[BrightonSEO 2022] Unlocking the Hidden Potential of Product Listing Pages

@areej_abuali #BrightonSEO
Unlocking the hidden
potential of product
listing pages

In BrightonSEO 2019, I said:
“Technical problems are People problems”

In BrightonSEO 2021, I said:
“As SEOs, it’s fundamental that we don’t
work in silos”

This year, I’m going to talk about a
*very* speciﬁc approach to
delivering value

But a story ﬁrst, to set the scene!

During the pandemic, I started an
in-house Head of SEO role for an
e-commerce company

I applied because the SEO role
sat in the Tech team

I’ll ﬁnally be in the driver’s seat and
sit in the team that has the power to
implement my recommendations

I come from the world of large
aggregator websites, where I dealt
with tech debt on 10M+ pages

But this e-commerce website was
FRESH, it was only a few years old

& it was one of the
cleanest I’d ever seen…

My ﬁrst thought was:

My ﬁrst thought was:
“Oh no, where’s the tech debt?”

Where are the tech legacy issues?

The crawl budget issues?

The crawl budget issues?
The indexability challenges?

Redirect chains…
Javascript rendering issues…
Broken internal links…

Where are my usual suspects?

The usual suspects are Tech SEO
issues that we’re used to ﬁnding

The usual suspects are Tech SEO
issues that we’re used to ﬁnding
…that make us feel like
we know what we’re doing

If the usual suspects are missing,
then…
What do we recommend?

“
Is there anything scarier than a
Tech SEO human
not ﬁnding
Tech SEO issues
on the website they’re working on?

The thing is, of course the website
had some issues, but they weren’t
big enough to make an impact

As SEOs, we love talking about
identifying quick wins

Or that term everyone hates
but still insists on using:
low-hanging fruit

But we never talk about what we
should do if there are none…

At this point, I was thinking:
“How do I prove my worth?”

So, I decided to spend some time
on where I’m most comfortable…

The Data
AKA: My comfort zone
1

The ﬁrst thing I did was dissect the
website and split it into templates

Category Pages (CPs)

Product Listing Pages (PLPs)

Product Detail Pages (PDPs)

Other

◉ Category pages (CPs)
◉ Product listing pages (PLPs)
◉ Product detail pages (PDPs)
◉ Other (Homepage, blog, etc…)
Core templates

I needed to ﬁgure out which
templates provided the most value

How do we deﬁne value?

How do we does the business
deﬁne value?

What’s the high level KPI that we’re
being measured against?

No, it isn’t visibility, rankings
or even sessions…

Organic Revenue

So let’s see which one of our templates
drives the most organic revenue

This is ﬁctional data

This is ﬁctional data
Organic Revenue
Product Listing Pages (PLPs) 60%
Category Pages (CPs) 20%
Product Detail Pages (PDPs) 10%
Other 10%

If PLPs are driving 60% of our
revenue, then let’s focus our effort
and energy in optimising them

As SEOs, we tend to focus our
recommendations on site-wide issues

But the more we dice and slice our
data, the more informed decisions
we can make

There’s no reason to put forward
recommendations that would impact
such a small portion of our revenue

Instead, we can focus our efforts
on *the* template that drives
the highest revenue

All websites have that
ONE template
that makes the most difference

In our example’s case, it’s
product listing pages (PLPs)

“
Deﬁne your one template that’s
worth optimising

Okay, let’s keep going!

The Discovery
AKA: My brainstorming
2

We know we want to focus on our
product listing pages, but what
should we do about them?

A few examples of PLPs

It’s important to break a template
down into its building blocks

There are our consistent site-wide
building blocks such as
navigation & footer

But there are also building blocks
that are unique to each template

Product Name

Product Name
Product Description

Product Name
Breadcrumbs
Product Description

Product Name
Breadcrumbs
Relevant Links
Product Description

Product Name
Breadcrumbs
Relevant Links
Filters
Product Description

I’m trying to deﬁne our template’s
building blocks

PLP building blocks
Content
Internal
Linking
Tech
Product name Breadcrumbs Filters
Product
description
Relevant Links

Let’s dive in

PLP building blocks
Content Tech
Internal
Linking
Product name Filters Breadcrumbs
Product
description
Sort Relevant links

Content

◉ Heading markup
Content

◉ Heading markup
◉ Description optimisation
Content

◉ Heading markup
◉ Mobile parity
Content

◉ Heading markup
◉ Mobile parity
◉ Hidden content
Content

◉ Heading markup
◉ Mobile parity
◉ Hidden content
◉ Thin content
Content

PLP building blocks
Content
Internal
Linking
Tech
Product
description
Relevant Links Sort

Internal linking

◉ Breadcrumbs
Internal linking

◉ Breadcrumbs
◉ Relevant Links
Internal linking

◉ Content block
Internal linking

Filters can make or break an
e-commerce website

Websites tend to have ﬁlters set up
in one of two ways…

They either attempt to…

◉ Index everything to capture as
much ranking opportunity as
possible

possible
◉ Noindex a huge chunk to avoid
suffering from index bloat

If we attempt to index everything…

◉ Google might not crawl all our pages

◉ Google might not index all our pages

◉ Our valuable pages might not be
crawled and/or indexed

◉ Our valuable pages might not be
crawled and/or indexed
◉ Our valuable pages might not rank

If we noindex a huge chunk, we’d
miss out on their ranking potential

possible
◉ Noindex a huge chunk to avoid
suffering from index bloat
So, neither option works…

So, how and where, do we

Where’s the opportunity?

