Built for marketing attribution and revenue analytics teams

The CRM that keeps the full touch history on the deal, not just the opportunity source dropdown.

Attribution work needs clean inputs: every touch, every campaign, every spend decision, tied to the deal that eventually closes. Strkr ships a CRM core where touch history is a first-class object, campaign spend ties to deals, and pipeline velocity by source lands in the standard report library.

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What this audience is actually dealing with

The pains that bring buyers here.

Attribution teams at mid-market B2B companies spend 40 to 60 percent of their time stitching together data from the CRM, the marketing automation tool, the ad platforms, and the finance system to answer basic questions like what did this closed-won deal cost to generate. The CRM is usually the biggest culprit because it treats attribution as a dropdown field on the opportunity. Strkr onboarding hears the pain points below on every intake call with a RevOps or marketing analytics leader.

Opportunity source is a dropdown

The CRM collapses the full touch journey.

Most CRMs ship an opportunity source dropdown with 11 to 24 values. The field captures the last-touch or the self-reported source but never the full journey. For a deal that touched four webinars, two paid search clicks, one SDR cold call, and one trade show meeting before closing, the dropdown picks one value. Strkr ships touch as a first-class object with timestamp, channel, campaign, cost, and content attributed to each touch.

Campaign spend lives in the ad platform

The CRM does not know the cost per touch.

Campaign spend lives in Google Ads, LinkedIn Ads, Meta Ads, HubSpot campaigns, and the trade show budget spreadsheet. The CRM does not know the cost. The result is a pipeline-generated number without a cost denominator, which means marketing ROI is approximate. Strkr pulls campaign spend through the standard webhook spec from the ad platforms and the campaign object so the deal carries actual cost per touch.

First touch and last touch are the only models

The attribution team cannot run multi-touch models.

First-touch and last-touch are two of five relevant attribution models (first-touch, last-touch, linear, time-decay, position-based). The CRM typically supports first and last. Multi-touch models require source data at the touch level, which the CRM does not store. Strkr stores every touch so the attribution team can run any model (first, last, linear, time-decay, position-based, custom) from the Strkr data layer without a separate attribution tool.

Pipeline velocity by source is manual

Which source produces the fastest-closing deals.

Pipeline velocity by source (how fast does a deal from paid search close versus a deal from trade show versus a deal from referral) is a critical revenue allocation signal. Most CRMs do not calculate it, so the marketing analyst rebuilds it quarterly in Excel. Strkr ships pipeline velocity by source as a standard report that updates in near real time with filterable segment slicing.

Account journey across contacts

The buying committee touches get fragmented across contact records.

A B2B deal typically involves four to seven people from the buying committee touching marketing over the sales cycle. The CRM stores touches on the contact record. The attribution analyst manually aggregates to the account level. Strkr ships touch rollup at the account level by default so the attribution analyst can see the full account journey without contact-level stitching.

Finance system does not know marketing cost

The CAC calculation is a monthly spreadsheet.

Customer acquisition cost (CAC) requires marketing spend by segment, deal revenue by segment, and typically overhead allocation. Finance has deal revenue. Marketing has spend. The CAC calculation is a monthly spreadsheet exercise. Strkr pulls marketing spend from the campaign object and deal revenue from the pipeline so CAC per segment lands in the standard report library with real-time refresh.

The attribution schema

Objects shaped like multi-touch analytics work.

Strkr ships a tunable attribution schema with Touch, Campaign, Deal, Contact, Account, and Spend as first-class objects. The attribution analyst can rename or extend anything. The default lands close to where mid-market B2B marketing analytics teams typically settle.

Touch object

Timestamp, channel, campaign, content.

A touch in Strkr captures the atomic marketing interaction with timestamp, channel (paid search, paid social, organic, email, webinar, trade show, SDR outbound, referral, direct), campaign, specific content or asset, and attributed cost. The touch ties to the contact and rolls up to the account and the deal.

Campaign object

Spend, impressions, clicks, leads, pipeline.

