CLV (customer lifetime value) — defined as the total worth to a business of a customer over the whole period of their relationship — is a metric that is highly desired by brands but is often found to be challenging to quantify accurately. We, at Nozzle, believe calculating CLV correctly is vital to understand how your customers interact with your brand.
A commitment to the effective use of CLV and its absence from Amazon Marketplace reporting processes, provided us with the motivation to create the Nozzle platform in the first place — we saw a gap with regards to CLV calculations, and we built Nozzle to solve this problem.
We are now able to make it easier to develop CLV-driven strategies. In the future, such strategies will be critical to your continuing success on Amazon.
What is CLV, and why is it important?
CLV is a crucial metric for ensuring long-term growth. It’s a direct indicator of how much value a customer is expected to create during their association with you. Overall, a higher CLV should lead to more significant profits. By retaining customers and encouraging them to spend more, you will see benefits show up on your bottom line.
So why is measuring CLV important?
- You can’t improve what you don’t measure: You can employ specific strategies around pricing, sales, remarketing, advertising and customer retention, continuously reducing costs and increasing profit.
- You make better decisions on customer acquisition cost: When you know what you will earn from a typical customer, you can increase or decrease ad spend to ensure you maximize profitability and continue to attract more suitable types of customers.
- You improve forecasting: CLV-based forecasts help you make forward-looking decisions around inventory, staffing, production capacity and other costs.
- You advertise smarter: Knowing your CLV gives you the power to turn a break-even ACoS to your advantage as well as informing your PPC spend, creating a competitive advantage in customer acquisition strategies.
How is CLV calculated? What do you need?
To calculate the CLV of a customer, you need to analyze the behavioral patterns and transaction history of that customer or similar customers, determine their lifespan and the margin they will generate for your business.
There are two calculation methods you can use for CLV:
Here is a simple formula for customer lifetime value:
- CLV = Average order value (AOV) x transactions x retention period
Another way is to look at it from an Amazon Seller point of view is:
- CLV = Total order value x average gross margin x retention period
Note: When calculating gross margin remember to not only include COGS (cost of goods sold), but also all Amazon fees.
Each input acts as a lever you can pull to grow your CLV. However, every move using a simple CLV could have unintended consequences that impact your CLV. For example, a price increase may improve your average order value, but it could push customers to purchase less often or look for lower-cost alternatives.
Complete CLV seeks to contextualize your simple CLV on an ongoing basis in order to help you understand how it's truly growing your business. This is done by calculating CLV year-by-year and month-by-month basis. You can factor in models of changing revenues and costs and compare the projected ROI of different investment possibilities to calculate present value.
This is the way we approach CLV calculation:
Fundamentally, the big difference here is looking at CLV without any approximations, estimations or forecasting. It’s a bottom-up approach that looks at each customer, what they’ve bought, and when they bought it — along with the profit generated by each ASIN. It goes through the entire purchasing history per customer to calculate it for every customer, and then takes the median. This is then shown to you over a period of time — e.g. how much is a customer worth to me after 3/6/12/24 months.
Let’s take a look at how our platform calculates CLV — below is a screenshot of the platform looking at the average LTV of customers over a 24 month period.
Cohort analysis involves breaking apart data sets into related groups for analysis, and is critical for the interpretation of CLV data in a valuable way. For example, we can compare people who first converted in Q1 of 2020 with people who first converted in Q1 of 2021, and how they compare in their respective first and second quarters, etc. And it all needs to be carried out at speed for you to benefit. We solved this problem by tapping into many Amazon APIs, pulling data from Amazon MWS to crunch the numbers using our proprietary AI algorithms, and then presenting the figures back in customizable dashboards.
Below you can see a screenshot of Nozzle’s flagship platform, presenting data points that refer to different customer-centric metrics — all of which are directly related to accurate CLV calculations.
Suggested watching: Check out our two webinars if you want a full breakdown on how to calculate and how to use CLV more effectively on Amazon:
Start Using Customer Lifetime Value To Your Competitive Advantage.
Book a demo with us to quantify your CLV and use this data to optimize marketing spend and increase profits.
Challenges to conquering CLV
By pursuing meaningful and accurate CLV on Amazon you will be way ahead of most of your competitors. But nothing comes easy — there are issues that you will face with CLV — especially if you go it alone.
Here are a few significant CLV-related challenges you will face along the way:
The first challenge is calculating CLV
- Attaining sufficient granularity: CLV works best when applied on a customer type, marketing channel or campaign basis — getting data of sufficient detail can be very difficult as it is scattered throughout Amazon reports.
- Collecting the right data at the right time: There are many moving parts to a good CLV calculation. For example, gross profit and refunds have to be calculated. Collecting and organizing this data on your own is a very challenging and time-consuming task.
- Quantification accuracy: The “lifetime” part of CLV is also very tricky to calculate accurately.
- Inability to assign CLV at the right level: CLV is a form of forecasting — if your data is too general and too high level, your conclusions may also be.
The second challenge is using CLV
Even if you can calculate CLV accurately, data is useless without actions and outcomes. Here are some of the business challenges to consider when using CLV:
- Choosing the right product and brand: Some products are intended for one-off sales, so be aware that not all products or customers are suited to CLV analysis. This situation will become rarer but needs to be taken into account.
- Not improving operations as a result of CLV: It’s one thing to calculate CLV, and it’s another to use those insights to act on and drive tailored customer engagement and actions.
- Too much siloed thinking to take advantage of CLV: Several departments are usually involved in a customer’s journey. Improvement to CLV can include marketing, sales, inventory and customer service functions working together.
Nozzle’s analytics platform gives you the means to address these challenges. We take data from numerous Amazon sources, convert it into CLV intelligence, operationalize it through our platform and then capture the outcomes for your team to drive iterative improvements.
Suggested reading: For more information on how to not only calculate and use CLV correctly, but to actually increase your average CLV, check out our blog — 3 Ways to Increase Amazon Customer Lifetime Value
Nozzle provides a shortcut to CLV and so much more
Over time, Amazon advertising is moving away from single product sales to more customer, persona, and demographics focus. We believe such changes will make Nozzle CLV analysis even more central to your retail, portfolio, and advertising strategies.
But it’s not all about CLV. Our analytics platform is built to help sellers master Amazon customer data and use it to drive the best commercial outcomes. We also offer state-of-the-art PPC optimization and automation tools. And you should have a look at our other retail analytics offerings, which include:
- Repeat purchase analysis
- Sales analysis
- Market basket analysis
- Geo-hotspot analysis
In fact, get in touch to book a demo today and learn how our analytics platform can transform your operation on Amazon.