When I say opportunity, I don’t mean
search demand

Yes, ‘dress’ has 800x the search volume,
but ‘maxi long sleeve dress’ is where
users are more likely to convert

Opportunity should be measured
based on conversion, not
*just* search demand

Which ﬁlters will more likely lead to
users converting?

It’s okay if we don’t know the
answer ourselves

Speak to our
→ customer team

Speak to our
customer team
→ CRO team

Speak to our
customer team
CRO team
→ data team

Speak to our
customer team
CRO team
data team
→ marketing team

Sift through our data to understand:

User ﬁlter
interaction

User ﬁlter
interaction
Most/least
clicked ﬁlters

User ﬁlter
interaction
Most/least
clicked ﬁlters
Internally
searched terms

User filter
interaction
Most/least
clicked filters
Internally
searched terms
High converting
filters

And yes, of course we can still look
at search volume data

But, please, we should not base
our entire strategy around it

It is only one metric out of many

You see, this is where as SEOs we
tend to go wrong

We only look at data that we care
about, without considering metrics
that other teams care about

We only look at data that we care
about are measured on, without
considering metrics that other
teams care about are measured on

“
Align yourself with metrics that
other teams are measured on, and
you're more likely to get their
attention and help

The Implementation
AKA: The part that actually matters
3

Let’s go back here…

What rules should we apply for the
ﬁlters that we want to surface?

For 1 *chosen* ﬁlter:

This should only apply when
choosing one ﬁlter, not a
combination of more than one

For *more than 1* ﬁlter:

The same rule should be applied
when choosing a ﬁlter that we
do not want to surface
(even if just one)

For an *unchosen* ﬁlter:

Let’s summarise our logic in
a ﬂow chart

Automation is key

As long as we brief in the exact
rules that need to be applied,
the implementation can and should
be automated

But before we make any changes…

We need to set a benchmark so that
we can measure the change

Setting a benchmark

◉ Number of indexed pages
Setting a benchmark

◉ Ranking of ﬁlter keywords
Setting a benchmark

◉ Organic trafﬁc of PLPs
Setting a benchmark

◉ Organic trafﬁc of PLPs
◉ Organic revenue of PLPs
Setting a benchmark

So, what’s next?

Getting it implemented

This is usually the part where I tell
you all about how I spent a full year
ﬁghting for dev resource

Plot Twist

It was fully done in 2 sprints only

*pauses for applause*

Welcome to the joy of
SEO sitting in the Tech team!

And here’s a few things I did
to be on the safe side

Playing things safe

◉ Test everything in a staging
environment
Playing things safe

environment
◉ Avoid a site-wide push,
instead break into iterations
Playing things safe

environment
◉ Avoid a site-wide push,
instead break into iterations
◉ Have a roll-back plan in place
Playing things safe

But I’m going to be honest with you

I wasn’t sure if I should keep the
next few slides in, but here goes…

I over thought every single aspect
about that ﬁlters recommendation
before writing it in a ticket

Coming from the world of
aggregator websites, I’m used to
deindexing pages

This time round, I was recommending
surfacing new ﬁlter categories

This would result in thousands of
new indexed pages

The idea terriﬁed me.

A few thoughts that went through
my head…

What if something went wrong?

What if my recommendation was
wrong?

What if we ended up losing
visibility, trafﬁc, revenue…?

Here’s what *really* scared me…

There’s a difference between
writing a ticket knowing it won’t be
picked up for a while…

& writing a ticket knowing it’s going
in the next sprint

There’s something both exciting &
terrifying about the thought of:

There’s something both exciting &
terrifying about the thought of:
“Woah, they’re actually going to
implement this.”

Does thinking and feeling that
make me a bad SEO?

I hope that by being honest with you,
it helps more of us open up about
these internal feelings we have

The Results
AKA: What *really* happened
4

Okay, let’s start with the good news!

The roll-out was successful

Everything functioned as expected

Nothing broke

The not so good news?

Nothing happened.

No impact.

I have no shiny upward graph
to show off

But, why?

Remember this?
Content
Internal
Linking
Tech
Product
description
Relevant Links

I was so ﬁxated on this…
Content
Internal
Linking
Tech
Product
description
Relevant Links

That I forgot everything else
Content
Internal
Linking
Tech
Product
description
Relevant Links

My recommendation was spot-on
but it wasn’t enough to have an
impact on its own

I’m used to working on 10M+ page
websites where tech changes can
have a massive impact

This isn’t necessarily the case with a
relatively small tech debt-free website

In my discovery, I plotted out
everything that needed to be done

But I focused on what I had the
most control on purely based on
where I sat

Just because I now sit in the Tech
team, it doesn’t mean I have control
over the full process

The other parts required engaging
with lots of teams outside Tech…

I should’ve made these teams a part
of my strategy from the beginning

I’ve spent a lot of time in the last
few years preaching the importance
of prioritisation with tech teams

https://www.areejabuali.com/blog/getting-tech-seo-implemented

Why didn’t I do the same with
other teams?

I thought because I now sit in the
Tech team, I’ll have it all ﬁgured out

You’re never in the perfect place

The grass isn’t always greener

SEO is very cross-functional and no
one has properly ﬁgured out where
it should sit yet

We need to have these honest
conversations of what’s working
and what’s not working

As SEOs, we need to ﬁnd a way to
work well across all teams

And share these learnings together
as an industry

One Final Thought

This year, I wanted to talk about
how important it is to dive deep into
that *one* opportunity that will help
us deliver value

But to ensure that we do it
cross-functionally

Our job isn’t just about knowing SEO…

Our job isn’t just about knowing SEO…
It’s about being effective

areejabuali.com
Thank YOU!

[BrightonSEO 2022] Unlocking the Hidden Potential of Product Listing Pages

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