Paid campaign planning and strategy development require a testing budget for large budgets. You’re buying statistics to determine your ROI, so a low ROI, potentially even 0%, can be acceptable during a test phase as it provides valuable data, but this should be specified as a potential rather than an expectation.
Several paid marketing tools claim to help you plan your campaign, and some indeed work. However, don’t rely solely on these tools or platforms to set your test budget. As a marketer who has managed over $6 million in paid marketing campaigns, I assure you that you do not want to rely solely on a tool when determining your test campaigns.
So, how do you determine a test budget?
1. Identify your population: Your total addressable market (your ideal buyer persona). For instance, targeting large enterprises in the US for a corporate marketing consultant role would exclude small to medium businesses, students, and other countries. Platforms like LinkedIn Ads, Google AdWords, and Facebook Ads can help identify your market quickly. Continuing with the example, the decision-makers from large US enterprises could be 12,000. Remember this number for sample size calculation.
2. Confidence Level: This is the specified probability within a margin of error. It’s how confident you want to be about the accuracy of your test results.
3. Margin of Error: The confidence interval represents the range in which the true value is expected to fall. I usually keep this around 5%.
Here’s the breakdown:
- My population is 12,000.
- I want a 95% confidence level for the test.
- I aim for a 5% margin of error, targeting at least 95% confidence in the results.
The sample size needed is 372, meaning I need at least 372 engagements from my population of 12,000 in my campaign. If using AdWords or LinkedIn, this means 372 clicks.
Ready for the fun part?
Suppose it costs $372 to engage with your 372-sample size (ideally). If 5% of these targets become customers, that’s 18.6 customers from a 372-sample size. Thus, you spend $372 for every 18.6 customers, equating to a campaign cost of $20 per customer. You can now calculate your profit per sale.
Here’s my approach:
- Calculate a customer’s LTV (Lifetime Value) minus the Campaign Cost Per Customer Acquisition to find the Net Value.
- For services, consider the average customer retention rate rather than just the immediate profit from the initial transaction.
- For one-off products, the calculation is simpler.
Remember, all these calculations are at a micro level, meaning they will help you calculate your return on investment at the campaign level. Marketing, sales, and finance often have different interpretations when it comes to evaluating ROI. For instance, if you are running a B2B campaign and your long-term goal is upselling, then even a loss in the test budget may indicate an even higher return on investment if your upselling strategy is strong. Therefore, the way I approach determining the test budget in this article may not suit all campaigns, especially those that involve upselling.
How to Calculate Test Budget for Campaigns that Involve Nurturing, Upselling and Cross-selling?
Let’s simplify this first. Assuming that your campaign plan, on a higher level, follows this sequence:
Promote > Sell > Nurture > Cross-sell and Upsell.
Calculating your budget can be straightforward if you have any existing data for nurturing to upsell/cross-sell ratio. You simply run the same logic, but this time, you calculate these ratios to get profit estimates.
Here’s the breakdown:
Initial Sale:
- Population: 12,000
- Confidence Level: 95%
- Margin of Error: 5%
Cross-sells and Upsells (using historical data):
- X percent of initial buyers upsold
- Y percent of initial buyers cross-sold
- Total = X + Y percent
- Initial Sale Calculation:
- If you have a 5% conversion rate from the initial campaign, that’s 18.6 customers from 372 engagements.
- Nurturing to Upsell/Cross-sell Calculation:
- Assume 20% of the 18.6 initial customers are upsold (3.72 customers).
- Assume 15% of the 18.6 initial customers are cross-sold (2.79 customers).
- Total additional sales from upselling and cross-selling: 6.51 customers.
Budget Calculation:
- Initial Campaign Cost: $372
- Cost per Customer (initial sale): $20
- Total Customers from Initial Campaign: 18.6
- Additional Customers from Upselling/Cross-selling: 6.51
Profit Calculation:
- Total Customers: 18.6 (initial) + 6.51 (upsell/cross-sell) = 25.11 customers
- Total Cost: $372
- Cost per Customer (including upsell/cross-sell): $372 / 25.11 = ~$14.81
Using these calculations, you can determine the viability of your campaign by comparing the cost per customer to the customer’s lifetime value and the profit margin of your product or service.
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