Introducing…The Website Quality Audit

the website quality audit

David Krevitt

Lover of laziness, connoisseur of lean-back capitalism. Potentially the #1 user of Google Sheets in the world.

Our agency uses 14 pieces of SEO software during any given workday.

It’s pretty crazy when you actually stop to think about it.

There’s a lot of productivity wasted in a disconnected ecosystem like this.

disconnected marketing ecosystem

When we set out to build our own SEO software, we didn’t want to compound this problem.

So instead of building a new tool, we decided to combine the ones you already use.

The Website Quality Audit Recipe

The Website Quality Audit (WQA) brings all of your SEO data together in Google BigQuery.

That means, as a baseline, you have all of your data – across traffic, keywords, backlinks and crawls – together in one data warehouse.  We believe this in itself is a huge win.

But on top of that, we’ve written a set of SQL models that runs daily to process your raw data into concrete potential actions your team can take.

We call this combination a “Recipe” – the basic formula that underpins your execution.

The Website Quality Audit is the first (of many) of our Recipes for BigQuery that are available for use right now.

A powerful, agile SEO audit

The WQA helps you make an informed SEO decision about what to do with every page on your website.

To setup, the recipes calls for data from 4 sources:

  1. Google Analytics: Organic traffic, leads/revenue, engagement metrics and more.
  2. Google Search Console: Keyword rankings, impressions and CTR.
  3. DeepCrawl: A full website crawl with all the associated data, refreshed monthly.
  4. Majestic: Backlink count, quality and velocity.

This data is refreshed daily to track actions / progress made (more on that later).

Based on this bedrock of data, the goal is to provide you with specific recommended actions to improve your site’s pages – across technical, on + off-page, and architectural buckets.

Let’s dive into how the recipe is put together, and what you can expect from the output (click to jump):

  1. The outputSheets workbook, Data Studio dashboard, and raw BigQuery tables
  2. Action recommendation logicAcross technical, on-page, off-page and site architecture
  3.  Starting your implementationRunning the Website Quality Audit on your sites

🤯 Pssstt…We can run this for you. Get started here.

If you prefer video, watch the entire walkthrough here:


The WQA output

Since all Recipes use Google BigQuery as their analytics warehouse, you have a lot of flexibility in where you ultimately make use of the output.

We provide two templates for you to make use of – but ultimately the data is yours, and you’re free to go ham on merging WQA data into your team’s process + building out more reporting.


The Data Studio dashboard

Since you have all this data in BigQuery, why not take advantage of Google Data Studio’s powerful visualization capabilities? In our opinion it’s the most straightforward (and free) data viz tool out there.

The WQA dashboard template offers you a sitewide pulse visualization, showing overall organic + keyword-level trends over time – with data refreshed each morning.

Think of it like a rolling monthly report of your Google Analytics + Search Console data, mashed up into one.

It also allows you to view your site’s trend in terms of action recommendations – ultimately showing your team’s progression on fixing technical or architectural issues.

Most importantly – since Data Studio’s interface is drag and drop, your team can go ahead and build your own reports on top of the WQA dataset, or just use the Data Studio Explore tool to browse results.

Browse the demo dashboard here.

data studio audit template


The Sheets workbook

Pulling data in directly from BigQuery, the workbook provides you with all the data you’d need to make page-level decisions. It’s quite similar to the original WQA built in Sheets, that you may know and love.

Building on the original, it also splits recommended ‘next steps’ for each site across technical, on-page, off-page and architectural action buckets.

The data in the Workbook refreshes after each month-end.

Check out the demo workbook here.

website quality audit


The BigQuery Console

We cannot stress enough that your data belongs to you, and you only.

You have access, in the BigQuery console, to the raw data that feeds your Website Quality Audit, as well as all of the intermediate data models the WQA runs to deliver your results.

All tables + key columns are documented in the Recipe SOP, so you’ll never be lost in using it.

We also provide a BigQuery SQL getting started guide, so you can get your team off the ground in running your own analyses in SQL.



The “action recommendation engine”

At the core of the Website Quality Audit is an action recommendation engine – since the recipe aggregates your data across a crawl, analytics + links, it’s able to pick out patterns in your site and recommend next steps.

Actions are bucketed into 3 categories, and are based on the original WQA standard operating procedure that you may know and love.

For detailed logic of how these actions are applied, check out the Website Quality Audit SOP doc here.


1. Technical Actions

Includes recommendations regarding robots.txt, sitemaps, canonicalization, crawl instructions, and index / noindex directives.

Technical actions break down into 5 sub-categories of action:


2. On + Off-page Actions

These actions are marketing + positioning related – they relate to how a page appears in search results, and how well those search results convert given the page’s content.

On + off-page actions break down into 5 sub-categories:


3. Architectural Actions

Specific recommendations around the internal linking structure, category organization and keyword cannibalization on your site.

Architectural actions break down into 3 sub-categories:


How to run your own WQA

You might be saying, “OK, that all sounds great, but how do I do this? And what’s it cost?”

Like all BigQuery Recipes from CIFL, the Website Quality Audit is a paid service that we execute on behalf of clients.

Recipes are recurring analyses, with data refreshing daily so you’re always on top of your metrics.

Cost depends on the size of your sites, as our amount of QC time + spend on crawl credits scales accordingly.

Ready to Dive In?

Book a time here to get started running WQAs in BigQuery.

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