Built for RevOps and admins who live in field setup
The field taxonomy is the data model. Most CRMs charge for that.
Fields look like the simplest thing in a CRM evaluation and end up driving the biggest total cost. Picklist cardinality limits, formula field tiers, rollup gates, dependent picklists only on certain SKUs. Strkr ships 14 field types with formulas, rollups, lookups, dependent picklists, and per-record-type visibility on every paid seat.
Shadrach is a RevOps lead at a mid-market SaaS company who inherited a Salesforce org with 1,142 custom fields on Account alone. Priya runs ops at a logistics firm on HubSpot Enterprise and spent six weeks waiting for a Signature Success rep to walk her through why her calculated property kept returning null on new deals. Both of them told the same story on an evaluation call: the field system is where the CRM either stays sane or becomes a political problem. The six items below are what shows up on every RevOps buyer call when the discussion turns to fields and admin surface.
Field explosion
A thousand custom fields nobody uses.
The typical mid-market Salesforce org carries 400 to 1,500 custom fields on Account, Contact, and Opportunity combined. Perhaps 30 percent get used weekly. The rest are archaeology: a 2019 campaign tag, a dead integration, a VP's one-time report requirement. The admin cost to prune is high enough that nobody prunes. Strkr's field admin surface shows last-write-date and last-read-date per field so you can see what is actually in use.
Formula tier gating
The formula field is on the next SKU up.
HubSpot calculated properties sit behind the Enterprise tier for most meaningful math. Pipedrive formula fields require the Power tier. Zoho Deluge-powered custom functions live on the Enterprise edition. The field type that most RevOps teams need (a formula that references related records) ends up gated. Strkr ships formula fields on every paid tier with the full operator set: arithmetic, text, date math, conditional, lookup chain traversal.
Picklist cardinality
The dropdown that broke at 1,000 options.
Industry-code picklists (NAICS carries roughly 1,057 codes), state picklists, country picklists, product-category pickers. Several CRMs cap picklist cardinality at 1,000 values or performance-degrade past 500. The workaround is a lookup object or a free-text field, both of which drift. Strkr supports picklists up to 10,000 values with type-ahead search and dependent-picklist chains that scale with the parent cardinality.
Rollup aggregation gates
The rollup only runs on Enterprise.
Salesforce roll-up summary fields require a master-detail relationship, which forces a schema design decision upstream. HubSpot calculated properties with lookup references land on Enterprise. Pipedrive does not do rollups natively. The workaround is a nightly batch job via middleware. Strkr rollups work across lookup relationships without the master-detail constraint, update in real time, and ship on every paid tier.
Dependent picklist complexity
Country then State then City should not take four hours.
Dependent picklists (the second dropdown filters based on the first dropdown value) are a standard business requirement that most CRMs implement with a dedicated admin surface and a 3 to 4 hour setup time for a typical chain. Strkr handles dependent picklist chains of up to 4 levels with a visual mapping surface, imports the Country-State-City chain from a shipped reference set, and lets admins override specific pairings without rebuilding the whole chain.
Field-level security
The per-role visibility only works on paper.
Field-level security (which roles see which fields) is advertised by every CRM and implemented inconsistently. Salesforce field-level security works but requires profile and permission-set gymnastics. HubSpot field-level permissions landed in 2022 and still have gaps. Strkr field-level visibility sits inside the Layouts system with per-role, per-record-type, and per-record-stage toggles. The admin configures once; the SDR, the AE, and the CFO see the fields they should.
The 14 field types in detail
Every field type a real CRM needs.
The baseline field types that modern CRM evaluation runs through. Each one ships on every paid Strkr seat with no SKU gating and no per-field cost. The nine cards below cover the capabilities each type carries and where competitors tend to fall short.
Text and long text
Short text, long text, and rich text with a cap you can trust.
Short text to 255 characters, long text to 10,000, and rich text with a 10,000 character server-side max plus a client counter that blocks save at the limit. Rich text ships with the standard inline toolbar (bold, italic, headings, lists, links) and renders inside the record detail without a lightbox. Priya at the logistics firm had been running her engineering-notes field as a HubSpot long text at 2,000 characters and losing paragraphs on paste; the first week on Strkr she stopped losing content.
