The Ultimate Guide to Email Marketing on Valentine’s Day

According to US National Retail Federation, in 2012 alone people were willing to spend on average $126.03 on Valentine’s Day for their significant other. In 2013, the spend went up to $130.97, so the total spend related to Valentine’s Day … Continue reading

According to US National Retail Federation, in 2012 alone people were willing to spend on average $126.03 on Valentine’s Day for their significant other.

In 2013, the spend went up to $130.97, so the total spend related to Valentine’s Day in the US was estimated at 18.6 billion dollars. In 2012 it was 17.6 billion dollars.

Just like Christmas, Valentine’s Day is a holiday celebrated by pretty much everyone nowadays. Actually, it isn’t just an american tradition anymore, countries all over the world are celebrating Valentine’s Day, and businesses are looking to leverage this.

As always, email marketing is  probably one of your best bets to capitalize on people’s willingness to spend money on Valentine’s Day.

Add some creative advertising and some engaging social media content to the mix and you got yourself a winning strategy.

Opportunity: checked.

Strategy: this article will help you out with that.

What To Do to Win Valentine’s Day

Your Valentine’s Day to do list should look something like this:

  1. add more subscribers to your email lists
  2. segment your list
  3. schedule when you are going to send the emails
  4. write great subject lines
  5. design amazing emails

Valentine’s Day is all about love and that means you shouldn’t have a “one night stand” with your email list. . (tweet this)

Treat this holiday right, and it can bring you HUGE benefits on long term.

Also, don’t make this holiday about you: make it about your customers and about your audience.

Help them experience a day they’ll never want to forget.

How to grow your email list very fast

I know, Valentine’s day is almost here. Getting more email leads & subscribers in such a short time is not an easy task.

Don’t freak out though, everything is not lost. We’ve got a few tips that can earn you some serious Valentine’s business.

Create a valentine’s Day Business Venture

Partner up with other companies, find companies that are not selling products or services suitable for Valentine’s Day. However, they might have bigger email lists than you do.

By partnering up with them you’ll get to increase the sales of your products and they’ll get a partnership commission out of a holiday which otherwise would bring them no extra sales.

Closing a partnership might take time so get it done right now.

ADD BUcketloads of subscribers by using behavioral targeting

If you are not using PadiAct, maybe this is the best opportunity for you to try it out.

You can start by defining a campaign and target people exclusively for the Valentine’s Day lists.

Here are a few tips to get loads of email subscribers from Day 1:

  • identify the most successful products of last year’s Valentine’s Day and ask people to subscribe while visiting similar products
  • target visitors after spending at least 2 minutes viewing the products (they are still in the researching phase)
  • offer them the best reason to subscribe, so they can’t refuse you: let people know about the Valentine’s Day exclusive emails with tips, gifts and promotions.
Setting up targeting rules inside PadiAct.

Example: How to target visitors with PadiAct.

Segment and clean your lists

On the romantic 14th of February and the days before it, the subscribers are going to receive loads of emails with Valentine’s offers. For them, it will be a tipping point and people will probably “abuse” the Report as spam or Unsubscribe buttons.

That’s why, you need to be one step ahead.

The week of 14th of February should be a week when open rates, click rates and purchases are at their best.

Here are a few segments that you should look into:

  • gender: craft emails respecting the fact men & women have different needs
  • activity: the closer you get to the last emails of your Valentine’s Day campaign, the more you should refrain yourself from sending emails to inactive subscribers
  • interest: use different call to actions in emails to identify user interest. Based on the links they’ve clicked, add subscribers in different buckets
  • age: a 40 year couple will probably have a different idea on how to spend that day compared to an 18 year one

A great way to keep your lists clean, is to allow people to opt-out of the Valentine’s Day emails, but to stay subscribed toyour other lists. A visible copy like the following one with the appropriate link should do the job:

I already found a gift and no longer want to receive Valentine’s Day emails.

Drip your emails

We already told you that love is in the air, a “one night stand” is very a bad idea.

Don’t plan a single email for Valentine’s Day. Avoid the “hit and run” approach.

Build a campaign that reminds people about the big day, a campaign with ideas on how to surprise their partners, makes it easy for them to find a gift and then follow up to make sure everything went well.

Is it your first Valentine’s Day email campaign?

Feel free to use the following Valentine’s Day Marketing Calendar:

20th-22ND January – announce Valentine’s Day

Send an email to all your subscribers reminding them that Valentine’s Day is coming. Tell them to hop on the exclusive Valentine’s day email list.

Give a few hints of presents or things they can do for their special one.

Add up to 3 call to actions in the email, each one of them describing a different user intention.

Future campaigns should be sent to visitors based on what link they clicked.

January 27th – 30th – content aware campaign

Based on expressed intention through the links they’ve clicked in the previous email, send them suggestions of gifts.

Make sure to add a story to each gift idea.

People would rather relate to stories than to product descriptions, so you’ll make their choice easier.

February 3RD – 5th – launch THE OFFER

The period when most people do the purchases. The more they delay, the harder it will be to find and have the perfect gift delivered on time.

Be creative about your incentive. Go beyond the classic discounts.

Discounts are always welcomed, but extravagant wrapping of purchased products can make a strong impression, especially on Valentine’s Day.

10th of February – continue with the promotion

Only send to people that opened at least one email in the last 3 months.

From this moment on, you are playing the safe card and you are keepings unsubscribes and spam reports as low as possible. This email should speak of urgency. It’s the last chance of buying a gift, if it’s not too late already.

13th of February – the day before

It’s probably too late to sell anything and deliver it on time. To the subscribers that did not purchase anything for their loved ones, offer them some tips on how to save the day. To the ones that did purchase, give them tips on how to surprise without actually giving them a gift.

This one email might be the one that actually helps you WIN your email list. If you provide them with great ideas on how to save the day, your subscribers will remember you and they will recommend you to all their friends.

15th of February – the day after

Encourage subscribers to write back their stories. Maybe even through in a prize or some gift cards.

Get as many testimonials & stories as possible.

Create content around your customers’ stories (it can be an article, a video or an infographic), and post it on Pinterest, Facebook and, what the heck, release it even on Google+.

