Poundshop Case Study
How Poundshop maintained ROAS target whilst driving daily spend and impressions up by 375% with Upp
Smart digital marketers use Upp’s powerful AI platform to acquire more customers and hit their targets.
Poundshop.com is the largest UK online pound shop founded by the ex-CEO and CFO of the infamous Poundland. Similar to many online Food & Beverage retailers during various lockdowns of 2020, Poundshop too received significant demand for their services.
However, whilst there was a huge demand, in 2021 Poundshop identified that with their fast turnover of SKUs and ever-changing range, a smarter approach to managing customer acquisition was needed. Google Shopping is one of Poundshop’s key customer acquisition channels. Read on to learn how Upp u-turned Google Shopping into one of Poundshop’s best-performing customer acquisition channels.
Poundshop wanted a data-driven approach to Google Shopping, whilst maintaining control
With more than 300 new lines launched on an average week, and many more during seasonal events, neither Google Shopping nor Poundshop’s agency could keep pace. ROAS (Return on Ad Spend) was often ‘spikey’, and daily budgets were often not spent.
When Upp first audited the account, we found that the campaign structure was a fairly typical one, splitting by product category. Whilst this is a human-readable and logical way to set up campaigns, it can severely restrict account growth. You can read more about why it leads to poor performance here.
The second challenge, more unique to Poundshop, is the velocity of new product lines added each week (often a challenge in the fashion industry, too). Usually, when Google sees these products added to existing campaigns amongst other similar products, Google doesn’t have enough understanding and data on new products to manage them effectively. This minimal data and understanding of new products, when compared to other products, means Google limits their exposure, resulting in Poundshop struggling to grow sales without negatively impacting ROAS.
As the account matured, this meant that fewer and fewer products were generating the majority of Poundshop’s sales through Google Shopping.
Upp leveraged product performance data to transform Poundshop’s Google Shopping fortunes
After deciding to switch to Upp, the first thing we did was plug into a source of order’s data. Often a traditionally dreaded part of the process and time consuming for many merchants, Upp has a plugin that integrates into Poundshop’s ecommerce platform, Magento 2.0. All Poundshop needed to do was grant Upp credentials.
Within weeks of using Upp, Poundshop knew they had made the right decision to switch from using their agency to manage Google Shopping to a platform that utilises product-level data to enhance performance 24/7 through AI and Machine Learning campaign automation. Immediately, Upp was pushing products that Google had never promoted, yet generated sales from other channels, from 17% to 68%.
As Upp tested different products and the platform learnt which of those products could generate conversions and achieve target ROAS, the overall growth of the account improved WoW, where previously Poundshop’s agency had hit the inevitable Google Shopping “glass ceiling”.
Today, six months since launch, Upp has managed to maintain Poundshop’s ROAS target whilst driving daily spend and impressions up by 375%.
“Whilst Google Shopping is a great tool to find new shoppers, having more manual control over campaigns can often be difficult when dealing with large ranges of SKUs, as is the case for Poundshop. Upp’s proposition was an attractive one as they can help continuously optimise our product range, organising SKUs into relevant campaigns to help maximise exposure at the right cost. It’s definitely the way forward.”
Alex – Head of Digital, Poundshop
Upp Technologies is the only connected retail performance platform in the market. They ensure retailers thrive by connecting their product performance data, automatically unlocking hidden opportunities and optimising business performance in real-time.