CAC per channel

CAC per channel is a one-off analytical project (can be made regular): we link marketing spend by channel with the number of acquired customers from analytics/CRM and compute CAC by channels, campaigns and periods; where data allows we compare CAC with LTV to assess payback, not just cheapness. Honestly about attribution, this is key: to assign a customer to a channel an attribution model is needed — and that is an estimate with assumptions (last-click undervalues the top of the funnel, a long cycle and multi-channel make it harder), different models give different CAC; we fix the methodology with you, there is no 'single correct' figure. Honestly about data: correct spend and correctly attributed customers are needed — with incomplete or duplicated data CAC will lie (garbage in, garbage out). Honestly about the essence: this is calculation and consolidation, NOT lowering CAC and NOT running/optimizing ads — we show where acquisition is expensive, while the work to make it cheaper (bids, creatives, landing pages, channels) is done by you or your specialist; the calculation itself does not lower CAC. Honestly about context: a cheap CAC is not always the best — it matters to compare with customer value (LTV); a channel with expensive CAC may bring more valuable customers. Requirements: access to spend and customer data (analytics/CRM). An important boundary: this is CAC calculation, not full end-to-end analytics (separate), not LTV modeling (separate) and not running ads. If there is one channel and few customers, a per-channel calculation is premature. Picture this: instead of 'we spend on all channels but don't know the cost per customer' you see CAC for each channel and where money is wasted. The base price starts from 12,000 ₽ per calculation; it depends on the number of channels and data state.

• You do not know what a customer from each channel costs.
• You compare channels by clicks/leads, not by cost per customer.
• You make budget decisions without per-channel CAC.
• Expensive channels eat the budget unnoticed.

• Collecting channel spend and customer data (analytics/CRM)
• Agreeing on the attribution methodology and period
• Computing CAC by channels, campaigns, periods
• Comparing CAC with LTV where data allows
• Flagging expensive/inefficient channels
• A report with observational conclusions
• Flagging data gaps
• Reviewing results with you

• You understand CAC for each channel and campaign
• You see where acquisition is expensive and wasted
• CAC linked to customer value (where LTV exists)
• A base for budget decisions (lowering CAC — separately)

• We clarify channels, data sources, methodology; collect access
• We link spend and customers, compute CAC by breakdowns
• We compile a report, review conclusions with you

• Will you lower my CAC?

  Not directly. We compute and show where acquisition is expensive, while making it cheaper (bids, creatives, landing pages, channel choice) is ad work done by you or your specialist. The calculation is a base for decisions, not the lowering itself.

• Why might CAC differ from my estimates?

  CAC depends on the attribution model (how to assign a customer to a channel) and on data quality. Different models give different figures — it is an estimate, not an absolute. We fix the methodology and compute on correct data.

• Is the cheapest channel always the best?

  Not necessarily. It matters to compare CAC with customer value (LTV): a channel with expensive CAC may bring more valuable customers. So where data allows we look at CAC together with LTV, not in a vacuum.