SEO Blog

Posts Tagged ‘Analytics’

2 New Tools in Google Analytics: Real-Time Widget and Benchmark Tool

Posted by:  /  Tags: , , , , , ,

2 New Tools in Google Analytics: Real-Time Widget and Benchmark Tool was originally published on, home of expert search engine optimization tips.

Google Analytics is every Internet marketer’s best friend. The tools are always changing and updating, making the Google Analytics blog an important one to keep up on so you know the features, capabilities and data available to you. There are a couple new tools that got us really excited because of the intel they provide about how visitors are using our sites. Learn about the new Customer Journey tool and the Real-Time Widget now available through your Google Analytics account.

The Customer Journey to Online Purchase

Google is offering more detailed information to make marketer’s lives easier. On April 25, Google introduced a new benchmarking tool for marketers: The Customer Journey to Online Purchase.

The tool is Google’s response to:

  • The increasing complexity of the customer journey and
  • The increasing need of marketers to make sense of the contribution of each marketing channel in the final purchase so that they can improve their strategy accordingly.

Before committing to buy online, a customer may engage with a specific brand through many different media channels over several days (or even months, in some cases).

Based on the different sectors, different marketing channels come into play at different times and contribute to the final purchase decision.

The tool has been built on data gathered from over 36,000 Google Analytics clients that authorised sharing, including millions of purchases across 11 industries in 7 countries (Australia is not included at the moment).

As it is explained on the Official Google Analytics blog, the tool includes benchmark data for:

  • How different marketing channels (such as display, search, email, and your own website) help move users towards purchases. For example, some marketing channels play an “assist” role during the earlier stages of the marketing funnel, whereas some play a “last interaction” role just before a sale.
  • How long it takes for customers to make a purchase online (from the first time they interact with your marketing to the moment they actually buy something), and how the length of this journey affects average order values. The length of the customer journey, in both number of days and number of interactions, varies widely depending on the type of purchase. Some decisions require substantial research, while others are made very quickly. Typically, more complex purchases lead to longer paths and larger purchase values.

Implications of the Customer Journey to Online Purchase Tool

  • Online retailers need to understand their customer journeys in the context of how a broader data set does similar journeys.
  • By understanding the different stages of the customer journey, businesses can evaluate the success or otherwise of online campaigns and the role each one plays in the conversion.
  • Using this information will help to design campaigns that deliver the right message at the right moment in a customer’s journey to purchase.

Google Analytics New Feature: Real Time Widgets

This is better than TV!

On April 16, Google announced four real-time widgets that can be added to any new or existing Google Analytics Dashboard, marking the first time real-time data has been possible in a dashboard widget.

The widgets make it possible for users to perform many types of real-time analysis and they can also be combined and customised with different filters to segment and compare data side by side.

To set-up a Real-time widget, webmasters simply need to click the +Add Widget menu option from the Google-Analytics dashboard.

Once a widget has been added, they can select Counter, Timeline, Geomap or Table from the Real-time section.

  • Counters show the number of active visitors on the site, in a similar way to the prime “Right Now” counter on the Real-Time overview report. The major difference is that it is possible to determine what the dimension is, if any, to be shown under the counter. On the Real-Time Overview report it shows New vs. Returning users, while on the widget it is possible to select a different dimension to break out that counter’s numbers from the set 11 dimensions available in all the Real Time Widgets: Campaign, City, Country/Territory, Keyword, Medium, Page, Page Title, Referral Path, Source, Traffic Type, or Visitor Type.
  • Timelines show the scrolling pageviews over either the last 30 minutes or last 60 seconds.
  • Geomaps show visits on a map. It is possible to choose to display by country or cities, and drill down a region from a world map down to a national one.
  • Tables show active visitors, with up to three of the dimensions listed above.

Another widget that has been recently added (May 5) to the real time reports is “Goal Conversions”.