Make it a Valentine’s Day that everyone remembers, and promote it heavily so that your competition will be jealous because they’ve decided to have a “one night stand” instead of actually providing help to their audience

Subject lines your email list will not ignore

One of your biggest challenges will be to get as many subscribers to open your emails. Here is what Experian found in a study they’ve conducted last year:

experian

As you see, subject lines are crucial, so here’s a list that can get you started on writing great emails:

  • Hurry, Cupid’s Counting Down! Send a Special Greeting Card
  • 3 Days Until Valentine’s Day. Find The Perfect Gift Today Or It Could Be Your Last.
  • Order now to avoid heartbreak this Valentine’s
  • For love or money?
  • Get gifts as extraordinary as your Valentine
  • Valentine’s Day gifts for your Rebecca
  • You’ll ❤ Key Pieces for the Season
  • We’ve got a crush (or two). How about you?
  • Ten Ways to Say “I Love You”
  • Wine, Chocolates & $0 Shipping
  • Will You Be Our Valentine? Sweepstakes, News, & More To Show Our LUV
  • Last Chance to Get the Look You Love Before V-Day

By sending up to 6 emails ’till the big day, you’ll have a chance to test a few sets of subject lines to find the best one for you.

Design amazing emails

Once you have subscribers open your emails, the copy and the design are going to be decisive in having people become customers as well.

Check out the following designs that were shared heavily on the web. Click on the images to get the full newsletter:

01-apple

02-perfume

03-pink

04-starbucks

05-restaurants

06-trips

07-jewels

08-furniture

 

How will you approach valentine’s day in 2014?

What are your plans for 2014’s Valentine’s Day?

What worked for you the last year and what do you plan to do better in 2014?

Did we miss something? We would love to hear your opinion on this article.

Collect Email Subscribers & Leads Using BlackMail

Here at PadiAct we are committed to growing your email leads & subscribers lists. This is what we know best, this is what we do for hundreds of online businesses. With this mission in mind we are constantly testing and … Continue reading

Here at PadiAct we are committed to growing your email leads & subscribers lists.

This is what we know best, this is what we do for hundreds of online businesses.

blackmail

With this mission in mind we are constantly testing and experimenting with features, pop-ups and targeting rules to find new and effective ways to get you more emails.

Recently, we developed a design that we think will skyrocket your subscription rates.

We introduce you: BlackMail

Hihi! Gotcha!

I had you worried there for a second.

Blackmail_form

BlackMail is a slick, yet elegant, predesigned subscription form that you can use as a popup, left to right slider and bottom slider, just like the other 2 predesigned styles (Default and Good Old Mail).

Adding the image is very easy, you just need to paste the URL where you hosted the image.

Recommended image width is 200px.

How to Start Using BlackMail

  1. Go and edit your campaign.

  2. Select the style to be BlackMail.

  3. Paste your image URL in the field

  4. Personalize the Interaction Look & Feel

  5. Quick preview it to see if you are happy with the results

  6. Fine tune your copy

  7. Save the campaign.

You’re done. Congratulations.

That’s it. Easy, right?

Now, just sit back, relax, and enjoy “the view” (the reports).

From now on, you will collect email leads and subscribers using “BlackMail”.

How to Use Google Analytics Content Grouping: 4 Business Examples

Content Grouping is a useful feature that let’s you group your website or app content together and view aggregate metrics for each group. This is particularly useful if you have a lot of content to analyze. Rolling up your content, based on your specific business structure, is very helpful when creating dashboards and other custom […]

How to Use Google Analytics Content Grouping: 4 Business Examples is a post from: Analytics Talk by Justin Cutroni

The post How to Use Google Analytics Content Grouping: 4 Business Examples appeared first on Analytics Talk.

Content Grouping is a useful feature that let’s you group your website or app content together and view aggregate metrics for each group. This is particularly useful if you have a lot of content to analyze. Rolling up your content, based on your specific business structure, is very helpful when creating dashboards and other custom reports.

In this post I’ll talk about how to actually use the data and walk through some examples for various business types.

If you have not set up content groupings, please check out my post on how to set up Google Analytics content groupings.

Standard GA Reports

Your content groupings are available in Google Analytics behavior reports. Navigate to the Behavior > Site Content > All Pages report. Notice at the top of the data table there is a selector for the primary dimension. This drop down list all of the content groupings that you added to Google Analytics.

Use the selector to choose a specific content grouping in your Google Analytics Content reports.

Use the selector to choose a specific content grouping in your Google Analytics Content reports.

This selector also exists in the navigation flow, so rather than viewing how users move from page to page, you can view how users move between the different types of content on your site.

You can also use your content groupings in the Navigation Summary report.

You can also use your content groupings in the Navigation Summary report.

Very handy for understanding the behavior of users!

It also exists in many other content reports, like the Landing Pages report and the Site Speed Page Timings report.

But who uses the standard reports these days? :) Analysis driven organisations use Custom Reports and Dashboards. Let’s look at how you can use content groupings in both features.

Custom Reports & Dashboards with Content Groupings

When you create a content grouping, Google Analytics will create a dimension for each content grouping.

Remember, a content grouping contains a number of groups, and each group can contain a number of pages or screens.

Each content grouping contains multiple content groups. A content group contains multiple pieces of content.

Each content grouping contains multiple content groups. A content group contains multiple pieces of content.

This means that the values for the content grouping dimension will be all of the content groups that you created within that grouping.

You can create up to five content groupings in Google Analytics, therefore you could have five new dimensions, one for each content grouping.

Use the content grouping dimensions just like you would any other dimension. Here’s a simple custom report that shows some a potential content grouping for a blog.

You can use your content groupings in a Google Analytics custom report.

You can use your content groupings in a Google Analytics custom report.

Then, when you look at the report, you’ll see something like this:

When you add a content grouping to a Google Analytics custom report, the data will be aggregated based on content group.

When you add a content grouping to a Google Analytics custom report, the data will be aggregated based on content group.

Note: I added this custom report to the Google Analytics solutions gallery. You can add it directly to your account here.

You can also use the content grouping dimension in your dashboards. Here is a very simple example using the page value metric and the content grouping dimension.

You can also use the Content Grouping dimension in a Google Analytics Custom Dashboard.

You can also use the Content Grouping dimension in a Google Analytics Custom Dashboard.

That’s really all there is to using content grouping in Google Analytics custom reports and custom dashboards. No go and give it a try!