Numeric and currency
Decimals, precision, and multi-currency without a module.
Numeric fields with 0 to 10 decimal precision. Currency fields with ISO 4217 codes, exchange-rate tables that refresh daily from a central bank reference, and roll-ups that compute in a canonical currency and display per user. The CFO closes the quarter and the pipeline figure in USD, GBP, and EUR agrees across the three regional dashboards.
Date and datetime
Timezone-aware dates with the quirks resolved.
Date fields that do not drift across timezones (a problem that bit Shadrach for a full quarter on his old Salesforce org when deals were closing on a Sunday for the EMEA team but Monday for the US dashboard). Date-only, datetime, and date-range types. Business-day math for SLA calculations with per-tenant holiday calendars. Fiscal-year math with per-tenant fiscal start dates.
Picklist and multi-picklist
Single and multi-select with 10,000-value ceilings.
Single-select picklists with inline type-ahead. Multi-select with a maximum selections cap you set per field. Values are stored as structured IDs so renames do not break history. Deactivated values hide from new selections but legacy records keep rendering the historical selection. Picklist value audit log retains who added what value when.
Dependent picklist
Up to 4-level chains with visual mapping.
The parent picklist filters the child picklist, which filters the grandchild, up to 4 levels deep. The visual mapping surface shows the matrix of allowed combinations and highlights unmapped parents. Imported reference sets (Country to State to City, NAICS 2-digit to 4-digit to 6-digit, Product line to Product family to SKU) ship so admins start with a working baseline. Overrides apply at the pair without rebuilding the chain.
Lookup and multi-lookup
Related-record references with cascade control.
Lookup fields point to another record (an Account on a Contact, a Product on a Deal). Multi-lookup fields point to a set of records. Cascade behavior on delete is configurable per field (set null, prevent delete, cascade delete). Lookup filters narrow the choosable set at edit time (only active accounts, only accounts in the user's territory). Lookup chains feed the formula and rollup engines.
Formula
Real formulas with lookup traversal and date math.
The full operator set: arithmetic, string manipulation, date math, conditional (IF, CASE), null-safe arithmetic, lookup chain traversal up to 5 hops. Formula fields recompute on dependency change. Circular dependency detection surfaces at save time instead of at the first null read. Shadrach rebuilt his old Salesforce roll-up-of-rollup chains as native formulas on Strkr in 90 minutes.
Rollup summary
Aggregates across lookup relationships, in real time.
Count, sum, min, max, average, and concatenation rollups across one-to-many relationships. The rollup updates in real time (sub-second for the common case). Filters narrow the aggregated set (sum of closed-won deals only, count of contacts marked primary only). Nested rollups work: the account roll-up of its deals that roll up their line-item quantities.
User, file, and URL types plus the rest
User references, file attachments, URL fields, boolean, address.
User lookup field for owner, assignee, or any role. File attachment field with S3-backed storage and per-field size caps. URL field with click tracking. Boolean with a labeled display mode. Address field as a structured block (line 1, line 2, city, state, postal, country) with validation and geocoding. Phone field with E.164 formatting and country-code picker. Email with validation and deliverability check.
The admin surface in detail
How Strkr admins stay sane.
The field admin surface is where real teams either stay in control of their CRM or lose a weekend every month to field debt. The six items below cover the admin capabilities that make the difference at the 100-field mark, the 500-field mark, and the 1,000-field mark.
Field usage analytics
Last-write and last-read dates per field.
Every field carries a last-write-date (when any record last had this field edited) and a last-read-date (when any user or integration last read this field through the API or the UI). Admins see the field debt directly. Shadrach ran this report in his second week and queued 340 custom fields for retirement, which the team closed over a 6-week cleanup sprint. The second quarter after the cleanup, Salesforce migration planning was easier because the field count was honest.
Change audit log
Who changed which field setting when.
