A contact in Strkr is not a spreadsheet row. It is the person, the company they work for, every message you have ever exchanged, every deal in flight, and the next step your team agreed to take. Flat per-seat pricing, AI drafting on paid tiers through the Enhancement module.
Contact management sounds simple until the team scales past one person. Then the duplicate records show up, the "we called them twice this week" moments start, and the question of which column is authoritative turns into a weekly standup topic. The five pain points below are what we hear on contact-management intake calls, whether the team is coming off a shared Google Sheet or a 240-field Salesforce instance.
Sarah logs the contact from a trade show. Jamal logs the same contact from LinkedIn. The marketing automation creates a third from a form fill. Three records, one person, zero merge logic. Strkr deduplicates on email, phone, and name plus company with a confidence score, surfaces the matches to a reviewer, and merges with full history preservation on approval.
Every quarter someone adds a field for a one-off campaign and never cleans it up. The contact card becomes a wall of empty values. Strkr's field-use report shows which fields have real data in the last 90 days versus which are dead weight. The admin can archive without data loss, which keeps the card clean without a scary migration.
A rep swaps 11 emails with a prospect, logs none of them, and leaves the account. The next rep opens the record cold. Strkr's Gmail and Microsoft 365 tie-ins log sent and received email on the matching contact automatically, with Strkr AI drafting a one-line summary for each thread so the next person can skim the history in two minutes.
Enterprise deals close through five to seven buying-committee members. A contact record that stands alone cannot represent the committee. Strkr's contact-to-contact and contact-to-account links model the relationship graph (reports-to, blocks, champions, influences) so the committee shape is visible on the opportunity.
When a rep leaves or a territory changes the new owner inherits a book of business with no context on who matters, who is a dead lead, and who is three weeks from a conversation. Strkr AI drafts a one-paragraph summary per contact at handoff, grounded in the recent interaction history, so the new rep walks in with context instead of guessing.
A contact card in Strkr is designed to answer the three questions a rep opens a record to answer: who is this person, what have we done together, and what should I do next. The cards below are the pieces of that answer.
The top of the card shows name, title, company, buyer-intent score, and consent status for SMS and email. The score pulls from Strkr AI's inbox-signal analysis and recent interaction cadence. The rep can see the lead temperature in two seconds without scrolling.
The main pane shows every touch (email, SMS, call note, meeting, task completion, record edit) in chronological order with sender, timestamp, and a one-line summary. The rep can filter by channel or expand any item to see the full content.
The right rail shows the linked company (with its own open-deal count and health score), active deals on this contact, open projects, and open tasks. One click into any linked record takes the rep to the right context without a second search.
For teams running enterprise motions the relationship graph section shows other contacts on the same account with role tags (champion, decision-maker, blocker, user, procurement). The graph is manually curated or AI-suggested from email thread participation.
A chip at the top of the card suggests the next action (send pricing, book a demo, update close date, schedule a renewal call) based on the deal stage, the time since last touch, and the Strkr AI analysis of the recent thread. The rep accepts or dismisses with one click.
The audit tab records every read, every write, and every AI prompt against the record with user, timestamp, and payload summary. The admin can review the audit trail at any time without pulling a database dump. 90-day default retention tunable per tenant.
Contact-management teams fail at migration more often than they fail at daily use. Strkr's import pipeline is built around the places other teams lose data: dropped email history, broken parent-child links, inconsistent country formats, and timezone drift on activity timestamps.
Upload a CSV of up to 500,000 rows. Strkr detects columns automatically and lets the admin confirm or override the mapping. Validation rules run before commit: required fields, email format, phone format, country normalization. Rejected rows export back to CSV with the error per row so the admin can clean and re-import.
Through the Gmail or Microsoft 365 tie-in Strkr can pull the past 24 months of sent and received email, match to the right contact record, and populate the chronological thread with original timestamps preserved. The AI retrieval index sees the full history on day one.
Most imports break the parent-child link between contact and company (contacts land as orphans, companies land as duplicates). Strkr's import pipeline matches companies first, confirms the match, and then attaches contacts with the preserved relationship. The post-import report shows exactly how many links held versus how many need manual review.
After import Strkr runs a deduplication pass on email, phone, and name plus company. Matches surface in a review queue with a confidence score. The admin can bulk-approve high-confidence matches (above 90 percent) and review the lower-confidence set manually. Merges preserve the full history from both source records.
All activity timestamps store in UTC and display in the viewer's timezone. For teams migrating from a tool that stored local-time strings Strkr's import tool offers a timezone attribution step so the historical cadence does not drift.
For 72 hours after import the admin can roll back the full operation with one click. The rollback restores the tenant to its pre-import state, preserves any new activity logged after import in a separate review tab, and lets the admin re-run the import with corrected mapping.
Contact management is not a static list. The team needs segments that reflect lifecycle stage, consent status, engagement recency, and ownership. The cards below are the segment patterns Strkr ships ready to use.
Strkr's lifecycle picklist runs lead, marketing qualified, sales qualified, opportunity, customer, renewal, churn risk, and lost. The admin can rename or add stages. The lifecycle drives segment eligibility for campaigns and the automation branches in the flow builder.
Every contact carries consent state for SMS and email independently. Segment builders can filter on consent (SMS-eligible AND email-eligible AND engaged in last 90 days) with the consent state resolved at send time, not at list build time. That means a contact who opts out between build and send is suppressed.
Strkr tracks engagement recency per channel. A contact who opened an email yesterday and clicked a link is hot. A contact who had an SMS reply 60 days ago but nothing since is cooling. The engagement bucket is a filterable segment and a visible chip on the card.
