How we increased our Web Google Shopping conversion by 65%
Spoiler: do not underestimate the power of highly relevant product alternatives.
“Why is our Google Shopping bounce rate much higher than our other acquisition channels?”
“What’s wrong with our product landing pages: is it the design or the featured info?”
If you’ve ever made these comments when trying to make sense of poor acquisition campaign results, we have some good news: you’re not alone. We did too.
As part of our company’s Traffic Collective, our mission is to make buying second-hand items desirable and drive more sustainable fashion habits by growing a community of buyers and sellers. To fulfill our purpose, Google Shopping has always been one of our key acquisition channels; so much so that we strongly increased our investment in recent years, making it our first source of new visitors today.
However, we soon started to notice that we were experiencing a low conversion on this channel, limiting our ability to scale it. We decided to launch a full user journey audit to optimize our Google Shopping campaign.
In this article, we’ve gathered some key learnings on how we tackled this landing page improvement opportunity. We’ll emphasize how we identified the problem and tested our new approach to validate the performance of the new Google Shopping campaign.
Initial user journey
Re-clarifying the user journey was the first step in our roadmap. The overall funnel was rather classic, but we noticed distinct behaviors when visitors landed on the product pages (PDPs). We split them into three categories: Happy Case, Successful Alternative, and Unsuccessful Alternative.
You can find the full description of the flow in the image below.
Understanding the user pain points
When buying fashion, users look for items matching specific criteria: size, color, expected condition, etc. In that context, it is unlikely that the first item they encounter will be the right one. They want to browse alternatives.
But we already covered that pattern thanks to how we designed our product pages… Or did we?
Well, here’s what we found. When landing on a product page (PDP), visitors could:
- Follow the breadcrumbs to go back to a catalog page, but the usage was very low.
- Start a new search/browsing session, but this also had limited adoption.
- Browse recommendations, but they were below the fold and not always available.
- Go back to Google Shopping, which was the main journey.
And there it was: the main source of our problems. Because we were not answering our users’ need to easily find product alternatives on Vestiaire Collective, our Google Shopping campaigns resulted in high bounce and low conversion rates.
From then on, we focused on one single goal: help our users find product alternatives by browsing our platform.
What we learned from the data
We further analyzed the behavior of our clients and discovered that users landing on the listing pages had a much lower bounce rate and a higher CVR than those landing on the product pages. So we were able to formulate the following hypothesis: if users can more easily find product alternatives on our catalog pages, they’ll spend more time discovering our platform and purchasing items.
Our solution design
We opted for a first new design showing a listing of items from the same brand and category as the clicked item in our campaign landing pages. We knew this improvement could bring value as these criteria are the most used in users’ searches.
The technical solution had a lot of flexibility as any catalog path could be associated with any product allowing us to test multiple combinations (adding/removing criteria).
Testing approach and results
When we started the tests, our website did not have proper A/B testing capabilities. So we had to find a workaround leveraging the ones of our product feed partner.
You can have a look at the full flow below.
Verdict? The results were excellent! We observed a substantial uplift in our Shopping traffic KPIs:
- -20% Bounce rate
- +24% Product page views per session
- +65% Conversion rate of New visitors to New buyers within seven days
Next up? Iterate and learn
We believed there were still improvements we could make to optimize the conversion rate. Because of limited A/B testing capabilities at the time, we had to make trade-offs to be able to move on while keeping a rational approach.
1. Adding a model criteria
Bags are one of the top-sold categories on our platform. Also, half of the bags sold on Vestiaire Collective have an identified model, which is a key purchasing criterion for the users. We hypothesized that filtering on the brand, category, and model could improve the relevancy of contents when that information was available.
Consequently, we launched another Productsup A/B test, measuring the ads’ ROI metric in Italy and the US.
Conclusion → Results were significantly better. We decided to roll out.
2. Showing the Welcome Offer on the Google Shopping landing page
New users can benefit from a special offer for their first order on the platform, which is a strong incentive to browse and convert. This discount was already being highlighted on the classic product page but not on our Shopping landing page. We launched a geo test and saw a positive trend in geographies where the Welcome Offer was displayed. This confirmed data from previous A/B tests indicating that showing the Welcome Offer positively impacts new users’ conversion in general.
Conclusion: We also chose to roll out this change.
Key takeaways
Here are the top three takeaways to remember from this Google Shopping campaigns revamp journey.
- Mobile-first doesn’t mean mobile only: Although Vestiaire Collective has a mobile-first strategy, our web platform represents 85% of our new traffic. Hence, optimizing it to help new users discover our products and keep growing our business is crucial.
- Do not underestimate the complexity of analyzing A/B test results: This was a challenge for this project, as we had to analyze the browsing behaviors on our website while the split was done in our tool to operate feeds.
- Showing the Welcome Offer from the beginning of the journey is a key incentive for users to purchase items.
