We all have recurring data analyses that we run on our sites, campaigns and shops.
These analyses propel our marketing forward and give us ammo to make informed decisions.
As helpful as these analyses are, they’re also time consuming.
At CIFL, we have a simple solution: Recipes 🍳.
With Recipes, we break your data analysis process down into repeatable steps, and execute them on your behalf.
While you sleep, we do the day’s data wrangling. You receive results in Google Sheets or Data Studio and take action.
Every Recipe is baked with the same 3 elements:
Ultimately, your team interacts with data visualizations, but you’re also welcome to crack open the raw data in Google BigQuery.
In our opinion, having access to your own raw data (in BigQuery) is an absolute must. Many data analysis platforms provide you with end results, but not access to your raw data to run your own ad hoc analysis.
With Recipes, all of your data lives in your own BigQuery database, for you to use in any way you see fit.
To help contextualize what this might look like for your business, let’s break down one of our favorite Recipes: The Website Quality Audit.
The WQA starts with a site crawl, and pulls together key SEO metrics for each page. It allows you to make decisions about the “quality” of each page on a site from an SEO perspective, and assign next steps for each page to improve that quality.
Here’s how the Recipe comes together…
The WQA pulls together landing page + keyword-level data from:
All data sources with constant data updates (Google Analytics + Google Search Console) are refreshed each night.
Slower-moving datasets (Deepcrawl, Majestic and SEMrush) are refreshed monthly.
After pushing all raw data to BigQuery, we run a set of SQL models (written in DBT) to output your page-level actions.
First, the WQA joins together URL-level data from all sources listed above, to form a cohesive picture of your site.
Then, the Recipe assigns page-level actions based on a set of SEO best practice rules. The current ‘next steps’ list is:
Using Deepcrawl data, the WQA also assigns a ‘page type’ (product, category, blog post / resource, lead generation, location) to each URL, so you can filter these actions based on a section of your site.
The Website Quality Audit is essentially a task list generator for your SEO campaigns.
Because of that, the primary visualization is a Google Sheets template, that your team can use to feed your campaign planning process and a Google Data Studio report to track overall site health.
Want to see more examples of Recipes? Click here to check them out.
We make a few promises about Recipes maintained by CIFL:
These are the rules we live by, and from our experience they’ll serve you well too.
Recipes can be set up for an unlimited number of your sites – a typical agency runs Recipes for anywhere from 20 to 70 client sites each night.
Recipes are configured site-by-site – to set up a new site, you first specify (via a form):
For the initial setup, data is backfilled and reports created within 2 business days.
Following that, data flows into BigQuery each night, and reports are automatically refreshed when you sit down for your morning coffee.
To easily access your list sites + reports, we share a master Tracking Plan Sheet with your team (read more about our Data Pipelines here).
A typical Recipe build runs $5,000 for initial setup, and most teams will set up one or more recipes. Support + coaching is available after setup if your team needs technical help down the line.
This is not cheap, but it’s also much cheaper than your analyst’s time.
Obviously that’s back-of-the-envelope math, but you get the picture – your team’s time is very valuable, and Recipes promises your team that time back.
Book a time here to see if BigQuery Recipes are right for your team.
Get off the ground quickly, with customizable data pipeline Recipes for BigQuery.GET COOKING