Risk management in SEO is a fascinating topic, IMO.
It’s the practice of analyzing the meaningful data you have like leads or revenue, with the goal of strengthening the weakest pages, so you can avoid that uncomfortable and bad situation of having a single page that drives in the vast majority of money.
Why is it important?
Relying only on few, or worse, one page to get your revenue is a very poor and risky strategy. Always consider that you’re not in the condition of determine what are going to be SERP results, and if your page goes down, you may lose a revenue source.
So, a very sensible way to behave is by applying the “Parthenon Strategy” by Jay Abraham to SEO.
Imagine your SEO efforts as a temple (Parthenon, BTW). How many columns are sustaining the roof and all the Phidias’ sculptures?
How many clusters are providing traffic (as always, consider traffic > leads/sales > money) to your website? How much of it are you leaving on the table right now?
Better maximize the impact you can extract from SEO, and from other channels as well.
BTW, learn how to track brand and non brand traffic and cluster your keywords in Looker Studio is fundamental. Always analyze what’s in front of you.
Anyway, let’s go ahead.
Here’s a video and a slideshare to present you the concept directly from Jay’s words.
What is the goal with this?
Your goal should be to picture:
- First, what clusters of pages are losing traction period over period. Once you get the cluster, look for the pages that are suffering. I usually note them in another file and leave the analysis of why they’re suffering for later.
- What pages bring in the highest number of conversions. As we’ve seen before, start with the clusters, and go deep to page level later.
The goal here is to uncover what pages are the ones where I absolutely can’t lose focus and traffic at the moment, and where I can spend some effort to get more financial impact, so I wouldn’t be that dependent from that bunch of strong pages anymore.
For what I know and I’ve seen, this is not something most of people pay attention to, but can give you a powerful and alternative lens to read through your data, and get precious and complementary ideas and information to enrich your analysis, reports and goals (yes OKR, I’m looking at you here).
This will allow you to force you to shift from reporting and analyzing traffic and visibility metrics only, to taking consideration of the metrics your company; executives or clients really cares about: the damn money.
BTW, this is inspired by a great piece of newsletter by Avinash Kaushik. Here’s the web version. If you’re not subscribed to Avinash’s newsletter, I strongly recommend you to do. You won’t be disappointed.
A dashboard for finding strong and week clusters and pages
Surprisingly, all you need to put together this awesome tool is free. You need to collect data from:
- Google Analytics: Sessions; Revenue or equivalent lead metric; page path; conversion rate. This may involve some other tools to have proper informations about revenue, and few chats with colleagues in BI or data science departments.
- Google Search Console: impressions; average position; query count; query and landing page.
- Looker studio: to put it all together.
Cluster the pages
First of all, cluster your pages the best way it can represent your website’s page templates.
An example can be:
- SEO Landing pages. All the pages that are meant to cover i-want-to-buy or transactional queries.
- News. I bet you’d guess: all the news content.
- Guides/informative evergreen content. All the content that try to attract i-want-to-know queries, or anyway any query we refer to as informational.
You can of course go as deep as you think it’s appropriate. An example may be:
- SEO Landing page
- Main page: usually the head page of the silo, like /man-shoes.
- Target pages: the one that refers to a specific target, like /mortgages-for-young-couples.
- Goal pages: where the goal is expressed, like: /scissors-for-gardening.
- Technology pages: it’s where you slice the specific category as /diesel-cars.
And so on. Of course that’s not all, it’s just to give you the idea and pass the concept. You see the clustering is getting more precise as long as you keep slicing.
You can do the same with informational content as well.
Once you’ve done, you can build your first table using:
- Clusters for rows. This is going to be a custom dimension in Looker Studio, based on a few ‘WHEN’ statements.
- Sessions; Share of traffic (percentage of the traffic on all the data); Conversions; Conversion Rate and Share of Conversions (same as before) for columns.
This table will highlight:
- The clusters responsible for the most of the conversions.
- Clusters that are performing poorly compared to their traffic.
- Clusters that tend to convert less.
This will help you answer to first important questions:
- Where should I drive my attention this week/sprints? Rank your clusters.
- What clusters are responsible for the larger part of conversions?
- Which ones are the b-series players?
- What clusters are the most risky?
Need to define what I mean for risky here: I mean where I absolutely can’t lose my performance because it would generate an important negative impact on revenue.
Let’s say, for example, you discover your Technology Pages are driving 50% of conversions of the ‘SEO landing page’ cluster; a cluster that drives 34% of all your organic conversions.
It’s a lot of money! We just discovered that a pretty small group of pages is driving almost 20% of the actual revenue.
Now figure this:
What would happen if you lose that 20% of gross?
Ask your CxO. He/she won’t be happy.
Go for the pages
You will see that, usually, there’s an entire collection of shadows in clusters.
Something is flat. Something is growing, something is losing.
Once you created the clusters table, go ahead and make another one using page paths as rows this time, and link the two tables. This will let you focus on a cluster’s pages with just a click.
Now take note of all the pages that are gaining traction (if it’s because of something you’ve done, hooray!!), and all the pages that are losing share of conversion. Again, still don’t start digging in what may have happened. Let’s just complete the picture for the moment.
This will help you answer few more questions like:
- What pages I’m most dependent on for my revenue?
- What pages should I strengthen to make my situation safer (be less dependent on strong pages)?
Again, imagine what can happen if you or someone else makes something wrong, and you get the page noindexed, blocked by robots.txt, or worse algorithmically filtered out from results.
Why is it happening?
Now it’s time to be chirurgical and find what’s moving exactly.
Build another table, this time based on GSC data, and use the Landing Page and Query dimensions as rows; and add a filter to the page to filter in only the page you want to analyze.
This let you see exactly (more or less) what pages are growing or losing on what semantic fields.
Mark down everything because this is pursuing you the material for the SERP check.
Final step: analyze the SERP and act consequently
Lastly, it’s time to analyze the SERP and understand what’s changed:
- A new competitor pops out on results?
- New SERP feature?
- Cannibalization? (This may require a double check in GSC or on your website to find new pages published).
And so on.
Once you have controlled and marked down everything, you can clearly define what to do to regain advantage on competitors.
Closing notes:
- Please take in consideration what’s the role of SEO and its weight in company revenue or company business model. Remember that depending on that, you may need more time to convince stakeholders and get the resources you need to make your strategy a real child.