Ownership runs at the contact and account level with a transfer workflow for territory changes. The transfer preserves history, writes an audit event, and triggers the handoff summary draft. Territory-based bulk assignment is a one-pass operation, not a weekend data project.
The segment builder supports any attribute on the contact, company, deal, or custom-object graph with AND / OR logic and nested conditions. Segments can be saved, shared across the team, or scheduled to recompute daily. The saved segment is a live query, not a frozen list.
The team describes a segment in plain English ("contacts who talked to us in the last 60 days, work at a company with more than 50 employees, and have an open deal") and Strkr AI drafts the segment criteria. The team reviews and tunes before saving. Faster than clicking through the builder for complex segments.
Many teams start with a shared Google Sheet or an Excel file on a shared drive and bounce to a CRM when the duplicate count hits double digits or when a rep leaves and the context evaporates. The comparison below is Strkr's contact-management posture versus the shared-sheet starting point.
| Feature | Strkr | Shared spreadsheet or legacy address book |
|---|---|---|
| Duplicate detection | Confidence-scored merge queue. | Manual find and fix every quarter. |
| Email history on the record | Automatic through Gmail or Microsoft 365. | Live in the inbox, invisible to the team. |
| Relationship graph | Contact-to-contact and contact-to-account links. | Zero. |
| Audit trail | Record-read and record-write with retention. | Google Sheets version history, if that. |
| Segment builder | Any attribute, saved queries, live refresh. | Filter formulas that break on next column add. |
| Consent state per channel | SMS and email tracked independently. | None. |
| AI drafting | Follow-up email in the firm voice. | None. |
| Role-based permissions | Field, record, and action scoped. | Edit access or view access, pick one. |
Teams move to real contact management at different triggers: a rep leaves, the duplicate count tips, a compliance team starts asking about consent, or the executive asks for a cross-team pipeline view. The four patterns below are the most common starting points.
An eight-person branding agency in Nashville ran a 1,200-row Google Sheet as their contact list for four years. The rep attribution column had three different formats. The migration ran in nine business days: CSV import, dedup pass, Gmail history pull for the past 18 months, and relationship graph tagging. The founder reclaimed about six hours per week that had gone to spreadsheet reconciliation.
A 42-rep team coming off a legacy CRM with 240 custom fields migrated to Strkr with the field-use report in hand. 180 fields had zero data in the last 180 days and got archived. The resulting contact card dropped from a six-screen scroll to a one-screen view. New-hire ramp dropped from six weeks to about three.
A regional nonprofit with 11,000 donor contacts needed consent tracking for email and SMS, pledge-level segmentation, and clean parent-child links between donors and household giving units. Strkr's custom-object graph modeled the household as a parent record with donors as children. The campaign team ran its first fully consent-compliant appeal in Q2 and saw opt-out rates drop from 2.4 percent to 0.9 percent.
A founder running a 120-contact executive outreach book for a Series B raise needed sharp relationship-graph tagging (who introduced me to whom, who is a champion, who is a decision-maker at the fund). Strkr's manual relationship-tagging and the AI thread summarization gave the founder a single view of the raise pipeline that replaced two spreadsheets and a Notion doc.
Book a 30 minute call. We will walk through the contact card, the dedup pipeline, and the AI drafting with your actual CSV or legacy export.
Yes. Strkr's architecture handles tenants into the multi-million record range without the admin console or pipeline board slowing down. Vector search uses HNSW indexing which stays fast past a million records. Teams with 500,000-plus contact tenants run on the same per-seat pricing as smaller teams: 29 to 119 dollars per user per month.
The import pipeline runs a deduplication pass on email, phone, and name plus company with confidence scoring. High-confidence matches (above 90 percent) can be bulk-approved. Lower-confidence matches surface in a review queue. The admin merges with full history preservation. Post-import deduplication runs continuously on new records so duplicates do not accumulate between imports.
Yes. Strkr's Gmail and Microsoft 365 tie-ins log sent and received email on matching contact records automatically with original timestamps preserved. The sync is bidirectional for sent email composed in Strkr. The admin can tune which labels or folders sync and which stay in the inbox. Message content stores encrypted at rest.
Consent is tracked per channel on every contact with source, timestamp, and consent text archived. STOP, UNSUBSCRIBE, QUIT, CANCEL, END, OPTOUT, STOPALL, ARRET, and REVOCAR are enforced at the data layer for SMS through Strkr Messaging. Email unsubscribe honors the preference instantly across every list and campaign. The audit log captures every consent change.
Flat per-seat pricing: Starter at 29 dollars per user per month, Pro at 59 dollars, Scale at 119 dollars. The 14-day free trial includes every feature. SMS runs 2 cents per segment and MMS 5 cents, metered separately. The AI Enhancement module is a 49-dollar-per-month flat add-on with 5,000 Strkr AI calls included. There is no contact-count surcharge, no record-count tier, and no field-count fee.
Role-based permissions scope to the field level in the Layouts work (planned). Today permissions scope to the record level, the action level (read, write, delete), and the object level. Owners can be restricted from seeing specific fields through custom-object isolation. Field-level permissions ship as part of the Layouts workstream.
When a user is deactivated their book of business can be transferred to another owner in one pass. The transfer preserves history, writes an audit event per contact, and triggers an AI-drafted handoff summary per contact for the receiving owner. The deactivated user retains record visibility in the audit trail but cannot read or write. Hard delete is suspended on active users to preserve referential integrity.
No sales call, no migration consultant, no four-month implementation. Enter your card, get 14 days of the full Pro tier, cancel any time before day 14 with zero charge. Spin up a workspace, import your CSV, and have something useful before lunch.
