If you're an SEO expert, you may be working on a site that redirects the home page to a subdirectory (for example, to a country-specific version of the site). Or, use placeholder content that links to the main site's home page in a subdirectory.
In both cases, you may have a hard time convincing clients and colleagues to follow best practices. If so, this article is for you.
By providing data-driven examples, we demonstrate how to communicate with executives in a way that makes both technical and commercial sense.
To do this, we'll show you how to use Python to calculate the TIPR for all your site pages and provide a before-and-after comparison scenario that justifies the requested changes.
We will explain the following:
First of all, let's talk about why you need to merge your home page with your route.
Hosting placeholder pages and route redirects on routes
Some sites may host placeholder pages on the root URL, or worse, redirect the root to a subdirectory or page.
Many global brands, especially those in the fashion space, end up running multi-region sites where each regional store resides within a regional folder.
For example, if you go to Gucci, you would expect to find the following stores:
…and so on.
In the case of Gucci, there are not only regional folders, but also language folders, and this is all very logical.
I live in London, so the root folder https://www.gucci.com/ redirects me to the UK store.
A site search for “Gucci.com” (site:gucci.com) reveals that the root folder is indexed and provides a local store selection menu.
For many sites, the root folder is permanently redirected to the default or most popular regional store.
Why you need to integrate your home page with Root
Search engines use authority (a measure of how likely a page is to be discovered via a hyperlink) to determine a page's relative importance on the Web. Therefore, the more authoritative a page is, the higher it can rank within search results (SERPs).
This is where the power of search engine rankings lies, given that most sites get the most links to their root URL.
This is not ideal for your site architecture, as it means that all your product listing pages (PLPs) and product description pages (PDPs) are one hop further away from your home page.
This extra hop sounds small. However, as we will discuss here and quantify later, that is not the point.
Let's visualize a link graph for a site that has its home page set in the root folder.
Below is the actual site. The root URL has a page-level authority score (according to Ahrefs) of 40 PR and redirects to the main English store /en (21 PR) before linking to all PLPs and PDPs.
Naturally, all pages through the logo (in blue), instead of linking to the root URL, link to the local store homepage (for users) and other local homepages (shown in pink), Artificially inflating the value of a region. home page.
Note that site pages at site level 2 (linked directly from the home page) have a page-level rating of 19 PR, and other pages at site level 3 have a page-level rating of 18 PR.
The page is also removed one step from the root URL, so it no longer has all permissions.
Consider the deterioration in the sound quality of your music when you create a copy of a copy rather than a copy of the original music.
This is the experience your site is providing to search engines as they try to evaluate the relative importance of your site's content.
If your store is linked to the root URL, you don't want this because it creates a load of redirects throughout your site, making the distribution of authority even more wasteful.
The best practice approach is to merge the route with the home page to eliminate the man in the middle and ensure that every site page has one less hop to delete, as shown below.
After merging the home page and root URL, the home page now has a PR of 72, much closer to the site's Domain Authority 75 DR, and each page gets an additional 1 PR, increasing its chances of ranking. Ta.
Difficulty communicating benefits to non-SEO expert leaders
To a non-SEO expert audience, such as your marketing or IT colleagues, this will all sound quite academic and abstract, and probably not believable at all.
Even using the diagram above, you're obviously more interested in the traffic impact, if not the revenue impact.
They probably have no idea about Google's PageRank metric for measuring page authority, and they don't care unless you provide them with numbers.
Estimate PageRank lift using Python
Fortunately, you can harness the power of data science to perform complex calculations in Python and estimate new PR values following best practices for navigating to the root URL.
Let's take a look at the PageRank formula.
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
As explained in Anatomy of a Large-Scale Hypertext Web Search Engine by the founders of Google:
“Assume that page A has pages T1 through Tn that point to it (that is, are citations). The parameter d is a damping factor that can be set between 0 and 1. Typically we set d to 0.85. … Also, C(A) is defined as the number of links going out from page A.
Note that PageRank forms a probability distribution over web pages, so the PageRank of all web pages sums to 1.
The main gist of the formula is that the amount of PageRank of a URL (A) is primarily determined by the PageRank (PR Ti) of the pages (Ti) that link to it and the number of internal links on those pages C(Ti). That means it will be decided. .
The Python version of the PageRank formula can be found here.
As a thought experiment with the above formal knowledge, we would expect the following:
- The new home page benefits from all pages linking to a root URL (PR Ti) that is shared with other outbound internal links C(Ti).
- All site pages can benefit from a stronger parent URL (the new home page merged with the root URL).
With that in mind, all we need to do now is recalculate the site-wide impact of merging the /en folder with the site-wide root URL. This is done in several phases.
- Calculate TIPR for all site pages: As mentioned earlier in What Data Science Can Do for Site Architecture, site auditing software provides relative PageRank internally, but this can be done externally from the Internet using link intelligence tools such as Ahrefs. Must be combined with PageRank.
- Calculate. new TIPR On the new home page: That is, /en is merged or migrated with the root URL.
- Calculate. new TIPR All subsequent and remaining pages on the Website.
As shown in the image above, the new best practice configuration will display the new TIPR value for all pages.
Once you've completed the TIPR calculation steps, your next job is to translate the technical benefits of SEO into commercial impact and secure buy-in from your colleagues.
One of the outcome metrics we model is organic search traffic as a function of TIPR. If you have enough data points (say 10,000), this can be achieved using machine learning (ML).
The input will be the TIPR pre-recalculation dataset that feeds the TIPR columns and search clicks (possibly combined from Google Search Console).
The graph below visualizes the relationship between TIPR and number of clicks.
The blue line is an approximate model that shows how many more clicks a page gets as the unit's PageRank increases.
Mathematicians often say, “All models are wrong, but some are useful.” However, the science is very convincing when using ML models and using Python's detect() function to give some confidence in the predicted rate of increase. You can find an example here.
In the above case, you can see that up to 20 TIPR, the traffic increase per page is 0.35 visits per month, and above 20 TIPR, the number of visits is 0.75.
Using a data-driven approach makes you more persuasive to executives
This may not be a big deal. However, adding up the hundreds of thousands of indexable URLs predicted an additional 200,000 additional monthly traffic for one client.
This prediction gave the company the confidence and motivation to finally implement the repeated recommendation from numerous SEO consultants to root the homepage.
The difference is that it is quantified both technically and commercially.
By combining TIPR and PageRank formulas to simulate before and after scenarios for technical SEO recommendations (in this case, setting the root URL as the home page), SEO becomes data-driven and, more importantly, , becomes more persuasive. .
It will help you further implement SEO recommendations, not only on the technical side, but also on the commercial side, and hopefully help you further your career.
That aside, taking a data-driven approach can also help you sense-check best practice recommendations based on ideas you read online.
That was as true today as it was 20 years ago. The best SEO professionals are constantly testing ideas, rather than following dogma of best practices without question.
Other resources:
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