Case Study


Embracing AI to overcome an increasingly competitive paid search marketplace.

Case Study


Embracing AI to overcome an increasingly competitive paid search marketplace.

Stannah are an industry-leading stairlift and homelift manufacturer and we’re proud to have been their digital partner since 2015.

We’ve seen Stannah’s search marketplace become increasingly competitive and therefore increasingly expensive, meaning PPC was becoming a less efficient channel for them in terms of ROI.

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

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

Responding to Shifts in Stannah’s Search Landscape

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.

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’d seen in the past.

The Stannah PPC account was a large account that had grown organically over time to maximise 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.

With more and more time spent on these kinds of optimisations, we had less time to take a step back and get a strategic view – meaning it was difficult to look for other opportunities and ways to overcome this challenge.

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’s search campaigns – whilst at the same time freeing up our specialists to make the right strategic decisions to drive greater success for the business.

Human Strategy, Machine Learned Delivery

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 – our visibility doesn’t 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.

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.

We then implemented a series of automated creative processes to better optimise the messaging we were putting in front of prospects, using responsive search ads and expanded ads within each ad group.

Finally, and perhaps most intimidatingly, we switched away from manual bid management to smart and automated bidding options.

While we had always strived to optimise our campaigns through manual adjustments, the scale of the challenge we faced meant that simply tweaking bids wasn’t going to be enough – so we handed that over to the machine.

Embracing AI and machine learning to this degree freed up our paid search specialists, enabling them to dig into the numbers – 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 optimise our campaign strategy towards those users more likely to become SQLs.

This also allowed us to understand what we needed to do earlier in the journey to influence those users to convert – both within paid search and through other channels like display.

Furthermore, we were able to dedicate more time to analysing and optimising our paid campaign landing pages to drive not only conversions, but conversions from the right kinds of people.

Striking Results Despite the Competition

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:

  • 23.1% increase in SQLs
  • -25% cost per SQL

Over the next 3 months of this approach we were able to continue optimising and – learning from the data we were seeing across the funnel – further improving the campaign. The results from across the account were equally impressive as we saw:

  • 20.8% increase in number of conversions
  • 28.5% reduction in CPA
  • 26.1% increase in conversion rate

What this shows is the incredible impact that machine learning and ROI can have on the bottom line. Not only because the machine will likely be more efficient at optimising bids and automating creative, it also frees up your time to do more analysis and make better strategic decisions, resulting in a more significant uplift across the board.

“It is so refreshing to work with a team that is innovative, accountable, responsible and feel more like an extension of our team rather than an agency. This campaign has been highly successful and we can’t wait to see what comes next.”

Fiona Neil,
Marketing Manager

Sectors: Manufacturing, Retail|Subjects: PPC