10 Top Open Source AI Platforms and Tools to Try Today

Open source AI platforms are helping humanity move toward a futuristic world faster than most anticipated.

OpenAI, Microsoft, and Google have had an outrageous month in the artificial intelligence (AI) space, and this field keeps accelerating.

What is open source AI?

Defining this term requires understanding a few others.

Open source is a software development term that means any programmer can jump in and work with it, the goal being to develop robust software in a shorter amount of time.

This is a great way to leverage the novel ideas of the best minds to fuel progress in technology. Think of open source as a group project where humanity benefits from A+ work.

Artificial Intelligence is a branch of computer science that develops programs and algorithms (step-by-step processes designed to solve a problem or answer a question) that help make various machines operate in more human-like ways.

There are several subfields of this science, including:

Natural language processing (NLP), which focuses on developing natural interactions between humans and computers. Specialized software helps machines process human language, create understandable words, and interact with humans through language.
Machine learning (ML), which prioritizes a machine’s ability to analyze information and use it to make recommendations or decisions based on the data sets it has provided.
Computer vision, which is all about creating machines that can understand and then interpret visual information.
Robotics that can physically perform tasks without human micromanagement, including interaction with humans.

Right now, companies verify we are human by having us choose photos from a set with one thing in common, such as cars or volcanoes. And if we were to see a car at the base of an active volcano, we can extrapolate that the car will be damaged. Machines are still developing these abilities.

Open source AI, then, can be defined as software engineers collaborating on various artificial intelligence projects that are open to the public to develop. The goal is to better integrate computing with humanity.

We need one last bonus keyword that helps us tie open source AI to marketing: Industry 4.0.

Industry 4.0 is the idea that advanced computing and AI have unlocked a new era in human productivity.

The first industrial revolution was about creating machines to do work via steam or water power.
The second industrial revolution was when we converted machines to electric power and embraced mass production. Products were built by human assembly lines, assisted by electric conveyor belts that brought the work to their hands.
The third industrial revolution was when we plugged computers into the machinery to boost efficiency and automation. Car factories now have machines programmed to quickly and precisely build cars without human assembly lines.
And now the fourth industrial revolution — dubbed Industry 4.0 — is about how the industry is changing now that humanity and computing are so closely interconnected. Business doesn’t just happen in boardrooms and on factory floors anymore. We carry it in our pockets.

We can sell and reinvest stocks from our kitchens at the touch of a button. Without touching anything, a voice-activated computer can order groceries, add appointments to our digital calendars, and tell us jokes as we work from home instead of commuting to an office.

It’s this new landscape, this new era in production via interconnected technologies, where open source AI for marketing comes into play.

How can marketers use AI?

AI offers a huge range of functionality to marketers who want to take the plunge, from small assists all the way up to running campaigns for you.

We’ll share some use cases to give you an idea of what’s out there.

Automated Social Posts

One of the smallest ways to leverage smart technology in marketing is to use a program that schedules and posts your pre-loaded social content.

You set the frequency (several times a day to once a month or more) and then load up all of your prepared content. It does the work for you on your own custom schedule.

Content Creation

This is an area where AI is booming. Marketers charged with creating written content have similar struggles across the industry. How do they keep coming up with ideas that will resonate with their audience? How can they produce content in less time to boost conversion?

Companies count on AI content to save the time it takes to create the body of such work, spend less on writers, and call on their experienced wordsmiths to then dial in on quality.

Personalized Emails and Data Capture

Most of us have experienced follow-up emails to the effect of, “Hey, you left an item in your cart!” or, “There’s an item on your wish list that just dropped in price!”

People cannot possibly write these billions of daily emails customized to each consumer’s shopping habits — but AI can.

Algorithms have been devised to pull user data, analyze how each customer interacts with a brand, and create personalized email content. Then, AI schedules and sends that content, all without any human interaction after it’s been set up.

Saying “Send a thank you note to Savannah” initiates an algorithm that pulls Savannah’s email address from your contact list, creates a thank you email, and splices Savannah’s name into it. The program can send it then or read the note to you, allowing you to make changes before sending.

Ad Targeting and Pay-Per-Click Campaigns

If you advertise on Google or Facebook, programs like AdWords give you deep insight and scalpel-minute details to help you gauge how your advertising campaigns are playing out. They also facilitate pay-per-click (PPC) bidding so you can efficiently allocate your ad budget.

AI can analyze who has been engaging with your ads, then redirect ad spend to groups that market research may not have anticipated. You may be delightfully surprised by how many leads you discover or conversions you gain.

Ethical Considerations Before Using Open Source AI

Nothing new comes easy. Even the highest level of technology development has important human elements that must be addressed sooner rather than later.

Biases

People write algorithms and datasets, and people have biases — whether they know the unique lenses through which they see the world or not. Those influences can and do change what a program does, especially if the AI’s output is designed to change based on human behavior in virtual spaces.

These problems become apparent when searching for bias-charged words. You’ll want to build programs that avoid stereotypes and false information.

So how can programming be less biased? This is one of the hottest topics in AI right now, and the solutions (and laws) are still being forged.

Incorrect or Incomplete Information 

Just because it’s on the internet and AI finds it doesn’t mean it’s true. And just because something’s popular doesn’t mean it’s right.

Likewise, just because you have true information doesn’t mean you have the whole picture, no matter how hard you push your search engine to find the truth.

10 Top Open Source AI Platforms and Tools

Now to the main event: We’ve compiled a list of open source AI tools to introduce you to some of the best options as you wade through this topic, decide if micro AI could help boost your ROIs, or if larger open source AI projects are what you need to meet your company’s goals.

1. TensorFlow

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TensorFlow is an entire support structure for programmers who want to help each other create something novel while reaping the benefits of other experts’ existing models.

TensorFlow is one of the most robust AI platforms and offers training videos to help jumpstart your success.

What we like: This platform supports several programming languages, including Swift, Python, and JavaScript — the most common programming language used on Earth.

Price: Free.

2. PyTorch

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PyTorch, like TensorFlow, is a one-stop shop for transforming ideas into functional applications. It’s an entire framework created to support various aspects of open source AI project development, including vast libraries and datasets to pull from.

This platform is easy to use for developers who already code with Python. Its object-oriented approach helps bundle up usable chunks of code that do just one job.

This known and reliable “object” can then be plugged into a more extensive sequence to do a more complicated job, helping programmers help each other.

Pro tip: Programmers fluent in Python flourish here, but it also has a C++ interface for those who don’t code with Python.

Price: Free.

3. Keras

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Billed as being designed for humans, Keras is an application programming interface (API) that allows you to quickly and easily share the front end of your deep learning models.

You can export your models from Keras and run them in browsers, iOS, and Android. Their Python libraries tend to focus on artificial neural networks.

Best for: Programmers who prefer a more streamlined user interface while working with the newest versions of TensorFlow, simplifying interaction with the software as it’s being built.

Price: Free.

