Confidently Make Category Ranking Changes With A/B Testing Functionality

Opportunity

Unlock the potential of A/B testing by experimenting with different category ranking changes and measuring the performance of up to three unique variants. This approach helps you identify which ranking strategies resonate most with your customers, allowing you to uncover patterns in what drives engagement and sales (e.g., product visibility, placement, or aesthetics). 

Using these insights, you can make data-backed decisions on product placements and promotions, creating a shopping experience that feels both intuitive and tailored for your audience. With a flexible and straightforward testing workflow, you’ll be able to refine your strategy with confidence and precision.

Example
  • Set up a search ranking rule that boosts certain colors based on what’s in season. For example, in the fall, test boosting products with green or orange to see which will provide you the most lift.
Value

Adopting a data-driven approach to A/B testing with Bloomreach Discovery gives you the clarity and confidence needed to make impactful site changes and better personalize every customer’s experience. A streamlined testing workflow not only simplifies the process but also ensures you can quickly identify what works best for your audience. 

By basing decisions on actual performance data, you reduce the risks of implementing untested ideas and avoid guesswork, leading to more effective results. Over time, this continuous feedback loop enables you to refine your strategies, improve site performance, and stay ahead of shifting customer behaviors. Ultimately, this approach builds a foundation for long-term growth by consistently delivering experiences that align with your audience’s needs and expectations.

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Video Transcript

As a merchandiser. My objective is to push
products with this season's trending colors.
But how do I know it's the right change to make
with bloomy discovery. I am able to confidently
make merchandizing decisions, knowing
I can A B test my changes
and easily see what performs best.
Let's take a look at our living room, furniture
query.
This is what I want of merchandise.
I wanna be able to boost this season's trending
colors
by coming into the dashboard. I can
select our site search and our ranking
rules.
I can add a search ranking rule
and type in my query
and I can come and I can do attribute based merchandizing
and all these attributes are pulling from the product
catalog.
Now, as we discussed, I wanted
to boost the season's trending colors
which are blue
and yellow
and I'm gonna give them a boost.
Now, you can see many more blue items
have popped up in the recall set. You'll start to see
some yellow items
and this gives you an idea of the power
of boosting these products for
the season.
Now, I may not be completely sure
that this is the right change to make. So I can
save this straight from my ranking rule.
Save this as a new test variant
including my living room, furniture merchandizing.
I can set up a new test,
select the allocation for test
bucket A and test bucket B. Now
test bucket B is going to be our Algo control
and it's very easy to come in and rename these
instances.
OK?
I can save this as a draft. I can preview
it and I can go in and activate this test.

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