Google Analytics conversion widget

Google Analytics real-time conversion widget

Implications of the Google Analytics Real-Time Widget

  • This helps businesses to instantly see how traffic is moving around their website.
  • This gives insight at a very specific level, enabling specific decisions to be made.
  • Real time widgets provide a drill-down that immediately displays the data that matters.

Bruce Clay Blog

How to Build a Google Analytics Tracking Code

Posted by:  /  Tags: , , , ,

How to Build a Google Analytics Tracking Code was originally published on, home of expert search engine optimization tips.

Need more input? As an optimizer who is regularly looking to learn more about how my recipients are interacting with content, I find myself regularly consuming analytics reports filled with Google Analytics tracking code data like Johnny Number 5 eats the Encyclopedia Britannica in the above clip from the 1986 gem Short Circuit.

Google Analytics tracking codes —  also know as custom campaigns or UTM codes — are custom tracking parameters that communicate to Google Analytics granular information about how your referral traffic is interacting with your calls to action. To implement a UTM tracking code simply add your desired parameters to the end of the URL you want to track insights for, like this:

UTM tracking codes can help you analyze traffic from banner ads, email newsletters, social media content, and any other campaign that links people to a property that you own (such as your website or your blog). You cannot use UTM tracking to analyze clicks to external websites, like YouTube or To track click activity on links that send people to properties you don’t own, Bitly is a great free resource.

How To Put Together a Google Analytics Tracking Code

UTM_Source=Awesome Google Analytics tracking code parameter

Bruce Clay, Inc. does not recommend or condone using “awesome” as a Google Analytics UTM code parameter. (But we may or may not find it amusing.)

There are five possible parameters you can set for each UTM tracking code: Source, Medium, Campaign, Content and Term. You don’t have to use all of them. For this blog post I am going to show you show to create a UTM tracking code for a link that directs people from a blog post to a page on my website. To keep it simple, I am only going to discuss the parameters needed for this scenario — Source, Medium and Campaign.

Note: When and how to use Term and Content parameters is really a whole separate blog post; leave a comment if you are interested in seeing us write about it.

The Medium (&utm_Medium) is the most broad parameter and tells Google Analytics — big picture — how to classify the medium by which your link was presented to the user. For example, was the link presented in a Facebook wall post? Then the Medium might be “viral” because the link you posted to your Facebook wall is now spreading virally all over the Internet and, accordingly, was delivered via a “viral” medium. (If viral is too abstract for you, “social” could also work.) Was the link transmitted to the end user via an email newsletter? Then your Medium might be “email,” or even more specifically, “ConstantContact” or “CheetahMail” to identify the service that delivered your newsletter. In our example above, our link was a blog post, so we used &utm_medium=viral.

Getting one step more specific from Medium, the Source (&utm_Source=) tells Google Analytics where the click came from, where the person was when they clicked the link. In our example above (utm_source=blog) the person clicked on a link that was posted to my blog (so the Medium is “viral,” and the Source is “blog.”). Other Source options might include Twitter, Facebook or newsletter (Medium equals “email” and Source equals “newsletter”).

The Campaign parameter (&utm_Campaign=) is one step even more specific than Source, and the parameter where you can really start to get granular with your tracking. The Campaign is how you identify the specifics of a link, from the details of where it goes all the way down to the color and size of the call to action. In the example above I used &utm_campaign=CRO-JThompson-image because I wanted to identify which of my silos encouraged the most clicks, the longest time on site, and — at the other end of the spectrum — the most site exits. I also wanted to collect data to help me determine which of my authors are being read the most, and if an image call-to-action perform better than a text call to action. If this link was a banner ad I might have included the dimensions of the banner (for instance 320 or 160) to help determine which banner size encourages more clicks. If I wanted to test how well a link to free content performs versus how well a link to paid content performs I might have included “free” or “paid” as Campaign parameters.