4. OpenAI

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OpenAI is all over the news, and for good reason — it’s changing the game of natural language processing (NLP) AI programs. They offer a model called Codex that changes natural language into code in the programming language you specify.

What’s more, like other open source AI projects, you can access their models and customize the code yourself.

OpenAI is mastering what Alexa/Siri does and taking the next step in Industry 4.0. This AI can synthesize its own natural language answers from the information it finds instead of just pointing to a website and reading it. Incredible stuff, and you can work with it!

Price: Free $18 credit to experiment for three months, then prices are token-based and depend on what you use as you go.

5. OpenCV

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OpenCV is well-known for its open source AI platform for computer vision. If TensorFlow has an undergrad degree in general AI, OpenCV holds a master’s in AI vision.

And it works pretty much everywhere because its library was written in C, which it claims can be ported to everything from “PowerPC Macs to robotic dogs.” It includes a new C++ interface, and wrappers have been developed for Java, Python, and other languages to encourage cross-language development.

Best for: Developing AI specifically for computer vision applications.

Price: Free, including for commercial use.

6. H20.ai

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H2O.ai’s AI Cloud Platform copy claims that it is “the fastest, most accurate AI platform on the planet” and appears to be aware of ethical issues in AI.

They strive to democratize AI by making it available to anyone, empowering humanity to use it to impact the world positively.

A solid choice for: Companies that prioritize development speed and also plan to use AI to enhance their offerings, working toward streamlined AI management across the board.

Price: Free to develop open source software and to use their H20 Wave API.

7. Rasa

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Rasa is great for building conversational AI (chatbots) and deploying it via the cloud for free. It’s flexible and touted as “future proof” because it’s been designed so you can plug any NLP or ML model into Rasa to give you increasingly accurate results as technology improves with time.

Best for: Branded conversational AI for enterprises that comes with built-in integrations for social messaging like Slack and Facebook.

Price: Free. There are also paid pro options for enterprises.

8. Amazon Web Services (AWS)

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If you have code to run or want a familiar place to start building, you can do it for free on AWS/ The platform also stores the results/output of your programs.

In addition, AWS offers numerous value-added features for business marketing, such as customizing your code for their content delivery network and managing task coordination for your various cloud applications, all for free.

Best for: If you have a handle on coding but could use some support services adjacent to development — including business features to help you level up toward Industry 4.0.

Price: Costs vary. There are short-term offers, 12 months free, and always free options.

9. GitHub

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Regardless of your chosen platform, the GitHub platform keeps collaborative work orderly.

GitHub is the biggest name in programming cooperation. The platform helps organize projects when many hands touch the same code, keeping track of version histories, notes, and Wikis.

Best for: Individuals or teams that don’t know each other but want to work productively on a project.

Price: Basic $0, Team $44, Enterprise $231.

GitHub AI Projects: Instagram Spam Protection & Fake Product Review Identification

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We’re including these open source AI projects in development on GitHub because so much of marketing involves moderating your social networks once content is live.

These projects allow you to pull pre-existing datasets for training your programming models to do the work more thoroughly — better protecting your brand to keep those leads rolling in.

Pro tip: Google open-sourced their ALBERT model for you to emulate. The program excels at natural language processing and is agile with language-specific issues like interpreting meanings in context.

Price: Free

The Future Unfolding Around Us

Be sure to keep your eye on the developing topic of AI. It’s happening quickly all around us.

It’s sure to be a wild ride! The cutting edge of technology always is, and AI gets sharper, smarter, faster, more enmeshed by the day.

How Social Media Influenced Coachella

Welcome to HubSpot Marketing News! Tap in for campaign deep dives, the latest marketing industry news, and tried-and-true insights from HubSpot’s media team.

Coachella didn’t start off as the Met Gala for influencers.

The festival was first held in October 1999 and was intended to be an accessible event for alternative music fans. Held just three months after the infamous Woodstock ‘99, the first Coachella had an audience of just 25,000 people and failed to make a profit, costing organizers nearly $1 million.

After taking a year off, Coachella made its comeback in April 2001. While Coachella began picking up popularity in its first decade, the 2010s ushered in a distinctly new era for the festival and it became a profitable and style-defining event.

So, what changed?

In its first few years, Coachella featured predominantly alternative artists, with headliners like Beck and Rage Against the Machine. By the 2010s, mainstream artists including Jay-Z, Lady Gaga, and Beyonce started drawing bigger crowds.

What started as a single-day event evolved into a six-day festival spanning over consecutive weekends.  By 2016, there were over 99,000 attendees at Coachella each weekend — combined to be nearly 10x the attendance of the first event.

How Influencer Marketing Changed Coachella

The rise of social media also had a major impact on Coachella’s growth. Influencer culture and “festival fashion” became nearly synonymous with the event.

As content creators and celebrities began attending Coachella in droves, what they wore nearly overshadowed what was happening on stage. Brands, particularly brands that relied on influencer marketing, began leveraging Coachella as a pivotal part of their business strategies.

In 2015 and 2016 H&M partnered with Coachella organizers to launch #HMLovesCoachella, a clothing collection that captures the boho aesthetic the festival is known for. H&M also hosted a pop-up shop at the 2016 festival where attendees could purchase the clothes on-site.

Perhaps no company has used Coachella as an influencer marketing tool as heavily as the LA-based clothing company Revolve.

How Revolve Uses Influencer Marketing at Coachella to Drive Revenue

It’s reported that nearly 70% of the company’s sales come from influencers, and experiential marketing with content creators at events like Coachella is a core revenue driver.

Since 2015, Revolve has hosted Revolve Festival, an invite-only party for celebrities and influencers.

Over the years Revolve Festival has made headlines for partnering with celebrity brands like Kendall Jenner’s 818 Tequila and Hailey Bieber’s Rhode Beauty, and for last year’s transportation issues that left influencers comparing the party to 2017’s disastrous Fyre Festival.  

Despite the controversy, Revolve Festival, combined with content distributed by influencers dressed in Revolve’s clothes, has helped the brand generate an astounding five billion social and media impressions.

Between sponsors throwing money at the opportunity to have their brands seen at the event, and influencers turning their experiences into content for their followers, Coachella has gone from a modest music festival to a $1+ billion marketing machine.

Elsewhere in Marketing

The latest marketing news and strategy insights.

Instagram is now letting users put up to five links in their bio.

YouTube is ending its in-video shopping feature.

Twitter gives Twitter Blue subscribers the ability to monetize their popular tweets.

Google is reportedly working on an AI-powered search engine to compete with Bing and OpenAI.

AI in content marketing: the HubSpot blog recently surveyed a group of marketers to learn how they’re using AI in their processes.

The Ultimate Guide to Google Data Studio in 2020

Google Data Studio is now Google Looker Studio, and it’s making data reporting even more accessible, visual, and impactful than before. The new interface, features, and functionality have some serious advantages when it comes to visualizing competitive data insights.