A campaign object ties to the touches it generated with total spend, impressions where available, clicks, leads created, pipeline attributed, and deals closed won. The campaign drives the ROI calculation and the attribution model inputs.

Deal object with full journey

Touch count, model attribution, velocity.

The deal object carries the standard sales fields plus the full touch history, the first-touch source, the last-touch source, the linear-attributed source split, the time-decay attributed split, and the position-based attributed split. The deal shows pipeline velocity (days from first touch to close).

Contact with touch roll-up

Every marketing interaction captured.

The contact object aggregates touches from every channel into one timeline. The attribution analyst sees the full journey per contact. The account rollup aggregates across all contacts for the account journey view.

Account object with buying committee

Multi-contact journey aggregation.

The account object aggregates touches from every contact associated with the account into one account-level timeline. For a B2B deal with a buying committee of five contacts the account view shows the collective touch pattern instead of five separate contact timelines.

Spend object

Platform, period, segment allocation.

A spend entry ties to the campaign with amount, period, platform (Google Ads, LinkedIn Ads, Meta Ads, trade show, outbound SDR, content, webinar), and segment allocation. Spend aggregates up for the CAC calculation per segment.

How Strkr handles multi-touch models

Attribution models that run on live data.

Strkr ships five attribution models that run against the live touch history. The attribution analyst switches models without rebuilding the data layer. The cards below describe each model and when to use it.

First-touch attribution

Credit to the first marketing touch.

First-touch gives 100 percent of the deal credit to the first touch recorded. Useful for understanding which channels bring new prospects into the funnel. Overweights top-of-funnel channels (SEO, content, PR, trade show awareness) and underweights mid-funnel and closing channels.

Last-touch attribution

Credit to the last marketing touch before close.

Last-touch gives 100 percent of credit to the final touch before closed-won. Useful for closing-channel ROI. Overweights sales-adjacent channels (SDR, direct demo request) and underweights early awareness touches that made the deal possible.

Linear attribution

Equal credit across all touches.

Linear splits credit equally across every touch in the journey. For a deal with eight touches each touch gets 12.5 percent credit. Useful for channel comparison when all touches matter. Underweights the first touch that opened the account and the last touch that closed the deal.

Time-decay attribution

Weighted credit toward the close.

Time-decay weights touches closer to close more heavily. A touch three days before close might carry 25 percent credit while a touch 90 days before close carries 5 percent. The decay curve is tunable. Useful for understanding which late-stage channels push deals over the line.

Position-based attribution

U-shaped credit distribution.

Position-based gives 40 percent credit to the first touch, 40 percent to the last touch, and splits the remaining 20 percent equally across middle touches. The default distribution is tunable. Useful for balanced top-of-funnel and bottom-of-funnel channel assessment.

Custom model

Define your own weight distribution.

For teams with a attribution philosophy Strkr supports custom models with programmable weight distribution across touch position, channel type, campaign tag, or any field on the touch. The custom model definition lives in the admin console and runs against the same touch history as the five standard models.

The attribution operating cadence

The views an attribution analyst runs weekly.

Strkr ships views shaped around attribution analyst weekly cadence. The cards below are the views a RevOps analyst or marketing analytics manager opens first on Monday morning.

Pipeline source dashboard

Pipeline generated by channel this quarter.

The pipeline source dashboard surfaces open pipeline and closed-won revenue by channel across the configured attribution models. The analyst switches models to see how the picture changes between first-touch, last-touch, linear, time-decay, and position-based.

Campaign ROI

Spend versus pipeline generated per campaign.

The campaign ROI view ranks every campaign by spend, pipeline generated, deals closed won, and ROI ratio. The marketing director uses the view to shift budget toward high-ROI campaigns and investigate low-ROI campaigns.

Pipeline velocity by source

Days from first touch to close by channel.

The velocity view ranks channels by average days from first touch to close. Fast channels (referral, inbound demo request) land in the top. Slow channels (SEO, long-cycle outbound) land at the bottom. The view informs the sales cycle planning and the sales ops forecast model.