One other note – the content grouping dimensions are hit level dimensions. This means that you can only use them with hit level metrics, like pageview, time on page, etc. You can not use them with session level metrics, like conversion rate, or revenue per visit.

Content Grouping Strategies

To really take advantage of content groupings you need to plan your content grouping carefully. You need to understand how your organization wants to analyze this data. So let’s look at a how different types of businesses might use content grouping.

Ecommerce: Patagonia.com

Patagonia sells outdoor equipment for men, women and children. They’re known for their ethos that you should travel “fast and light” when in the outdoors – take only what you need. They’re also known for their environmental advocacy. They incorporate both of these messages into their marketing stories.

Effectively breaking down the content structure could help each department at Patagonia better understand their marketing initiatives and site optimization efforts.

So how might we create a content grouping strategy based on their business?

Google Analytics Content Grouping can be used to organize the content on an ecommerce website.

Google Analytics Content Grouping can be used to organize the content on an ecommerce website.

Product pages: I would start by grouping all product pages together. It’s really important to understand what percentage of your users are making it to product pages. If people don’t look at product pages then they usually can’t buy something. And I’d take it one step further – group product pages by product line. I’d also be sure to differentiate category pages from the generic product pages.

You can mimic your product architecture with your content groupings.

You can mimic your product architecture with your content groupings.

Special selling tools: One cool feature that the Patagonia site has is the ‘kit builder’. This is a tool that let’s a customer build the best clothing combination for different conditions or activities. This is another section that could really use it’s own content group.

Special shopping tools can be categorized in their own group.

Special shopping tools can be categorized in their own group.

Checkout pages: Next I’d group all checkout pages together. These are all the pages in your checkout process. The percentage of people that see checkout pages might be very small, but I like to put these pages in their own group. They’re not product related, and they’re not marketing related. So they need their own group.

Account management pages: Many ecommerce sites let customers manage account settings, check the status of their order, manage returns, etc. I would lump all of these pages together in an Account Management group.

Marketing pages: Now we get into a large chunk of the content – marketing pages. Patagonia has a lot of information about their brand, and initiatives. Rather than lump all of this together as just Marketing pages, I would actually break all of this up into groups based on the different initiatives.

In the case of Patagonia I would use all of these different groups that you can see in the navigation.

Use a Google Analytics Content Grouping to categories marketing pages.

Use a Google Analytics Content Grouping to categories marketing pages.

Support pages: Business is all about relationships – and that’s represented by different types of support content. We can create a support group that containing any materials related to support. Again, you can create sub-groups for different types of support content (product support, order support, etc.)

Error pages: I like to group all error pages into a single group, then I can drill into the group and view the specific errors. This group can contain all different kinds of errors, depending on your personal preference. It could be technical errors, like 404 or 502 errors. Or it could be more functional errors, like when a user adds an incorrect credit card number during their purchase.

Software as a Service: Mailchimp.com

Mailchimp is a popular service that helps businesses manage their email marketing initiatives. Like all SaaS sites it’s primarily divided into two sections: a marketing section and an application section. The content grouping will mimic this general structure of content.

Product marketing pages: If people are going to sign up for the Mailchimp service then they need to know about the features! Product marketing page are pages dedicated to product information, this includes information about price, features, etc.

For a SaaS site, create groups for different kinds of marketing content.

For a SaaS site, create groups for different kinds of marketing content.

In addition to specific product information, there’s also a lot of thought leadership material to help drive marketing.

Marketing content pages: These pages are non-product marketing pages that help you demonstrate your thought leadership. It may be blog pages, or other content. In our example of mailchimp.com, there might be multiple groups. For example, they have a blog, but they also have a ton of research about email marketing. I would put this material in a marketing content group. Or even better, in the Reports group!

I would create a Google Analytics content group for the research reports on the MailChimp site.

I would create a Google Analytics content group for the research reports on the MailChimp site.

Application pages: The other side to a SaaS site is the actual application. This is the section of the site where you log in and actually use the product. Like the marketing pages, there can be many different types of application pages. Let’s go back to our example of Mailchimp.com. I would break down the content based on product features.

Perhaps we could use the application navigation as a template for the content structure.

You can create different groups for each part of the online application.

You can create different groups for each part of the online application.

Account management pages: Here’s another example of grouping different parts of the application together. We could easily group together the pages that control account management. And you can see from the image above that there are sections of the app dedicated to other functionality – all should be grouped accordingly.

Error pages: Like other types of sites it’s a good idea to group all error pages together. See the ecommerce section above for more details. These groups can be both website errors or application errors – like a login error page.

Gaming Application: Clash of Clans

We all use our mobile devices for incredibly important things, like waging medieval warfare on other clans! HA! Anyone out there like Clash of the Clans?

You can categorize app content using Google Analytics Content Groupings.

You can categorize app content using Google Analytics Content Groupings.

In reality, gaming apps are very similar to other business models – like publishing and commerce. Some games generate revenue from in-game ads while others up-sell users on features, like new levels. Some do both. We can group games content together just like we do ecommerce.

Game level screens: Most of the content for a game is probably level based. We can replicate this base structure in Google Analytics. If you’re a fan of Clash of the Clans then you there are other parts to the game in addition to levels. There are attack screens, chat windows, etc. All of these screens can be added to groups to roll-up the data.

Ecommerce screens: These screens are used to sell the user on pay features. In the case of Clash of Clans you can buy more gems, which can then be used to purchase other items, like more armies!

I would put all ecommerce app screens into a separate content group.

I would put all ecommerce app screens into a separate content group.

Configuration screens: Most apps have a configuration section. This is where the user can change everything from the language, to colors, etc.

Error screens: Last but not least we have error screens. Again, these can be technical app errors or functional errors, like login issues.

For Publishers: MarketingLand.com

Let’s face it, content grouping was made for the publishing industry! They’re the ones that have to organize thousands of pages of content. I don’t want to dwell on publishing too much, but let’s take a look at MarketingLand.com, a popular destination for anyone working in the digital marketing world.

I’ve actually written about how to customize google analytics for publishing sites in the posts Custom Variables for Publishers and how to measure how far users scroll down a page. I think both of those techniques still apply.

But now, if you’re a publisher, you can also use content groupings to organize the data about your content. This provides one more way to roll up data for analysis.