In this guide, we’ll introduce some of the coolest, newest features of the platform to get you ramped up quickly. We’ll also walk you through the most notable changes between Google Data Studio and Google Looker Studio.

Pro Tip: Even with the major overhaul, Google Looker Studio is still entirely free and accessible to all (even if you don’t have any data of your own!)— that means you can follow along with this tutorial in real-time.

With Looker Studio, you can create custom dashboards, reports, and visualizations to gain insights into your business operations. The platform offers a wide range of data connectors and report templates, allowing you to interpret data from various sources.

1. Log into Looker Studio

To log in to Looker Studio, you’ll need a Google account — I recommend using the same one as your Analytics, Search Console, and/or Google Ads account.

After logging in, you’ll land on a page displaying your most recent Looker Studio reports.

2. Explore the Looker Studio Dashboard

If you’ve used Google Docs, Sheets, or Drive before, this dashboard should look pretty familiar. In the center, you have the option to start a blank report, start a tutorial, or see report templates. To the left, you’ll see a column that houses several tabs including Reports, Shared with me, Owned by me, Trash, and Templates. At the top, you’ll see three more tabs: Reports, Data sources and explorer.

Let’s go over each of these tabs in detail.

Reports

Here’s where you can access all of your reports (equivalent to a workbook in Tableau or Excel).

To create a report in Google Looker Studio:

Click the Create button.
Choose Report.
Add a data source.
Customize your report.

Once you’ve created your report, you can access it later in your dashboard. To soft through several reports, filter them by name, owner, or last opened date by using the dropdown filters.

Data Sources

Data sources list all the connections you’ve created between Looker Studio and your original data sources.

To create a data source in Google Looker Studio:

Click the Create button.
Choose Data source.
Enter in your company information, click Continue.
Set up email preferences.
Select a Google Connector.
Authorize the Google Connector using a Google Account.
Choose the account and property you want to view.
Click Create Report.

Pro Tip: If you’re using Google Analytics and/or Search Console (which I highly recommend), you’ll need to individually connect each view and property, respectively. So if you have three GA views for three different subdomains, you’ll need to set up three separate data sources.

Looker Studio currently supports 760+ data sources. Below are the most popular sources:

Explorer

Explorer is an experimental tool that lets you experiment or tweak a chart without modifying your report itself.

For instance, let’s say you’ve created a table in Looker Studio that shows the top landing pages by conversion rate. While looking at this table, you think, “Huh, I wonder what I’d find if I added average page load time.”

You don’t want to edit the chart in the report, so you export it into Explorer — where you can tweak it to your heart’s content. If you decide the new chart is valuable, it’s easy to export it back into the report.

Template Gallery

The template gallery is a collection of templates and examples you can use depending on your business needs.

For instance, if you run an ecommerce store, the ecommerce revenue template would be very useful.

Google Looker Studio Tutorial

Connect Data Sources to Google Looker Studio

Here’s a step-by-step guide on how to connect data sources to Google Looker Studio.

1. Create a data source.

Click “Create” and choose “Data source”.

2. Use Google Analytics.

The process is nearly identical for other sources.

If you want to follow along exactly with what I’m doing, connect the Google Analytics Demo Account for the Google Merchandise Store.

3. Authorize the connection and select an account.

Next, you’ll be prompted to authorize the connection. Once you’ve done that, you’ll need to select an account, property, and view.

You’ll be presented with something like the view below: a list of every field in your Analytics account (both the standard ones and the ones you’ve added).

Does this feel overwhelming? Yep, same here.

We could do a lot in this step — add new fields, duplicate existing ones, turn them off, change field values, etc. But, of course, we could also do all those things in the report itself, and it’s much easier there. So let’s do that.

Create a Report in Google Looker Studio

1. Click “Create Report” in the upper right.

Looker Studio will ask if you want to add a new data source to the report; yes, you do.

Here’s what you’ll see. It’s pretty bare, but not for long!

2. Click “Add a chart” in the toolbar.

It’s time to add your very first chart. The good news is that data Studio makes it easy to compare chart types with some handy illustrations.

3. Choose the first option under “Time series.”

For the purpose of this tutorial, we’ll start with a “Time series” chart. This chart type shows change over time.

Once it appears on your report, the right-hand pane will change. Here’s what you should see:

By default, the dimension is “Date”; you can change this to any of the time-based dimensions, including “Year,” “Hour,” etc.

I will stick with “Date” because the Demo Account doesn’t have a lot of historical data.

Looker Studio will automatically select a metric (i.e., what’s displayed on the Y-axis) for you. Feel free to change this; for instance, it defaulted to “Pageviews” for me, but I’d rather see “Revenue per user.”

4. Add another metric.

First, make sure you’ve selected the chart, so you see the pane:

You have two options for adding a metric (or dimension).

You can click the blue plus-sign icon — which will bring up a search box so you can find the field you want — or you can drag a field from the right into the metric section.

To delete a metric, simply hover over it with your mouse and click the white “x” that appears.

5. To add a table, choose the third option under “Add a chart.”

My chart defaults to Medium (for dimension) and Pageviews (for metric), so I change it to Product and Unique Purchases.

And I think this table’s formatting could use some work.

Change the “Rows per page” from 100 to 20 (much easier to read) and check the box for adding a Summary row.

6. Finally, click “Style” to go to the style tab.

Scroll down and select “Add border shadow.” This is one of my favorite ways to make a data visualization pop off the page.

7. To see the finished product, click “View” in the top corner.

This transitions you from Editor to Viewer mode.

Voila!

8. Click “Edit” to finish up and name the report.

Double-click the title (right now, it’s “Untitled Report”) to change it.

And with that, your first Google Looker Studio report is complete. Click that familiar icon above the Chart Editor and add some email addresses to share your report.

Okay, don’t share the report just yet—I’m about to reveal the secrets that’ll help you seriously upgrade it.

Beginner Google Looker Studio Tips

1. Use templates.

There’s no need to reinvent the wheel. If you’re not sure where to start with Looker Studio, I recommend browsing through their templates for inspiration.

Pay attention to the report’s creator. Many templates were built by the Looker Studio team; you can find them all in the “Marketing Templates” section. But there are also 45+ user submissions located in the “Community” section. A few of my favorite templates:

GA Behavior Overview: This dashboard pulls out the most relevant information from the Behavior section of Google Analytics
Paid Channels Mix Report: Use this template to understand how your ads are performing on Facebook, Twitter, LinkedIn, search, and more.
Website Technical Performance Indicators: Get a quick overview of how your site is performing in real-time, including JavaScript and 404 errors and page load times.

There are also a bunch of fun, non-marketing templates in the gallery (found in the “Featured” section), like F1: How Important Is the First Race? and Star Wars: Data from a galaxy far, far away. Definitely take a look if you’re curious to see the full potential of GSD unleashed.

2. Publish your report.

Want to show off your superior analytics and data visualization skills to the world? Submit your report to this gallery using this Google form.

