CDP and End-to-End Analytics
Collect customer data from the web, applications, CRM and payments into a single 360° profiles* we're counting LTV*, CAC* ROAS*, build attribution* scoring* and then activate the audience through channels (Reverse ETLNo black boxes, just transparent calculations and dashboards.
Request audit and implementationWhy Businesses Need CDP and End-to-End Analytics
Fragmented data breaks marketing and product work. We build a loop: event collection (web/app/server), identification* and user stitching, storage and data marts, metric and attribution calculation, and segment activation in ads, email, and messengers. As a result, budget moves to efficient channels and communications become personal and measurable.
Business effects
- +10-30% of revenue from personalization and precision segmentation.
- 15-35% of CAC due to net attribution and shutdown of “junk” sources.
- +12-25% to retention due to the correct triggers and scorings.
Tools and architecture
Implementing a mature stack: data collection, routing and cleaning; identification and profiles; storage and data marts; computation and models; dashboards and audience activation.
Data collection and routing
- Tracking Plan*: Events, properties, identifiers, schemes.
- SDK for web/mobile + Server-to-Server* for critical events (registration, payment).
- Anti-AdBlock: First-level domains, retros, deduplication.
- Import CSV/JSON/APIs: CRM, billing, offline sales, coltrekting.
360° identification and profiles
- ID-Resolution*: user_id, device_id, email/phone hashes, identity graph.
- Stitching*: Deterministic/probabilistic, windows and weight schemes.
- Profiles*: Demography, events, transactions, channels, speed, RFM/CLV
- Consent* and the status of data processing by the user.
End-to-end analytics and attribution
- Attribution*: first/last touch, position-based, multi-touch*.
- Imports of expenditure*: Cabinets/CSV, exchange rates, VAT/commissions.
- ROI/ROAS metrics, CAC*, LTV*, margins by segment.
- Attribution windows: click/post-view, de-duplication of conversions.
DWH, data marts and dashboards
Activation: Audiences and Reverse ETL
- SegmentationRFM, behavior, probability of purchase/outflow.
- Reverse ETL*: uploading audiences in ads/e-mail/CRM/push.
- Triggers: abandonment, price-drop, back-in-stock, first value.
- Control of frequency and cannibalization of channels.
Typical stack
Implementation process
Data audit and objectives
Inventory of sources (web/app/CRM/payments), clarification of KPI: LTV, CAC, margin, repurchases, ROI/ROAS.
Tracking Plan and collection
Uniform Event and Property Scheme, S2S for Critical Steps, Deduplication/Retrai, Consent Banner and Processing Statuses.
Identification and profiles
Rules for crosslinking identifiers (det/prob), graph identities, unification of attributes, control of collisions.
End-to-end analytics and attribution
Import of expenses, normalization of UTM, attribution windows, data marts on orders / leads, reports on channels / creatives / segments.
Audiences and activation
Segments RFM/behavior/scoring, Reverse ETL into channels, triggers and frequency rules, A/B circuits.
Dashboards and procedures
Role-oriented panels (CEO/marketing/product/CRM), dictionary metrics, SLA updates, alerts.
What do you get?
Artifacts
- Tracking Plan* and the CDP data model.
- ID-Resolution/Stitching rules and profile scheme.
- Attribution methodology with formulas and windows.
- Dictionary of metrics and update procedures.
Infrastructure
- Deployed DWH, event/order/attribution/audience data marts.
- Dashboards (marketing/product/CRM/finance) and allerts.
- Reverse ETL connectors: ads, e-mail, CRM, push.
Activation and growth
- Segments (RFM, propensities, churn) and trigger scenarios.
- Experiments on channels/offers, control of incrementality.
- Team training and joint weekly insights.
Examples of KPI
- E-commerce: CR, AOV, repeat orders, margin, returns.
- SaaS: Activation D7, Retention D30, ARPU/ARPPU, churn.
- LeadGen: CPL/CPA, lead-transaction conversion, LTV by source.
Cases
E-commerce: Profiles and Audiences
User_id/email/phone crosslinking, RFM + back-in-stock/price-drop segments. Reverse ETL in ads + e-mail gave +18% to retention revenue and -22% to remarketing CPA.
SaaS: End-to-end and attribution
Expense import, 7/28 day windows, position-based model, creative reports. Budget reallocation: -19% CAC, +11 pp D7 activation.
Offline + online: leads and sales
Collecting and CRM integration, user-level attribution, remarketing holdout, confirmed incrementality +9.5% to orders.
Checklists and quality control
Data Quality
- Event coverage ≥ 95%, discrepancy of web ⁇ CRM orders ≤ 2%.
- Scheme Validation: mandatory fields, types, ranges.
- Attitudes for the fall in conversions / events, SRM / traffic distortion.
Identification
- Hierarchy of identifiers: det → prob, windows and timeouts.
- Anti-merger: Coincidence thresholds, manual moderation of conflicts.
- Audit the shares of anonymous / crosslinked profiles through channels.
Attribution and expenditure
- Normalization of UTM, deduplication of clicks / postviews.
- Import costs with exchange rates and commissions.
- ROI/ROAS versus P&L and unit economy
Privacy and compliance
- Consent*: banners, consent logs, granular opt-in.
- Masking/hashing of identifiers, role-based access.
- Storage time, log of configuration changes.
| Signal. | Threshold | Action. |
|---|---|---|
| The difference between web vs CRM | > 3% by orders | S2S/hour windows check, deduplication, retrai |
| Fall of events | > 15% from median | Alert, SDK/tag versions, rollback |
| Attribution bias | > 20% vs historical profile | Windows/UTM/Post Viewing, Reassin |
| Percentage of anonymous | > 60% in key segments | Login strategy, triggers and identity bonuses |
FAQ
How long does the basic implementation last?
Usually 5-10 business days: Tracking Plan → collection / S2S → DWH / data marts → attribution / expenses → dashboards → Reverse ETL and the first segments.
Do you need a separate team of analysts?
No. We leave clear rules, activation scenarios, and we train marketing/product, and we train maintenance if we want.
Can I count offline sales and calls?
Integration of CRM/telephony, adding offline events to profile and attribution, P&L check.
What about privacy and the law?
We implement the consent banner, opt-in/opt-out logs, minimization, masking of identifiers, roles and storage periods.
Decoding of terms
- Tracking Plan: a formalized scheme of events/properties and rules of sending.
- Server-to-Server: sending key events from the backend.
- ID-Resolution: crosslinking different identifiers of one user.
- StitchingTechnical rules for the unification of identities.
- 360° profileA user card with events, attributes and transactions.
- AttributionDistribution of channel contribution to conversion/revenue.
- Multi-touch: Multi-channel Attribution Model.
- Imports of expenditure: downloading costs from normalization offices/files.
- DWHData Warehouse (Data Warehouse)
- ETL/ELT: the conveyor of extraction / transformation / downloading data.
- Segmentation: Breaking the audience down by traits and behavior.
- Reverse ETLUploading storefronts and audiences back to external channels.
- scoringProbabilistic assessments of behavior (buying, outflow, etc.).
- Retention: retaining users over time.
- LTV: lifetime value of the customer.
- CAC: Cost of attracting a customer.
- ROAS: refund on advertising costs.
- Consent: User consent to data processing and cookies.
Ready to put data together and start earning more?
We will configure collection and identification, build profiles and attribution, assemble dashboards, and launch activations. In a couple of weeks you will have transparent numbers and manageable campaigns.
Request an audit and work plan