Content Category: Almost all publishers group content by category – and now this can be done with the content grouping feature.

Publishers can create content groups based on the organization of their content.

Publishers can create content groups based on the organization of their content.

Some publishing sites organize content in other ways, like by author or publication date. I would suggest creating content groups for topic categorization, and custom dimensions for any secondary organization (author, date, etc.)

Account pages: Some publishers, like the New York Times, offer a premium membership service. This is not the case with MarketingLand.com. But, if it did have a member’s section, you could group all of those pages together.

Error pages: Do I need to go over this again :)

I hope this post provides some inspiration for how you might use Content Grouping for your business. Ultimately how you organize your content groupings will be based on your organization. There is no right or wrong – just use a structure that is useful.

Questions or comment? Leave a note below – and happy grouping!

How to Use Google Analytics Content Grouping: 4 Business Examples is a post from: Analytics Talk by Justin Cutroni

The post How to Use Google Analytics Content Grouping: 4 Business Examples appeared first on Analytics Talk.

How to Set Up Google Analytics Content Grouping

Today everyone is creating content – lots and lots of content. Measuring that content can be a challenge given the sheer volume that’s out there. That’s where Google Analytics Content Grouping can help. This feature let’s you categorize your content based on your own business rules. Then, rather than view your data based on page […]

How to Set Up Google Analytics Content Grouping is a post from: Analytics Talk by Justin Cutroni

The post How to Set Up Google Analytics Content Grouping appeared first on Analytics Talk.

Today everyone is creating content – lots and lots of content. Measuring that content can be a challenge given the sheer volume that’s out there. That’s where Google Analytics Content Grouping can help.

This feature let’s you categorize your content based on your own business rules. Then, rather than view your data based on page URL or screen name, you can view based on your specific groups.

In this post I’m going to talk about how content grouping works and how you set it up.

Key Vocabulary: Groupings and Groups

There is a little terminology we need to cover before we get into the setup: groupings and groups.

You can create multiple content groupings in Google Analytics.

Within a grouping you can create multiple content groups.

A group is a collection of content. It could be pages in a certain section of your website. Or it might be screens from a certain part of your app. It can be just about anything.

A grouping is just a bunch of groups.

Each content grouping contains multiple content groups. A content group contains multiple pieces of content.

Each content grouping contains multiple content groups. A content group contains multiple pieces of content.

You can create multiple content groupings in Google Analytics and switch between them in the reports.

Here’s an example. For my blog I created a grouping called Blog Content Categories.

Within that grouping I create a number of groups to categorize the different types of content on my blog. There’s a group for posts, a group for about me pages, a group for error pages, etc. In the configuration I created a rule that puts each page in a group based on the structure of the URL.

You can view your content data based on groups, rather than URL, screen name or title.

You can view your content data based on groups, rather than URL, screen name or title.

Any item that is not added to a group will appear in the (not set) content group.

It’s important to know that there is not one specific report where you access this data. When you create a grouping it’s literally becomes a new dimension of data. You choose to view that dimension in almost all of the content reports.

Let’s take a look at how you actually create a grouping and groups.

Creating Groupings & Groups

Google Analytics does not automatically create content groupings – you must configure the tool to do that. Navigate to the settings for a specific view and choose Content Groupings.

Content Grouping is a view level setting.

Content Grouping is a view level setting.

Here you will see a list of all your groupings. You can choose to create a new group or edit an existing group.

Here's a list of your Google Analytics content groupings. You can add or edit groupings here.

Here’s a list of your Google Analytics content groupings. You can add or edit groupings here.

There are three methods you can use to create a content group – let’s take a look at each.

Tracking Code Method

This method requires you to add a small piece of code to each page on your site or in your app. The code will literally set the name of the content group when the page or screen renders. Here’s how the code would look for Universal Analytics:

ga('create', 'UA-XXXXXXXX-Y', 'example.com');
ga('set', 'contentGroup5', 'Group Name');
ga('send', 'pageview');

Or, if you’re working in iOS the code might look like this:

id tracker = [[GAI sharedInstance] trackerWithTrackingId:@"UA-XXXX-Y"];
[tracker set:[GAIFields contentGroupForIndex:5]
value:@"Group Name"];

The code for a content group is similar to the code for a custom dimension. You can set 5 content groups using the tracking code. Each group is associated with a number, one through five, as shown in the example above.

Check the Google Analytics support documentation for more code examples.

Basically this method let’s you suck in the group name, via code, from some other system. It might be a CMS, a data layer, or just the HTML of the page.

The key is that you somehow add the name of the group to the Google Analytics code.

Pros: Using the tracking code method you can use code to automatically adjust to changes in your content and new content groups.

Cons: It requires IT involvement to set up. But once it’s configured very little IT support.

I should also mention that content grouping is coming to Google Tag Manager. This will provide another way to programmatically set the content group – so stay tuned.

Extraction Method

The extraction method extracts (get it) the name of your content groups from an existing dimension of data. The idea is that you use a regular expression to parse the dimension and automatically extract the name of your group.

For example, the name of your content groups might be in the page title, like this:

Your website might use the name of the content in the Page Title or Screen Name dimension.

Your website might use the name of the content in the Page Title or Screen Name dimension.

I would need to specify that my group name is in the Page Title dimension, and then provide a regular expression that extracts the appropriate value.

The content grouping extract method will automatically pull the name for a content group from a dimension of data.

The content grouping extract method will automatically pull the name for a content group from a dimension of data.

For those of you that do not use regular expression, the value in the parenthesis will automatically be extracted. Google Analytics will then use the value as the group name.

You can see that this one rule will work for every product page on my site – as long as they are well formatted.

Pros: No coding involved. Flexible collection.

Cons: You might need to update your regular expressions when you add new content to your site or app. Specifically something that does not match your existing rules. Believe me – updating settings SUCKS. People forget to do it all the time.

In you’re new to regular expressions check out this reg ex tutorial in the Google Analytics help center.

Rules Method

The rules method is almost exactly like the extract method. The ONLY difference is that you have to MANUALLY name the group. The value for the name is not automatically pulled from a dimension of data.

The content grouping extract method will automatically pull the name for a content group from a dimension of data.

The content grouping extract method will automatically pull the name for a content group from a dimension of data.

