Teams running sales and service against the same accounts need one record of truth, not two. Strkr ships native case management with SLA tracking, queue routing, severity escalation, knowledge base integration, and Strkr AI triage so the service team and the sales team see the same account history.
Case management lives in a separate tool for most mid-market teams: Zendesk, Freshdesk, Intercom, HubSpot Service Hub, or ServiceNow. The sales CRM lives somewhere else. The split means an AE opens a sales call blind to the three open support tickets, and the support agent closes a ticket blind to the open renewal opportunity. The patterns below are the gaps.
The AE opens the sales call and does not see the three open critical support tickets that landed in the past two weeks. The conversation goes wrong immediately. Strkr surfaces open cases, SLA countdowns, and severity flags on the account record every AE opens, so no sales call starts blind to the service context.
A support agent resolves a critical case without knowing the renewal opportunity is at risk. The agent does not route to the CSM for a check-in. The renewal lapses. Strkr surfaces open deals, upcoming renewal dates, and account health on the case record so the agent closing the ticket sees the sales context in-view.
SLA tracking across different tools uses different clock-starts, business-hours definitions, and escalation rules. Strkr ships SLA tracking with configurable business hours, hold-state exclusions, severity-based response and resolution targets, and automatic escalation to the next tier when the SLA threshold trips.
Support agents search a help-center tool, a product documentation site, an internal wiki, and the CRM to answer a single question. The response time balloons. Strkr integrates the knowledge base natively (ships as part of Strkr Docs) and the agent sees suggested KB articles on each case driven by the ticket content, which cuts the search tax.
Simple round-robin assigns cases to whichever agent is free, ignoring skills and account familiarity. A tier-1 agent gets a tier-3 case, response time slips, resolution quality drops. Strkr ships skills-based routing, account-owner routing (the agent who worked the last ticket on this account gets priority), and workload-balance routing.
Service metrics (ticket volume, severity mix, time-to-resolution, CSAT) live in the service tool and do not feed the sales CRM, so the CSM finds out about a critical account in a renewal conversation. Strkr surfaces service metrics on the account record and feeds the account health score so the CSM sees the risk signal weeks in advance.
The Strkr case object is a first-class record type with its own schema, lifecycle, SLA, and audit log. Cases link to contacts, accounts, deals, and products natively. The cards below are the primitives on every paid tier.
Cases follow a configurable lifecycle: new, assigned, in-progress, waiting on customer, waiting on internal, resolved, closed. Each state carries SLA clock behavior (business hours running vs paused). State transitions log in audit with user attribution. The lifecycle is admin-configurable to match the team's support process.
Cases carry severity (critical, high, medium, low) and priority (urgent, high, normal, low). Severity drives SLA; priority drives queue order within severity. Admins configure the SLA matrix per severity (critical: 15-minute response, 4-hour resolution; low: 4-hour response, 72-hour resolution). The matrix feeds the queue router.
SLA clock runs during configured business hours and pauses on hold states (waiting on customer, waiting on vendor). The admin configures business hours per team, time zone, and holiday schedule. The SLA breach alert fires at configurable thresholds (50 percent of SLA elapsed, 75 percent elapsed, breached) with routing to the manager and the on-call tier.
Case routing supports skills-based routing (match case tags to agent skills), account-owner routing (the agent who worked the last ticket on this account gets priority), workload-balance routing (even distribution across agents), and round-robin fallback. Multiple rules compose with priority order.
Strkr suggests relevant KB articles on each case based on the case content. The agent clicks to insert the article link into the response or opens the article to read before replying. The KB lives in Strkr Docs or in an integrated help center (Zendesk Guide, Freshdesk Freshknowledge, Intercom Articles, Help Scout Docs).
On case arrival, Strkr AI drafts the suggested severity, category, and first-response template based on the case content and the account history. The agent reviews in 10 seconds and sends. The triage saves roughly 2 to 4 minutes per case on first-touch, which compounds across hundreds of daily cases on high-volume teams.
