How to calculate ARR per customer in LinkedIn Ads

Make the most of your LinkedIn Ads data

What is ARR per customer ?

ARR per customer:Ā is the total ARR divided by your total number of customers. It will allow you to measure whether your annual $ per customer is growing, meaning you're probably upselling or cross-selling your customer base.

What is LinkedIn Ads ?

Linkedin ads allow you to reach your ideal customers on the world's largest professional network.Ā AdvertisingĀ onĀ LinkedInĀ helps businesses of any size achieve their goals. Create and run campaigns using simple self-service tools, and track their performance with easy-to-read reports

How to calculate ARR per customer in LinkedIn Ads ?

It can be difficult to calculate ARR per customer directly inside of LinkedIn Ads; that's where Whaly comes in.

Whaly helps you build models on top of LinkedIn Ads and many other solutions. You simply connect Whaly to your LinkedIn Ads account, and then you can create your formula in Whaly to calculate your ARR per customer.

How does Whaly work ?

01
Access all your data
No more manual import or stale data. Whaly automatically updates your data and is integrated to the tool you use to give you the most flexibility.
02
Build metrics like a pro
Use our state of the art studio to access your data, prepare your reports by cleaning and formatting your data. Combine your different sources to explore your data in a way you never had before.
Build your metrics
03
Visualize your data
Whaly offers best in class data visualization capabilities.
Visualize your data
Edouard Mascre
We leveraged Whaly on the Sales team to build and share dashboards with ton of partners without having to continuously update things on many spreadsheets. It also gives us deeper insights on sales activity. The dashboards built can be shared with everyone in the company. Whaly saves us hours of data wrangling every day.
Edouard MascrƩ
Co-Founder @ Pennylane
Benjamin Cambier
Mansa grew really fast in the past months and we were in urge of more precise metrics, especially for acquisition and deals analysis. Our engineering team was already swamped so we started our data analysis with Whaly. We compute our CAC per acquisition channel and understood at what stage the pipeline is under performing in minutes.
Benjamin CAMBIER
Co-Founder @ Mansa