Like the extract method you can create rules based on different dimensions of data- the page title, page url or the screen name. If the dimension value matches the rule then the content is added to the group.

Pros: No coding. Don’t need to know regular expressions.

Cons: You need to remember to update your rules when you add new content or if your site urls or app screen names change. Again – updating your analytics settings SUCKS. People forget to do it all the time.

Which method should you use?

That’s a tough question. Personally, I think page category is a critical piece of data that should be added to a page data layer. If you take this approach then using the tracking code method is very scalable.

I also like the extract method. It’s very flexible and reliable – as long as you have processes in place to maintain your implementation :)

Important things to know

Ok, so here are a few very important things to know.

You can use all three methods for creating groups within the same content grouping.

The grouping logic is applied to your data sequentially. That means that Google Analytics first applies the tracking code method first. Then it applies the extraction method. And finally it applies the rules method. You can use all three methods for your implementation.

When a page or screen matches a rule it is added to that group.

A page or screen can only be in ONE content group at a time! That means that an page or screen can only belong to one group at a time.

And finally, content groups are NOT applied to historical data. They are only applied from the moment you configure the feature.

A Best Practice

Because Google Analytics applies all grouping methods to your data, it is possible to use a combination of grouping methods.

But, because they they are applied SEQUENTIALLY, it’s a good idea to put your very specific grouping rules first, followed by your general rules. This way the later, general rules will catch anything that slips through the early, specific rules.

Content Group methods are applied sequentially.

All three content grouping methods are applied to each piece of content. They are applied sequentially.

It’s really, really important to try and get your groups right the first time. While you can edit your groups, there is no way to change the data that has already been processed.

Make sure you test your groups first before announcing them to your entire team.

It’s also a good idea to add an annotation to Google Analytics so everyone knows when the data was added.

Ok, I think that’s it for how to implement this feature.

Don’t worry – I’ll explain how to use content groups in a couple of days.

How to Set Up Google Analytics Content Grouping is a post from: Analytics Talk by Justin Cutroni

The post How to Set Up Google Analytics Content Grouping appeared first on Analytics Talk.

Dimension Widening: Import data directly into Google Analytics

There are lots of different ways to put data in Google Analytics. You can collect data from a website with JavaScript. You can collect data from an app using an SDK (Android or iOS). Or you can collect data from any network connected device using the measurement protocol. But there’s another way to add data […]

Dimension Widening: Import data directly into Google Analytics is a post from: Analytics Talk by Justin Cutroni

The post Dimension Widening: Import data directly into Google Analytics appeared first on Analytics Talk.

There are lots of different ways to put data in Google Analytics. You can collect data from a website with JavaScript. You can collect data from an app using an SDK (Android or iOS). Or you can collect data from any network connected device using the measurement protocol.

But there’s another way to add data to Google Analytics – you can import data using a feature called Dimension Widening.

You can add data to Google Analytics a number of ways - including Dimension Widening.

You can add data to Google Analytics a number of ways – including Dimension Widening.

With Dimension widening you can import additional dimensions and metrics directly into Google Analytics via a CSV upload or programmatically import data via an API.

Let’s take a look at how you might use Dimension Widening to augment the data in your account, and ultimately do better analysis.

Why Add More Data?

Analytics is more valuable when you can align the tool more closely with your business strategies and tactics. Adding additional data, like customer history, content publishing information, advertising cost data, etc. can help provide context to your data, thus making it easier to gauge performance and identify opportunities for improvements.

Adding additional data can also streamline your reporting (yes, basic reporting still happens) by consolidating all of your data in a single system that everyone has access to.

That’s where Dimension Widening comes in.

It is a mechanism to move data into Google Analytics.

How Dimension Widening works

You can upload two types of data to Google Analytics: Dimensions and Metrics.

A dimension is an attribute of a user or the sessions she creates.

A metric counts something – like time, money, clicks, etc.

When you use Dimension Widening you are uploading values for one or more dimensions or metrics.

You can upload values for existing dimensions/metrics or you can upload values for new dimensions/metrics that do not exist in Google Analytics.

When Google Analytics process the data it will join your custom data to the the existing data using something called a key.

The key binds your data, the data uploaded in a CSV file or sent programatically, to the Google Analytics data. When Google processes the custom data it will look at the value for the key, and then try to find the same value in the Google Analytics data.

If Google Analytics finds a matching keys then it will take the data in that row of the custom data and pull it into Google Analytics.

The key links your custom data to the data in Google Analytics.

The key links your custom data to the data in Google Analytics.

There are four basic steps to configuring Dimensioning Widening.

1. Identifying the data you want to import.

Step one is really simple, identify the data that you want to add to Google Analytics.

Remember, you can import a value for any dimension or metric that currently exists in Google Analytics. OR you can import values for custom dimensions and custom metrics that are not normally found in GA – more on this below.

When choosing the data you want to import ask yourself this – what data to I need to understand the behavior of my users? How can I make my analytics life easier by consolidating data in Google Analytics?

You also need to define your key. This is obviously critical. If you can’t define a key then you can’t import data.

2. Create the schema in Google Analytics.

Once you define your key and the dimensions/metrics you want to import it’s time to add the schema to Google Analytics. Think of this step as telling Google Analytics how to interpret the CSV file (or data feed) that you will import.

Choose a property in the admin section, then choose Data import and Dimension Widening.

The Dimension Widening settings are in the Data Import section of a property.

The Dimension Widening settings are in the Data Import section of a property.

To begin you need to name the data set you will import. You can actually upload multiple data sets (more on this later), so make sure you name it something very descriptive, like “Campaign Data” or “Content Information”.

Then choose the view where you would like the data applied.

Every data set must have a name, and you must specify which views to apply the data to.

Every data set must have a name, and you must specify which views to apply the data to.

TIP: Dimension widening will permanently change the data in a reporting view! It’s a good idea to test your dimension widening on a TEST view before applying it to your main reporting view.

Now add the schema. First, add the key that you’ve defined for your data.

Next, specify the dimensions and metrics that you want to add.

You must enter a schema into Google Analytics. Add the key along with the dimensions you would like to widen.

You must enter a schema into Google Analytics. Add the key along with the dimensions you would like to widen.

Here’s something cool – as you choose your key and dimensions Google Analytics will automatically show you the column headings that you will need to add to your CSV file.