Six Essential Google Analytics Tracking Code Details

  •  Every UTM tracking code starts with a question mark. For example: ?utm_. This question mark tells Google Analytics where your link URL ends and your tracking starts. If you don’t include the question mark Google will think your link is which, as an alteration of the URL permalink, will result in a 404 error. The question mark is important.
  • There are five possible parameters you can set for each UTM tracking code: Source, Medium, Campaign, Content and Term. The parameters you choose to use are strung together in one sentence (no spaces) and separated by ampersands (&). It doesn’t matter what order you list your parameters in, but your first parameter must start with a question mark and all the following parameters must start with ampersands. The & tells Google Analytics where one parameter ends and the next begins. If you forget the ampersand and write your code like &utm_medium=viralutm_campaign= Google Analytics will think that your Medium is “viralutm_campaign=” which, as you can imagine, will skew your Medium and Campaign data pretty badly.
  • Since the Google Analytics URL builder makes it easy for any of your team members to create and assign UTM tracking codes it is critical to have a discussion about UTM parameter conventions before anyone on your team starts creating UTM codes willy-nilly. I highly recommend creating a spreadsheet or other living document (a Google Drive spreadsheet works great) that clearly outlines conventions for Source, Medium, and Campaign. (If you are using Content and Term parameters regularly, make sure to add conventions for those parameters as well.) You may even consider taking your spreadsheet to the next level to establish a record of every link posted and its associated Campaign allocations. While a spreadsheet that documents every link your company pushes out is a larger commitment, these resources become invaluable as associates join and leave your team.

Note: If you’re crafty you’ve noticed the links in this blog post have not been amended to include Google Analytics UTMs. This is because the Bruce Clay, Inc. content team is  currently developing our analysis goals and tracking conventions. Since I am a data-hungry Johnny Number 5 monster I have been using Bitly as my personal one-man-band interim tracking convention because I can’t survive a minute without data. I do not recommend this as it’s not scalable long-term. 

  • UTM codes are case sensitive so Google Analytics will collect data for potatoes and Potatoes as two separate reports. This means, since Google Analytics does not have the human sensibility to tell you that there is a capitalized version of your Campaign floating around somewhere in your referral traffic data, you may be analyzing incomplete data if your team isn’t careful about capitalization.
  • Hyphens allow Google Analytics to understand each word individually; underscores are considered alphanumeric characters and connect words to make phrases (see dashes vs. underscores for more detail). For instance: sandals-coupon versus sandals_coupon. If you are building UTM codes for a newsletter send it might make sense to use an underscore to connect your newsletter identifier with the release date of the newsletter — for instance, DealerUpdates_2013July09-colorado. In this example you will be able to find data in Google Analytics for the specific term “DealerUpdates_2013July09” which will tell you exactly how that specific dealer updates newsletter that was sent out on July 9, 2013 performed. You are also able to analyze how every email sent to your Colorado demographic performed, but because “DealerUpdates_2013July09”and “Colorado” are separated by a hyphen the Colorado data will not be exclusive to the July 9 email.
  • Worth noting again, you must own a URL in order to attach UTM tracking to it. In other words, you can only use UTM tracking to assigned parameters to links that go to your properties — your website, your blog, your app, etc. You cannot use UTM tracking to analyze clicks that go to external properties like or

Why Use Tracking Codes?

I consistently use Google Analytics tracking codes to measure where my referral traffic is coming from, which of my initiatives are meeting traffic goals, how my target markets prefer to receive communication, and the ebb and flow of industry based on seasonality.

They give you a granular snapshot of your referral traffic, how your consumers (and potential-consumers) are interacting with the calls to action you’re putting out there, and they are a great way to quench an unrelenting need for specific ROI data.

Are you a Johnny Number 5? How have Google Analytics UTM codes made your life easier?

Bruce Clay Blog

Why Google Analytics Tagging Matters – Whiteboard Friday

Posted by:  /  Tags: , , , , ,

Posted by RachaelGerson

When Google Analytics doesn't know where a traffic source comes from, it assumes the traffic is direct and lumps it in with your direct visits. This happens frequenly with social shares, as many of us make the mistake of not tagging our links accordingly.