Read over the full instructions at this link, but here’s what I’d keep in mind:

Don’t share sensitive information. I recommend creating a report with publicly accessible data, so there’s absolutely no chance you get in trouble for sharing data you don’t own. (Pro tip: recreate one of your existing company reports with dummy data from one of Google’s sample data sets!)
Make it awesome. The public reports are impressive, so don’t hold back with design, features, and so on.
Add context. Provide on-page explanations of what you’re measuring or monitoring with captions, instructions, maybe even a video of you walking through the report.

3. Connect to 760+ data sources.

As I mentioned, you can bring data from Google-owned sources into Looker Studio, including Search Console, Google Ads, YouTube, and Campaign Manager.

But that’s just the tip of the iceberg. There are also more than 120 partner connectors — essentially, third-party bridges between Looker Studio and platforms like Adobe Analytics, AdRoll, Asana, Amazon Ads, and AdStage (and that’s just the As).

Check out all the options here.

4. Create your own report theme.

Whether your report is meant for internal stakeholders, like the leadership team, or external ones, like clients, it’ll be more effective if it looks good.

To adjust the report’s style and formatting, click the Layout and theme option in the toolbar.

Any changes here will apply across the report—meaning you only need to pick fonts, colors, etc., once versus every time, you add a new module to the report.

Looker Studio comes with two built-in themes: simple and simple dark. But it’s easy to create your own — and the results are way more impressive.

Click on “Customize.”

Use your brand style guide to choose primary and secondary colors, fonts, and text color. You might need to get creative here; HubSpot uses Avenir Next, which Looker Studio doesn’t offer, so I went with its cousin Raleway.

If you’re creating a report for a client and don’t know their hex codes, Seer Interactive’s Michelle Noonan has an excellent tip: use a free color picker tool to identify what they’re using on their website.

You can also create a custom chart palette in this tab and edit the border and background settings.

5. Embed external content.

Just like you can bring your report to the wider world, you can also bring the wider world to your report.

You can insert Google Docs, Google Sheets, YouTube videos, and even live webpages with the URL embed feature. Embedded content is interactive, so it’s far more powerful than a screenshot.

Click “URL embed.” in the navigation bar to add content.

From there, simply paste the URL. Next, you may need to resize the box that appears to fit your content’s entire length and width.

The options here are pretty endless. One of my favorite ways to use this feature is to embed a Google Form gauging how helpful the report was for my audience:

If a section of the report needs extra context (or my viewers aren’t that technical), I’ll add a short video explaining what they’re looking at and how to interpret the results.

To personalize a report for a client, I’ll add the URL of their website, blog, and/or whatever pages they hired me to create or improve.

And for the HubSpot blogging team, I’ll add the latest version of the Search Insights Report so they can compare our progress to the results.

6. Send scheduled reports.

If you have a group of stakeholders that need to see your report regularly, consider using Looker Studio’s “scheduled report” feature.

Click on the drop-down menu beside the “Share” button and select “Schedule email delivery.”

First, enter your recipients’ email addresses, then choose a schedule, whether daily, every Monday, or every month.

This is particularly handy when working with customers, since you may not want to give them access to the live report.

7. Download the report as a PDF.

Alternatively, you can download your report as a PDF. This is helpful for one-off situations, like if your boss asks for a status report or your client wants to know how an ad has performed so far this month.

To download the file, click “download” on the drop-down menu.

Looker Studio gives the option of downloading your current page or the entire report. You can even add a link back to the report so your audience can dig in deeper if they’d like and add password protection to ensure your data stays safe.

Intermediate Google Looker Studio Tips

7. Add a date range.

Give your viewers more freedom by letting them select which dates they’d like to see information for.

For example, my reports always default to the last 30 days, but if one of HubSpot’s blog editors wants to see how their property performed in the previous calendar month, the date range controls let them adjust the report.

They can choose from predefined options, like “yesterday,” “last seven days,” “year to date,” etc., or pick a custom period.

To enable this, first navigate to the page you want to give users date control. Next, click on the drop-down menu by “Add a control.” Next, click “Date range” from the toolbar.

A box will appear on your report. Drag it into the position you want — I recommend somewhere in the upper right or left corner, so your audience sees it first — and adjust the size if necessary.

Clicking this module will bring up a panel on top of your report called Date Range Properties. Set the default date range to “Auto date range,” if it isn’t already.

If your viewers select a date range using the date range widget, every report on the page will automatically update to that period.

There are two ways to override this:

Set a time period within a specific chart. That time period will always supersede the date range control.
Group the charts you want to be affected by the date range control with the module. Select the chart(s) and the box, then choose Arrange > Group.

Now, only the chart(s) in this group will update when someone adjusts the date range.

Make sure this setting is clear to your viewers — otherwise, they’ll probably assume all the charts they’re looking at on their current page are using the same time period.

8. Create interactive chart filters.

Want to make it even easier for your audience to filter the charts in your report? Create responsive chart filters.

This sounds fancy, but it simply means selecting a dimension in a chart will filter all the charts on that page for that dimension.

For instance, if you click on “organic” in this chart, the other charts on the page will update to show data for organic traffic only — just like you’d applied a traditional filter control.

You can also create chart controls for time, line, and area charts. For example, if a user highlights say, January through March on a time chart, the other charts on the page will show data for January through March as well — just like date range control.

And also, just like filter controls, you can group chart controls.

To enable chart control, select the appropriate chart. In the right-hand panel, scroll to the bottom and check the box labeled “Apply filter.”

Add a caption next to charts that support interactive filtering, so your viewers know it’s an option:

9. Add a data control.

Data controls may just be one of the coolest Looker Studio features, full-stop. Place one of these bad boys on your report, and you’ll give viewers the ability to choose the source of the data being piped into your charts.

This is a game-changer for anyone managing a complex property or working with multiple stakeholders.

For instance, imagine you’re the admin of HubSpot’s Google Analytics account. You create a Looker Studio report monitoring key website performance indicators, like average page speed, number of non-200 response codes, number of redirect chains, and so on.

You share this report with the blogging team, who has access to the Google Analytics view for blog.hubspot.com. (Need a refresher on how views and permissions work? Check out our ultimate guide to Google Analytics.)

You also share the report with the Academy team, who has access to the GA view for academy.hubspot.com, and the Leads Optimization team, who has access to offers.hubspot.com.

To see this report populated with the relevant data, these teams simply need to select their view from the “data source” drop-down, and voila — all the charts will update automatically.

Pretty nifty, right?

Not only does this save you from rebuilding the same report for different groups, but it also means you don’t need to worry about accidentally sharing sensitive or confidential information. Each viewer can only select data sources they’ve been granted access to.

You can include multiple data controls in a single report.

Add the data control widget to your report by clicking this icon:

Then choose which primary source you’d like viewers to pull from:

10. Add a dimension breakdown.

Instead of telling you what a dimension breakdown is, it’s easier to show you how it works.

Suppose we want to see users by source. To find out, we create a simple bar chart.