As you add your schema Google Analytics will provide the column headers for your CSV file.

As you add your schema Google Analytics will provide the column headers for your CSV file.

Notice that they’re not the names that appear in the drop down boxes. They’re the dimension/metric names that are used in the API. Fear not – you don’t need to understand what they mean.

3. Build your CSV file.

Once you finish defining your schema choose save.

You’ll be presented with two options: get more details of your CSV file OR get an API key to upload your data programatically. Let’s focus on the Get Schema option.

Once you define your dimension widening schema you can download a CSV template or get an API key.

Once you define your dimension widening schema you can download a CSV template or get an API key.

Click the Get Schema button.

This window contains some really useful information. First, a list of the column headers that you need to add to your CSV file. This includes your key and all the other dimensions that you are adding to Google Analytics.

There’s also a way to download a CSV template for your specific data. The template is just an Excel file with the headers added to the first row.

Google Analytics will provide the column headers for your CSV and provide a CSV template that you can fill with your data.

Google Analytics will provide the column headers for your CSV and provide a CSV template that you can fill with your data.

4. Upload your CSV file or Send Data via API

Remember, there are two ways to add your data – via an API or manually via a file upload process. Let’s focus on the later – the file upload.

This isn’t too complicated, just click upload :) Once the file is uploaded Google Analytics will widen your data as it is processed.

You can check on the processing of your data using the Refresh button.

You can check on the processing of your data using the Refresh button.

NOTE: when you use Dimension Widening the data you import is NOT applied to historical data. Your data is only applied going forward.

I find that GA can process the file very fast (minutes). You may want to refresh your list often to determine if the new data has been added.

That’s it! That’s the basic process.

But you probably want to use Dimension Widening to import custom data, not data that’s already in Google Analytics. Let’s take a look at how to do that.

How to add Custom Data

You can also add custom dimensions and custom metrics to Google Analytics via dimension widening. The process is almost exactly the same. The only difference is that you must first define your custom dimensions or metrics in the Google Analytics admin section.

To upload a dimension or metric that does not exist in Google Analytics you must first define those custom dimensions or metrics.

To upload a dimension or metric that does not exist in Google Analytics you must first define those custom dimensions or metrics.

There’s not a lot of configuration here. Just give your dimension a name and choose a scope.

NOTE: You can only widen between dimensions and metrics of same scope. For example, you can’t widen from user scope Key to Hit scope dimensions. Check out this (somewhat old) article on Custom Variables to learn more about scope.

That’s it. Now you can choose these custom dimensions (or metrics) when you add your schema for Dimension Widening.

Once you define a custom piece of data it will be available in the Custom Data schema interface.

Once you define a custom piece of data it will be available in the Custom Data schema interface.

Then create your CSV file with the correct headers and upload your data.

Note: Custom Dimension and metrics are only available in Google Analytics customizations – this includes custom reports, custom segments and dashboards. They can also be used in certain analysis tools, like secondary dimensions.

An Example: Uploading simple publisher data

Let’s say I’m a publisher. I want to add the publication year, author for each article. My key to join my data with GA data is the URL of each page. I already defined two custom dimensions, one for page publication year and one for page author.

I’m going to define my data schema in Google Analytics.

Defining a custom data in your dimensions widening schema.

Defining a custom data in your dimensions widening schema.

Now I build my CSV file using the correct headers for my key and dimensions that I would like to widen.

A sample CSV file with custom dimensions.

A sample CSV file with custom dimensions.

Next I upload my file…

And finally, I have data in my custom dimensions. Here I can see the data in a Custom Report.

Custom Dimensions can be used in a Custom Report, Unified segment or other customization features.

Custom Dimensions can be used in a Custom Report, Unified segment or other customization features.

Best Practices for Managing CSV files

You might want to widen your data based on multiple keys. For example, you might want to widen your product data (using the product ID as a key) and your campaign data (using campaign name as a key).

In this case you’ll need to define two different schemas and upload two different CSV files. Make sure you name them something logical!

Another thing to consider is when to update your CSV files.

For example, let’s say that you’re a publisher, and you’re uploading new data about your content. But you’re publishing new content every day. And probably multiple times a day. You would need to upload a new CSV file every time you publish content. This is too manual. In case you probably want to consider a programmatic solution.

Use the CSV file for things that do not change often. Use the API for things that change a lot!

What about JavaScript and real-time collection?

Given my previous example, you may be asking yourself, “can’t I just collect custom data in real-time using JavaScript?”

Absolutely!

You could do something fancy, like add the data to a data layer, then pull it into some custom dimensions. No problem!

The point is that you don’t always have the time or the IT resource to implement the data collection. Even if you use a cool technology like tag management, it may be that the data you want to add comes from an isolated system. And that it would take too much effort to transport the data from it’s home all the way to the web server.

Dimension widening can be seen as a somewhat faster, less IT intensive way of joining your data together.

Things to be aware of…

Ok, a few things that you need to be aware of when using Dimension widening.

1. Your data is NOT applied to historical data. Your data is only applied going forward.

2. You can NOT widen on ALL dimensions. You can NOT widen on the following dimensions:

  • custom variables
  • product dimensions and metrics
  • campaign dimensions
  • time-based dimensions (hour, minute, etc)
  • geo-dimensions (country, city, etc)

3. If you would like to expand your dimensions and populate Custom Dimensions you MUST use Universal Analytics. The reason is that Custom Dimensions only exist in Universal Analytics. They do not exist in the previous version of Google Analytics.

4. You can not change a schema once it has been entered into Google Analytics. You must delete the schema and then define your new schema.

I know some of these caveats may seem limiting, but remember, this is just the initial version. I know the team is working hard to expand the functionality.

Do you think you will use Dimension widening? If so how? Feel free to share your examples below!

Dimension Widening: Import data directly into Google Analytics is a post from: Analytics Talk by Justin Cutroni

The post Dimension Widening: Import data directly into Google Analytics appeared first on Analytics Talk.

Bye Bye JavaScript! Auto Event Tracking with Google Tag Manager

Implementing analytics, or any type of conversion tracking, is a big pain in the ass. There, I said it! But it’s been getting easier and easier with adoption of Tag Management tools. Google Tag Manager is going to make it even easier with the introduction of a new feature called Auto Event Tracking. Auto Event […]

Bye Bye JavaScript! Auto Event Tracking with Google Tag Manager is a post from: Analytics Talk by Justin Cutroni

The post Bye Bye JavaScript! Auto Event Tracking with Google Tag Manager appeared first on Analytics Talk.

