Nine connected service families, delivered by experienced practitioners. Engagements are scoped to your data readiness, business question, and budget. Advanced methods require suitable data; these are professional services, not publicly available autonomous modules.
Fragmented systems and inconsistent customer identities prevent a dependable business view.
Deliverables
Documented pipelines, warehouse models, source inventory, identity rules, data contracts, QA checks, access responsibilities, and handover runbooks.
Explore capabilities & agency applications
Services and methods
ETL/ELT, BigQuery and warehouse modeling, API integration, data contracts, CDP strategy, identity resolution, consent-aware customer data integration, source reconciliation, and data governance.
Agency application
Connect a client’s media, digital, and CRM data for reporting while preserving provenance, consent requirements, and client-specific permissions.
CRM, ecommerce transactions, ad-platform exports, web and app events, product activity, consent records, and existing warehouse tables.
Methods, tools & limitations
Source mapping, pipeline design, SQL transformations, deterministic identity matching where permitted, schema validation, lineage documentation, and reconciliation.
Implementation methods may include dbt transformations, API connectors, data contracts, schema drift detection, identity resolution and consent-aware source integration. Governed datasets include source documentation and tested model definitions.
Manual spreadsheets, inconsistent metrics, and disconnected reporting make executive decisions harder than they need to be.
Deliverables
Stakeholder discovery findings, business requirements documents (BRDs), functional specifications and user stories, KPI definitions and acceptance criteria, source/data mapping, SQL transformations and semantic data models, dashboard wireframes, usable dashboards, metric reconciliation and UAT records, deployment documentation, training, and an agreed maintenance plan. Deliverables are selected to match the engagement scope.
Explore capabilities & agency applications
Services and methods
End-to-end BI implementations; dashboard-only development; requirements and solution-architecture engagements; existing dashboard reconstruction, migration, and modernization; and white-label BI delivery for agencies. Build executive, marketing, operational, and financial dashboards in Power BI, Tableau, Looker, and Looker Studio.
Agency application
Offer a complete white-label BI implementation or a defined dashboard build under your brand. Reconstruct a client’s existing reporting, migrate dashboards between tools, supply solution architecture for a pitch, or support executive reporting and ongoing maintenance.
Validated warehouse tables, campaign delivery, CRM pipeline, revenue records, digital metrics, and agreed KPI definitions.
Methods, tools & limitations
Metric modeling, source reconciliation, dashboard information design, stakeholder review, refresh validation, and performance diagnostics. Stakeholder interviews and discovery; business requirements gathering; BRDs, functional specifications and user stories; KPI acceptance criteria; source-system assessment and data mapping; SQL transformations and semantic models; wireframes and information architecture; data visualization, filtering, drilldowns, and usability review; row-level security and role-based access; metric reconciliation, UAT, and QA; deployment, documentation, training, and maintenance. Platform licenses, source access, security policies, refresh cadence, ownership, and maintenance responsibilities are agreed before implementation.
Engagements can include requirements-only or solution-architecture work, dashboard-only builds, end-to-end implementation, dashboard repair and reconstruction, migration and modernization, or white-label agency delivery. Functional specifications, user stories, KPI acceptance criteria, row-level security, training and maintenance are agreed explicitly.
BI delivery lifecycle · scoped to your engagement
Discover
Specify
Model
Design
Build
Validate
Deploy
Maintain
Illustrative dashboard — synthetic data
BI Studio
Explore a synthetic executive dashboard. Filter the period or segment and inspect the source evidence.
Working browser example
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Available now: local dashboard filtering and deterministic KPI calculations. Planned: authorized data connections and agent-generated, independently validated summaries. No client data is accepted here.
Unreliable digital tracking and unexplained funnel drop-off leave teams unable to connect website and app behavior to real business outcomes.
Deliverables
Measurement plan, event taxonomy and data-layer specification, configured or repaired analytics implementation, tagging audit and QA report, funnel/journey diagnostics, digital experience dashboard, prioritized CRO backlog, and governance/handover documentation.