This is interesting — yet there’s some context missing. For example, is all of that organic traffic coming from Google? (Since this is U.S. data, probably, but imagine creating the same chart for China or Japan, where Baidu and Yahoo have a far greater presence.)

What about referral traffic? Clearly, we’re getting a significant number of users from referral links; is a single source driving most of them, or is it distributed fairly equally across a wide variety of sources?

We could create separate bar charts for each source — first filtering by medium and then making the dimension “Source” and the metric “Users.”

Or we could click a single button and have Looker Studio do it for us.

Under Breakdown Dimension, click “Add dimension.”

Add “Source.”

Here’s what you should see:

Pretty sure my former Data Analytics professor would cry if he saw this. But don’t worry, we’re not done yet.

Jump over to the “Style” tab and check the box “Stacked bars” to turn your regular bar chart into a stacked bar chart (you should see the chart type update accordingly).

Looker Studio will automatically make your bar charts “100% stacking,” meaning that every bar will go to the top of the chart. However, this style is misleading — for example, here, it suggests every medium drove the same number of users.

Uncheck this box.

Now check it out:

11. Use Looker Studio Explorer.

To bring any chart into Explorer, mouse over the space next to its top-right corner. You’ll see three vertically-stacked dots appear; click them.

Select “Explore.”

You’ll see something like this:

You can toggle between different visualizations; add and remove dimensions and metrics; change the date range, and apply segments.

Note: Unlike every other Google tool out there, Explorer does not automatically save your work.

To preserve your chart, click the “Save” button on the top nav bar (to the left of your profile icon). Once you do that, your Explorer “report” will be saved in the Explorer section of your dashboard. In addition, every change you make will be saved by default.

Speaking of that dashboard, if you prefer, you can also start with Explorer (rather than a Looker Studio report). Go to your Looker Studio dashboard and select “Explorer” in the top menu.

Create a new Explorer view by clicking the “Create” button on the left side..

At first, Explorer confused me. It feels very similar to the core Looker Studio — what was the point of having both?

However, after spending some time in Explorer, I’ve come to appreciate its unique value.

Unlike Looker Studio, any modifications you make to a chart in Explorer are temporary. That means it’s a great place to dig into your data and try out different ways of visualizing it without making any permanent changes. Then, once you’re happy with your chart, simply export it back into Looker Studio.

To do this, click the small sharing icon in the top navigation bar.

Then choose whether to add your Explorer work on a new or existing Looker Studio report.

Advanced Google Looker Studio Tips

12. Create report-level filters.

By default, a filter applies to every chart on that page. But what if the viewer goes to the next page? The filter won’t go with them.

This is confusing for non-technical folks and inconvenient for data-savvy ones. To bring a filter up from page-level to report-level, simply right-click on it and select “Make report-level.”

13. Create blended fields.

Looker Studio is powerful because you can bring in 760+ sources of data into a single report. But, thanks to a new feature, blended sources, it just got even mightier.

Heads up: this will get a little technical. Stay with me, and I promise it’ll be worth it.

If you’re familiar with JOIN clauses in SQL, you’ll understand data blending right away. No idea what SQL is? Not a problem.

The best way to think about blending data is with a Venn Diagram. You have two data sets. Each data set has unique information — e.g., such as the data living in the green and blue areas.

But they have (at least) one data point in common: the information in the blue-green overlap section.

This shared data point is known as a key. If your data sets do not have a key, they’re not blendable.

For example, suppose you want to compare how users behave on your website versus your app. The key is the user ID, a custom dimension you’ve created in Google Analytics that your app analytics software also uses. (Note: The key doesn’t need to have the same name in both data sources; it just needs to have identical values.)

You blend your website behavior report from GA with your app usage report. This gives you all the records from the first report along with any matching ones from the second; in other words, if a user has visited the site and used the app, they’ll be included.

However, if they only used the app but didn’t visit the site, they will not be included in the new blended data.

This is known as a LEFT OUTER JOIN. (To learn more, check out this W3Schools primer.) Why do you care? Because the order of your data sources matters.

Put your primary data source first — e.g., the one where you want all the values, regardless of whether there’s a match in your second source.

Now that we’ve gotten all that out of the way, let’s set up a blended field.

First, add a chart to your report, then click on “Blend Data.”

This panel will pop up:

Select your first data source on the left. Remember, this is the primary data source. Then add your second data source. Looker Studio lets you add up to five data sources in a chart, but let’s stick to two for now.

Now pick your join key(s). If the field exists in both sources, it will turn green. If it doesn’t exist, you’ll see this:

Remember that the key acts as a filter for the second data source. So in this example, only records that match the landing page from the GA view for hubspot.com will be pulled from Google Search Console.

Choosing multiple keys will further limit the number of records pulled from the second data source.

Once you’ve picked your join key(s), pick the dimensions and metrics you want to see for your first data source. Then do the same for your second.

You can also limit the results by adding a filter or date range (or for GA sources, segments). Filters, date ranges, and segments applied to the left-most data source will carry over to the other data sources.

Once you’ve finished customizing the report, click “Save.” Congrats: you just created your first blended data chart!

If you find it easier to create two separate charts and then combine them, Looker Studio offers a great shortcut.

Just select both charts, right-click, and choose “Blend data.”

Unfortunately, Looker Studio can get confused pretty quickly, so I’d still make an effort to learn how to blend data using the right-hand pane.

14. Blend your data source with itself.

Try this workaround if you’re bumping into limitations with your data source connectors: blend a data source with itself.

To give you an idea, the GA data connector only lets you add one “active user” metric to a chart, so there’s no way to see 1 Day Active Users, 7 Day Active Users, and 28 Day Active Users on the same chart… unless you blend your Google Analytics data source with itself.

Follow the same instructions as above, but instead of picking a new source for your second data source, just select the first one again.

And since all of the fields are identical, you can pick whichever join key you’d like.

This option is also perfect when comparing trends across two-plus subdomains or segments.

For instance, I wanted to look at organic users for the HubSpot Blog (blog.hubspot.com) and primary site (www.hubspot.com) at the same time.

This helps me figure out if we’re growing search traffic across the board. It’s also helpful when traffic decreases — have rankings dropped site-wide, or just for the blog (or the site)?

However, you can’t add two separate “user” metrics to a chart at once… unless, of course, you’re blending data.

Create a new blended data source (following the same process as above) to set this up.

Add your first view to the left-most column, your second view to the following column, and so on.

Note: Make sure you’re choosing views with mutually exclusive data. In other words, I wouldn’t want to use “blog.hubspot.com” as my first source and “blog.hubspot.com/marketing” as my second source because all the data for the blog.hubspot.com/marketing view is included in the blog.hubspot.com one.

Because of that overlap, we wouldn’t be able to spot trends clearly.

Use “Date” as the join key.

I added the organic traffic segment to both sources, but you can choose whichever segment you’re interested in (paid traffic, social traffic, etc.) Or leave it off entirely! Tons of possibilities here.