CAC by segment

Customer acquisition cost per segment.

The CAC view shows acquisition cost per segment (SMB, mid-market, enterprise, by vertical, by region) with marketing spend attributed and deal revenue closed. The CFO uses the view for budget planning. The marketing director uses it for channel reallocation decisions.

Account journey replay

Every touch for a closed deal.

For a closed-won deal the account journey replay surfaces every touch in chronological order with timestamps, channels, campaigns, costs, and content. The analyst uses the replay for post-deal pattern recognition and sales-marketing retrospective reviews.

Attribution model comparison

Side-by-side across all five models.

The model comparison view runs the same pipeline through all five attribution models side by side. The analyst sees where the models agree (durable finding) and where they disagree (channel dependent on model choice). The view surfaces insights that single-model analysis misses.

Head-to-head

Strkr vs a generic CRM plus dedicated attribution tool.

Most mid-market B2B companies run a generic CRM plus a dedicated attribution tool (Dreamdata, Bizible, Attribution, Factors, HockeyStack, Full Circle) to patch the attribution gap. The comparison below is Strkr versus that two-tool stack.

Feature Strkr Generic CRM plus dedicated attribution tool
Touch as first-class object Yes with timestamp, channel, cost. In the attribution tool only.
Five attribution models Built-in, live refresh. Attribution tool handles. CRM shows last-touch.
Campaign spend tie Live from ad platforms via webhook. Manual CSV import or paid connector.
Pipeline velocity by source Standard report with live refresh. Monthly manual export.
Account journey rollup Automatic across all contacts. Manual stitching across contacts.
CAC by segment Standard report. Spreadsheet exercise.
Custom attribution model Programmable weight distribution. Fixed to the dedicated tool models.
Monthly cost of stack $29 to $119 per seat on Strkr. CRM seats plus $1,200 to $14,000 per month for attribution tool.
Data model consolidation One source of truth. Two tools, syncing lag, reconciliation friction.
How teams use Strkr

Five attribution and revenue analytics playbooks.

The playbooks below are patterns Strkr onboarding sees across RevOps and marketing analytics deployments.

Pattern A

The 180-employee SaaS consolidating off Bizible.

A 180-employee SaaS company ran Salesforce plus Bizible plus Marketo for the attribution stack with $14,000 per month in combined tooling plus a RevOps analyst spending about 20 hours per week on attribution stitching. Strkr onboarding ran a 28-business-day migration consolidating to Strkr for the CRM and attribution layers while keeping Marketo for marketing automation. Monthly spend dropped by 68 percent and the RevOps analyst reclaimed about 14 hours per week.

Pattern B

The 240-employee cybersecurity vendor adopting multi-touch.

A 240-employee cybersecurity vendor ran HubSpot with last-touch attribution only. The marketing director wanted multi-touch models but HubSpot limited the capability. Strkr onboarding ran a 22-business-day migration consolidating to Strkr for both CRM and attribution. The marketing director got multi-touch models and the pipeline velocity by source report in the first month post-cutover. Budget reallocation driven by the new models lifted pipeline per spend dollar by 32 percent in Q2.

Pattern C

The 420-employee devtools company reporting ROI to board.

A 420-employee devtools company needed clean marketing ROI reporting for board updates. The existing stack (Salesforce plus Full Circle plus Marketo) produced numbers but the data lineage was opaque. Strkr onboarding ran a 32-business-day migration consolidating the stack. The marketing director brought the board a one-page ROI dashboard with data lineage visible from spend through touch through deal. The board questioning cycle dropped from 90 minutes per meeting to 20 minutes.

Pattern D

The 90-employee agency running client attribution.

A 90-employee B2B marketing agency ran attribution for 24 client accounts in a tangle of spreadsheets, dashboards, and screenshots. Strkr onboarding configured a multi-tenant deployment with per-client workspace isolation. Each client got their own touch and campaign data with their own attribution models. The agency reclaimed about 180 hours per quarter previously spent on attribution reporting.

Pattern E

The 85-employee services firm linking marketing to deals.