Explore capabilities & agency applications
Services and methods
Google Analytics 4 (GA4) and Adobe Analytics implementations and audits; Google Tag Manager and server-side tracking; measurement frameworks, event taxonomy, and data layers; website and app performance analytics; ecommerce and lead-generation funnels; path and behavioral analysis, and customer journey analytics; attribution between digital touchpoints and CRM outcomes (web-to-CRM measurement); conversion rate optimization, experimentation, and personalization; consent-aware analytics, tagging QA and reconciliation; digital experience reporting and measurement governance.
Agency application
Implement digital measurement for a client launch; audit a GA4 or Adobe estate; reconcile paid traffic with qualified CRM leads; diagnose checkout or enquiry friction; and supply white-label digital experience reporting. Personalization is scoped to available data, consent, and implementation constraints.
Authorized GA4 or Adobe Analytics access, GTM containers and implementation documentation, website/app release context, consent settings, event or warehouse exports, ecommerce orders or CRM lead stages, and experiment data where available. Server-side work also requires agreed hosting and deployment access.
Methods, tools & limitations
Implementation audits, event and data-layer specifications, tagging QA, event-to-order/lead reconciliation, funnel and path analysis, journey mapping, attribution diagnostics, CRO research, and personalization hypotheses. Experiments and holdouts are scoped where suitable.
GA4 and Adobe Analytics, Google Tag Manager and server-side tagging are supported professional implementation options. Scope covers website and app analytics, behavioral segmentation, ecommerce and lead generation, consent-aware event QA, personalization analysis and web-to-CRM outcomes. Attribution requires compatible identifiers, lawful access and reconciliation.
Illustrative demonstration — synthetic data
Digital Journey Explorer
Follow a synthetic acquisition cohort from discovery through engagement to conversion. Change segments to inspect stage counts.
Working browser example
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Available now: a nested-session funnel with deterministic drop-off calculations. Abandonment means not reaching the next measured stage, not proof of a usability defect. Planned: authorized journey analysis and validated analytical agents.
Platform-specific reports and incomplete attribution leave agencies and brands without a coherent view of campaign performance or a defensible budget decision.
Deliverables
Cross-channel campaign dashboards, automated reporting workflows, measurement and data-quality assessment, reach/frequency diagnostics where supported, attribution or lift readouts, validated model documentation, response curves, forecast intervals, and media-allocation scenarios with assumptions.
Explore capabilities & agency applications
Services and methods
Cross-channel campaign measurement across Google Ads, Campaign Manager 360 (CM360), DV360, Meta Ads and other platforms; paid search, paid social, display, video, programmatic and CTV; campaign dashboards and automated media reporting; reach, frequency, CPA, CAC, ROAS, attributed revenue contribution, audience overlap and performance diagnostics; Marketing Mix Modeling (MMM); Multi-Touch Attribution (MTA), where appropriate; incrementality, lift studies, and geo experiments; media response curves, adstock, saturation, and marginal ROI; campaign and budget forecasting; media allocation and optimization scenarios; and online-to-offline measurement where data permits.
Agency application
Provide a media agency’s client performance pack, investigate channel discrepancies, evaluate paid-media effectiveness, or compare budget scenarios. Advanced models are commissioned only when data and identification assumptions support the question.
Dedicated marketing science capability
Marketing Mix Modeling (MMM)
Estimate channel contribution and explore allocation scenarios using aggregated time-series data. MMM is a scoped analytical service, not an automated guarantee of causal identification or improved ROI.
Inputs
Consistent historical spend and media delivery by channel and time period, sales or conversion outcomes, pricing, promotions, seasonality, distribution and relevant external demand drivers. Suitable history, spend variation, and data granularity are assessed before commissioning.
Methodology
Specify a defensible model and controls, model media carryover/adstock and saturation where justified, estimate channel contributions and response curves, and compare constrained budget scenarios. Use experiment evidence for calibration when available; document identification assumptions and uncertainty.