In today's Whiteboard Friday, Rachael Gerson sheds some light on "dark social" and explains why tagging in Google Analytics improves the accuracy of your referrals. Take credit for the work that you're doing, and tag your links!



Video Transcription

"Hi, everyone. I'm Rachael Gerson. I'm the head of analytics at SEER Interactive. We're a digital marketing agency in Philadelphia, although we are growing and spreading across the world. Although we're primarily known for our SEO, we actually have an amazing paid search team and a really talented analytics team. I want to share our story with you. The timing on this story is actually really convenient because it ties with what I wanted to talk to you about.

My sister wrote a blog post last night. She has a new blog. No one ever goes to it. I think I may be the only person who knows it exists. She wrote the post. I read it this morning and went, "This is really good content. I'm going to share this." And I put it out on Twitter.

She saw me share it, and she put it on Facebook and thought, "Okay. Let's see what happens." In the last 8 hours, she's gotten 74,000 page views to this one blog post. I'm looking at the real-time traffic right now, down here. There are 1,500 people on the site. This thing is blowing up. It's going viral.

We can see it spreading through Twitter. We can see it spreading through Facebook. We can see it being referred by random sites, but we're also seeing a lot of traffic come in as direct. Since no one knows this blog exists, I highly doubt they're typing in the 40 plus characters of the URL to go directly to this page. They're not. It's being shared socially. This is the idea of dark social.

It's not a new idea, but it's a fascinating idea, and that's what I wanted to talk to you about today, was this idea of dark social, that content spreads, if it's good content, socially, organically.

Dark social sounds like a bad thing. It's not. It's actually really awesome and really fun to dig into. Let's say that someone read this post earlier, and they shared it on Twitter, Facebook, whatever. We kind of know where that came from for the most part. They may have texted it to a friend or copied a link and sent it in chat. In both cases, when the person clicks on the link and goes to the site, they come in as direct.

Direct is Google Analytics' version of, "We have no idea what this is, so let's call it direct and throw it in that bucket." We know it's not direct. That's our dark, organic social. It's spreading organically in all different ways, and we're getting traffic because of it. It's pretty amazing.

I wanted to talk to you about the analysis I'm doing on the dark social side because it's really fun stuff. Unfortunately, in talking to a lot of people, I found they're not there yet.

Here's the problem. When we say direct it's our catchall bucket and we need to look at direct to get an idea of our dark social, organic social, whatever we want to call it, if things are not tagged properly, we can't dig into to what's [out] to this dark social side. Actually, we can't do anything. If things aren't tagged properly, you're not taking credit for the work that you're doing.

For your paid search, for your social media, for email marketing, whatever it is, you have to tag your links. Otherwise, you're not getting credit for the work that you're doing.

You know what really sucks, by the way? When you work really hard on a project and, at the last second, your boss takes credit for it. That was your project. You did all the work for it. Why is he taking your credit? It sucks!

What we're talking about right now is the digital marketing version of that. It's the online version, where you're giving your credit away for the work that you're doing. Honestly, you need that credit to keep your budget, to keep your job, to get a promotion, to get any of these things. You need to prove your value.

When we talk about tagging, it's using UTM parameters. Dark social, organic social, that's really sexy. It's fun. We can dig into that. UTM parameters are not sexy. They're not fun, but they're necessary. If you're not doing this, you're wasting your time and you're wasting your money. Now that sucks.

How are you wasting your time? If you're not doing this, you're putting all kinds of time, hopefully, into analysis, if you're looking at what you're doing, but your analysis is based on data that's not accurate. You're putting your time into marketing efforts that may not actually be working as well as you think they are. You're putting your money into marketing efforts. You need to know that your stuff's actually working. Keep doing that. Make your well-informed decisions to help the business and drive it forward.

Again, time is money. You need to make sure you get all this stuff right, so you can do all the other stuff.

