The LTV and RFM dashboard gives you an overview of key lifetime value and retention metrics. This dashboard provides at-a-glance LTV and repurchase rate metrics for different customer cohorts like LTV and repurchase rate by first order date, first order channel, or first order SKU. LTV-to-CAC ratios are shown for different customer cohorts, and the bottom section contains RFM (recency, frequency, monetary) customer segments to enable merchants to understand the makeup of their customer base.
LTV is typically calculated as the sum of Gross Margin (Net Sales less SKU Cost, Shipping Cost, and Fulfillment Cost) for the cohort divided by the number of Customers in the cohort. We break these totals down into 30 day periods labeled as "Months Since First Purchase".
The LTV Dashboard has three sections:
Lifetime Value and Repurchase Metrics
The top row of this dashboard (below) shows key statistics related to the size and health of your customer base. This includes total emails acquired (via Shopify), the number of customers who have ever purchased, customers who have purchased in the last 12 months, and the % of customers who purchased in the last 12 months.
Shopify considers an email a "customer", but we find this to be confusing if there has not been a purchase.
Total customers ever purchased/active customers includes only valid orders. Read more on valid orders here.
The first charts shows the average customer lifetime value (LTV) and repurchase rate over time. The "Months Since First Purchase" metric represents how long an individual has been a customer. For example, on the day your customer made their first purchase, their TOB equals 0. The next 30 days following that, that customer’s "Months Since First Purchase" is equal to 1. "Months Since First Purchase" of 2 represents the 30 days following that, and so on.
By calculating LTV in this way you can assess your entire customer base through the course of their customer journey, regardless of when they first became your customer. For example, if customer A purchases SKU 001A on January 1, 2019 for their first purchase, and customer B purchases SKU 001A on January 1, 2020, they can still be grouped in the same cohort with LTV measured in 30 day increments since their first purchase. A "Months Since First Purchase" value of 1 will include the 30 days after Customer A's first purchase, and the 30 days after Customer B's first purchase.
The bar charts in the center display LTV and Repurchase Rate at key customer milestone timeframes since acquisition. 12 and 24-month LTV are common timeframes to reference.
Repurchase rates calculate the number of customers that ever make a second purchase. If a customer makes a third or fourth or fifth purchase this does not increase the repurchase rate.
The next graphs represent LTV and Repurchase Rates by two very common questions Daasity receives from merchants:
- By Marketing Channel in which Customer was acquired. This is based on your unique rules entered into Channel Mapping in your Brand Data sheet.
- By First SKU purchased. Keep in mind that customers can purchase multiple SKUs in their first purchase.
By First Order Channel
Knowing which marketing channels are bringing you the most valuable customers is vital information to better inform your acquisition strategy.
By First Order SKU
These tiles show the lifetime value (Gross Margin per Customer cohort) and the Repurchase percentage cohorts based on the first SKU the customers purchased. These tiles help identify the most valuable SKUs to advertise to potential/new customers.
Layer Cake Graph
The “layer cake” graph displays sales by quarter of acquisition cohort. This graph places a customer into a cohort according to the quarter in which they made their first purchase, and then stacks those cohorts on top of each other using an area graph. Each cohort creates a "layer" of revenue, with the goal being to have a balance of revenue from new customers and those acquired in prior quarters/years.
The large peaks are from newly acquired customers, and then those peaks drop off to be thinner layers each subsequent quarter as a portion of those customers come back and produce additional sales.
The Layer Cake graph is a great way to understand if you are retaining your customers. If the gross sales in a particular month is made up almost completely of new customers then you likely have a retention issue. For merchants with more than 18 months of sales, you generally do not want more than 50% of your revenue coming from new customers for any given month.
To improve repurchase rates, consider some of the following strategies:
- Make sure you segment your customer base in your retention campaigns. You can segment by products purchased, price points, if customers used a discount in their purchase, time of year customers purchased, or using our out-of-the-box segmentation found in our Retention dashboard.
- If you are not getting good responses from email, consider adding SMS as a retention option.
- Use product affinity to make sure you are presenting customers with the products they are most likely to buy.
- Always test your email campaigns. Different copy, images, products, and offers can product wildly different results.
- Consider adding a subscription option.
The next section is LTV:CAC. The LTV to CAC ratio is a very important metric for all direct to consumer companies to understand how long it takes for their marketing investments to pay off. An LTV:CAC ratio will be equal to 1 where total gross margin for a group of customers is equal to the acquisition cost for those group of customers, which would represent when that specific cohort has “paid back” the amount equal to their cost of acquisition.
These two visualizations show the LTV:CAC ratios for customers that were acquired during different months. The first visualization shows LTV and CAC on the same axis, while the second gives you the actual LTV:CAC ratio.
- A good rule of thumb is that the LTV:CAC ratio should be above 1 in the first 6 - 12 months after a customer is acquired, and should be over 3 in the first 36 months after a customer is acquired.
- Investors like to understand the LTV:CAC ratio to make sure that companies are spending their marketing dollars efficiently and that they are acquiring customers that come back and purchase often (or customers spend enough on an initial purchase to make up for low repurchase rates). A company that can't reach an LTV:CAC ratio of 3 in the first 36 months of a customer's lifecycle is not sustainable.
- If your LTV:CAC ratio is too low there are some long term fixes you can make. First is to make sure you are spending your marketing dollars efficiently and cutting spend in channels where you see a high cost of acquisition or cost per order. Second, think about strategies to improve AOV, lower product / shipping / fulfillment cost, or improve repurchase rates. See above in this article for tips on improving repurchase rates.
RFM: Recency, Frequency, Monetary
The next section is Recency, Frequency, Monetary (RFM); the traditional database marketing approach to customer segmentation and scoring. The top visualization shows Average Gross Margin per Customer by RFM decile. The RFM decile places each customers into 1 of 10 segments based on their RFM score, which takes into account the recency, frequency, and amount of a customer’s lifetime purchase history. The three donut charts below that show the percentage of your customer base falling into each of your recency, frequency, and monetary segments.
Read more about RFM here.
Total Emails Acquired
Total Customers Ever Purchased
Customers That Have Purchased Last 12 Months
% Of Customers That Have Purchased Last 12 Months
LTV At 3, 6, 9, 12, 18, 24 Months Since First Purchase
LTV - Lifetime Value
Repurchase Rates At 3, 6, 9, 12, 18, 24 Months Since First Purchase
Customer Repurchase Rate
LTV By First Order Channel
Repurchase Rate By First Order Channel
LTV By First Order SKU
Repurchase Rate By First Order SKU
LTV - Gross Sales By Quarter Of Acquisition Cohorts
LTV and CAC By Month of Acquisition
LTV - Best to Worst Customers Ranked and Grouped
Customers Count by Recency
Customers Count by Frequency
Customers Count by Monetary