Case Study

In a partnership that has now spanned 5 years, Search Machines have increased Mr & Mrs Smith’s non-brand bookings by over 1,000% percent! 

In this case study we share some key insights from this amazing journey.

Background

Search Machines were approached by the luxury hotel website Mr & Mrs Smith who had struggled to get their PPC marketing to work for a number of years. Prior agencies had failed to achieve the growth required and were failing to reliably hit the ROI target. 

Working with Search Machines has transformed our performance marketing. Specifically since the introduction of Atlas which has grown our ROI by 55%.

Lee RuddleCHIEF CUSTOMER OFFICER, MR AND MRS SMITH

Client Goals

Their goal was to aggressively grow non-brand conversion volume with a ROI just above breakeven.  In order to achieve this goal, we started with a detailed analysis of the client’s accounts. This highlighted three significant issues: 

  1. Inadequate keyword coverage of existing hotels
  2. Unexplored areas of new traffic
  3. Inefficient bidding due to poor segmentation of traffic

The Search Machine Solution

The first two issues were resolved using Search Machines’ software ATLAS. We utilized its ability to crawl Google for all the relevant traffic, understand it, and then generate super specific ads. We explored both the existing hotels and new untapped areas of demand.

In tandem with this, we needed to create an account structure to enable efficient bidding. ATLAS can rapidly create optimal account structures and so we were able to deploy fully fledged campaigns within a few weeks. 

The impact was instant with 168% growth in the first month vs May 2017.

We then carried that growth forward achieving 1068% growth by Jan 2020.

At this time the due to the pandemic the brief from the client changed. We needed to help rebuild booking volume but at as high a ROI as possible within their budget.  

Throughout this incredibly turbulent time we helped to bring booking volume back to pre-Covid levels at an ROI of 2.2, twice the previous target.

Data driven performance gains

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