Drive CAC Payback with Predictive Analytics | Pecan AI

Drive Customer Acquisition Cost (CAC) Payback with Predictive Analytics

Customer acquisition cost (CAC) payback measures the relative cost to acquire a new customer and the time it takes to pay back that cost.

Customer acquisition cost (CAC) payback is a metric that measures the relationship between the cost to acquire a new customer and the annual revenue generated from that customer. 

This metric is closely related to customer lifetime value (LTV). In fact, both metrics consider the monetary value of a customer compared to the cost of acquiring this customer.

The relationship between these two metrics is usually referred to the LTV:CAC ratio. This ratio is used to help determine the budget needed to acquire new customers. 

Furthermore, LTV:CAC ratios can help you understand if you’re spending too much on customer acquisition initiatives or if you are missing out on opportunities present in the marketplace. 

In addition, a second useful calculation, the CAC payback period, also lets you know how long it will take for you to break even on acquiring each customer.

These are popular metrics for companies like SaaS companies and direct-to-consumer businesses to use.

How Are the LTV:CAC Ratio and CAC Payback Period Calculated?

The CAC payback period formula is usually as shown below:

customer acquisition cost payback

You can then multiply the ratio by 12, representing the 12 months in the year, to find out how many months it will take to reach the break even point on the cost of acquisition for that customer.

For example, let’s say you operate a subscription business charging $7.99 a month. Over the course of a year, a subscriber will generate $95.88. To acquire this subscriber, you ran a Google Adwords campaign that cost $75.00. Based on the above approach, your payback period would be:

$75.00/$95.88 = .78 (LTV:CAC ratio)
.78 * 12 months = 9.36 months

Therefore, it would take just over 9 months for you to recover the cost of customer acquisition for your subscription business.

What Is a Good CAC Payback Period?

According to many online resources, the customer acquisition cost payback period is usually measured in months, with a lower payback period being the ultimate goal. There are a number of reports offering benchmarks that can help you optimize your business to drive more efficiency. 

For startups, the typical payback period is around 12 months, but in some cases, the CAC payback period can be as high as 15-18 months. To be sure, these differences may be related to your specific industry, the nature of your products and/or services, and the cost of what you sell.

How Can I Accelerate the Payback Period?

There are undoubtedly numerous ways to accelerate time to payback. For the most part, these are related to the traditional 4 Ps of marketing.

  • Price: Research how your product is priced within the market. Explore whether you are able to adjust your price to drive more sales opportunities. In most cases, setting your prices too low will lengthen this period.
  • Promotion: Consider ad campaigns or demand generation tactics to drive interest and sales inquiries.
  • Place: Evaluate the placement of your product promotions and who you are reaching with your advertisements. A great way to accelerate payback is to optimize your advertising conversion rates.
  • Product: Ensure your product is clearly and articulately described on your website and in marketing collateral. Highlight core customer pain points that your product/service resolves.

How Does Predictive Analytics Drive CAC Payback?

Predictive analytics helps accelerate the payback period through four core predictive modeling techniques.

To this end, a few examples of predictive analytics for payback are:

  1. Predictive Lifetime Value: With predictive lifetime value, you’re able to predict what a customer’s lifetime value will be in 30, 60, and/or 180 days from now. Knowing this information, you can adjust service levels, promotional offers, and other customer-focused activities. Adjustments may either increase the customer’s value or lower the costs associated with servicing the customer.
  2. Conversion Rate Modeling: With conversion rate modeling, create proactive measurement strategies that forecast conversion events. You can fill data gaps and select campaign optimizations based on future customer buying behavior.
  3. Upsell/Cross-Sell Predictions: Predict which customers will buy more and which will buy accessory and complementary products. This predictive approach is a great way to drive higher lifetime value and lower your payback period from months to weeks.
  4. Churn Predictions: Predict which customers have a high likelihood of churning. Identifying these customers sooner, prior to fulfilling payback, will ensure you maximize return on investment.

In any case, it’s always easier to boost revenue from existing customers than to acquire new ones. 

Paying attention to your LTV:CAC ratio and your CAC payback period is an important way to ensure you’re seeing maximum return on acquisition costs as rapidly as possible. Predictive analytics offers vital insights into customers’ future to inform this effort and help your business grow.

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