In fact, here are some additional ideas for blending a source with itself:

Compare two-plus custom segments
Compare two-plus landing pages
Compare two-plus goal completions

15. Create a basic calculated field.

When your existing data doesn’t give you enough information, it’s time to create a calculated field.

Calculated fields take your data and, as their name suggests, and make calculations.

It’s probably easiest to explain with an example.

Let’s say you want to look at the average number of transactions per user. You can create a calculated field that takes the metric “Transactions” and divides it by the metric “Users.”

Once this field has been created, it’ll be updated automatically — so you can change the chart’s time range, dimensions, etc., and the average transactions per user data will update accordingly.

There are two ways to create a calculated field.

Create a data-source calculated field

This option makes the field available in any report that uses that data source.

It’ll also be available as a filter control or in new calculated fields (like calculated field inception).

Obviously, this is a good option if you plan on using this custom metric more than once. The only caveat — you must have edit rights to the original data source. You also can’t use a data source calculated field with blended data.

To create a data-source calculated field, add a chart to your Looker Studio dashboard, then choose the data source you want to derive your new field from.

Click “Add a new field” in the lower left-hand corner.

(You can also do this by clicking the pencil next to the data source and then selecting “Add a field” in the upper right corner of your field menu.)

Use the left menu to search for the metrics you need; click one to add it to the formula.

If the formula has an error, a notification will appear in red underneath the editor explaining where you went wrong.

If your formula works, you’ll get a green checkmark.

Click “Save” to add your new field to the data source.

And don’t forget to name yours — which I forgot to do. 🙂

Now you can add this calculated field to any chart just like a regular field.

Create a chart-level calculated field

For this option, you’ll only be able to use the field for that specific report.

This option is a little easier because all the limitations of the other type are reversed.

While you can’t use a chart-level calculated field in another chart, filter control, or additional calculated field, you don’t need edit rights to the original data.

You can also use a chart-specific calculated field for data blending, which we’ll cover in the next step.

To create a chart-level calculated field, simply click “Add a field” underneath the existing dimension(s) and metric(s) you’ve selected.

When you choose to add a new field, this pane will pop up:

From here, enter the formula for your new field — simply typing in the name of your desired metric will trigger a menu of options — and click “Apply.”

Your new field will be added to the chart.

Loves Data’s Benjamin Mangold has an excellent round-up of sample calculated metrics, including:

Average goal completions per user
Non-bounce rate
Pageviews per transaction
Value per session

You can check it out for inspiration.

If you want a little practice before you start going to town on your own data, Google offers a handy sample exercise.

16. Create an advanced calculated field.

Okay, so there’s a lot you can do with simple algebraic calculated fields. But there’s even more you can do once you introduce functions and RegEx.

Don’t be scared off! We’ll walk through these step-by-step.

If you’re comfortable with Google Sheets and/or Excel functions, you already know how to use functions in Looker Studio.

For instance, let’s say that you majored in English, and it’s always bothered you that “Source” in Google Analytics is lower-case.

You can use the UPPER function to transform Source into all upper-case.

Simply click “Add dimension” > “Create new field.”

Then enter the UPPER formula:

As Google Sheets expert Ben Collins points out, this trick will also standardize any custom naming; for example, if some people on your team used “chat” for a campaign, and others used “Chat,” the UPPER function will aggregate both together.

Perhaps you want to create a new field for city and country.

Just click “Add dimension” (since city and state are categorical, not quantitative, variables) > “Create field.”

Then use the CONCATENATE function to smush together the City and Country fields.

Check out the complete list of functions Looker Studio supports.

One of the niftiest is CASE. If you’re unfamiliar, it’s essentially an IF/THEN statement. This function lets you create custom groupings.

For example, let’s say you’re looking at the table we created in the last step:

Here, Looker Studio is treating Facebook mobile traffic (m.facebook.com) and desktop traffic (Facebook) as two different sources. There’s also l.facebook.com — desktop traffic coming via a link shim, which Facebook implemented in 2008 to protect users from potential spam. What if you want to combine all Facebook traffic into a single source?

A CASE formula solves this issue neatly. Here’s the formula:

CASE

WHEN condition THEN result

WHEN condition THEN result

ELSE result

END

You can have one condition (like the example below) or several. The ELSE argument is optional, so feel free to leave it out if you don’t need it.

Here’s the formula we’ll use to group Facebook traffic:

CASE

WHEN REGEXP_MATCH(Source,”^(l.facebook.com|m.facebook.com|facebook.com)$”) THEN “Facebook”

END

This formula tells Looker Studio, “If the source matches l.facebook.com, m.facebook.com, or facebook.com, call it ‘Facebook.’”

To add a CASE formula, you must be able to edit the data source.

Click the pencil icon next to your source to bring up the data field editor.

Then click “Add a new field” in the upper right corner.

Enter your formula.

If the formula works, you’ll see a green checkmark. Give your new field a name and click “Save.” Now you can add this field to any chart or data viz that uses this data source.

You might be thinking, “Okay, great, but was that formula written in Klingon? How do I come up with my own?”

Don’t know RegEx? No problem! This blog post has five formulas to get you started.

17. Create a calculated blended field.

This is the pinnacle of Looker Studio mastery, requiring all the skills you’ve already learned and a hefty dose of luck — just kidding, it’s super easy.

Create a blended data source per usual.

In this example, I blended together the GA views for www.hubspot.com and blog.hubspot.com.

Then click “Add metric” > “Create Field” as you would to create a normal calculated field.

Enter your formula.

I wanted to see “Total Users” (i.e., users from www.hubspot.com plus users from blog.hubspot.com), which is a simple calculation:

Note: It can get a bit hairy here if you’re using two different fields with the same name, as I’m doing here. Sometimes Looker Studio is smart enough to recognize the difference, and sometimes it’s not.

If you run into issues, I recommend editing the name of one or both fields in the original data source(s), which you can do at any time by clicking the pencil next to the blended data source.

Then click the pencil next to the field name you want to change.

This pane will appear; edit the title accordingly.

Then click “Save” and go back to your calculated field to update the formula:

Done! I can now see both in my report.

Google Looker Studio is the Best Way to Visualize Your Data

Now that you know Looker Studio inside and out, you’re well-prepared to create stunning interactive reports for your coworkers, clients, and executives. Use the tips I shared above to make the most of it and successfully show the ROI of your marketing efforts.

Editor’s note: This post was originally published in October 2018 and has been updated for comprehensiveness.

 

The 11 Best Ways to Send Large Files

We all know the frustrating feeling — you’ve collected all the images you need for your next campaign, but when you go to press “Send” you’re told, “Sorry. File too large.”

Figuring out how to send large files on the fly is a pain. Unfortunately, our email accounts can’t carry as much storage as you might think. Gmail, for instance, can only hold files up to 25 MB.

Additionally, large files can eat at your storage space, even if it’s just sitting in your Sent folder. If you’ve got a file you can’t send the traditional way, don’t worry — we’ve got several alternatives (some free), to ensure the largest of files can be sent to whoever, within minutes.