Cases are created from inbound email (to a configured support address), chat conversations (Intercom, Drift, HubSpot Chat sync), inbound phone calls (voicemail transcribed and triaged), web form submissions, Slack messages (shared channel integration), and API calls. The channel is tracked on the case for routing and reporting.
Macros insert canned responses with variable substitution (account name, agent name, deal reference). Macros are workspace-shared or personal. The agent inserts a macro, edits the substituted fields, and sends. The pattern replaces copy-paste from a shared doc.
Cases link to the related deal (if this is a pre-sales support ticket), the product (which product the case covers), and the feature (which feature of the product is affected). The links drive reporting (which product has the highest case volume, which features generate the most support load) and the renewal-risk signal.
The single-account-view is the central thesis of case management in a CRM. The sales and service teams work the same accounts; separate tools fracture the view. The cards below are the surfaces where sales and service share context in Strkr.
The account record shows open cases, SLA countdowns, severity flags, assigned agents, and days since last update. The AE opens the account before a sales call and sees the service context immediately rather than discovering it from the prospect three minutes into the call.
The case record shows open deals (opportunities), upcoming renewal date, account health score, and account tier. The agent closing a critical case sees the renewal is in 45 days and routes a check-in to the CSM. The pattern prevents the resolved-ticket-but-lost-renewal failure.
The account health score consumes service signal: case volume trend, severity mix, time-to-resolution, CSAT scores, open critical count. The CSM sees the health score degrading before the renewal conversation and intervenes with a success check-in. The pattern turns support data into retention leverage.
The account timeline includes case events alongside calls, emails, meetings, and deal stage changes. The exec reviewing an account sees the full history (sales touches plus service events) in one chronological view. The pattern replaces the mental merge the exec would otherwise do across two tools.
The account dashboard surfaces service metrics (open case count, average resolution time, CSAT trailing 90 days) alongside sales metrics (open deal count, pipeline value, closed revenue). The combined view is the surface the CSM uses for QBR prep and the exec uses for strategic-account review.
Case comments are visible to the sales team by default with configurable scoping: internal-only comments (not visible to sales), sales-visible comments (visible to the AE and CSM), customer-visible messages (visible to the customer). The admin configures the default per team. The pattern lets sales stay informed without exposing every internal comment.
Service operations has its own set of workflows: queue dashboards, agent-workload views, SLA breach reporting, CSAT survey distribution, escalation chains. The cards below are the service-ops features that make Strkr viable as the full service platform rather than a case-side companion to a dedicated tool.
The queue dashboard shows live queue state: cases waiting on assignment, cases waiting on customer response, cases at risk of SLA breach. The dashboard refreshes in real time via subscription. The manager uses the dashboard as the primary daily work surface rather than a weekly report.
The agent workload view shows each agent's open case count, severity mix, average time-to-resolution, and skill tags. The manager rebalances the queue by dragging cases between agents or by applying bulk routing rules. The view is also the primary surface for 1-on-1s and performance review.
The SLA breach report fires daily with cases that breached the SLA, cases that came within 25 percent of breaching, and the root causes (assignment delay, agent workload, missing context). The pattern drives the weekly service-ops meeting with specific data rather than a general sense of velocity.
On case resolution, Strkr sends a CSAT survey via email (or inside the ticket thread for ticket-centric tools). The survey captures a 1 to 5 rating plus optional comment. Responses feed the account health score, the agent-performance dashboard, and the quarterly service review. Low scores trigger follow-up from the manager within 24 hours.
Escalation rules route cases to the next tier when SLA thresholds trip, when severity escalates, or when specific keywords (legal, lawsuit, chargeback) appear in case content. The chain respects on-call schedules, agent availability, and the escalation history on the account.
Agents collaborate internally through side conversations (dedicated internal threads on a case) and internal comments (visible to agents, invisible to the customer). Slack integration pushes high-severity cases to a shared service channel for team awareness. The collaboration surfaces replace the sidebar Slack DMs and the shared-mailbox pattern.
