Ever wondered how Upp's technology and retail decision intelligence for Google Shopping differs from Bidnamic?
If you have, you're not alone. So we thought it'd be a good idea to compare some of our similarities and differences.
For retailers new to Google Shopping, it's hard to know where to begin with the platform. And harder still for even the most experienced to improve their results — with plenty of tough questions to answer, from ‘what budget should I allocate?' and ‘what's a good ROAS target?' to ‘how do I cost-effectively acquire new customers?'.
More experienced retailers may also feel that they've lost a bit of control and transparency as a result of Google Shopping's upgrades over the last couple of years. These changes mean businesses may not know why ROAS achievement isn't consistent, or where it should be, and why CPC costs are increasing while budgets aren't being fully utilised.
Upp. and Bidnamic see these issues and agree that Google Shopping isn't as accessible or reliable as a source of profitable revenue as it could be. So using AI and machine learning, we both help clients automatically manage and optimise the performance of their Google Shopping accounts.
But, that's where the similarities end.
How Upp. is different to Bidnamic
Unlike Upp, Bidnamic isn't a fan of the recent upgrade moving Google Shopping campaigns to Performance Max. Instead, the Bidnamic team pitches its own solution as an alternative, working with retailers to stick with Standard Shopping.
Bidnamic reviews tell you that it's a machine learning solution that automates bidding strategies to save customers time and improve account performance. This effectively offers the simplicity of Performance Max for Google Shopping, but with the transparency of Standard Shopping.
Google isn't putting any budget or development into Standard Shopping, as it is determined to expand its offering with Performance Max instead, so Bidnamic developed their own solution.
In contrast, after auditing hundreds of different retailers' Google accounts, we are sure that Performance Max can outperform Standard Shopping, and we've chosen to work with Google's vision and ensure that we improve it where necessary to make Performance Max work for retailers.
To maximise Google Shopping performance, retailers need to make sure you're using all of the data within your commerce ecosystem — including orders, competitor performance, return volumes, promotions and price points, customer data, and all the other data that is unique to your business.
Upp.AI constantly analyses this against auction dynamics, and ensures that Google Shopping not only truly understands how to best advertise your products based on your targets, but also automatically applies the improvements and optimisations that will make the biggest difference long-term.
Only technology helps you keep up
Part of the challenge with Google Shopping is that its frequent changes can have a huge impact on the way you work. If you're expecting Google to just leave things as they are, then at some point you'll be left playing catch-up.
That's why Upp.'s AI neural network has been specifically developed to identify pattern opportunities within your data — automatically maximising performance across all of Google Shopping's different ways of working.
All while consistently providing full data transparency through a dashboard and performance reports, which emphasise the insights that matter most to your business.
Summary
So in summary, Bidnamic is an alternative to Google Shopping's Performance Max, whilst Upp. not only seamlessly integrates with it, it is also the only Google Shopping optimisation software to action its own recommendations, 24/7 against real-time auction dynamics and product data gained from your entire commerce ecosystem - so you don't have to lift a finger. All without losing control of your outcomes and whilst gaining transparency.
If you're curious how Upp.'s technologies and machine learning capabilities can maximise your Google performance automatically, then please get in touch today to find out more.