Skip to:

How to Send Large Files in Email
How to Send Large Files Over the Internet
How to Send Large Files via File Sharing Service

How to Send Large Files in Email

1. Upload your files to a cloud storage space, and share them or email them to others.

Pros

Easy to use
Great for internal company sharing

Cons

Limited to your service provider

Using a cloud storage space like Google Drive, Dropbox, or OneDrive is one of the easiest and most popular methods for sending large files. Depending on your email provider, you’ll likely be able to use corresponding cloud storage — like Google Drive for Gmail, or OneDrive for Outlook.com.

If you’re sending an attachment within a provider like Gmail, you’ll see the Google Drive button already integrated. Simply press it, choose your file, and then send it like a regular attachment.

Alternatively, Dropbox allows you to upload large files and then send a web link via email or text to your recipient. With Dropbox’s free tier, you’ll receive 2 GB of storage space. For $9.99 per month, you can increase your storage to 1 TB.

Best for: Ease-of-use when sending attachments through your email provider. Most likely to use when sharing files internally with colleagues.

2. Use WeTransfer, a free online service.

Pros

Free
No download required
No install required

Cons

Limited file size for free version (2 GB)

Image Source

WeTransfer is one of the simplest ways to share files online with the added bonus of not having to register to use the service. Once on the website, all you need to do is upload your file (up to 2 GB), enter a destination email, enter your email, a title, and a message and you’re all set. 

Best for: Emailing large files without having to sign up or download anything.

How to Send Large Files Over the Internet

3. Use a VPN.

Pros

Sends files securely
Keeps sender’s location private

Cons

Could slow connection
Requires tech savvy to install

A VPN, or Virtual Private Network, is a service that protects your data and provides you with more privacy when you’re online by routing your internet connection through a server. A VPN can protect you from hackers, or even online ads, and is a secure option, particularly if you’re often using public wi-fi.

Some internet service providers (ISP) use broadband traffic management to moderate upload bandwidth — if this is the case for your ISP, you can use a VPN, which will prevent your ISP from recognizing how large your files are, enabling you to send them.

However, this isn’t the best option in our list for two reasons — one, the large file could slow down your VPN connection, and two, your files aren’t guaranteed to be intact upon delivery. To ensure a high-quality delivery, you might want to try an alternative option, like a Zip compression.

Best for: If you’re using public wifi and you’re sending private documents, this is a good option for increasing security measures. However, this may not be the best option if you need to ensure high-quality delivery.

4. Use FTP via FileZilla

Pros

Fast transfers
Simple to use

Cons

Unencrypted

Image Source

FTP, or File Transfer Protocol, is an option for transferring files online by uploading a file to your hosting server. FileZilla is a free FTP tool you can use to transfer files.

Once installed, users can easily select the files to be transferred with FileZilla’s two-pane display by clicking and dragging them into place. It’s great for sending files greater than four gigabytes. The software is frequently updated so if you encounter any bugs, changes will be resolved quickly.

The few downsides to using FTP is that files are not encrypted and with FileZilla, the free version also includes adware but upgrading to the paid version will eliminate this issue.

Best for: Using FTP software is best for transferring large, non confidential files that don’t need to be encrypted.

5. Transfer files using SFTP.

Pros

More secure than FTP
Speedy file transfers

Cons

Requires tech savvy to install

FTP, or File Transfer Protocol, is an option for transferring files online by uploading a file to your hosting server. However, the disadvantage of FTP is that it isn’t that secure — which is where SFTP comes in.

SFTP — or Secure File Transfer Protocol — is a protocol that works in a similar way to FTP, except it uses secure shell for encryption. This is a good option for limiting accessibility to those outside your recipient list. Some of the other options in this list, including file transfer options that rely on email, are likely less secure than an SFTP.

Best for: A more secure option than traditional online file-sharing, to be used when sending highly classified files to colleagues or clients.

Other Ways to Send Large Files

6. Use file compression software, like 7-Zip.

Pros

Eliminates storage obstacles
Quick transfer time

Cons

You have to manually compress files
Recipient must know how to decompress files

Image Source

If you have multiple files, you might consider using a free compression software like 7-Zip, which can compress an entire folder of files at once. Zip files in general support lossless data compression, and are good for saving time and space while ensuring your files remain intact. Most operating systems can extract Zip files easily, without additional software.

7-Zip is available for Windows, Mac, and Linux. You can also provide a password for your files with 7-Zip, to ensure they’re safe to send online.

Best for: Sending a folder full of files at once to a recipient.

7. Purchase a USB flash drive.

Pros

Simplest way to transfer files
Portable

Cons

Data is gone if you lose it
Not ideal for time-sensitive deadlines

If you want to collaborate on a project or video with a large storage size, you might consider uploading it to a USB flash drive, which can range in size from 2 GB to 1 TB. This might allow you to pass your files more easily between coworkers, or back your files up for additional protection.

Best of all, if you use a USB you can take some strain off your computer, extending its data storage.

Best for: If you’re interacting with your team in person, a USB flash drive is a good option for physically handing files to team members, and takes some of the storage strain off your devices. Alternatively, a USB flash drive is safe to use as a back-up, so if your computer crashes you don’t lose access to your files or folders.

8. Use Jumpshare, a free online service.

Pros

Free
Get up to 2 GB of storage space

Cons

No client side encryption

Image Source

There are plenty of free online services that make uploading and sending large files both easy and incredibly quick. Jumpshare, for instance, lets you send up to 250 MB worth of files with a free account — simply upload a file or folder, and Jumpshare provides you with a link to share the files.

Plus, you can download the Jumpshare icon to your desktop. When you drag-and-drop files onto it, a link will be copied to your clipboard, which you can send to anyone, even if they don’t have their own Jumpshare account.

Best for: Easily, and quickly, sending files via links to colleagues. Best used for files or folders for which there aren’t too many privacy concerns, since the link is shareable with anyone.

9. Try Rakuten Drive Pro.

Pros

Secure password protected
Send files up to (50GB)

Cons

Free version has ads

Rakuten Drive, formerly Sendy, provides 1 TB of cloud storage and unlimited Cloud storage to transfer large files. What sets this tool apart from the rest is the ability to send your files using a password with recipients, so you can share files without needing access to everyone’s email addresses. Alternatively, you can send a link through email or a company messenger, like Slack, when you don’t need to transfer the files in real time.

Rakuten Drive enables you to attach big files using Chrome Extension, Outlook add-ins, and Send Anywhere’s website. It’s $7.99/month for the PRO version — or you can try the free version if you don’t need the PRO features.

Best for: The password enables you to quickly message or send files to anyone, without needing an email address. This might be good for quickly Slacking files to colleagues, or texting a file to a friend.

