The three things most marketing automation vendors keep inside their walls (the journey definition, the event stream behind the journey, and the attribution rule that credits the pipeline) all live in your Strkr tenant as portable, exportable records. Export the journey as JSON. Query the event stream through the open API. Pick the attribution rule yourself and change it when the model should change.
Mid-market marketing automation platforms generally hold three artifacts on the vendor side of the fence. The journey definition is a proprietary graph that the tenant cannot export in any usable shape. The event stream behind the journey is readable through the vendor UI but opaque at the row level. The attribution rule that credits the campaign that produced the pipeline is a reporting construct the tenant cannot inspect, override, or carry out. Each of those three decisions makes the next renewal easier for the vendor to win. Strkr turns all three into portable, versioned, auditable artifacts that live in the tenant.
A Strkr journey is a record. It has a schema, a version history, an exporter that writes a JSON file, and an importer that re-creates it in another workspace. The journey carries into a staging environment, out of the platform for backup, and across tenants for consolidation. The record is portable in the shape your team can read.
Every event the journey emits (send, open, click, reply, score change, stage transition) writes a row with the actor, the step, and the timestamp. The event stream is readable through the API, exportable to the data warehouse, and queryable from the audit log. There is no vendor-side black box between the step and the row.
Attribution is a configurable rule on the workspace. First-touch, last-touch, linear, time-decay, position-based, and tenant-defined custom models all compile to the same campaign-attribution table. The rule is auditable. Changing it logs the change and recomputes the historical view against the new rule for comparison.
Strkr publishes the egress plan with the contract. Contacts, accounts, journeys, events, campaigns, attribution rules, and audit log all export in documented formats. The tenant does not need legal to negotiate egress at renewal; the plan is already on file.
The REST API exposes every record used by the journey (contact, account, campaign, event, attribution row). The data warehouse team syncs the records directly, bypassing any vendor-managed connector that could rate-limit or reshape the stream.
The audit log on a Strkr tenant captures every write across marketing and sales. GDPR requests, SOC 2 Type II evidence collection, and internal investigations read one log. The vendor is not between the compliance officer and the answer.
Marketing automation renewals usually turn on three things: the invoice size for the next year, the migration cost if the team wanted to leave, and the strategic lock-in of the journeys the demand team has built over three years. Vendor ownership of the journey graph, event stream, and attribution rule makes the migration cost formidable and keeps the renewal invoice in the vendor seat. Tenant ownership flips the posture. Here are the seven negotiating moves ownership unlocks.
The team can export every journey to JSON and import it into a staging workspace, a backup bucket, or a successor platform. The leverage at the renewal table is real: the vendor knows the migration is a day, not a year.
If the event stream is already syncing to the warehouse, the attribution model is already reproducible outside the vendor. The reporting layer survives a platform change. The vendor has one less dependency to charge for.
When the tenant owns the attribution rule, swapping first-touch for multi-touch is a workspace setting, not a vendor project. The CFO conversation goes faster because the math is portable.
The egress plan ships with the contract. At renewal, the counterparty cannot slow-walk the response to a data export request. The timeline is on paper and the format is on paper.
Pricing on seats, not on marketable contact count, removes the renewal pressure the vendor usually gets from database growth. The year three invoice looks like year one plus seat growth, not year one plus 60 percent list inflation.
Direct API access means the data engineering team sets its own sync cadence, its own retry policy, and its own backfill. The vendor cannot throttle the data layer as part of a renewal tactic.
When every write is in one tenant-owned audit log, the vendor cannot slow the GDPR response or the SOC 2 evidence request as part of the renewal conversation. The log is already yours.
The attribution rule is only as honest as the underlying data model and the audit posture on top of it. Here are the nine moving parts on a Strkr tenant that make the attribution reports reconcile with the finance view of pipeline and closed-won. The point is not to pick a model that flatters the demand team; the point is to pick a model that holds up when the CRO asks where the revenue came from.
Form submission, journey enrollment, event scan, meeting attended, content download all write a campaign-member row with the campaign, the contact, the source, and the timestamp. The member rows are the primary key for the attribution math.
Opportunities link to contacts through the opportunity-contact-role table. The attribution rule walks the campaign-member rows for every contact on the opportunity to compute the credit. The link is a database relation, not a vendor model.
The attribution rule is a configurable record on the workspace. First-touch credits the first campaign on the earliest member row. Last-touch credits the latest. Multi-touch distributes credit by model. Time-decay weights recent touches heavier. All four compile to the same campaign-attribution table.
