A Home-Furnishing RETAILER
Use Case: Millions in Ad Spend Savings
How Metricstory's findings allowed this eCommerce team to cut back 15% of their monthly spend on Google PLAs with no impact to revenue.
The Problem
For this mid-size home furnishing customer, identifying overall trends across their Google Ads and Google Shopping campaigns was part of their weekly review process with their paid search agency. However, with approximately $800,000 in monthly ad spend for PLAs alone, the volume of data surrounding campaign, ad group, and search term performance was nearly impossible to sift through in detail on a regular cadence.

This savvy eCommerce team wanted more! They were seeking granular insights to help them better understand how individual products and search queries were performing across paid search so that they could hone in and improve their return on ad spend (ROAS) with a deep understanding of what was and wasn't performing up to their standards.
Metricstory's Solution & Findings
Metricstory automatically uncovered $754,455 of inefficient spend across all of the home furnishing company's paid search campaigns during a 24-week period (text ads and PLAs). This inefficient spend was attributed to individual search queries performing with under 100% return on ad spend (ROAS) across the entire purchase path. Combining Google Analytics, Ads, Merchant Center and the Multi-Channel Funnel, Metricstory identifies search queries with low value across the entire conversion path so that clients can have confidence that the query has a minimal impact to revenue. The home furnishing company's eCommerce team described these powerful findings as a "curated, silver platter list" of easy opportunities to improve their profitability.
$120,000

of inefficient spend on Google PLAs identified per month
15%

savings captured across PLAs based on Metricstory's insights
$1.44 million

annual savings on ad cost with no impact to revenue
Customer Action & Results
Utilizing Metricstory's findings, the eCommerce team determined they could cut back 15% of their monthly ad spend, starting with their PLAs, due to poor search query performance. They shared the report with their agency to make the changes, and then carefully monitored their returns. Several weeks after cutting back spend, the team saw no difference in their revenue generation, but a significant increase to their ROAS and profitability.