Einstein Search Dictionaries
Einstein Search Dictionaries is the Salesforce configuration feature that lets admins define synonyms, abbreviations, and equivalent terms so global search returns the same records regardless of how the user phrases the query.
Definition
Einstein Search Dictionaries is the Salesforce configuration feature that lets admins define synonyms, abbreviations, and equivalent terms so global search returns the same records regardless of how the user phrases the query. Mapping "acct" to "Account", "IBM" to "International Business Machines", or "qty" to "quantity" means both query forms find the same records. Dictionaries apply across the Lightning global search bar, list-view searches, Experience Cloud search, and any search that uses the Einstein Search engine.
Dictionaries are managed per language; each org maintains separate dictionaries for English, French, German, and so on, scoped to the languages the org uses. The configuration is no-code: admins add term mappings in Setup, the index picks them up automatically, and search behavior changes within minutes. The feature is one of the cheapest improvements to global search quality, and one of the most underused; orgs that invest in dictionary curation see immediate measurable improvements in zero-result rates.
Why the dictionary edit is one of the highest-ROI hour-of-admin-time options
Where Search Dictionaries lives in setup
Setup, Search, Search Dictionaries. The page lists existing dictionaries per language, with the term mappings inside each. Click into a dictionary to add, edit, or remove mappings. Each mapping is a list of terms that should all return the same search results: ["account", "acct", "client", "customer"]. The mapping is bidirectional and symmetric; searching for any term in the list finds records that match any other term in the list. Mappings apply across all searchable objects unless restricted via dictionary scope.
How dictionaries change search behavior
When a user searches, Einstein Search expands the query through the dictionary before running it against the index. A search for "acct" becomes a search for ("acct" OR "account" OR "client" OR "customer") with the dictionary mapping above. Results returned are de-duplicated and ranked by relevance. The expansion happens server-side; users do not see the expanded query. The dictionary affects every search that goes through the Einstein Search engine, which is the global search bar, list-view filter search, and Experience Cloud search. SOQL queries are unaffected.
Term mapping patterns that pay off
Three patterns produce the largest ROI. Abbreviations and shorthand: acct, qty, mgr, dept, hrs, mins. Industry-specific terms: SKU and product code, PO and purchase order, RMA and return authorization. Company-specific terms: internal product names mapped to formal product names, project codenames mapped to official names. Add 50 to 100 mappings in the first audit; most orgs see noticeable improvement in search satisfaction surveys within a week of the change going live.
Language scope and the multi-language reality
Each language has its own dictionary. An English dictionary mapping acct to account does not affect French searches. Multi-language orgs need to maintain dictionaries per language they support. The translation work is real; "acct" in English has different shorthand equivalents in French (cpt for compte). Most multi-language teams underinvest in non-English dictionaries because the admin is usually English-first; the non-English search experience suffers as a result. A quarterly review with native speakers per language catches the gap.
Standard vs custom dictionaries
Salesforce ships standard dictionaries for common terms (basic abbreviations, common synonyms). The standard dictionary is read-only and updates with Salesforce releases. Custom dictionaries are admin-managed and contain the org-specific mappings. When a term appears in both a standard and a custom dictionary, custom wins. The pattern is to leave standard untouched and add custom mappings for everything org-specific. Most teams discover halfway through their audit that some of what they were planning to add already exists in standard; check standard first.
Common authoring mistakes
Three mistakes recur. Over-broad mappings: putting both "account" and "user" in the same mapping confuses results because the two terms refer to different objects. Single-direction thinking: forgetting that the mapping is symmetric and adding only ("acct" -> "account") when the team also needs ("account" -> "acct"). Lack of audit: adding 100 mappings on day one and never reviewing again. Each mistake produces a search experience that is slightly worse than no dictionary at all, because users learn to distrust the search.
Sourcing mappings from real query data
The fastest path to a useful dictionary is mining the zero-result search log. Salesforce reports surface queries that returned no results, sorted by frequency. The top 50 zero-result queries each week tell admins exactly which terms users want to search for that the system does not recognize. Adding mappings for those terms produces the most direct measurable improvement. Pull the report monthly, add 5 to 15 mappings, review impact next month. The cadence is what compounds value.
How to build and maintain a Search Dictionary that earns its keep
The 80/20 rule for Search Dictionaries: 80 percent of the value comes from the first 50 mappings sourced from real zero-result queries, and 20 percent of the value comes from the next 200 mappings sourced through anecdote. Mine the data, then iterate monthly. Skipping the data step produces mappings that look thorough and miss what users actually search for.
- Pull the zero-result search log
Setup, Search, Search Insights (or Reports, Search Term Reports). Sort by frequency, descending. The top 50 queries with no results are your initial mapping candidates.
- Map each top zero-result query to existing terms
For each query, find the term it should match (acct -> account, qty -> quantity, mgr -> manager). Add the mapping as a symmetric list in Setup, Search, Search Dictionaries.
- Confirm standard dictionary coverage first
Some terms already exist in the standard dictionary. Adding a duplicate in custom does not hurt but wastes admin time. Check standard before authoring.
- Add per-language dictionaries for multi-language orgs
English admins regularly forget the non-English dictionaries. If the org operates in French, German, Spanish, etc., the same mappings need translation work per language.
- Wait one week and re-pull the zero-result log
The added mappings should reduce zero-result rates on the queries you addressed. The log confirms whether the mappings work or need refinement.
- Add per-object scope if mappings create cross-object noise
Some mappings should apply to specific objects only (a custom acronym used on Account but not on Contact). Use dictionary scope to restrict.
- Schedule a monthly mapping review
Pull the zero-result log monthly. Add 5 to 15 new mappings. The cadence is what keeps the dictionary aligned with how users actually search.
Per-language dictionaries. Each language needs its own mappings; English mappings do not affect French searches.
Mappings are symmetric by default; every term in the list is interchangeable with every other.
Restrict a mapping to specific objects when the term has different meanings on different objects.
Standard is Salesforce-managed and read-only; custom is admin-managed. Custom wins on conflict.
Zero-result log mining is the highest-ROI source; anecdote is the lowest-ROI source.
- Over-broad mappings (account + user in one list) confuse results across object types. Keep mappings tight to a single concept.
- Mappings are symmetric by default; "acct" -> "account" automatically also makes "account" find "acct" matches. Plan accordingly.
- Multi-language orgs need per-language dictionaries. The English admin who forgets this leaves the non-English search experience untouched.
- Standard dictionary coverage is wider than most admins expect. Check standard before authoring custom mappings to avoid duplicating work.
- Mappings that are not reviewed go stale. Quarterly review with the zero-result log keeps the dictionary aligned with how users actually search.
Trust & references
Cross-checked against the following references.
- Search Dictionaries referenceSalesforce
- Salesforce Search overviewSalesforce
Straight from the source - Salesforce's reference material on Einstein Search Dictionaries.
- Einstein Search DictionariesSalesforce Help
- Search OverviewSalesforce Help
- Search Term ReportsSalesforce Help
About the Author
Dipojjal Chakrabarti is a B2C Solution Architect with 29 Salesforce certifications and over 13 years in the Salesforce ecosystem. He runs salesforcedictionary.com to help admins, developers, architects, and cert/interview candidates sharpen their fundamentals. More about Dipojjal.
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