Let's talk about a few examples of where tagging actually matters. If we're looking at Twitter, if you don't tag your links, things will still come in. You'll see showing up. In your real-time traffic, you'll see Twitter as social coming in, and you'll see some of that in your multi-channel funnels as well.

If you tag your links, you're going to always know it's Twitter. You're going to know which campaign it was. You're going to know all the information you put into it. You're also going to be protected from the other side of it. That's when people use Twitter apps. For example, HootSuite doesn't come in as Twitter unless you've tagged it. People clicking on a link that you post on Twitter that's untagged in HootSuite are going to come in as HootSuite referral usually.

If you posted on TweetDeck, they're coming in as direct. By the way, I'm still playing with all of this, and it all changes. I've played with stuff that's changed before. So if this is different by the time it comes out, I apologize. Just keep up with it all the time.

That's our Twitter side. On Facebook, if we don't tag our links, they'll come in as Facebook referral. It's nice and easy. It's clean. We know what it is. The exception to that is if someone's trying to open a link in Facebook, they click on the link, it doesn't load fast enough, they're probably going to click Open in Safari if they really care about it. Once they open in Safari, that's a direct visit. We just lost the Facebook tracking in it.

There're also a missing piece here, and that's if you do tag this stuff, you get an extra level to your analysis. You can say, "This is all the same campaign. It's the same effort, same content." You can tie it together across all these different platforms, and that helps.

We get to email. If you're putting time and money into your email marketing, you want to take your credit for it. If you're not tagging your email, it's usually going to come in one of two ways:  One as a referral from all the different mail things that can come in or as direct.

At least with the mail, where is says, we know it's mail. We can't track it down to what you did versus what someone sent. We have some analysis on it. If it's direct, you lose everything. So tag your email.

Paid search. It's nice. AdWords actually makes it really easy for us to tag our paid search. We can connect Google Analytics and AdWords very easily, and they play really well together. It's awesome. The problem is when you don't tag your stuff. If you don't tag your paid search, either through AdWords or through your manual tracking parameters on other platforms as well, it comes in as organic.

This actually happened to us at SEER. One of our SEO clients, we were watching their traffic, and organic traffic spiked. The account manager went, "Hey, guys, this is awesome." To which the client responded, "Oh, we forgot to tell you we launched paid search," and the account manager discovered they weren't tagging their paid search. This paid search manager accidentally just gave away their credit. We don't want to have that happen.

Let's say you've actually tagged everything properly in your URLs. All this is done. These are just a few examples, but all of the other stuff is taken care of. Let's look at the tracking on the site itself. We see this happen pretty often with paid search landing pages, where we have to put this on our checklist that this is done immediately.

We'll create brand new landing pages that are optimized for paid search for conversion. They're different from the rest of the site. They're a totally new template, which means that if the Google Analytics code is in a template already for the site, it may not be in here. If we don't have someone add it back in, what's going to happen is paid search will drive all this traffic to the site, they'll get to that page, go to page two. Page two has the Google Analytics code, but they don't know where it came from. This is going to show up as direct. Paid search just gave away their credit. We can't have that happen. You worked too hard for that credit.

I've also seen it where people make little mistakes with the tracking on the site. Spotify did this a few months ago, and I sent them a message to help them out with it. They were tagging all of the links on their site with UTM parameters. When visitors would hit those different links, they'd reset the visit ,and it would be a new visit with each one. Spotify, all their marketers were giving away their credit through that.

Let's say you've got all this other stuff right. Good job. That's awesome. There's still stuff that you can't control unfortunately. There are a lot of things that can cause traffic to come in as direct when it really isn't. I have a short list that people have been adding to at [bitly/direct-rome]. If you have others, keep adding them because I want to have a giant list of all the things we can tackle and fix, but the list just keeps growing.

If you look at mobile traffic, for example, iOS 6, we can't tell if it's search or if it's direct. That's a problem. For me, if I'm doing an analysis and I really need that part, or I really need to know that part for sure, I may cut that out so it's not throwing off my data. There are different ways to deal with that, and that's a whole other topic.

