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How deep-diving into Product & SKU Intelligence helped our client to improve ROI by 45%

Piyush Gupta
Reading Time: 4 minutes
Deep diving into product SKU

One of our clients had hundreds of products on their website. 

The products were of different sizes, quantity, price range, and category. 

But they were not sure what products they should use on their Facebook and Google ads.

Or which products were bringing them, quality customers, with high Customer Lifetime Value (CLTV) at a low Customer Acquisition Cost (CAC) 

About The Client

  • Leading E-Commerce Player
  • 300+ products on the website
  • Targeting luxury audiences around the world

Problem Statement

Improving the ROI of the ad campaigns while maintaining the scale. The client already had decently optimized their Facebook and Google ads accounts which were generating decent returns.

Key Analyses

Build an in-depth model to understand what products are suitable for acquiring high-quality customers. Also analysing product features to determine customer targeting options.

Sample Report and Metrics Used

From we were able to fetch product wise data on 

  • Customer Lifetime Value (CLTV): CLTV is defined as the average revenue you make or expect to make from a customer by providing your services/products in return.
  • Acquisitions: New users acquired by the business
  • Repeat Percentage: Percentage of acquisitions coming back to the business (offline or online) to make a purchase
  • Customer Acquisition Cost (CAC): The average amount of money spent by the business to drive one acquisition. Calculated as the total amount spent divided by the total number of acquisitions.

All these metrics were easily available once we connected the client’s ad accounts and CRM to

What is data driven digital marketing tool that connects your Google Analytics, Google Ads, and Facebook Ads and provides easy access to powerful monitoring, analyses, reports & dashboards

So, How did we do it?

First, via data stitching using we found out the LifeTime Value, the Total number of acquisitions, and the Repeat percentage of all the products on the google sheet. 

Sample data:

ProductAcquisition countCLTVRepeat percentage
Product 120703177.1544.59%
Product 23261636.9921.58%
Product 32461337.3319.49%
Product 419162156.8722.55%
Product 52772599.088.45%
Product 67441863.473.23%
Product 79401947.7219.99%
Product 821702502.098.75%
Product 93882650.614.81%
Product 1014442391.958.03%
Product 111191587.2519.64%
Product 1211371970.845.39%
Product 131921850.126.87%
Product 147672311.754.59%
Product 1558944.394.96%
Product 1667233782.8629.90%
Product 1727662417.118.50%
Product 184461376.235.75%
Product 1928561.146.51%
Product 2033454133.9882.21%
Product 2135323468.5351.94%
Product 22102982.822.76%
Product 231541130.3911.37%

* This is a sample of the data, actual data had 300+ products.

Upon deep diving the above selection we can already see that there are certain products with higher CLTV and Repeat percentage. 

Then, we divided these products into different categories and price brackets using the labeling feature in .  

And then we easily fetched the metrics based on these parameters.

Data fetched:

CategoryAcquisition countCLTVRepeat percentage
Category 129002275.810.56%
Category 27672311.754.59%
Category 323963277.8545.72%
Category 445193831.3914.87%
Category 54741395.376.09%
Category 621623023.1724.66%
Category 72561308.136.68%
Price BracketAcquisition countCLTVRepeat percentage
50 – 100 $24023303.088.35%
100- 150 $152644724.1135.36%
150 – 200 $97305090.2544.02%
200$ +25032770.4616.78%

*so, we found the winning category and the right price range to target our customers with.

Insights we got from the above data

Now, we drove the following insights from the gathered data:

  1. Got a list of all the products that were attracting high-quality customers
  2. Understood the category wise CLTV
  3. Got an idea of the pricing preferences of the customers


Finally, we used these insights to make the business decisions and drive up the net ROI of the business with the following actionable

  • Passed the above finding as new attributes into the product feed for both Facebook ads and Google shopping ads
  • Created separate product sets for products that were attracting high-quality customers and bid higher for them compared to the holistic feed
  • Increased the use of high-quality customers attracting products in the top of the funnel campaigns
  • Created a CAC benchmark for products relative to their respective CLTVs
  • Provided insights on product team on what kind of product to source


After fully incorporating the above actionables we were able to increase the overall ROI  of the business by 45%. 

Checkout how we can help your online eCommerce platform to register faster growth and a higher ROI. Book a Demo now!

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