Pillow Talk.

Pillow Talk is a proudly Australian owned and operated omnichannel retailer, which specialises in bed linen and homewares. Having recently celebrated 40 years of business, an impressive milestone in today’s retail climate, Pillow Talk is a true Australian success story that operates nearly 60 stores Australia-wide.

Our objective was to increase online sales, ROAS and help grow the email database significantly.

Before Alpha Digital began management, the account was generating an approximate ROAS of 101% with only a focus on branded terms. We identified new opportunities with the account as it was missing key revenue drivers such as Google Shopping, Google Remarketing, and a long-tail keyword strategy.

Much of the account was spending a significant amount of money with low returns. Most campaigns had a broad keyword structure resulting in low quality traffic that was both damaging to the brand and the bank balance. Additionally, campaigns were sending users to broken URLs resulting in a poor user experience and poor ROAS.

Campaign Structure – We created a hyper-granular long-tail keyword strategy which helped us create individual campaigns for each product category. This allowed for easy budget allocation to top performing product categories. This was then split down between brand vs non-brand allowing us to allocate budgets for both prospecting and nurturing existing customers.

Shopping – Through a third party, we developed a shopping feed and introduced multiple Google Shopping campaigns to help accelerate growth. Google Shopping campaigns were then segmented between non-brand, brand and top sellers. This segmentation along with Google’s ROAS bidding strategy allowed us to set individual targets for prospecting and nurturing search terms.

Traffic Quality – Using a custom built negative keyword frequency tool – we identified low quality broad match keywords such as “gift cards” on existing campaigns saving the account over $10,000 in ad spend.

Audiences – We introduced custom audiences such as “AfterPay Customers” as we observed these customers provided a higher average order value.