The point is control whatever you can. Where you control the spread of information, make sure you're doing your part. If you're sharing a link socially, tag your links. That way, if people want to share it or retweet it, the tracking is already in place there. If your posts on the site have social plugins, put the tracking in your social plugins too. It makes it easy if someone wants to hit the share on Facebook or to share on Twitter. It already has the tracking. It goes through, people get to the site, your tracking's in place, and you can breathe a sigh of relief.

Now once you've done everything else up here, your tagging is right on your URLs, your tracking is right on the site, there's nothing you messed up by accident, you've controlled everything you can with these other issues, you kind of have to accept what's left. You know that there's stuff that you can't account for. There's direct in there that may have been shared through a text, through a chat, through any other thing. You don't know where it actually came from.

First off, that gets a dark social. We can now start doing our awesome analysis, like dark social or other things, because we have confidence in our data. We can trust that we're making the right decisions for our business, and we can save our time and our money this way.

If you have questions or thoughts, hit me up on Twitter or in the comments below, because I love talking about this stuff. Maybe another time, we'll talk about this organic social idea."

Video transcription by

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

SEOmoz Daily SEO Blog

Using Google Analytics to Power an Effective Q&A Strategy

Posted by:  /  Tags: , , , , , ,

Posted by junseth

Alarm Grid's Executive Team - from L to R: Eric, Sterling, Joshua (me)When we started Alarm Grid we struggled with how we were going to stand out in a world of like a trillion other security companies. We were late to the game, no doubt, and in a world with as much competition as there is in an old industry like home security, it seems like there isn't much you could do to compete with the million minds that have come before you. Since then, we've done a lot of fun things that have helped us to gain traction, but my favorite strategy we've executed on thus far is our security FAQs strategy. We have built an amazingly large database of super relevant Questions and Answers, and our users love them. Before we begin, let me introduce you to our executive team: Eric is on the left, Sterling is in the middle and I'm the guy on the right.

Like anything done in marketing, there aren't a whole lot of "new" ideas per se. But the question needs to be how to execute it based on what's available to you. As I've seen Q&A strategies executed previously, I think there are two main ways to put them together. The first is the way companies like SEOmoz or Trulia have done it. Both use their base of strong, engaged communities to answer questions. Trulia relies on users looking for homes to ask, and realtors looking for business to answer. SEOmoz is generally relying on its community members who are interested in seeking experts or being experts to answer and ask questions. This model works really really well. I can't tell you how many times I've had an SEO question or an analytics question and ended up on one of the SEOmoz pages with a good answer from some person I've never heard of or met. Very helpful, extremely engaging. The other method is what sites without much of a community do: a bunch of old guys who know their product too well get together in a room and think of 100 questions about their products. Then they answer the questions in 30 words or less, brush off their hands, and call it a day.

When you know too much about your product, you can't know what questions users will ACTUALLY find useful

So we needed a method that sat between the community approach and the stodgy old-men-in-a-room approach. Since we don't have an engaged set of users and we're not that old, we needed to figure out a method of populating the database that sat in between the two approaches, and I'm proud to say, I think we figured out a great way to accomplish this.

If you're a business owner, you're probably wondering if this FAQ business is a good idea for you. When we gave the strategy a try on Alarm Grid, we had the same question. I poured through Google Analytics (GA) data and saw that users had already started coming into the site with questions. They weren't getting them answered, but they were asking them.

So, what I did was I used GA to power our entire Q&A engine. When we started, we honestly thought we'd be able to keep up with the questions that came in. We now have a backlog of over 10,000 questions we want to get to… and that's with just Honeywell products in our catalog. Our goal is to get 80% of these questions answered before we add more brands to the catalog. Wish us luck.

I'm presuming that you already have GA installed on your site, and that you know anything about how to log in to your account… so here we go:

1) Click on Advanced Segments in the standard reporting section of your Google Analytics.

