Generative AI such as Google’s new Virtual Try-On feature, is just one of a number of Advanced AI and machine learning technologies that are transforming eCommerce.
It’s easy to see how this feature benefits customers – getting a better sense of what clothing will actually look like on our bodies has consumers everywhere cheering. Finally, the online retail experience becomes closer to in-store, all from the comfort of home.
However, the gain for online retailers, although less apparent, is enormous. By providing a more personalised experience, you improve customer engagement and satisfaction. This, in turn, leads to increased sales, reduced return rates, and stronger customer loyalty. Additionally, retailers can gather valuable customer preferences and behaviour data, enabling them to optimise their product offerings and marketing strategies.
Our AI and automation in retail content series is exploring cutting-edge retail technology and its potential impact on retail performance.
First up, it’s Google’s Virtual Try-On, and how this technology could help tackle one of retail’s most significant challenges: returns.
The rising rate of returns in eCommerce
Retailers have been trying to reduce the cost of returns for years – a problem that’s only getting worse.
Every purchase online is twice as likely to be returned as those items bought in-store. Drapers estimate that return rates rose a further 1% from August to October 2021 compared to 2019. This represents an estimated 90 million more returns in 2021 compared to 2019 – and is predicted to increase.
There’s an ever-growing pool of alternatives for customers to turn to when they’re unsatisfied with a product. So retailers are turning to tech to improve customer satisfaction and reduce the headache of returns.
Technology innovations are significantly able to combat this issue. Here’s how Google’s new Virtual Try-On feature is helping PPC managers reduce returns as part of their Google Shopping strategy 🎯
How Google’s Virtual Try-On will reduce returns
The Virtual Try-On allows shoppers to see what an item of clothing would look like on a body type and skin colour closer to their own – rather than the image the brand has uploaded for its ad.
This will reduce returns by minimising the need for ‘bracketing’ – where consumers buy multiple sizes or colour variations of an item so they can try on at home.
Over 60% of online shoppers do this because they’re unable to try the item on in-store. Google’s Virtual Try-On will go some way to help reduce bracketing but it still leaves the challenge of size variations – yet to be addressed via AI.
Impact on PPC Managers
As new tech is launched into the world of eCommerce – whether it be from Google, Amazon, Meta or others – it’s the PPC Managers who adopt them quickly that gain the competitive edge.
However, if you’re not yet automating the basics of Google Shopping campaign management, and are still stuck spending hours trying to understand why Performance Max performed better last week compared to this week, it’s almost impossible to find the time to capitalise on new features like Google’s Virtual Try-On.
And the impact can be quite scary.
When we looked at the data from a high-end fashion retailer based in the US we uncovered that they recorded 9 days of negative net sales due to returns, with a return rate of 54%, over that past month.
A staggering 61.2% of total sales were negative net sales and a handful of product lines were responsible for this. By helping the retailer understand what was happening, we could redirect ad spend away from high-return rate products.
Reducing the rate of returns, and leaning on new tools like Google’s Virtual Try-On and intelligent ad automation tools like Upp.AI, is absolutely critical for online retailers to improve their true ROAS and ensure profitability for the business.
Automate the basics, gain an early lead
As with any machine learning technology, so much of what makes it successful is the data you feed it.
If your Performance Max campaigns are only learning from the data they’re getting from Google’s own tools and not your own business data (stock, sales, return rates etc.), how do you know it’s putting spend in the right places? And how can you change that?
These are big questions that are increasingly difficult to answer, especially with Performance Max – it only truly works if you have the right feedback loop with real-time, accurate data.
Luckily, there’s technology that asks and answers these questions every second of every day, and moves your products across campaigns with different bidding strategies without you having to lift a finger.
Upp.AI puts the right product, in the right place, at the right time – within your ROAS, margin or budget targets.
With Upp.AI optimising your Google Shopping campaigns in real-time, you can now focus on making sure that your ads are as amazing as they can be – think stunning graphics, hyper-accurate tags and descriptions. With you lifted out of the endless task of optimisation and campaign management you will have the space for more testing, learning and trialling new features like Google’s Virtual Try-On when it launches (UK launch yet to be announced).
Here’s what James, our Lead PPC Strategist has been saying to retailers:
“[Google’s Virtual Try-On feature] is great for our clients because we already automate the other side of Ads; the campaign setup, campaign management, analysing the results and optimising accordingly.
Not only can AI read and understand data better, but all these hours saved are hours digital marketers can put into their feed/imagery to get the general quality up and gain an early lead”.
PPC teams at Charles Tyrwhitt, Roman and Nkuku are using Upp.AI to gain a competitive advantage and improve ROAS across large inventories. Get in touch today to uncover the missed revenue opportunities in your Google Shopping account and see how you can benefit.