A custom attribution model is a workspace record with a credit function (SQL, a visual rule, or a webhook). The team ships a model that credits named stages, campaign tiers, or audience segments differently. The rule is auditable and versioned.
A per-rep attribution report shows which campaigns the quota came from on which deals in which quarter. The AE comp conversation and the demand team planning conversation read the same report.
Each campaign row carries spend, campaign-member count, pipeline attributed, closed-won attributed, and ROI. The marketing operations lead reads a ranked list of campaigns at the end of the quarter without exporting to a BI tool.
Changing the attribution model logs the change (actor, timestamp, previous value) and allows a comparison view that shows the historical pipeline under both rules. The CFO reads the delta before signing off.
The member table and the attribution table are both exportable through the API or the warehouse sync. Finance can rebuild the pipeline view in its own system any night. The attribution math is portable.
Snowflake, BigQuery, Databricks, and Redshift all sync from the Strkr event stream directly. The attribution report in the BI tool reconciles with the attribution report in Strkr because they are reading the same rows.
Data ownership is often framed as a philosophical point. In practice it is measurable in dollars, cycle time, and renewal leverage. The six outcomes below are what the finance team should see twelve to eighteen months after shifting marketing automation to a tenant-owned posture.
The renewal invoice is predictable because the pricing model does not reprice on marketable contact count. Finance plans the year with real numbers, not vendor-tier guesses.
Open API access and signed webhooks shorten the lag from event to warehouse to BI tool. Reporting runs on today's data instead of yesterday's.
Export a journey from the staging workspace, import into production, keep the version. No vendor services team needed. The release workflow mirrors the engineering team's.
The attribution report in Strkr matches the attribution report in the warehouse because the math is tenant-owned and the rows are shared. Weekly reconciliation gets short.
A GDPR data subject access request runs against one audit log. The DPO responds inside the regulatory window without pulling from four systems.
When the journey graph, event stream, and attribution rule all belong to the tenant, the next renewal is a product conversation rather than a migration-cost conversation. Strkr competes on usefulness, not on friction to leave.
Owning the journey graph, event stream, and attribution rule is less abstract when read as a list of moves the ops team actually makes. The nine moves below are the ones teams exercise in the first year of running Strkr. Each one depends on the ownership posture being real rather than performative.
The ops lead picks a journey, clicks Export, and downloads a JSON file that fully describes the trigger, the steps, the decisions, the sends, the delays, and the goal checks. The file imports cleanly into a staging workspace or a backup bucket.
A scheduled flow exports every journey, segment, and scoring rule to S3 (or equivalent) each night. The configuration layer is backed up alongside the data. Recovery from a bad edit is a restore, not a redesign.
The data team enables the Snowflake sync. Events start writing to the warehouse within minutes. The analytics team builds the reports they want on top of the stream rather than waiting for a vendor dashboard.
The CRO decides the attribution model should change from last-touch to multi-touch time-decay. The ops lead edits the workspace setting; the change is logged; the historical view shows the pipeline under both rules side by side for the CFO.
A lost-deal retrospective requires the AE and the demand team to see every touch, every score shift, and every ownership change. The audit log answers in one query. The retrospective takes an hour, not a day.
At renewal, the ops team shows the vendor the backup plan, the warehouse sync, and the journey exports. The vendor knows the migration cost is a day of ops work. The renewal becomes a product conversation.
A 20-minute tour of the journey export, the event stream, the attribution rule, and the egress plan. The artifacts stay on your side of the fence.
A Strkr journey is a record on the tenant with an exporter that writes a JSON file and an importer that re-creates it elsewhere. The journey is portable between workspaces, backable up to object storage, and readable through the open API. The vendor does not hold a proprietary copy you cannot carry out.
Yes. Every send, open, click, reply, score shift, and stage change writes a row that is readable through the REST API, exportable through the warehouse sync, and queryable from the audit log. The event stream is first-class data on the tenant.
The tenant. First-touch, last-touch, linear, time-decay, position-based, and custom models all compile to the same campaign-attribution table. The marketing ops lead switches the model without a vendor engagement, and the change is logged in the audit log.
Contacts, accounts, journeys, events, campaigns, campaign-member rows, attribution rules, attribution output, and the audit log all export in documented formats. The plan ships with the contract so the data team does not negotiate at renewal from a cold start.
Strkr is HIPAA compliant with a BAA available on request, GDPR and CCPA compliant, and SOC 2 Type II is in progress through the fourth quarter of 2026. The single tenant audit log makes compliance evidence collection a single query instead of a cross-system reconciliation.
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.
