query optimizer to avoid full table scans on those fields, reducing query execution time for affected records.
**How does the recommender process select which fields to index?**
The process applies a formula to estimate the total query processing time that could be saved over a one-week period if a given field were indexed. The formula considers two factors:
The recommender indexes the highest-value fields it identifies, but only when the estimated time saved exceeds a minimum threshold. Fields with low selectivity or infrequent query usage will not meet the threshold and will not be auto-indexed.
**If an auto-created index is removed, will the process add it back?**
No. When an auto-created index is removed, Salesforce marks it as removed in the custom index recommender table. The automated process will not re-create that index in the future.
Additionally, Salesforce tracks usage statistics on all auto-created custom indexes after they are created. This data informs ongoing tuning decisions by the recommender process.
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