Diagnostics
Assess missing data, spend variation and collinearity, residual patterns, out-of-time forecast error, parameter plausibility, stability and sensitivity to specifications. Review uncertainty and consistency with lift tests; distinguish model fit from causal validity.
Deliverables
Data-readiness assessment, documented model and assumptions, diagnostic/validation report, channel-contribution estimates with uncertainty, media response curves, marginal ROI estimates, budget scenarios, and a stakeholder readout with explicit limitations.
For media agencies: support an evidence-backed client planning conversation. Findings depend on the data, model assumptions, and validation; savings or campaign gains are not guaranteed.
Historical media spend, impressions, reach/frequency and delivery exports; channel and campaign taxonomy; conversion and revenue history; CRM and offline outcomes; promotions, pricing, seasonality and other controls; and consented exposure or journey data where available. Reach deduplication, CTV, MTA, and offline linkage depend on platform access, identity coverage, privacy constraints, and data quality.
Methods, tools & limitations
Cross-platform reconciliation, campaign diagnostics, audience overlap analysis where feasible, attribution sensitivity checks, MMM, experimental lift/holdout design, forecast validation, and constrained budget scenarios. Platform-reported attribution is distinguished from causal impact.
Scope may include campaign pacing, audience overlap, reach and frequency, CPA, CAC, ROAS, online-to-offline measurement, geo experiments and investment forecasting across Google Ads, DV360, Campaign Manager 360, Meta Ads, paid search, paid social, programmatic, display, video and CTV. Coverage depends on platform permissions and compatible outcomes.
Illustrative demonstration — synthetic data
Media Intelligence Lab
Compare synthetic campaign records with explicitly separate illustrative response estimates and allocation scenarios.
Working browser example
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Available now: deterministic browser calculations using synthetic inputs. Planned: independently validated MMM, attribution, and scenario services through authorized APIs. The current example does not infer causation or recommend an optimal budget.
Consented CRM profiles, transaction history, product usage, surveys, Search Console, public market reports, and licensed competitive datasets where available.
Methods, tools & limitations
Segmentation, cohort comparisons, descriptive retention analysis, market sizing with explicit assumptions, survey analysis, and search/competitive visibility reviews.
Methods include customer profiling, RFM, cohort analysis, customer lifetime value, churn and retention analysis, propensity scoring, audience development, acquisition/retention comparisons and journey segmentation with CRM and behavioral integration. Identity coverage and observation windows limit interpretation.
Growth, retention, pricing, and resource decisions rely on uncertain demand and incomplete views of customer value.
Deliverables
Documented and validated models, scored cohorts where justified, forecast intervals, customer-value scenarios, prioritized recommendations, decision rules, limitations, and human review requirements.
Explore capabilities & agency applications
Services and methods
Data science, propensity modeling, churn forecasting, CLTV, retention modeling, revenue and demand forecasting, pricing intelligence, customer value optimization, next-best-action recommendations, opportunity prioritization, and decision support.
Agency application
Forecast a client’s demand, assess churn risk, compare customer-value segments, or prioritize opportunities with explicit assumptions and evidence rather than an unexplained score.
Observed changes and attributed conversions do not establish what a campaign or product change actually caused.
Deliverables
Test plan, success metrics, assignment and tracking requirements, analytical readout, uncertainty intervals, validity limitations, and recommendations for further measurement.
Explore capabilities & agency applications
Services and methods
A/B testing, experiment design and readouts, conversion experiments, holdouts, incrementality and lift measurement, geo experiments, and quasi-experimental analysis where appropriate.
Agency application
Design a media holdout, assess a CRO test, or help an agency explain the difference between platform attribution and incremental business impact.
Experiment assignments, pre/post outcomes, campaign and exposure data, geography, CRM or revenue outcomes, intervention timing, and sufficient comparable history.
Methods, tools & limitations
Power and feasibility assessment, randomized design where possible, causal identification reviews, balance and contamination checks, uncertainty estimation, sensitivity analysis, and validity diagnostics.