An 85-employee professional services firm had marketing campaigns and sales deals but the two never connected cleanly. The marketing director could not prove campaign ROI. Strkr onboarding ran a 18-business-day migration landing touch tracking, campaign spend tracking, and attribution models. The marketing director took the quarterly ROI report into the budget conversation and got a 42 percent budget increase for the next fiscal.

Run attribution on a CRM where touch is a first-class object.

Book a 30 minute call. We will walk through the touch schema, the five attribution models, and the pipeline velocity by source report with your actual channel mix and campaign structure.

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Common questions

What buyers in this bucket ask most.

Does Strkr integrate with Google Ads, LinkedIn Ads, Meta Ads, and HubSpot campaigns?

Strkr integrates with every major ad platform and marketing automation tool through its REST and GraphQL API, outbound webhooks with HMAC signing, and the published OpenAPI spec. For Google Ads, LinkedIn Ads, and Meta Ads the integration pulls campaign spend, impressions, clicks, and lead events in near real time. For HubSpot and Marketo the integration pulls campaign structure, email engagement, and lead events. The engineering sprint runs one to two weeks per platform. Teams typically start with the top three spend channels and expand from there.

How does Strkr handle offline touch like trade shows and SDR outbound?

Offline touches land through two patterns. For bulk offline touches (trade show badge scans, webinar attendance) the integration pulls through the webhook spec from the event platform or the SDR tool (Outreach, SalesLoft, Apollo). For individual offline touches (a sales rep marking a meeting, a trade show follow-up conversation) the Strkr contact timeline accepts manual touch entries with the same fields as automated touches. The attribution models treat offline touches equivalent to online touches with the campaign spend allocated appropriately (trade show booth cost allocated across trade show touches, SDR tooling cost allocated across outbound touches).

Can Strkr handle account-based attribution for enterprise sales?

Yes. The account object aggregates every touch from every contact associated with the account into one account-level journey timeline. For enterprise deals with buying committees of five to 11 people the account view shows the collective pattern instead of fragmented contact-level timelines. The attribution models can run at either contact level (classic MQL-to-opportunity attribution) or account level (buying committee attribution common in enterprise sales). The admin configures the default at the pipeline level.

What does Strkr cost compared to Dreamdata, Bizible, Full Circle, or HockeyStack?

Strkr runs flat per seat at $29 on Starter, $59 on Pro, and $119 on Scale per user per month, with a 14-day trial. For a 12-person RevOps and marketing analytics team on Pro the monthly spend runs $708 for seats plus $49 for AI Enhancement. Dreamdata typically prices $1,200 to $8,000 per month. Bizible (now Marketo Measure) runs $2,500 to $14,000 per month. Full Circle runs $1,800 to $9,000 per month. HockeyStack prices around $1,500 to $4,500 per month. Strkr sits well below the dedicated attribution tools because attribution is a native capability rather than a bolt-on product.

How does Strkr handle the data lineage audit for board or executive reporting?

Strkr audit log captures every touch creation (source system, timestamp, user or integration that created it), every attribution model run (model version, parameters, result), and every spend entry (source platform, user or integration, timestamp). The data lineage report traces from a closed-won deal back through every touch to the originating spend and campaign. The CFO and CRO see the lineage without needing to request a special audit pull. For companies in audit cycles (public company, pre-IPO, SOX-compliant) the lineage report serves as the attribution-related evidence package.

What is the compliance posture for a RevOps and attribution analytics team?

Strkr is HIPAA compliant with a BAA available on request, GDPR and CCPA compliant today, and SOC 2 Type II is in progress with a target of 2026-Q4. For GDPR specifically the touch data on EU residents respects data subject rights (access, deletion, portability) through the standard GDPR tools in the admin console. Integration tokens live in AWS KMS, platform credentials live in AWS Secrets Manager, and the audit log captures every record read and write with 90-day default retention tunable per tenant. SSO (SAML and OIDC) is live on Scale tier through Clerk for enterprise-grade identity.

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