The admin audit log captures field creation, label changes, type changes (where allowed), picklist value additions and deactivations, formula edits, visibility changes, and deletions. The compliance officer at a regulated firm pulls the audit as evidence that field changes went through the approval path. The ops lead at a non-regulated firm uses it to find out which admin broke the deal probability formula on a Tuesday morning.
Bulk edit and migration tools
Rename, retire, and remap at scale.
Rename a field and the API, the formulas, the layouts, and the saved views refresh together without a breaking change. Retire a field and the system archives the data for configurable retention before purge. Remap values at import time (your legacy Qualified-A picklist value maps to the current Qualified Discovery value) with a one-screen mapping surface. These three operations are the deepest friction on most CRM migrations and ship on Strkr out of the box.
Per-record-type layouts
The Lead layout, the Contact layout, the Deal layout per type.
Record types (Lead, Contact, Deal, Account, Product, Order, Case, custom objects) each carry their own layout. Within a record type, per-pipeline or per-stage layouts show the right fields at the right moment. The SDR sees the lead-qualification fields on a lead. The AE sees the deal-stage fields on a deal in Discovery. The CS lead sees the renewal fields on an account approaching renewal. Priya rebuilt her 7-pipeline HubSpot deal setup as 7 Strkr pipelines in an afternoon.
Field-level permissions
Per-role, per-record-type, per-stage visibility.
Field visibility and editability toggles per role (SDR, AE, Manager, Admin, CS, Finance). Per record type (hide the margin field from BDRs on all pipelines). Per stage (expose the win-reason field only when a deal reaches Closed Won). The admin configures once in the Layouts system and the behavior cascades to the record detail, the list view, the inline edit, and the API serializer so no path leaks a field the role should not see.
Import mapping library
The CSV import that does not require three attempts.
The CSV import surface remembers the mapping from the last import of a similar file. Fuzzy-match on header names (Company becomes Account Name, Phone becomes Phone, Mobile becomes Mobile Phone). Picklist value remap at import. Duplicate detection on configurable match keys (email, phone, external ID). Error rows export back with the validation failure attached so the admin fixes once instead of guessing.
What breaks on competitors
The field-system failures that drive migration.
Teams move off a legacy CRM for a reason. In the field-system space, the reasons concentrate on six issues that each cost real money or real time. The cards below are the field-system failures that show up on every migration call.
Salesforce field limits
800 custom fields per object on Enterprise.
Salesforce caps custom fields at 500 on Professional, 800 on Enterprise, and 900 on Unlimited. Teams that cross 500 fields on Account hit the limit mid-project and either pay for the next tier or compromise the data model. Strkr caps at 1,000 fields per object with the understanding that nobody should actually get there, with the field-usage analytics surfacing the cleanup opportunity.
HubSpot calculated-property gaps
The Enterprise-tier formula that still cannot do what you need.
HubSpot calculated properties support a working set of operators but hit specific gaps: multi-step lookup chain traversal is limited, date-math around fiscal calendars requires workarounds, and the editor is a single-expression field rather than a multi-step formula with named intermediates. Strkr formula fields support named intermediate values so complex calcs stay readable 18 months after the admin who wrote it leaves.
Pipedrive field type ceiling
The CRM for sales simplicity hits the complexity wall.
Pipedrive's field type set is deliberately narrow (text, numeric, picklist, date, user, phone, email, address, monetary) with limited formula support until the Power tier and no rollup fields native. The simplicity is a feature at 10 to 30 reps and a constraint at 60 reps. Strkr covers the simplicity bands with sensible defaults and scales to the rollup-plus-formula depth without a tier change.
Zoho module admin tax
Deluge is a scripting language, not a configuration surface.
Zoho CRM's power features frequently require Deluge, Zoho's proprietary scripting language. Admins without a developer background end up either outsourcing to a Zoho consultant or living with the baseline. Strkr's formula editor is a visual builder with a text-mode toggle for the admin who wants to type. Both modes compile to the same runtime so the handoff from a visual-first admin to a text-first admin is lossless.
Attio flexibility, Attio ceiling
Flexible data model, newer platform, feature gaps on the enterprise end.
