In a previous video, you learned a simple calculation for ROAS (return on ad spend): ROAS = Revenue generated/Ad spend. You also learned that Lifetime Value (LTV)—sometimes called Customer Lifetime Value—is the average revenue generated per customer over a certain period of time.
Both ROAS and LTV enable you to get an estimate of your return on investment, or ROI, for a campaign. ROAS gives you a way to measure the short-term performance of your campaign. It answers the basic question: Did the campaign bring in more revenue than what was spent on the campaign? LTV answers a more strategic question: Did the campaign increase or promote the “stickiness” of customers so they made additional purchases? When you consider both ROAS and LTV, you are placing a value on both the numeric and strategic aspects of ROI for your marketing effort.
The video covered ROAS calculations based on revenue and what you can do to improve ROI if ROAS doesn’t meet your expectations. This reading provides more information about using LTV as a measure of ROI.
ROI using LTV
The definition of LTV does not provide a specific time period for which to calculate the average revenue generated per customer. The amount of time can be years, quarters, or months. Months is most commonly used in retail. When the time period is from the past to the present, LTV is sometimes referred to as total LTV. When the time period includes future dates, the LTV is referred to as predicted lifetime value (pLTV). Because pLTV relies on transactions and customer behaviors to predict a future LTV, pLTV becomes more accurate with each additional purchase and customer interaction that occurs.
Using pLTV is a common method to estimate the impact of digital marketing efforts before every sale comes through. For example, when newly registered customers make their first purchase, you can use the historical performance of similar customer types to predict the amount of revenue they will bring in over time.
Pro tip: When determining the ROI of completed campaigns, use total LTV rather than pLTV. You can use pLTV to predict the ROI for campaigns that are still in progress.
Two ways you can use LTV to measure the success or ROI of a completed campaign are:
- LTV by channel
- LTV to CAC ratio (LTV:CAC)
LTV by channel
Just as you can measure ROAS for each channel in a campaign, you can measure LTV in the same manner. Attribution of conversions by channel must be enabled in advance.
For each channel in your campaign, calculate the following:
LTV = Average Order Value (AOV) x Purchase frequency
Comparing the LTV for each channel provides insights on ROI by channel.
LTV to CAC ratio
You also learned that customer acquisition cost (CAC) is the average cost of acquiring a paying customer. LTV and CAC are used to calculate an LTV to CAC ratio. This ratio is helpful to determine if the value gained from adding new customers during a campaign is enough to cover the cost to acquire them. The higher the ratio, the better the ROI.
You can calculate the LTV to CAC ratio for a campaign or channel using the following:
LTV to CAC ratio = LTV/CAC
A result of 2 or higher is normally considered good. An ideal result is around 3. A result below 2 could occur if you’re intentionally spending more to gain market share. However, if that isn’t the case, you might need to cut budget spend to reduce the CAC and increase the LTV to CAC ratio. If the result is above 3, your ROI is solid and you have a steady and robust revenue stream. With a result above 3, you would presumably have enough budget to expand your business. For example, if your goal is to diversify the kinds of products associated with your brand, you could support that goal with advertising campaigns that are adequately funded.
Marketing mix models
Marketing mix models, sometimes called media mix models, are statistical models advertisers use to predict the effectiveness and ROI of their advertising spend. These models rely on at least two years of historical data from previous campaigns. Since they were first developed in the 1960s, they have become more reliable in predicting campaign ROI because of the recent benefits of artificial intelligence (AI) and machine learning. The actual models are beyond the scope of this reading, but you should be familiar with these terms.
ROAS and LTV are a good place to start when trying to determine the short-term ROI of a campaign. Marketing mix models can help predict the ROI for campaigns, but building them requires additional technical skills, like computer programming and knowledge of statistics.