Bombinate Case Study
Learn how Upp became a critical part of Bombinate’s tech stack for sustainable growth and consistent performance
Smart digital marketers use Upp’s powerful AI platform to acquire more customers and hit their targets.
Bombinate is a curated marketplace connecting people to makers and the planet through quality pieces and authentic stories. It has built a home for some of the finest craftsmanship brands in the world, celebrating their talent and making them available to discerning consumers who demand more from the products they use every day – conscious manufacture, detail and quality. With Made In Workshops, Not Sweatshops as one of their core values, unwavering quality lies in everything they do.
Challenges and Goals
Fast fashion is now a prevalent strategy for many years and brands such as Primark, H&M, Shein, and Zara all have become large multinationals by driving a high turnover of inexpensive seasonal and trendy clothing that appeals to fashion-conscious consumers. However, the trend is changing as the fast fashion trend is not sustainable given the negative impact it has on the environment and labour. The collapse of fast fashion retailer Missguided and Love Island ditching its fast-fashion sponsor Boohoo for eBay, in order to stay relevant with consumers who are more environmentally conscious and aware.
Ethical fashion or sustainable fashion is nothing new having started as far back as the 1960s but is clearly mainstream as 67 per cent of consumers consider the use of sustainable materials to be an important purchasing factor, and 63 per cent consider a brand’s promotion of sustainability in the same way. Bombinate company values and products resonate with consumers who emphasise social and environmental commitments in their purchasing decisions.
Reaching such consumers is easier said than done and Bombinate approached Upp to manage its Google Shopping channel to:
- Better reach a growing audience of ethical fashion consumers whilst utilising ad budget more efficiently to maximise revenue potential
- Optimise Google Shopping, scale it and manage performance more consistently for the UK, France, Germany and the Netherlands regions
A data-led solution that delivers consistent results
In order to help Bombinate, Upp carried out its unique data-led audit to determine the cause of underperformance and where opportunities can be unlocked to achieve Bombinate’s objectives. The data-led audit revealed that:
- Bombinate accounts were not aligned to multi-region best practices
- Google is not surfacing products effectively in auctions leading to high overspend and underspend resulting in a high proportion of wasted visibility within the account
- A number of products starved of visibility thus impairs Google’s ability to effectively surface products that convert well, entrenching damaging performance biases
- A large opportunity to increase revenue without increasing budget
With this data-led insight at hand, Upp devised a clear strategy and solution to optimise and improve Bombinate’s performance in the short term and ensure consistency in performance for the long term:
- Configure Google Ads account to align with multi-region best practice
- Better measure performance by connecting ads shopping data to true order data
- Manage and report regions separately to better inform the AI and Machine Learning model and the accuracy of reporting
- Through data and reporting, automate the creation and management of shopping campaigns, redistribution and assigning of spend to efficiently spend ad budget and maximise revenue potential
- Focus on products with the highest opportunity for revenue potential with the goal to increase the visibility of them
- With the strategy above in place, this will provide data enrichment and improvements for the majority of SKUs enabling Upp to recommend ad budget to achieve and maintain Bombinate’s revenue and ROAS target range
- Protect margin whilst maximising revenue potential in conjunction with Upp’s recommended ad budget
- Optimise product selection to maximise revenue without eroding existing margin relative to budget allocation
- Continue to drive product visibility, upwards, across the entire product range
- Continue to optimise ad spend and switch to a goal-specific strategy to achieve sustainable growth and success
Implementation and onboarding
Upp implementation and onboarding process are very simple and straightforward. They use a two-step process that is Account Setup and Data Integration, this process is streamlined and in comparison to an agency-delivered service is much faster and reduces time to market for retailers to go live.
Account Setup – Upp created Bombinate an account, configure it to their requirements such as currency and set them live on the platform
Data Integration – Once a Bombinate is live, Upp plugs into their datasets: product from Merchant Center, connect to their custom ecommerce store via our API and campaign performance from Google Adwords.
As part of the data integration, Upp carries out due diligence by checking the mapping of the data to make sure the cost, product and orders all use the same key for SKU in the platform. This also means SKU on an order matches the SKU on a product.
Upp also made sure relevant training and support were provided to users of the platform so they can have positive interactions with it, minimise disruptions to the business and get what they needed to support internal activities and processes.
Our success and continuous optimisation
Being on Upp resulted in Bombinate achieving targets that were before not possible with results from the past 12 months (June 2021 to June 2022) showing:
- Average 678 clicks and 186k impressions per day
- Average ROAS of 316% per day
Upp’s ability to analyse datasets and take into account the market conditions Bombinate operate in to deliver consistent performance that translates into sustainable business growth. The relationship and partnership with Bombinatre continue to grow stronger as Upp improves and builds more features to their platform with the aim to keep unlocking opportunities within their customer datasets.