10. Upload the file and generate a link to share via MyAirBridge.

Pros

Free version
Share up to 20 GB

Cons

Password protection only for the Enterprise version

Image Source

MyAirBridge is a free tool that enables you to upload and share up to 20 GB through an email, shared link, or downloaded to your own storage space. You can use your own mobile device to upload files. For larger files the uploading takes a while, and it may not be the cleanest interface on the receiving end (the link your recipient receives takes them to direct download), but it gets the job done for personal or small team use.

MyAirBridge also offers plans ranging from Basic ($2.99/month) to Enterprise ($65.99/month). With the Enterprise option, users have access to 15 TB of storage, unlimited uploads of up to 100 GB, and the option to password-protect files for extra security.

MyAirBridge is a good option if you want to download various files (including music or video files, game applications, or documents) to your own storage space. For instance, you might use the tool to download music from your mobile device to your computer.

Best for: Downloading files to your own storage device, or use when downloading music, gaming, or video files.

11. Share a collection of assets to your team via Brandfolder.

Pros

Stores all files in one place
Sets user-level permissions

Cons

No free version

Image Source

Consider sharing brand assets, or a collection of assets, with your team, partners, or customers using Brandfolder. Brandfolder lets you use tiered access to share files with intended individuals, and even measure performance of each asset using Brandfolder’s Brand Intelligence feature.

Used by major brands including Slack, Bumble, and Hotels.com, Brandfolder enables you to store all brand-related assets in one place. Brandfolder is cloud-based, and uses user-level permissions to ensure employees and clients only have access to the appropriate files and folders.

Brandfolder offers Premium and Enterprise options. Request a quote to learn how much it would cost for your team to implement.

Best for: A more professional-looking option when sharing brand-related assets with clients or agencies, and a good long-term solution for storing all major files in one place for your team to access easily.

How to Send Large Files via Email Attachment

While you can’t send large files via email attachment the traditional way, there is a workaround using a cloud storage device. Start by storing your files in a cloud storage provider like Google Drive, Dropbox, or OneDrive.

When you want to send the file, simply share the file with someone, and then notify them via email that you have done so. For example, if you’re using Google Drive, simply click share in the top right corner of the document you’d like to send. From there you’ll be prompted to enter the recipient’s email information and select whether or not they should have editing permissions. Google Drive will automatically send them an email notification or you can choose to send them a link instead.

Another way is to utilize built-in integrations with Gmail or Outlook. If you use Gmail or Outlook.com, you’ll find a Google Drive or OneDrive integration. When attaching your file to an email, you can click the Google Drive or OneDrive button to share the file.

When the recipient receives your email, they can download your file to their computer, or open it online through the cloud storage service you used to send it.

Sending Large Files Made Simple

Sending large files doesn’t have to be an obstacle in your workday. By using the methods above, you’ll be able to share large files with ease and collaborate with your team seamlessly.

Editor’s note: this article was originally published in June 2021 and has been updated for comprehensiveness.

Heat Maps: Everything Marketers Need to Know

Heat maps are a game-changer for marketers who want to optimize their website and blog for better engagement and conversions.

By mapping out where users click, hover, and scroll, heat maps can provide powerful insights into what your visitors like, what they don’t like, and what they’re ignoring.

Here, we’ll take a closer look at heat maps, how they work, and the different types of maps you can use to optimize your website for more conversions and less friction.

Table of Contents

What is a heat map?

How do heat maps work?

Different Types of Heat Maps [+ What They Can Tell You]

How to Use Heat Maps

Imagine a marketer is re-designing a landing page and wants to position a call-to-action in a high-traffic area. Instead of taking wild guesses on where it should go, she generates a heat map of her website, allowing her to see where visitors are most engaged.

This is what makes heat maps so effective. They allow marketers to visualize, understand, and interpret complex data at a glance.

By identifying patterns in movement and behavior, marketers tailor their websites to improve user experience, increase conversion rates, and even reduce bounce rates.

How do heat maps work?

A variety of color schemes can be used in heat maps — from grayscale to rainbow. However, rainbow-schemed maps are typically preferred because they enabling you to interpret data points more easily.

The “hot” sections of a heat map — typically represented by warmer colors — are most popular with users. Alternatively, the “cold” sections — typically represented by cooler colors — are less popular.

There are two main categories of heat maps:

Interaction heat maps are used to identify how users interact with a website or blog. They do this by tracking clicks, mouse movements, and scrolling behavior.
Attention heat maps are more complex, leveraging eye-tracking technology to record the movement of a user’ eyes as they scan a webpage.

Next, we’ll discuss the different types of heat maps and the benefits of each.

Different Types of Heat Maps [+What They Can Tell You]

1. Scroll maps

Scroll maps show you the percentage of visitors who scroll through each section of your webpage. The hotter the section, the more visitors have viewed it. This data can help determine where to place CTAs or important information on your webpage.

For instance, if your visitors only scroll down 50% of the page, placing a CTA closer to the top — rather than the middle or bottom — would make sense.

Remember: When using scroll maps, always look at metrics on different devices, including smartphones and tablets.

(Image Source)

2. Click maps

As the name suggests, click maps identify the parts of your page that visitors click on the most. The hotter the section, the more frequently your visitors click on it.

This data can show you if visitors care to click on your CTAs or other buttons that allow them to take a desired action. It can also show you if they’re getting distracted by non-clickable elements or experiencing navigational issues.

(Image Source)

3. Hover maps

Hover maps, also known as mouse-tracking heat maps, show you where visitors hover their cursor while reading your webpage. The hotter the area, the longer they hang their cursor over it.

This data can help determine how visitors actually navigate your website, so you can place important elements in a location where they’ll receive the greatest amount of attention possible.

For example, a marketer can track the hover patterns on a checkout page to see where customers experience the most friction.

(Image Source)

How to Use Heat Maps

Analyzing the heat map of each type of page on your website would be ideal, but, unfortunately, it isn’t efficient. The most effective way to leverage heat maps is to analyze the pages that influence your website’s conversion rate the most: your home page, landing pages, and high-conversion blog posts.

Home Page

Your homepage is an introduction to your brand. If you constantly monitor which sections visitors are scrolling through and whether they’re hovering over key information and clicking on CTAs, then you’ll know exactly where to place the most important elements of your homepage, reducing your bounce rate and increasing your conversion rate.

Landing Pages

Your landing pages are the last step in turning visitors into leads. If you can analyze your users’ behavior on these pages, then you can implement the optimal landing page design for generating the most amount of leads for your business.

High-Conversion Blog Posts

Your CTAs placement on your blog posts can heavily influence their conversion rate. For instance, at HubSpot, even though our end-of-post banner CTAs are visually engaging, we found out that they only generate a small fraction of our blog leads.

After analyzing our heat maps, we discovered that our anchor text CTAs, which are just hyperlinked blurbs of text located after each blog post’s introduction, actually generated the majority of our blog leads because most visitors saw the CTA at the beginning of the post and not the one at the end.

Back to You

Whether you’re A/B testing your website design or figuring out the best place to put a call-to-action on your blog posts, heat maps are your best tool for measuring attention and designing content that connects with your audience and converts them into leads and customers.