The common mid-market stack is Zendesk for service plus HubSpot for sales, synced loosely through an integration. Here is the head-to-head on dimensions that matter when one team is covering both motions.
| Feature | Strkr | Zendesk + HubSpot |
|---|---|---|
| Shared account view | One record of truth with cases, deals, calls, emails, meetings | Separate records, synced via integration with drift |
| SLA tracking | Business hours, hold states, severity-driven, escalation chains | Zendesk SLAs; HubSpot ticket pipelines |
| Queue routing | Skills, account-owner, workload-balance, round-robin | Zendesk triggers and routing; HubSpot workflows |
| AI triage | Severity, category, response draft via Strkr AI | Zendesk Advanced AI add-on; HubSpot Breeze credits |
| KB integration | Native via Strkr Docs; external KB connectors | Zendesk Guide; HubSpot KB; separate records |
| Account health scoring | Service and sales signal combined in one score | Separate scoring in each tool, manual merge |
| CSAT survey distribution | Native post-resolution with health score feed | Zendesk native; feeds back to HubSpot via sync |
| Multi-channel case creation | Email, chat, phone, form, Slack, API | Zendesk covers most channels; HubSpot ticket channels |
| Reporting across sales and service | One pipeline including deals and cases, cross-filtered | Separate dashboards, manual cross-reference |
| Pricing basis | Flat per-seat with cases and deals included | Zendesk per-agent plus HubSpot per-seat |
The patterns below are motions that are live on customer accounts right now. The common thread: teams that unified sales and service on one record saw measurable lift on renewal rate and service response quality.
A 42-rep B2B SaaS team with 12 CSMs runs sales and CS on Strkr. The CSM sees open support cases on each account at QBR prep and the AE sees the service context before every renewal conversation. Pre-Strkr the renewal rate ran 82 percent; after 10 months on the unified stack it climbed to 94 percent. The CFO attributed the lift to the early-warning signal from the account health score fed by service metrics.
A 24-agent service team at a mid-market SaaS struggled with first-response SLA (critical cases, 15-minute response window). Pre-Strkr compliance ran 71 percent because the Zendesk queue was first-in-first-out across skills. The move to Strkr with skills-based routing plus Strkr AI triage draft lifted compliance to 96 percent. The service director reports that the AI-drafted first response is often sufficient and the agent spends their time on resolution rather than drafting.
An 18-advisor wealth firm uses case management for client-service requests (statement questions, allocation changes, beneficiary updates). Compliance requires every case to be tagged for regulatory review (reportable, non-reportable, requires signature). Strkr AI triage drafts the tag; the advisor reviews in 10 seconds. Pre-Strkr the manual tagging hit 60 percent coverage. Current coverage is 100 percent, which satisfied the firm's compliance posture.
A 60-rep ERP implementation partner runs ongoing project-support tickets that need to tie to the originating implementation deal. Strkr case-to-deal linking surfaces the deal context on every ticket (project phase, in-flight commitments, scope decisions). The support team saves roughly 15 minutes per ticket on context-gathering, which added up to roughly 60 hours per week across the team.
A 12-advisor real-estate team treats buyer inquiries (property questions, financing questions, scheduling questions) as service cases alongside listing-side deals. The AE sees active inquiries on the buyer profile and the inquiries route to the right agent via skills matching (listing agent, buyer agent, financing specialist). Average CSAT on inquiry handling climbed from 4.1 to 4.7 over two quarters.
Start a 14-day trial with case management, SLA tracking, queue routing, Strkr AI triage, KB integration, and CSAT surveys included on every paid tier.
