Strand Boosts Revenue by 16.5% With Anonymous Visitor Personalization.
UNIQUE INSIGHT: The common belief is that displaying multiple product recommendations on a single page is incompatible with a modern and elegant brand image. In reality, the opposite is true. When presented both visually and effectively, personalized product recommendations enhance brand image and drive a measurable lift in revenue.
STRAND’s story.
Founded in 1927 under the name Strandbags the company has been a consistent and reliable presence in the lives of thousands of Australians and New Zealanders.
As part of the brand’s evolution and new purpose to elevate all of life’s journeys – whether you’re planning a trip around the world, or simply popping out to the shops – the company was recently rebranded as STRAND.
With an online store and over 300 physical stores dotted across Australia and New Zealand, STRAND continues to bring and help you find the right accessory to complete your look and make a statement. Whether you are looking for fashion, functionality, or a mix of both.
Before
STRAND’s digital team were tasked with a significant business transformation goal: pairing their customers’ delightful in-store shopping experience with an equally effective online buying experience.
CHALLENGE
Key members of the team had prior experience with similar digital transformation projects, which gave them a clear understanding of the scope and risks of such an undertaking.
One of the transformations the STRAND team accomplished involved the successful integration of Amazon Personalize AI technology used to power personalization on Amazon’s marketplace. To begin the process, STRAND benchmarked Amazon Personalize against competing solutions and found that it significantly outperformed the next best alternative.
However, the team determined that the cost and implementation timeline for Amazon Personalize would be prohibitive for the STRAND project. There was additional concern about the ongoing expense of using and supporting the Amazon solution due to the extra overhead required for software code maintenance and upgrades, tech assistance, and systems engineering.
Looking for a simpler solution to take advantage of the Amazon Personalize technology, the STRAND project team reached out to the Amazon Personalize team.
After
Amazon Personalize pointed STRAND to Obviyo after learning that STRAND was in the process of re-platforming to a Shopify Plus ecommerce site.
As an Amazon Web Services (AWS) partner, Obviyo used Amazon Personalize to build Obviyo Recommend, a personalized product recommendation app for Shopify. The app fully automates all integration and deployment steps, eliminating the dependency on IT resources.
This breakthrough has made it possible for STRAND to add Amazon Personalize capabilities without the cost or complexity of traditional system integration.
PHASE I: SOLUTION LAUNCH
Obviyo Recommend provides an extensive library of Growth Bots, ready-to-go intelligent micro-applications that blend branded content with personalized product recommendations.
MindArc, the agency implementing STRAND’s re-platforming to Shopify Plus, was easily able to include Obviyo Recommend in the initial launch of STRAND’s new Australian and New Zealand online stores.
INITIAL RESULTS
Initial results have far exceeded all expectations:
- Conversion lift: + 33% (in less than a week after launch)
- Revenue impacted: +16.5% of total sales (within four weeks after launch)
These results can be attributed to the ability of Amazon Personalize to quickly learn and make highly personalized recommendations based on visitor actions and context in real time.
PHASE II: INNOVATIONS AND OPTIMIZATION
Given the proven effectiveness of the personalized product recommendations provided by Amazon Personalize, the strategy for revenue growth was to increase the percentage of visitors engaging with recommendations.
To achieve this goal, all STRAND’s team had to do was increase the number of Obviyo’s growth bots at every touch point with potential buyers.
STRAND’s rebranding placed emphasis on a modern and clean brand image, so the STRAND team were reluctant to rapidly increase the number of product recommendations blocks visible on their store pages.
Instead, they decided to leverage Obviyo’s testing and optimization platform to experiment with new personalization ideas.
The following are a few examples of such innovation experiments.
STEALTH RECOMMENDATIONS
Hypothesis: Presenting personalized product recommendations on the home page is ineffective and not aligned with a modern and elegant brand image. Instead, recommendations should be triggered once visitors engage with the lifestyle images marked by dotted lines on the screen captures below.
Desktop
Mobile
Experiment: Instead of immediately sending a visitor to a new page after clicking on a home page element, a created treatment triggers a pop-up with personalized recommendations in a collection chosen by STRAND. The visitor can close the popup and continue exploring the home page, click on a product of interest, or click on a ‘Show More’ link to explore the entire collection.
Desktop
Mobile
TEST RESULTS
| Device | Conversion Lift | Revenue Per Visit Lift |
| Desktop | +6.18% | -15.13% |
| Mobile | +13.44 | +8.63% |
Insights – Conversion Lift: With a conversion lift of +6.18% and +13.44% on desktop and mobile devices, respectively, Stealth Recommendations demonstrated that it is better to avoid sending visitors to the next web page until they first discover a product of interest.
Insights – Revenue Per visit: The RPV metric reflected a +8.63% lift for mobile shoppers, who represent the majority of site visitors. However, desktop device visitors reflected a -15.13% drop in RPV, indicating that Stealth Recommendations led to purchasing lower-priced items.
RECOMMENDATIONS WITH TABS
Hypothesis: Presenting multiple personalized product recommendations on product pages stacked on top of each other creates friction in the product discovery process. Instead, presenting recommendations as a multi-tab module is much more effective.
Treatments: Tab interface was stylized to incorporate the brand logo icon. Performance analytics was used to determine the order of presentation of product recommendations.
Desktop
Mobile
Insights: Personalized recommendations have performed much better than collection-specific recommendations, indicating that shoppers are not committed to a particular brand and are open to discovering something new.
Sitewide Results
Note: results below are for STRAND Australia (STRAND New Zealand’s results are very similar)
Time interval: 30 days
REVENUE IMPACTED
Revenue Impacted represents personalization-assisted sales where a visitor engaged with (clicked on) at least one recommended product.
CONVERSION LIFT
Conversion Lift is calculated based on the difference in conversion rate between the cohort of visitors who engaged with personalized recommendations and those who did not.
REVENUE PER VISIT DIFFERENCE
RPV Difference measures the relevancy of personalized recommendations by comparing results between two cohorts: visitors who engaged with recommendations and those who did not.
TIME ON SITE
Time On Site difference is calculated by comparing the time spent on the site by two cohorts: visitors who engaged with recommendations and those who did not.
UNIQUE INSIGHT
The common belief is that displaying multiple product recommendations on a single page is incompatible with a modern brand image.
In reality, the opposite is true.
When displayed effectively and on-brand, personalized product recommendations enhance the brand image and drive a measurable lift in revenue.
MERCHANT VALUE
With Obviyo’s Growth Bots and optimization capabilities, STRAND is dramatically improving the product discovery experience on their site.
As a result, they’re significantly increasing the revenue-per-visit (RPV) of visitors and overall net new revenues.
“The Obviyo revenue growth automation platform powered by Amazon Personalize is a super powerful combination. It enabled us to stage personalized buying experiences on our Australian and New Zealand sites, but more importantly, it empowered our teams to experiment and innovate how to best serve our customers while enhancing our brand image.”
– James Gill, Head of eCommerce Trade & Merchandising