Paid Ads CAC Forecasting
This use case explains how to model paid advertising, customer acquisition cost (CAC) and new customers for eCommerce and direct to consumer brands in Model Reef.
You will:
Define ad spend by channel and campaign group.
Model traffic, click through and conversion rates.
Compute CAC, new customers and revenue from acquired customers.
Connect CAC and customer flows to unit economics and cashflow.
Model Reef is not an ad platform or attribution system. It consumes summary metrics from those systems and projects them forward within a financial model.
When to use this pattern
Use this pattern when:
Paid acquisition is a significant driver of growth.
You want to understand how ad spend, CAC and LTV interact.
You need to allocate budget across channels or campaigns.
You want advertising decisions reflected in P&L and cash forecasts.
It is commonly paired with:
SKU Margin and Contribution Modelling
Multi Channel Revenue Forecasting
Retention or cohort modelling in the Use Cases section for SaaS and subscriptions.
Architecture overview
Step 1: Define channels and campaigns
Decide how you want to group paid acquisition, for example:
Channels:
Google Search.
Google Shopping.
Meta (Facebook and Instagram).
TikTok.
Other paid social.
Campaign groups within channels:
Brand versus non brand.
Prospecting versus retargeting.
Upper, mid and lower funnel.
In the branch tree, you can create branches such as:
Channel - Paid Search.Channel - Paid Social.Channel - Other Paid.
Or keep branches at customer or revenue channel level and track ad spend by driver per channel.
Step 2: Create ad spend drivers
In the Data Library, create drivers for ad spend per channel or campaign, for example:
Ad Spend - Paid Search.Ad Spend - Paid Social.Ad Spend - Other Paid.
Enter or import planned spend per period. You can represent budgets as:
Fixed amounts per period.
A percentage of revenue with caps and floors.
A ramp up schedule as you open new markets or products.
Attach these drivers to Opex variables in the appropriate branches, typed as Opex, for example:
Opex - Paid Search Spend.Opex - Paid Social Spend.
This ensures ad spend flows into P&L and cashflow correctly.
Step 3: Define funnel efficiency drivers
For each channel or campaign, create drivers for funnel performance, for example:
Cost per Click (CPC).Click Through Rate (CTR)if modelling from impressions.Traffic Conversion Rate(visitors to orders).New Customer Share(what proportion of orders are from new customers).
You can either:
Derive these from historical data and assume future stability.
Or set them up as scenario driven drivers that change under different budget and strategy assumptions.
These drivers allow you to translate spend into traffic, orders and customers.
Step 4: Compute clicks, traffic, orders and new customers
Create variables that compute:
Clicks = Ad Spend ÷ CPC.Traffic = Clicks(or Traffic = Impressions × CTR if you model impressions explicitly).Orders = Traffic × Conversion Rate.New Customers = Orders × New Customer Share.
You may want to separate:
First orders from new customers.
Repeat orders from existing customers (handled in a separate retention model).
Store these as operational drivers and variables that can be reused in revenue and cohort models.
Step 5: Calculate CAC and link to revenue
Calculate CAC per channel as:
CAC per New Customer = Ad Spend ÷ New Customers.Or, if you prefer per order:
CAC per Order = Ad Spend ÷ Orders.
Use these outputs to:
Feed into a unit economics view that compares CAC to first order contribution and LTV.
Inform budget and bidding strategy.
Then connect customer or order flows to revenue, for example:
Revenue from Paid Search = Orders from Paid Search × Average Order Value.Average order value can be a driver per channel or shared across channels.
Ensure these revenue variables are typed as Revenue and flow into P&L and cash.
Step 6: Build CAC and paid media dashboards
Create dashboards that show:
Ad spend per channel over time.
New customers and orders per channel over time.
CAC per customer and per order.
Revenue and contribution generated per channel.
CAC payback period when combined with contribution and retention models.
You can add simple rules such as highlighting channels where CAC exceeds target thresholds or where contribution or LTV to CAC ratios are weak.
Step 7: Use scenarios for budget and efficiency changes
Clone your model into scenario models that reflect different paid media strategies, for example:
Increased spend across all channels with stable efficiency.
Higher spend with diminishing returns on conversion rates.
Reallocated spend from one channel to a more efficient one.
Tighter budgets with an efficiency focus.
For each scenario, adjust:
Ad spend drivers.
Funnel efficiency drivers.
Conversion and repeat behaviour if needed.
Compare scenarios using:
CAC and new customers.
Revenue from paid acquisition.
Contribution and LTV to CAC metrics.
Cashflow impact of advertising investments.
Check your work
Ad spend drivers tie back to realistic budget planning or historical spending patterns.
CPC, conversion and new customer share metrics reflect actual channel performance.
CAC values are in line with what marketing teams see in platform dashboards.
Revenue and contribution from paid acquisition look sensible relative to overall sales.
Troubleshooting
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