If I had $1,000 more to invest, what would give me the best return?

You freed up $1,000 in budget. Google Ads? Meta? Content? Referral incentives? Here's how to model the return on each option using your own historical data.

7 min read

The short answer

Where should you invest $1,000?Look at your current CAC per channel, multiply $1,000 by each channel's conversion rate, and estimate the revenue those new customers would generate. The channel where $1,000 produces the most incremental revenue is your answer. But you need historical data from ad platforms, CRM, and accounting to make this projection reliable.


Why $1,000 produces wildly different results depending on where you put it

Based on your current data, here is what $1,000 might produce on different channels: Google Ads at $300 CAC gives you about 3 new customers generating roughly $9,000 in revenue. Meta Ads at $900 CAC gives you 1 customer generating maybe $2,800. A referral bonus program at $250 per referral could produce 4 customers generating $20,000+.

The same $1,000. Three completely different outcomes. The difference is not just the cost per customer. It is the value of the customer each channel produces. Referral customers might spend 2-3x more than paid acquisition customers. That changes the math entirely.

Without cross-referencing your ad spend (from platforms), customer source (from CRM), and actual revenue (from accounting), you cannot make this comparison. You are left guessing, or worse, letting the platform with the best sales pitch win your budget.


Incremental return modeling: predicting what $1,000 will produce

To model the return on an incremental investment, you need three inputs per channel:

  • Current marginal CAC. How much does the next customer cost on this channel? This is not the same as the average CAC if you are already experiencing diminishing returns.
  • Average revenue per customer by channel. Customers from different channels generate different revenue. Referral customers might average $5,000. Meta Ads customers might average $2,800. This matters more than CAC alone.
  • Expected incremental customers. Divide $1,000 by the marginal CAC. If marginal CAC is $300, you get roughly 3.3 customers. Round down to be conservative.

Multiply expected customers by average revenue per customer. That is your projected return on the $1,000 investment.


How to model an incremental $1,000 investment across channels (6 steps)

This assumes you have already calculated your channel CAC and revenue per customer. If not, you will need to do that first (see our guides on channel CAC and channel ROI). With that data in hand, this takes about 30-45 minutes.

  1. 1
    Gather your channel-level data

    For each channel, you need: current monthly spend (from ad platforms), current customer count (from CRM, verified in accounting), and total revenue from those customers (from QuickBooks Sales by Customer Summary or Xero paid invoices).

  2. 2
    Calculate current CAC and revenue per customer

    CAC = channel spend / channel customers. Revenue per customer = channel revenue / channel customers. Record both for each channel.

  3. 3
    Estimate marginal CAC

    If you have 3 months of data and spend has been increasing, look at the most recent month's CAC. If it is higher than the average, use the most recent month as your marginal CAC. If spend has been flat, use the average.

  4. 4
    Project customers from $1,000

    For each channel: $1,000 / marginal CAC = projected new customers. Round down. Be conservative for channels where you have limited data.

  5. 5
    Project revenue from those customers

    Projected customers x average revenue per customer from that channel = projected revenue. This is your expected return on the $1,000.

  6. 6
    Rank and decide

    Sort channels by projected revenue per $1,000 invested. The winner gets the budget. If the top two are close, split the $1,000 between them.

Total time: 30-45 minutes if you have your channel data ready. 60-90 minutes if you need to pull it from scratch across ad platforms, CRM, and accounting.


Why most $1,000 decisions are made on gut feel

The analysis above is sound. But most business owners do not have 45 minutes to spare when the question comes up. The budget discussion happens in a meeting, or during a call with an ad rep, or at the end of a long day. You do not have the data in front of you. So you go with what feels right.

And “what feels right” is usually influenced by recency (the last channel you saw results from), sunk cost (you have already invested in this channel), or sales pressure (the Google rep is on the phone right now). None of these are good decision criteria.


Or see what $1,000 would produce on each channel, automatically

Bottomline maintains your channel efficiency data in real time. When you are ready to allocate budget, the answer is already calculated: projected customers and revenue per additional $1,000 on each channel.

What $1,000 more would produce (projected)
Referral incentives~4$19,60019.6x
Google Ads~3$9,3009.3x
Content/SEO~5$8,5008.5x
LinkedIn Ads~2$6,2006.2x
Meta Ads~1$2,8002.8x
From a real Bottomline report. Projections based on your historical channel data, verified against accounting.

The answer is clear: $1,000 in referral incentives projects $19,600 in revenue. Google Ads projects $9,300. Meta Ads projects $2,800. Instead of a 45-minute spreadsheet exercise, you have the answer in one card. And because Bottomline updates this every month, the projections get more accurate as it accumulates more data about your business.

Get your answer. Every month, automatically.

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