Case Study - UZO Furniture

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Identifying issues and lost opportunities within the existing Google Ads Account and building a custom strategy that matches the client's business goals.

Google Ads Management

02

Deploying SEM campaigns. Setting up conversion tracking and performance reporting. Creating a media plan and managing the yearly budget.

Optimizations

03

Monitoring account performance. Identifying and proposing new tactics to improve main KPIs.

Results

04

Increasing online quote submissions and store sales generated by ads.

Introduction

About the project

UZO Furniture is a family-owned furniture store located in Augusta, Georgia. They carry the most popular brands and have an 18,000 square feet warehouse and liquidation center where customers can purchase furniture at heavily discounted prices. Most of their inventory is displayed on their website but the majority of their sales are carried in-store. They pride themselves on offering superior customer service and they have furniture designer experts available on site. The main challenge was that the client was missing an eCommerce feature on their website, which meant that users weren't able to order any items online, instead, they could submit a quote requesting the prices.

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Challenge

Identifying lost opportunities

The efficiency presented limitations in the existing Google Ads account due to the structural composition of the campaigns which mixed upper and lower funnel traffic together, decreasing quality scores and limiting proper budget allocations. The starting point was to restructure the campaigns in order to increase efficiency, relevancy, and to capture traffic from users that are actively looking to purchase furniture. The keyword universe included broad terms which triggered a large number of irrelevant searches causing early budget depletion and low conversion rates. Ads were not tailored to keywords was leading to low-quality scores, and inflating CPC. Ad extensions were used incorrectly resulting in missed opportunities. Conversion actions were improperly tracked causing misleading metrics.

Improvements

Main Optimizations

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Restructuring

Implementing brand and generic campaigns in order to strategise and manage budgets in accordance with performance level.

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Improving Relevancy

Decreasing the keyword universe and excluding irrelevant searches to have more control over budgets and to reach the right audiences. Building ads and ad extensions tailored to each keyword group in order to increase the quality score which resulted in higher CTR and, CVR and lower CPCs.

Updating creatives across the account so that they are in line with Google's Best Practices and taking advantage of the latest features.

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Leveraging Machine Learning

Tracking additional actions that were bringing value to the business such as phone calls ( +60 sec.), submitted quotes, store visits, and local actions. Following these changes, I was able to successfully leverage machine learning features by using smart bidding strategies in order to make real-time auction modifications resulting in higher and better-quality conversions.

Results

900

Increase in ROAS

Increase in in-store sales YoY

45

Decrease in CPS

The cost per in-store sale decreased significantly which enabled the use of the media budget more efficiently

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Increase in CTR

The click-through rate increased and consequently the ads were more relevant to what the users were searching for

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Increase in CVR

A considerable increase in conversion rate, resulting in more sales

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