Confidently Make Category Ranking Changes With A/B Testing Functionality

Opportunity

A/B test different category ranking changes and measure performances of up to three variants.

Example
  • Set up a search ranking rule that boosts certain colors based on what is “in season”. For example, in the fall, test boosting products with green or orange and get the data that will provide you the most lift.
Value

Take a data-driven approach to confidently make changes on your site with a streamlined A/B testing workflow.

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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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