HPCU Analysis – Next-Level Content Audit

When data-driven SEO meets content marketing

Author

Katharina Wohlfahrt

Content editor

Is data-driven SEO on its way out?

Maybe not, but data-driven SEO alone is no longer enough. The goal of a website should be to satisfy user needs – and that's what content marketing is all about. Being relevant, providing benefits, offering solutions to problems ... Even a flawlessly optimised website will be penalised sooner or later if there is no added value for users.

That’s why it’s essential that SEO and content marketing go hand in hand.
As Sistrix beautifully explains: Data-driven SEO is a rocket capable of flight. But every rocket needs fuel, and that fuel is good content.

HPCU = High Performance Content Unit

HPCU stands for

High
Performance
Content
Unit

The term describes content pages that frequently succeed in ranking in the top 10 of search results. At least 20 percent, to be precise. High-performance content units are thus recognised by Google as relevant more often than average. At the same time, they satisfy the users’ search intentions.

Other classifications are:

Mid Performance Content Unit (MPCU): at least 10 % in the top 10 of search results
Low Performance Content Unit (LPCU): significantly less than 10 % in the top 10 of search results

HPCU analysis: the process explained

The HPCU analysis makes it possible to categorise content into high-performing and low-performing pages. For this purpose, quantitative figures are combined with qualitative assessment. The process allows content experts to make well-founded statements regarding promising content optimisations.

High time to take a closer look at the individual steps, don’t you think?

1. Numbers as the foundation

Numbers don't lie – that’s why they form the reliable basis of an HPCU analysis. The analysis is carried out in an Excel spreadsheet, with the first, data-driven part containing the following information and KPIs:

list of all landing pages / content pages / data objects
sessions
aggregated sessions
aggregated session share
bounce rate in percent
pages per session
rankings in the top 10 results
rankings in the top 100 results
top 10 vs. top 100 results (in percent)
visibility

What follows right after is a classification into HPCUs, MPCUs and LPCUs. Up to this point, only objective data are taken into account.

2. Enriching data with content know-how

The second step is to evaluate the content – and to strike the right balance between quantitative and qualitative analysis. To do this, important content-strategic notes are added to the Excel spreadsheet providing answers to the following questions:

What is the objective of the page?
Is it a hub page?
Is the content relevant regarding SEO?
Does the content strengthen the brand?

This qualitative part of the HPCU analysis can of course be extended by customer-specific parameters if desired. For instance, if the HPCU analysis is also used for company-internal purposes.

At this point, a more detailed examination of the content is required. Content know-how is used to reveal potentials and weaknesses.

3. Interpretation = specific recommendations for action

The primary goal of the content analysis and the classification into performance levels is to increase relevance! For this purpose, we make specific recommendations for action – depending on the categorisation and in close coordination with our colleagues of the WPO team at elements. The following basic classification will give you a general idea:

high-performance content → optimise & scale
mid-performance content → analyse & improve
low-performance content → consolidate & integrate

So it's all about

getting rid of content that isn’t relevant,
boosting relevant content and
if necessary, creating completely new content (hero content).

Tip:

Have the courage to hit “delete”!

Meaningfulness and relevance vs. ego and politics: Content experts have to deal with this weighing of interests on a daily basis. The HPCU analysis serves as a valuable tool for argumentation in this regard. It helps to make the right decisions and to select the content that readers are actually looking for.

This way, sentences such as "We have always done it this way." or "This content is essential for us." will quickly lose their power. It’s important not to waver when it comes to implementing the recommendations for action. Only those who have the courage to delete content that does not work can truly benefit from an HPCU analysis.

But as is often the case, black-and-white thinking won’t get you anywhere either. Just because content is currently not working and is considered an LPCU does not mean that it is really not relevant for users. Perhaps the page lacks content or a user-friendly design. That’s exactly why it’s so important that the numbers are interpreted by experts.

HPCU analysis – a practical example

Remove non-relevant content to boost relevant content – that sounds nice in theory, but does it actually work? The example of travel website Urlaubsguru proves that it does. The outcome of a performance analysis: A total of 125,000 pages were removed from the index. Or to put it another way: Only four percent of the content remained in place – and these pages now rank as high-performance content units among the top 10 search results for the travel industry in Germany.

In a nutshell:

The advantages of an HPCU analysis

data-driven SEO analysis of previously defined pages
interpretation of data sets from a content standpoint
evaluation based on real data
solid foundation for the conceptualisation of the website navigation
recommendations for action regarding the content

For us, an HPCU analysis is the cream of the crop when it comes to content auditing and thus an important part of the strategy process. Curious about the results of an analysis of your website? Let's unlock the full potential of your content!

Tip: Our blog post on content KPIs gives you an overview of the most important figures that content editors should keep an eye on.