Implementing analytics, or any type of conversion tracking, is a big pain in the ass. There, I said it! But it’s been getting easier and easier with adoption of Tag Management tools. Google Tag Manager is going to make it even easier with the introduction of a new feature called Auto Event Tracking.

Auto Event Tracking let’s you track almost any user action without any additional JavaScript. It automatically captures user actions like clicks and form submissions.

TL;DR: watch this video.

For all you Google Analytics users, this means that it is no longer necessary to add JavaScript to track PDF downloads, outbound links or other user clicks. Those tasks, and many others, can be automated with Google Tag Manager.

I know – it’s exciting! Less coding = faster data collection = more reliable data quality = better insights.

There are a number of new additions to GTM that make auto-event tracking possible. Let’s take a look at how the system has changed to make this possible.

How Auto-Event tracking works

Here’s a brief overview of how the new auto-event tracking works.

Listen, Capture Collect. How the Auto-event tracking works for Google Tag Manager.

Listen, Capture Collect. How the Auto-event tracking works for Google Tag Manager.

1. Listen: A new type of tag, called an Event Listener tag, will listen for different types of user actions, like clicks or form submissions.

2. Capture: When the Event Listener tag detects an action it identifies it and captures it (technically it pushes a Google Tag Manager event onto the data layer).

3. Collect: You can then automatically collect the action using additional tags, like an analytics tag.

Remember, this all happens without any additional coding. All you need to do is add the necessary settings in GTM.

There are three new pieces of functionality that make this possible:

1. The new Google Tag Manager Event Listener tag.

2. New events that indicate a user action has occurred.

3. New macros that collect information about the user’s interaction with the content.

The Event Listener Tag & Automatic Events

Let’s start with the new tag, called The Event Listener tag. This is a special tag that – wait for it – listens for a user action on a page :)

When the tag detects an action it automatically collects the action and identifies it. From a technical perspective is pushes a Google Tag Manager event to the data layer.

There are four different types of user actions that the tag can detect. Again, each action results in a Google Tag Manager event.

Click listener: this tag will listen for clicks on a page. This includes button clicks, link clicks, image clicks, etc. When a click occurs, the Google Tag Manager event gtm.click is automatically generated.

Form listener: this tag will listen for any form submissions. When a form submission occurs the Google Tag Manager event gtm.formSubmit is automatically generated.

Link click listener: same as the click listener, except it only captures clicks on links. When a link is clicked, the Google Tag Manager event gtm.linkClick is automatically generated.

Timer listener: the timer listener will collect data at some regular interval that you specify. For example, if you specify an interval of 10,000 milliseconds, GTM will fire an event every 10 seconds.

Obviously, if you want to automatically listen for user actions you must include one of the above tags on the page where you would like to capture the user action.

For example, let’s say you want to capture clicks on outbound links (this means links to other websites). Chances are you have outbound links on all of your pages. So you should add the Link Click listener tag to all pages of your site.

Remember, to add a tag you need to specify a rule that governs when the tag is added to a page. Here’s the default rule to add a tag to all the pages on your site.

Use the GTM All Pages rule to add a common event listener to every page on your site.

Use the GTM All Pages rule to add a common event listener to every page on your site.

But let’s say you want to capture a form submission, like a contact form. There really isn’t any need to include that tag on all of your site pages. So you can create a rule to add the tag to just your form page, like this:

To control the form listener tag, restrict the placement with a rule.

To control the form listener tag, restrict the placement with a rule.

The new Events are important because they identify that an action has happened. I’ve got some example below.

Understanding the New Auto Event Macros

In addition to the new tags & events there are also a number of new macros that help collect the action that occurred.

A macro is a piece of data that you can use in your tags. Some macros are automatically populated, like the url macro (which is the url of the page), the hostname macro (which is the hostname of the site), or the referrer macro (which is the HTTP referrer).

With the Auto Event Tracking macros you can automatically add data about the element the user interacted with to your analytics tag (or any other tag).

There are five new macros that can provide elements information:

Element url: This macro stores the value of the href or action attribute of the element that triggered the event. For example, a click on the link < a href="http://www.cutroni.com">Analytics Talk< /a> would result in an value of http://www.cutroni.com.

Element target: This macro stores the value of the target attribute of the element that triggered the event. Nerd Bonus: The value is stored in the gtm.elementTarget variable in the data layer.

Element id:This macro is the value of the id attribute of the element that triggered the event. For example, a click on the link < a href="http://www.cutroni.com" id="outbound_link">Analytics Talk< /a> would result in an element id value of outbound_link. Nerd Bonus: The value is stored in the gtm.elementId variable in the data layer.

Element classes: This macro is the value of the class attribute of the element that triggered the event. Nerd Bonus The value is stored in the gtm.elementClasses variable in the data layer.

Element: This macro is also the value of the action or href attribute of the element that triggered the event.

Let’s put this all together and look at some of the common analytics tracking tasks you can implement with data layer.

Tracking Clicks

Sometimes we need to track user clicks – a click on a button, image or link. Before Auto Event Tracking we would need to add extra JavaScript to the site in order to fire analytics code. Now we just use the Click Listener tag to detect a click.

Let’s walk through how to track ALL clicks on a page and capture them with a Google Analytics event.

First, add the Click Listener tag to the necessary pages. You can add it to all pages, or just a select few. It depends on what you need to track.

The Click Listener tag will listen for user clicks and execute when a click is detected.

The Click Listener tag will listen for user clicks and execute when a click is detected.

Next, we add our Google Analytics tag to execute, and thus collect, when the click happens. Notice that I am hard-coding the Event Category to be click but the Action and Value will be dynamically populated with data from the HTML element that the user clicked on.

We can use a GTM macro to automatically capture the HTML element that the user clicked on.

We can use a GTM macro to automatically capture the HTML element that the user clicked on.

The value of the action is capturing the generic name of the HTML element. This might be [object HTMLInputElement] for a form element or [object HTMLBodyElement] for the body of the page. These are fairly descriptive and can help you understand what happened.

