Introducing intelligent return on ad spend

The entire team at Upp.® is very excited to be announcing the launch of iROAS™ (intelligent return on ad spend) at our event Why AI is the key to transforming Google Shopping for retailers and brands on 23rd May. It’s a game changer for us and for the retailers we work with, and we can’t wait to help more and more businesses streamline their marketing spend to put profit first. 

In many ways, we see iROAS™ as the next evolution in how retailers operate. Retailers have moved to eCommerce from brick-and-mortar stores successfully.  But now, with increased, always-on competition and rising advertising costs combined with changing consumer habits are making successful online retailing difficult.

More intelligent processes behind the scenes are what can help companies with these issues and for marketing that means getting more products in front of more people, without having to sink all of their profits back into marketing spend and in-house technical expertise. 

So, what’s iROAS™ all about? Well, it all starts with reframing what a traditional ROAS formula looks like. 

Updating the ROAS formula for today’s market

One of the topics we come back to time and again at Upp. is the problems that a traditional ROAS (return on ad spend) metric presents for many retailers. 

For example, a traditional ROAS formula does not go below zero. So if your ad spend is generating a negative return, you are blind to just how much into the red you are. 

The limitations extend into Google’s tools themselves, where teams traditionally group and set their ROAS using product-based Performance Max campaigns.

With a lack of intelligence around how well those products perform at a SKU-level, and with bid adjustments only being made at a broad campaign level, products generating a negative ROAS can eat into a retailer’s profit margins without their marketing teams even knowing.

Broadly speaking, most types of ROAS focus on revenue, rather than return – ignoring all the non-marketing costs associated with producing a product and getting it to consumers. 

That can be incredibly misleading. Because while your ROAS may be saying a particular product is delivering a reasonable amount of revenue compared to ad spend, the actual profit once all is said and done may not be anywhere near as positive. PROAS (profitable return on ad spend) formulas go a little way towards fixing this issue, but are really just a bandage over an existing problem rather than a complete solution. 

iROAS™ is that complete solution, using machine learning technology to be far more accurate and comprehensive than either traditional ROAS or makeshift PROAS methodologies. It’s something Upp. has been refining since its founding, with unique, patent-pending algorithms that our engineers have developed specifically to suit modern retailers – helping them make high-impact, automated marketing decisions in a matter of seconds. 

As a result, retailers get more oversight and better management of their entire inventories – reducing waste and increasing profit by emphasising the products with the biggest upsides. 

How iROAS™ delivers true return on ad spend

Intelligent return on ad spend revolves around the individual SKUs that make up a retailer’s inventory. Each of these tracking numbers are grouped into optimised Google Shopping campaigns with custom budgets that are based on the real-world data businesses already have access to, but lack the manpower to make use of without enormous expense. 

By using machine learning to analyse and sort though this data, iROAS™ establishes the exact break-even point for every single product, which in turn allows for far more accurate decision-making across not just marketing, but promotions and discounts too. All in service of increased profits by selling more stock and minimising wasted spend. 

It’s a continuous process too, with Upp.’s platform constantly checking, updating, and optimising campaigns as new data emerges. And with easy access to all of the insights and optimisations that Upp. is making, retailers also get a far better insight into their overall performance and contribution margins, which can support better decisions around non-marketing factors like pricing and production.

Get to the future of retail first

As businesses continue adapting to a retail marketplace that’s more competitive than ever before, next-generation tools have emerged to help them operate in a way that’s optimised to the sector’s challenges and streamlined to protect profits. 

Some retailers are one step ahead of the rest. These early adopters to AI and machine learning technology in retail are already enjoying a distinct competitive advantage. On average, retailers using Upp. are seeing a revenue increase of 27% within the first 90 days and an astonishing 52% within 12 months.

Upp. sits at the centre of these new tools, giving businesses confidence that the products working hardest for them are receiving an appropriate marketing push – every minute of every day. That means no more ‘set and forget’ campaigns that are too slow to pivot alongside changing customer behaviour, or frustrating reporting dashboards that throw up example after example of wasted spend.

All of that is built into iROAS™ – the heart of Upp.’s platform and the key to a competitive advantage for forward-thinking retailers who know the market is evolving, and are ready to evolve with it.

Join us on 23rd May to learn more about how AI and automation are improving Performance Max campaigns compared to every traditional method. Places are limited so register your interest early.