Do you ever wonder what other brands are doing, so you can sanity check or validate what you’re doing?
Everyone does. It’s natural.
Here we walk through real use cases of how brands are adopting predictive personalization.
What is it?
Predictive personalization is the practice of using machine learning to predict the affinity and intent of every person who interacts with your brand…
…and then deliver precisely tailored content, products, and messages to each individual. Automatically.
It’s a modern marketing technique for conversion rate optimization.
Below we’ll show you 4 examples of eCommerce brands out there that are taking advantage of this toolset.
What are their goals?
How do different eCommerce verticals personalize individual shopper experiences at scale?
Before diving into how, why are brands going down that path?
Let’s confirm what goals these businesses are after:
- building your business through increased sales & revenue, and
- supporting that by giving your customers relevant experiences.
Relevance is the center of good digital shopping experiences.
Which is critical for generating the responses, engagement, and conversions we’re ultimately after.
The core metrics that eCommerce companies, thus, focus on are:
- Sales & Revenue
- Conversion Rate
- Click-through Rate
- Average Order Value
- Return on Ad Spend
Predictive personalization supports these metrics.
Now let’s put this into context with 4 real use cases.
Consumer electronics retailer Gemini Sound is focused heavily on conversion rate optimization. Their VP of Product & Marketing, David, owns the CRO initiatives personally.
He explains that his team uses a combination of tactics to do CRO:
“Designing site elements in a variety of different ways. Redoing layouts across pages. Changing copy. Working on SEO a ton. Building out additional marketing flows. Working to bring customers back: via email or SMS.
Some things work and some don’t work. We’ve just continued trying.”
Gemini deployed predictive personalization widgets on their site and within hours the click-through and conversion rates were leaping up.
What was actually going on?
To drive conversions, they used predictive personalization to do 1:1 product recommendations in key areas across the customer journey.
Their VP gave me an overview:
“Jarvis introduced personalized widgets across our Shopify store to show users not what we wanted them to see, but what they wanted to see. Each unique person sees something unique to them, based on Jarvis’s predictions.
This in turn led to more clicks, more people staying on the site longer, more conversions, and it affected a variety of other KPIs that were all getting better and better.”
The relative difference was jarring:
- Click-through Rate: 101% higher
- Visitor Conversion Rate: 73% increase
- Average Order Value: 28% growth
- Revenue Per Visitor: 128% jump
What is our takeaway?
This merchant used predictive personalization for conversion rate optimization: to create a one-to-one product list. They showed each shopper the most relevant possible set of sound equipment – given their stage of the buying process.
And it worked!
Another men’s apparel retailer, Bearbottom Clothing, built their store on Shopify to have an easily manageable site to edit and optimize.
Their CMO, Josh, runs their Shopify instance and focuses a lot of attention on ad-attribution and ROAS. He wanted a way to spend less time on the site, and more on high quality traffic.
After evaluating a large, multi-faceted personalization engine – which empowers marketers to build experiences, define rules, and set weighted product recommendations – they selected a hands-off predictive personalization engine to automate the process.
Why? To reduce workload for their lean team.
Cross-site deployment launched quickly. The test results made the Bearbottom team smile.
- Personalized recommendations had a 55% higher clickthrough rate.
- Overall conversion rate was 8% higher.
- The revenue per website visitor increased by 9%.
What is our takeaway?
This brand wanted to fully automate personalization to save their man-hours – which was limited and spread thin. They used predictive personalization to manage the legwork, which simultaneously drove higher performance. Josh’s team could spend time where they needed to.
Another winning scenario.
The eCommerce website for Twiddy & Company Vacation Rentals is a well oiled machine.
Their team has a relentless focus on providing their customers the best experience possible: from the online browsing and booking experience, through the time in each rental property.
Their goal was to provide a personalized customer experience at scale, predicting what properties their guests would want to book – then showing it to them front and center.
But to add complexity, they also have a secondary business objective: ensuring the best ROI for their real estate investors (the home owners that Twiddy manages properties for).
So Twiddy’s CEO & Director of Marketing, Ross & Shelley, deployed predictive personalization to:
- A) tailor website property recommendations to individual visitors, and
- B) launch tailored property “picks” through targeted email campaigns.
The engine predicted which customer would book next, which properties they would reserve, and how much they were likely to pay for the property.
Twiddy & Co saw the power of this predictive engine:
- 600% more direct booking flows initiated
- 250% improved website conversion rate and revenue per session
- $1M+ in new revenue generated per month
What is our takeaway?
This company has a unique use case. They must optimize property owner ROI and provide relevant, high quality booking options for customers.
Turns out with predictive personalization, they were able to tailor price-promotions and personalized recs to meet tandem goals.
Even complexity – with multi-faceted goals – can be addressed.
Truck-accessory brand Decked was experiencing a decline in the ROI of their paid traffic for months.
You too may be familiar with this pain.
Whether it was creating a higher AOV via larger cart size, plain-old converting more net new visitors, or generating more upsells with accessories: their Director of User Acquisition needed improve performance.
She and her team decided that creating more efficient use of their traffic could help boost ROI.
They ran a split-test to test personalization against this hypothesis.
As a result, her team was able to put in – effectively – no additional effort, and see automatic growth:
- Shoppers that engaged with the predictive personalization experience versus the control had a 13% increase in conversion rate.
- The new method generated 21% higher revenue per store session, compared with the control.
What is our takeaway?
This merchant needed better returns on their ad spend, by whatever means necessary. Predictive personalization enabled the team to convert more paid-traffic – and generate more revenue per site-visitor.
Ads are expensive. Shoppers are invaluable. Treat them appropriately!
These are just four examples.
Brands across industries are working to address nuanced challenges in their merchandising and conversion funnel.
Predictive personalization creates relevance at key customer touch points. It makes website and email campaigns more efficient. It turns more shoppers into sales.
And the best part: it’s automated. It’s time saving. It performs for you without pulling levers, selecting weights, and defining rules.
It’s a no-brainer to run a split test to see if this technique works. That’s what the four brands above did.
If you’d like to learn about how to launch a test, reach out to our team!