{"id":5472,"date":"2019-09-27T10:18:00","date_gmt":"2019-09-27T10:18:00","guid":{"rendered":"https:\/\/staging.elixirrdigital.com\/us\/?post_type=case_study&p=5472"},"modified":"2026-03-16T10:51:34","modified_gmt":"2026-03-16T10:51:34","slug":"stannah","status":"publish","type":"case_study","link":"https:\/\/staging.elixirrdigital.com\/us\/case-studies\/stannah\/","title":{"rendered":"Cutting CPA by 28.6% and improving paid search for Stannah"},"content":{"rendered":"\n
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\n Back to Case Studies<\/a> <\/div>\n

\n Case Study<\/p>

\n Stannah<\/h1> <\/div>\n
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Embracing AI to overcome an increasingly competitive paid search marketplace.<\/p>\n <\/div>\n <\/div>\n<\/div>\n

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Stannah are an industry-leading stairlift and homelift manufacturer and we\u2019re proud to have been their digital partner since 2015.<\/p>\n

We\u2019ve seen Stannah\u2019s search marketplace become increasingly competitive and therefore increasingly expensive, meaning PPC<\/a> was becoming a less efficient channel for them in terms of ROI.<\/p>\n

However, we also knew that search could be a powerful tool for them \u2013 it had always been our most successful channel. We just needed a combination of the right management approach and the right strategy.<\/p>\n

By embracing machine learning and AI, we were able to put the day to day management in the hands of the machine \u2013 freeing up our experts to do the strategic work that was required to find success across the sales pipeline.<\/p>\n

Responding to Shifts in Stannah\u2019s Search Landscape<\/h2>\n

Search has always been a key part of our digital strategy for Stannah, and since our PPC specialists took over, it has historically driven high lead volumes at an efficient cost.<\/p>\n

However, due to changes in market conditions and the search landscape, we were seeing lead volumes stagnate and cost per acquisition increase. The main cause of this was a huge shift in the competitive landscape, due to competitors coming in with much higher search budgets than we\u2019d seen in the past.<\/p>\n

The Stannah PPC account was a large account that had grown organically over time to maximize results. However, with this new competitive challenge in the marketplace, our PPC specialists were spending more and more time in the weeds trying to find the tweaks to the account that would return the campaign to levels of success it had seen in the past.<\/p>\n

With more and more time spent on these kinds of optimizations, we had less time to take a step back and get a strategic view \u2013 meaning it was difficult to look for other opportunities and ways to overcome this challenge.<\/p>\n

We needed a fresh approach, and embracing new and emerging search technologies gave us a way to do that. By using machine learning and artificial intelligence, we embarked on a mission to overhaul Stannah\u2019s search campaigns \u2013 whilst at the same time freeing up our specialists to make the right strategic decisions to drive greater success for the business.<\/p>\n

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Human Strategy, Machine Learned Delivery<\/h2>\n

One of the key elements of our approach to Stannah is our ability to see how the leads we generate perform down through the pipeline \u2013 our visibility doesn\u2019t end at an Analytics conversion. The ability to understand how many sales qualified leads we are generating has long allowed us to make decisions that best benefit Stannah.<\/p>\n

With this information in hand, we set about preparing our search campaigns for a full machine learning strategy. That meant consolidating campaigns that were previously split out by device and keyword match type.<\/p>\n

We then implemented a series of automated creative processes to better optimize the messaging we were putting in front of prospects, using responsive search ads and expanded ads within each ad group.<\/p>\n

Finally, and perhaps most intimidatingly, we switched away from manual bid management to smart and automated bidding options.<\/p>\n

While we had always strived to optimize our campaigns through manual adjustments, the scale of the challenge we faced meant that simply tweaking bids wasn\u2019t going to be enough \u2013 so we handed that over to the machine.<\/p>\n

Embracing AI and machine learning to this degree freed up our paid search specialists, enabling them to dig into the numbers \u2013 to look at how leads were performing through the sales pipeline and also further up the funnel. By building out a detailed attribution model that tracked those more desirable leads through their whole journey, we were able to better optimize our campaign strategy towards those users more likely to become SQLs.<\/p>\n

This also allowed us to understand what we needed to do earlier in the journey to influence those users to convert \u2013 both within paid search and through other channels like display.<\/p>\n

Furthermore, we were able to dedicate more time to analyzing and optimizing our paid campaign landing pages to drive not only conversions, but conversions from the right kinds of people.<\/p>\n

Striking Results Despite the Competition<\/h2>\n

The initial results of this change were striking. In the month after we made the switch, automating bidding and creative as well as putting into action our new strategy across the funnel, we saw:<\/p>\n