But a better strategy would be to capture the element class or element id. These are usually more descriptive.

Here’s the rule that determines when to acctualy collect the click. Basically it will collect EVERY click on the page using a Google Analytic event. We’ll look at a few examples later that will restrict the collection to only certain elements.

The gtm.click event indicates that a user clicked on something. This causes the Google Analytics tag to fire.

The gtm.click event indicates that a user clicked on something. This causes the Google Analytics tag to fire.

I should note that this approach will NOT work for content that is in an iFrame. For example, if you embed a YouTube video in your page, you can not capture clicks on the buttons, etc.

Using this general approach can generate a lot of data – crappy data! Let’s look at reducing the amount of data by tracking certain types of clicks.

Tracking Outbound Links

We all want to know where people go after they visit our site. Did they leave using a link in an article or did they just navigate away?

To track a click on an outbound link we follow the same general process we outlined above. The big difference is we need to make sure we only track clicks on links that go to another site.

First, we add the Link Click Listener tag to the necessary pages. Because there usually outbound links on every page, I apply the Link Click Listener tag to every page on the site.

The Link Click Listener tag will listen for user clicks on links.

The Link Click Listener tag will listen for user clicks on links.

Now we need to add an analytics tag to collect data when a click happens. Let’s use Google Analytics and collect the data in an event! Notice that I am hard-coding the Event Category value to outbound-link.

The Event Action will be dynamically filled with the destination URL. That’s the URL of the page the user will land on. This is all made possible thanks to the element url macro.

The element url macro will automatically add the destination url to the Google Analytics event.

The element url macro will automatically add the destination url to the Google Analytics event.

Here’s the important part – the tag rule. Notice that there are two parts to the rule. First I need to check for clicks on links. But I also added an additional condition that stipulates the link must not match cutroni, which is the domain of this blog. Now the Google Analytics tag will only fire and collect the click if the link is to a different domain.

Add a rule to specify what is an outbound link clicks on your site.

Add a rule to specify what is an outbound link clicks on your site.

Tracking file downloads

File downloads are very similar to outbound link clicks. I just use a different Listener tag.

Let’s just skip to the analytics tag that will collect the data.

I’m using a Google Analytics event again. The category is hard coded as file-download. The event action will be the URL of the file and it will be dynamically populated using the element url macro.

The element url macro will automatically add the PDF url to the Google Analytics event data.

The element url macro will automatically add the PDF url to the Google Analytics event data.

Just like I did with the outbound link tracking, I need to modify the rule to include a condition. The condition specifies that the user clicked on a link that contains .pdf.

To track a PDF link click add a condition to your tag firing rule.

To track a PDF link click add a condition to your tag firing rule.

Hopefully you can use this example and track clicks on any type of file that you want.

Tracking Form Submissions

Now let’s move on to forms. You could track a form using the Click listener tag. Basically you would track all of the clicks on the Submit button. But the form

We start with the Form Submission listener tag. Rather than add this tag to every page on the site, I like to only add it to pages where there is a form.

The form listener tag can be configured to delay the form submission while data is collected.

The form listener tag can be configured to delay the form submission while data is collected.

ALso notice that you can configure the form listener tag to delay the form submission to insure that the data is collected.

The tag will delay the form for up to two seconds only. Anything longer than that will create a bad user experience. GTM is smart like that :)

Just like the click tracking, there is also a form-submit event that will be generated when a user submits the form. We use this event to set up our analytics tag with a rule to control the execution.

This rule will only fire the Google Analytics event tag when a form is submitted.

This rule will only fire the Google Analytics event tag when a form is submitted.

I can actually pull some of the data in the form elements directly into my analytics tag using a macro.

For example, let’s say I have a form element named Gender. I can use a macro to capture the data, then use that macro when I define my Google Analytics Event, like this:

You can collect data from a form element using a macro and send the data to Google Analytics.

You can collect data from a form element using a macro and send the data to Google Analytics.

REMEMBER it’s not cool to collect personally identifiable information.

Here’s a bit more information on creating and using macros.

But overall, tracking a form submission is fairly straight forward. Very much like the other scenarios above.

There you have it, some of the common ways to use the new Auto Event Tracking feature.

That was a really looooong post. Hopefully it gave you a good understanding of how this feature works and how you can use it to make data collection easier to implement and maintain.

Give auto-event tracking a shot and be sure to share your experience in the comments below.

Bye Bye JavaScript! Auto Event Tracking with Google Tag Manager is a post from: Analytics Talk by Justin Cutroni

The post Bye Bye JavaScript! Auto Event Tracking with Google Tag Manager appeared first on Analytics Talk.

Local Marketing With Google Adwords Express

In 2011 Google launched what they called AdWords Express dubbing it ‘the easiest way to advertise on Google.’ In this article I’ll cover some pros and cons of the service as well as clear up a few informational elements surrounding th…

In 2011 Google launched what they called AdWords Express dubbing it ‘the easiest way to advertise on Google.’ In this article I’ll cover some pros and cons of the service as well as clear up a few informational elements surrounding this new advertising channel and how it differs from traditional Google AdWords. First understand that […]

Local Marketing With Google Adwords Express is an article taken from: Ecommerce Optimization & Marketing protected under copyright law. Reproduction in any form without consent is strictly prohibited.

If you want to find out how to increase your website conversion, increase sales, and win more customers you should visit the original Ecommerce Optimization site.

The post Local Marketing With Google Adwords Express appeared first on Ecommerce Optimization & Marketing.

Mobile Marketing Trends

Like the TV before it and the computer after that, at one point it may have been hard to imagine much less believe that mobile devices would be a regular part of daily life for the majority of the population. On a planet with approximately 7 billion pe…

Like the TV before it and the computer after that, at one point it may have been hard to imagine much less believe that mobile devices would be a regular part of daily life for the majority of the population. On a planet with approximately 7 billion people, 2011 saw an astonishing 5.3 billion mobile […]

Mobile Marketing Trends is an article taken from: Ecommerce Optimization & Marketing protected under copyright law. Reproduction in any form without consent is strictly prohibited.

If you want to find out how to increase your website conversion, increase sales, and win more customers you should visit the original Ecommerce Optimization site.

The post Mobile Marketing Trends appeared first on Ecommerce Optimization & Marketing.