Attio ships a flexible object-and-attribute model that reads well on the setup screen. The ceilings show up at the enterprise end: fine-grained permissions, long-form audit, compliance retention postures, and large-scale import tooling are still maturing. Strkr matches the flexibility of the Attio-style model and ships the enterprise plumbing (SOC 2 Type II in progress through 2026-Q4, HIPAA with BAA on request, long-form audit retention) that regulated teams need in year one.
Monday CRM field limits
Column types that stop short of a real CRM taxonomy.
Monday CRM is built on Monday.com's board model. The column-type set is strong for project tracking (status, people, timeline, numbers) and thinner on CRM specifics (dependent picklists, lookup chain traversal, roll-ups across relationships, address with geocoding). Teams migrating from Monday CRM to Strkr typically cite the gap: the CRM-primitive field types with the CRM-adjacent plumbing (audit, retention, permission layering).
Head-to-head
Strkr fields vs Salesforce custom fields.
Salesforce is the default comparison for any serious field-system evaluation because the Salesforce data model has set the pattern most RevOps teams expect. The head-to-head below covers the capability match-up a RevOps lead runs during a replatform evaluation.
Feature
Strkr
Salesforce custom fields
Custom field cap per object
1,000 per object with field-usage analytics
500 Professional, 800 Enterprise, 900 Unlimited
Formula fields
Full operator set with named intermediates on every tier
Mature formula engine on every edition
Rollup summary fields
Rollups across lookup, real-time, on every tier
Rollups require master-detail relationship
Picklist cardinality
10,000 values with type-ahead
1,000 inactive plus active, performance notes
Dependent picklist chain
Up to 4 levels with visual mapping
Dependent picklists supported, 1 level common
Field-level security
Per-role, per-record-type, per-stage from Layouts
Via profiles and permission sets
Field usage analytics
Last-write and last-read-date per field
Available via FieldUsageMetricsRecord object
Admin audit log
Every setting change with before and after values
Setup Audit Trail with 180-day retention
Formula editor
Visual builder with text-mode toggle
Formula editor with syntax check
Pricing basis for formulas and rollups
Included on every paid tier
Included on every edition
How teams use Strkr
How RevOps teams run Strkr field systems.
The common thread across RevOps customer accounts: the field system scales with the business instead of becoming a political drag on it. The playbooks below are motions live on customer accounts right now.
Mid-market SaaS, 240 reps
Salesforce cleanup migration completed in 11 weeks.
Shadrach's team moved from Salesforce Enterprise with 1,142 custom fields on Account to Strkr with a pruned 310 fields. The field-usage analytics report drove the cleanup. The data move preserved 7 years of history on the retained fields. Formula fields rebuilt in 2 weeks. Rollup fields rebuilt in 1 week because the master-detail constraint went away. The team is on track to save roughly 198,000 dollars in year-one license cost against the Salesforce renewal that was going to land in Q2.
Logistics firm, 85 users
HubSpot calculated-property rebuild as native formulas.
Priya's team moved 44 calculated properties and 12 report-only workarounds to native Strkr formula and rollup fields. The win: 4 of the 44 calculated properties had been running on a middleware script because HubSpot could not express the logic. All 4 moved to native Strkr formulas with named intermediates. The ops team cut middleware spend by 1,100 dollars a month and the formulas are readable by the next ops hire without a knowledge-transfer session.
Multi-region manufacturer
Dependent picklist chain for 42 countries, 580 regions.
A manufacturer with distribution in 42 countries and 580 subregional sales territories rebuilt the Country-Region-Territory dependent picklist chain on Strkr. The visual mapping surface imported the base chain from reference data and the ops team overrode 23 specific pairings. The chain update that used to take a quarterly admin project now takes a single admin a half day when a new territory is added.
Regulated financial services firm
Field-level security audit cleared in one review.
A regulated financial services firm (RIA, 32 advisors) moved to Strkr and cleared the first annual field-level-security audit in one review session. The finding on the prior CRM was that 11 fields marked as compliance-sensitive were visible to roles that should not have seen them. On Strkr the Layouts system scoped the fields to the compliance-cleared roles and the audit evidence pulled directly from the audit log. The CCO called the audit the smoothest in 6 years of attestations.
