Cross-channel attribution

Cross-channel attribution is building an attribution system that distributes the value of conversions among the touches of different channels (search, display, social, email, direct visits): choosing and setting up a model (last-click, linear, position-based, data-driven), linking ad account/analytics/CRM data, tagging (UTM — see 461), reports on channel contribution and assisted conversions. The work: auditing data and channels, choosing a model for the business, setup, honest interpretation. Honestly about 'precise attribution does not exist', this is key: no model shows the 'true' contribution of each channel — it is fundamentally an estimate with assumptions. Last-click overvalues the last channel and undervalues the top of the funnel; data-driven and multi-touch are more useful but also models, not truth. Whoever promises 'precise ROI per channel' is being disingenuous. Honestly about 'privacy breaks tracking', this is critical: cookie restrictions, ITP/blockers, cross-browser/cross-device transitions, offline — part of the user's path is not tracked; there are always 'blind spots' in the data and discrepancies between systems. We honestly show the limits of the data rather than painting a nice complete picture. Honestly about 'a model is a decision tool, not a verdict': attribution helps reallocate the budget more meaningfully than last-click, but decisions also require common sense/experiments (incrementality, holdout tests), not blind faith in the model. Honestly about 'discrepancies are normal': different systems (ad accounts vs analytics vs CRM) count differently; full agreement of figures is unattainable — we explain why. Honestly about 'does not create sales': attribution measures and helps decide but does not bring revenue itself. Honestly about the effect: it sets up multichannel attribution with a suitable model and honest interpretation of data limits, improving understanding of channel contribution, but this is an estimate with assumptions, not absolute truth/precise ROI; privacy limits the data; it helps decisions, does not replace common sense/experiments. Honestly about access: access to ad systems/analytics/CRM, tagging, sometimes server-side data are needed. An important boundary: this is attribution/measurement; UTM tagging — 461; event tracking — 460; per-channel analytics setup — 469. The base price starts from 30,000 ₽ for model/report setup.

• The real contribution of channels is unclear; budget decisions based on last-click are distorted.
• A misconception that 'precise' attribution / precise ROI per channel exists.
• Privacy/cookie restrictions create blind spots; blind faith in one model.
• Discrepancies between ad accounts, analytics and CRM are interpreted as an 'error'.

• Auditing channels, data and current tagging (UTM/tracking)
• Choosing an attribution model for the business (last-click/linear/position-based/data-driven)
• Linking ad account/analytics/CRM data, setting up reports on contribution/assisted conversions
• Honest interpretation: data limits, blind spots, system discrepancies
• An honest assessment: which model to choose and where its limit is
• Honest boundaries (precise attribution does not exist — an estimate with assumptions; privacy limits the data; a model ≠ truth; discrepancies are normal; does not create sales)
• Documentation and handover
• Review with you

• Set up multichannel attribution with a suitable model and reports
• A more honest understanding of channel contribution (better than last-click)
• An honest assessment: what attribution shows and what remains a blind spot
• Honest boundaries (not absolute truth/precise ROI; privacy limits it; experiments are needed)

• We audit channels/data/tagging, choose a model for the business
• We link data, set up reports, honestly interpret the limits
• We honestly set boundaries (no precise attribution; a model is a decision tool) and hand over

• Will you show precise ROI per channel?

  Precise — no, honestly: perfectly precise attribution does not exist, any model is an approximation with assumptions. Last-click overvalues the last channel; data-driven is more useful but also a model, not truth. Plus privacy/cookie restrictions create blind spots. Whoever promises 'precise ROI per channel' is being disingenuous. We will give a more honest estimate of contribution than last-click and honestly show the limits.

• Will attribution replace my decision-making?

  No, honestly: attribution helps reallocate the budget more meaningfully, but decisions also require common sense and experiments (incrementality, holdout tests), not blind faith in one model. A model is a tool, not a verdict. We will honestly say where the model is reliable and where it needs to be checked by experiment.

• Why don't the figures in the ad account, analytics and CRM match?

  This is normal, honestly: different systems count differently (attribution windows, deduplication, cookie/privacy, offline). Full agreement of figures is unattainable — this is not an 'error' but the nature of the data. We will honestly explain the discrepancies and reconcile the data as far as is correct, without the illusion of perfect precision.