For mid-market service teams (10 to 100 agents) running standard case patterns (email, chat, phone intake with SLA tracking, skills-based routing, KB integration, CSAT survey, escalation chains, internal collaboration), Strkr replaces Zendesk cleanly. For enterprise-scale service operations (200-plus agents, specialized workforce management, deep IVR trees, bespoke integration with field-service platforms, enterprise WFM like NICE or Verint, high-volume contact-center-as-a-service patterns), Zendesk or ServiceNow still carry more specialty depth. The decision point is roughly scale and complexity: mid-market standard patterns go on Strkr, enterprise-scale specialty operations usually need a dedicated platform. We publish a decision guide for teams working through the trade-offs.
Business hours are configurable per team, time zone, and day of week. Holiday schedules are configured per region (US federal, country-specific, custom holidays). Hold states (waiting on customer, waiting on vendor, waiting on internal) pause the SLA clock automatically. The admin configures per-state behavior (which states pause the clock, which do not). SLA breach alerts fire at configurable thresholds (50 percent elapsed, 75 percent elapsed, breached) with routing to the manager and the next escalation tier. The combined posture handles the common mid-market service patterns and the stricter enterprise expectations around SLA fidelity.
On case arrival, Strkr AI reads the case content, matches against the knowledge base, and reviews the account history to draft three outputs: suggested severity (critical, high, medium, low), suggested category (billing, technical, account change, feature request), and a first-response template. The agent reviews in 10 seconds, edits as needed, sends. The AI runs on the three-tier model router so simple cases route to a light tier model and complex multi-signal cases route to the complex tier. The per-case unit cost is low enough that the triage is included on every paid tier with no credit meter below the plan cap. The pattern saves roughly 2 to 4 minutes per case on first-touch, which compounds materially on high-volume teams.
Cases and deals link natively on the account record. When an AE opens an account, open cases appear with SLA countdowns and severity flags alongside open deals. When an agent opens a case, open deals appear with pipeline stage and renewal date. The account health score consumes service signal (case volume trend, severity mix, time-to-resolution, CSAT) so the CSM sees the renewal-risk signal weeks before the renewal conversation. For teams running pre-sales support, cases link directly to the originating deal so the pre-sales support work ties to the opportunity. The combined posture closes the sales-service gap that otherwise shows up as lost renewals and surprise churn.
For teams that keep a specialty service tool alongside Strkr, native integrations exist with Zendesk, Freshdesk, Intercom, HubSpot Service Hub, Help Scout, and Front. The integration bi-directional-syncs cases, comments, and status so the Strkr account view shows the external case activity without the agent switching tools. For teams migrating fully to Strkr, we ship migration utilities for Zendesk, Freshdesk, and HubSpot Service Hub that import historical cases with activity history and attachments. The migration typically runs in a weekend with the admin reviewing the imported data on Monday morning.
Strkr is HIPAA compliant with a Business Associate Agreement available for teams handling protected health information in case content. Case content is encrypted at rest and in transit. Role-based access controls which agents can see which cases. The audit log captures every case access and content change. SOC 2 Type II controls are in progress through 2026-Q4. For GDPR and CCPA requirements, data-subject-access and deletion workflows cover case content with configurable retention. For regulated-industry patterns (financial services suitability, healthcare privacy, legal privilege), the admin configures case-content scoping and retention per record type. We publish the full compliance documentation on request for procurement review.
Strkr ships an open REST API and webhook subscription system covering every case object (create, read, update, delete, comments, attachments, status transitions, SLA events). Teams running specialized tools alongside Strkr (field-service dispatching platforms, legacy ticketing databases, custom product-telemetry pipelines, external compliance-review systems) build integrations against the API with standard REST or webhook patterns. The documentation is public and the API respects the same permission model as the UI. For teams building more sophisticated integrations, the GraphQL endpoint provides schema introspection and finer query granularity. Rate limits are generous enough for mid-market use cases; enterprise contracts carry higher ceilings. The open-API posture is deliberate because case-management requirements vary too much across industries for a vendor to anticipate every integration need, so we invest in making the API extensible rather than trying to ship every integration natively. We also publish the webhook schema so teams can build custom routing or custom reporting against case events without waiting on roadmap-level feature requests.
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