Blockspring vs Supermetrics for Sheets

blockspring vs supermetrics

David Krevitt

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

The humble spreadsheet is making a comeback.

Spreadsheet scripts have long been a business hacker’s favorite tool for automating work.

But now services like Blockspring and Supermetrics give you the same ability, without learning to code.

They both pull data from popular APIs (Google Analytics, Twitter, Slack, etc) directly into a Google or Excel spreadsheet.

This lets you build automated dashboards, research Twitter data, or program a Slackbot – all without writing code or bugging someone else to.

But where to begin?

Both Blockspring and Supermetrics come with a learning curve, and are useful for slightly different jobs – diving straight into the deep end can come at the risk of bellyflopping.

In this post, I’ll cover 5 ways we use Blockspring and Supermetrics to automate our marketing.

NOTE: if you’re struggling to build it yourself, you can hire me to build it for you, just hit me up.

Getting started

Both tools are spreadsheet add-ons, which means they come with a handy user interface in the sidebar of a Google or Excel sheet.


Connecting to services

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They each allow you to select a data source and set data parameters, before pressing a button to populate data into your sheet.

Blockspring does connect to a wider array of data sources (105 vs 23 for Supermetrics) – but for nuts and bolts work, they both connect to most of the same APIs (Google Analytics, Adwords, Twitter, etc).


Setting up reports

For a peek at how they pull data, let’s compare a Google Analytics report setup from Blockspring (left) vs Supermetrics (right):

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They both present the same rough options for configuring data – selecting columns (metrics & dimensions) to display in the report, dates for which to run the report, etc.


Supermetrics-only reporting features

But Supermetrics is tuned more specifically for digital marketing reporting, as it comes out of the box with the ability to:

  1. Select a dynamic date range for a report (last 7 days, last X months)
  2. Compare that date range to a previous period (for week-over-week, etc comparison)
  3. Group by date ranges (to view metrics summarized by month or year, useful if you need to backfill a lot of data)
  4. Visualize data in charts or heatmaps, vs the standard table view
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Blockspring and Google Charts can be customized to do most of the same things, but it takes more setup than Supermetrics’ couple clicks.  This is reflected in pricing – Supermetrics at $49/month for the Pro plan, vs $10/month for Blockspring.


Outputting data

Functionally, the data outputted by Google Analytics is essentially the same from each service:

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If you’re creating a KPI dashboard using the raw data outputted by Supermetrics and Blockspring, there are limited differences between the two services.

But, if you’re directly creating individual marketing reports to share with your team, Supermetrics chart and date summary features can come in handy.

Now that you’ve got the lay of the land, let’s dive into how I use both services in my day-to-day marketing and business operations work.

How I use them

Both Blockspring and Supermetrics can support sophisticated spreadsheet dashboards, pulling all of the data from services you use (Google Analytics, Mailchimp, Facebook, Twitter, etc) into reports for your team.

I use Blockspring more specifically for research, since it allows you to chain data sources together. It’s invaluable to my process for SEO research, lead sourcing, and social media analysis.

Let’s take a look at a few specific examples, including how you can replicate my approach.

1. Dashboards + reporting

This is where Supermetrics and Blockspring both shine.

If you’re making one-off reports, I’d recommend starting with Supermetrics, but since I specialize in KPI dashboards, I use both of them interchangeably.

The big win is being able to pull all of your data into one spreadsheet.  Use a number of different services, but you can hook them all together (screenshot of 4 blocks).  Exporting and saving CSVs was just too much of a hassle – at this point, I won’t use a service unless they let me access data from a spreadsheet.

I’ve used them to create five types of dashboards.


a. Company KPIs

Connect a database to run and visualize KPI queries for acquisition, activation, retention and revenue.

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b. Salesforce pipeline (Blockspring-only)

Connect Salesforce to view current and closed pipeline status – check out a sample one we built here.

example salesforce


c. Web analytics dashboard

Connect Google Analytics to view data in a spreadsheet.

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d. Content operations dashboard

Connect Mailchimp, Facebook, Twitter and GA to view content results alongside a content plan.

I pull live data into the same sheet I use to plan blog / social / newsletter posts + ads supporting them, in order to have a live view of how content is performing while planning new posts.

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Connect Adwords, Facebook and Twitter ads to view campaign data inline with where copy + creative are drafted. Check out a sample we built for a client here.

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A note on dashboards: part of the fun of using these services is, once you’ve aggregate your data in one Google Sheet, you can send it out to other places where it’s more useful to you (like Google Data Studio). 

2. SEO research

Both Blockspring and Supermetrics support both Moz and SEMRush for SEO research, but I prefer using Blockspring because of the ability to chain data together.

For example, if I’m researching link building opportunities for a group of keywords, I’ll combine a few blocks to come up with a list of potential targets for outreach:

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You can repeat this process infinitely until you have a good grasp on keywords + related backlink opportunities.

There’s a number of other SEO research that can be done with Moz + SEMRush – searching keyword difficulty, or domain authority for a link target – the possibilities are really endless.

3. Scraping, sourcing and lead scoring

I use Blockspring as my prototype scraper, before getting my team involved to build out a production version.

When you’re doing research into a source of potential leads for a business, often you come up with an empty net – building software before you know what you want built is a pain, and something I’m way too lazy to inflict on people I work with.

So I mock up a process in a spreadsheet before passing it along to a developer.  Let’s walk through one example: finding potential guest post opportunities.

One way to do this is to search for results that rank highly for a keyword, and check to see if they have author pages (indicating that they might accept guest posts).  This can be done with three chained search calls in Blockspring:

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Results that have an /author page are worthy of further investigation, to see if you could contribute (or reach out to existing authors there to score a link).

I’ve also used similar chained-Block sourcing approaches for YouTube and Twitter research – being able to pass data around like this saves a *ton* of time when prototyping a new sourcing process.

4. Team Communication

Blockspring integrates with a handful of downstream communication services, so that you can take action based on data in your sheet.

I mainly use two blocks, for sending daily analytics summaries:

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Supermetrics has a similar feature, which lets you share PDF report snapshots with your team over email.

5. Social media automation

I’m by no means a social media expert, but I do know it’s a great way to strengthen existing relationships with your customers (since they likely spend way more time on Twitter or Facebook more than they spend on your site).

Blockspring helps me understand who my customers are on social media, and quickly start engaging with them there.  I chain a few blocks together to make this happen:

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There’s a lot more Twitter automation that can be done with Blockspring – it allows you to publish tweets directly, or schedule social posts using Buffer.

In closing

Curious to get started automating your work with Blockspring or Supermetrics, but not sure where to jump in?

Check out some of our pre built data analysis “Recipes” + get help from other CIFL members. Can’t wait to see what you build!

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Get off the ground quickly, with customizable data pipeline Recipes for BigQuery.