Where sample size and identification permit, methods include sample-size and power planning, treatment-effect heterogeneity, uplift modeling, experimental QA and statistical interpretation. Randomization, contamination, interference and multiple comparisons affect causal certainty.
Recurring reporting and manual monitoring consume analytical capacity and delay investigation.
Deliverables
Automated reporting jobs, monitoring and alert definitions, scoped activation workflows, operating runbooks, analytics ownership plans, and documented review/escalation responsibilities.
Explore capabilities & agency applications
Services and methods
Reporting automation, anomaly detection, predictive alerts, AI-assisted workflows, automated activation workflows, data monitoring, analytics operations, and reusable analytical templates.
Agency application
Reduce repeated manual reporting steps, flag unusual performance for review, or route an approved analytical recommendation into a client workflow. These are scoped professional services today; Commonsent Autonomous and its coordinated agent platform remain in development.
Validated warehouse metrics, dashboard and job logs, source-quality signals, business performance feeds, consent preferences, approved workflow rules, and access constraints.
Methods, tools & limitations
Workflow mapping, reporting/job orchestration, alert calibration, anomaly and drift monitoring, QA rules, scoped AI-assisted analysis, and human approval gates.
Professional scope can include automated data QA, briefings, reporting, anomaly detection, analytics monitoring, reproducible execution, orchestration and human-in-the-loop workflows. Agentic systems engineering is scoped individually; the full Commonsent Autonomous platform is In Development.
Revenue Leak Audit, fixed fee, delivered in 5 business days
We audit your tracking, funnel, follow-up, and site head-to-toe (the same first pass behind every engagement) and hand you a ranked list of where money is leaking and what fixing it takes. The fee is fully credited if you continue to a Foundation engagement.
Fixed scope & price, no retainerDelivered in 5 business daysCredited toward Foundation
Senior-led work, with automation where it helps and hands-on where it doesn't. Recurring engagements are fixed-scope and fractional, but if you'd rather commission a single project, that option is below too. Start anywhere; move up as you grow.
Best first step
Trust your numbers
Foundation · one-time setup
Scoped on the callone-time
A fixed-fee audit and setup: we clean up your tracking and stand up one trustworthy source of truth. No subscription, start here, add ongoing support only if you want it.
Under the hoodGA4 + server-side tracking repair · single canonical data warehouse · executive dashboard · handover walkthrough
Know which marketing actually works, test changes with confidence, and have your data monitored automatically so problems surface before they cost you.
Under the hoodEverything in Foundation · multi-touch attribution · experiment design & readout · automated monitoring & alerts
One-time setup (waived if you start with Foundation)
Not every problem needs a monthly engagement. Sometimes you need a specific question answered, a dataset cleaned up, a dashboard built, or a one-time analysis done right. Bring in a senior analyst on a scoped, fixed-fee project basis, human-led, delivered, done. No subscription, no lock-in.
A specific analysis or reportA one-time tracking or data cleanupA dashboard buildA second opinion on your numbers
Fixed fee, scoped up front
Quoted per project after a short conversation. 50% to start, balance on delivery.
The $1,500 professional Revenue Leak Audit is a scoped expert engagement. The free self-service leak audit is an automated starting point, not the same deliverable.
Specialist professional services · Available Today
Social Listening & Narrative Intelligence
Make public conversation useful for reputation, communications and commercial decisions.
Capabilities and methods
Brand and topic monitoring, sentiment and theme analysis, competitive share of voice, narrative trends, review monitoring and coordination-pattern analysis with human review.
Inputs and deliverables
Authorized social-listening exports and public captures; source mappings, coverage assessment, evidence-backed reports, themes and response considerations. Consent, platform terms and sample bias constrain interpretation.
Agency application
White-label reputation briefs and campaign integrity reviews for PR and communications clients. Compatible Meltwater, Brandwatch and Talkwalker exports require field validation; import support is separate from live API access.
Policy and regulatory monitoring is a future specialization. Signal remains a working pilot with validation in progress.