Non-profit development team
Rollup field for lifetime giving across 14 years of history.
A nonprofit development team of 18 built a lifetime-giving rollup across 14 years of migrated gift history. The rollup aggregates gifts, pledge payments, DAF grants, soft credits, and matching gifts into one per-household lifetime value. The development director opens a household record and sees the full giving arc in a single number that updates in real time as new gifts post. The quarterly board report pulls from the rollup instead of a weekend Excel reconciliation.
A field system that stays in your control at 100, 500, and 1,000 fields.
Start a 14-day trial with the full field system enabled: 14 field types, formulas with lookup traversal, rollups without master-detail, dependent picklists with visual mapping, field-level security from Layouts, and the field-usage analytics that keeps the field count honest.
How many custom fields can I create per object in Strkr?
Strkr caps custom fields at 1,000 per object with field-usage analytics surfacing the cleanup opportunity. The practical reality is that healthy CRM instances run 150 to 400 custom fields per object. Teams migrating from Salesforce with 500 to 1,500 field counts typically see 60 to 70 percent of those fields drop out as archaeology once last-read-date and last-write-date reports surface the unused ones. The field cap is not the right constraint to optimize against; the right constraint is honest field usage, which is why Strkr makes the usage visible rather than the cap tight.
Do formula fields work across lookup relationships?
Yes. Strkr formula fields support lookup chain traversal up to 5 hops, which covers every real-world case the RevOps teams we have talked to have raised. The syntax is a dotted path (parent.account.industry, deal.contact.account.owner.region). Named intermediate values keep complex formulas readable so the admin who wrote the formula is not the only person who can edit it 18 months later. Circular dependencies surface at save time with a clear message pointing to the chain, which prevents the historical Salesforce behavior where a bad formula first manifests as nulls on random records.
How do rollup fields work without a master-detail relationship?
Strkr rollups operate across lookup relationships, which is the common CRM shape (a Contact belongs to an Account, a Deal belongs to an Account, a Line Item belongs to a Deal). The rollup engine computes count, sum, min, max, average, or concatenated string across the related set with optional filters (sum of closed-won deals only, count of primary contacts only). Updates happen in real time for the common cases. Nested rollups are supported (the account roll-up of its deals that roll up their line-item quantities, for example). This is the single most frequent capability request from Salesforce migrations because Salesforce rollups require the master-detail constraint, which forces a schema design upstream.
What is the migration path from Salesforce custom fields?
Strkr has a Salesforce migration tool that reads the custom-field metadata via the Salesforce Metadata API, maps field types to the Strkr field type set, carries picklist values with their active and deactivated status, migrates formula field expressions (with a translation layer for Salesforce-specific functions), and preserves the full data history including deactivated-value legacy records. Field-level security maps from Salesforce profiles to Strkr Layouts role scopes with a one-time mapping decision per profile. Most mid-market migrations complete in 8 to 14 weeks for firms up to 400 reps, with a 2-week parallel-running period before cutover.
Can I retire a field without losing the historical data?
Yes. Field retirement runs through a two-step flow. Step one deactivates the field (removes from layouts, hides from the API serializer, blocks writes) while retaining the data. Step two purges after a configurable retention period (default 90 days, extensible to the tenant retention policy max). The audit log captures both steps with the admin, the timestamp, and the record count affected. For regulated tenants on retention policies, the field retention clock integrates with the overall tenant retention policy so the compliance posture stays consistent. Retired-field data can be restored during the retention window if the admin realizes something is still referencing it.
How does the field admin surface compare to Salesforce Setup?
Salesforce Setup is the industry benchmark for depth and the industry warning for admin burden. Strkr's field admin surface targets the depth with a tighter admin surface: one page per object with the field list, type, usage analytics, and permissions inline. Formula and rollup editors open as drawers rather than full-page redirects so the admin stays in context. Picklist value management, dependent-picklist chain configuration, and field-level security sit on the same screen as the field definition. The admin learns the system in days rather than the weeks a new Salesforce admin typically needs to find their way around Setup. The depth is comparable; the time-to-productive is specifically different.
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