Market context

Scope: Research & insight > positioning, strategy & TOV > brand system and guidelines > website. 
Sector: Retail advertising / AI

Upp. is an AI powered retail intelligence platform that leverages inventory insights to automate advertising decisions, in real-time, for brands on Google Shopping. The tech connects disparate data from advertising, operations, market trends, and influencers, then layers with AI-driven decisioning to enable retailers to improve ROI and reduce wasted ad spend.

The platform operates with both granularity and scale - analysing 85M+ SKUs, each with 120 unique data points, equating to 7B+ analyses per day. Upp. utilises advanced AI and machine learning to automate Google Shopping campaigns by grouping SKUs, allocating the right return on ad spend (ROAS) budget, and determining break-even points and contribution margins for profitable sales.

Challenge

Our challenge was to bring Upp.’s retail intelligence platform to life.

Upp. competes against digital agencies who run paid marketing campaigns for their clients in channels such as Google Shopping. However, Upp. discovered that 40% of Google Shopping ad spend generates absolutely no revenue, therefore producing sub-optimal performance.

So, to set it apart within this competitive arena, Structure positioned Upp.’s intelligence as something no digital agency (or human being) can compete with due to it's operational granularity and scale capability. Upp. creates genuinely game-changing results in both revenue growth and profitability for the eCommerce retailers who use it.

Creative response

The creative approach mirrors Upp.’s focus on inventory to optimise ad performance. Upp. analyses hundreds of data points for every product it manages to drive preformance-led decisions.

Creative execution:
The dynamic plinths we created show how Upp. works across a retailer’s inventory where some products are elevated above others based on a range of data points, e.g., weather, product availability etc.

The plinths:
Throughout the creative, we used the plinths as a regular design mechanic, each one represents the data that underpins each product, e.g., operations, market trends, influencers etc.

Each plinth displays a single product and moves up and down, representing how the algorithm continually promotes certain products based on the data gathered.

Additionally, the plinths are used as a basis for the rest of the identity system: as abstract 3D patterns (to represent the data) and as abstract 2D patterns that add texture to the photography.

Let's talk about your growth ambitions.