Click on Advanced Segments

2) Select the button on the bottom right side of the drop down entitled "New Custom Segment"

This button unveils a glorious land of powerful analytics possibilities wherein you can create enormous value. The first thing you're going to want to do here is to make sure that you select "include" on the rule.

Click on Include under Advanced Segments

3) Select Keyword from the list of variable segment.

Select Keyword from the list of variables

4) Then select "Matching RegExp"

Select Matching Regexp

5) Put this cute little chunk of code into the text box

(It's different looking than it is in the pictures above because I cleaned it up for this post so I didn't have to be so embarrassed about posting it).


Now I ain't no RegExpert. I am terrible at Regex. And most of you probably don't even know what Regex is, so I'm sure there are more efficient ways to write this. But so you understand what you've done, let me clue you in. You're filtering for anyone who comes to your site using the keywords within the parentheses including any query that a user makes that contains a question mark. The regex idiot proofs it so that you anyone can add weird capitalizations and still have their search filtered (at least that's supposed to be how it works). If you want to clean up the regex, feel free. I would love to see it done, it just doesn't matter that much since this works pretty darn well.

6) Give your filter a cute name. We call ours "Add to FAQ" since that's what is supposed to happen.

Give your filter a cute name

7) Save your segment and turn it on.

8) In the left-hand column click on "traffic sources" then "sources" then "search" then "organic".

Select Traffic Sources, Sources, Search, Organic

8) Now, set the date range to show only one day – yesterday.

Select Yesterday in the calendar

9) Scroll to the very bottom of the page and select the dropdown next to the words "Show rows" and select 500.

Select Show Rows

Now this is a bit optimistic. You really only need the maximum possible number of results from each day. The number starts small, but if you execute this strategy correctly, you may be seeing 500+ visitors each day asking questions and getting to your site.

10) Go back to the top of the page, and select "Email," and fill the email(s) you want the daily spreadsheet to go to in the pop-up.

Click on Email

Also make sure to change the "Frequency" to "Daily." You can actually make it as frequent or infrequent as you want. I recommend daily, because, particularly when you are only seeing a few FAQs a day, it's better that everyone gets a few FAQs in the morning before things get hopping. Think about it, if you have two employees pumping out two FAQs every morning, first thing, you will have 1460 FAQs in by the end of the year. The average FAQ, in our case, bumps our average daily uniques by 1/3 of an user. Each FAQ takes an average of 15 minutes to write. At the end of the year, we'll have used about 730 hours of our employees' time to grab an extra 5,000 unique visitors each and every month. That's a huge boon for an ecommerce site.

Set frequency to Daily

And that's that.

What I like to do is once a month, dump the spreadsheets into a big, master list. Then I can filter on the spreadsheet by keywords within the questions, which allows us to manage our more than 10,0000 outstanding questions. We generally attack them by subject. So, for example, we do a week of Vista 20P (which is a Honeywell product we carry) questions only or some weeks we answer all the questions people have asked about Alarm Grid's alarm monitoring. This is the most effective kind of inter-linking we could possibly put together. The Q&As are relevant, and the anchor texts are surrounded by perfect semantically relevant writing. We require all articles contain 300 to 500 words, even if it's just a simple answer. We also find that it's best not to bury the lead. So when a user lands on a page, start by answering the question, then put more text below it that will expound and further explain why the answer is "yes" or "no."

You can do a lot of other fun stuff as well with this strategy. For example, to root out duplicates, you could only have questions where the user doesn't land on a URL with /faq in it. Our system is accurate up to about 87% when we do this, meaning this uproots 87% of all duplicates. There are a ton of other fun ways you could run this engine, but there isn't enough time in a day. If you do something fun that is hugely helpful for you, I'd love to know about it.

So give this all a try! And then report back, Let me know and the rest of the Alarm Grid team know how it works for you!

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

SEOmoz Daily SEO Blog

Marketing Analytics and the Problem of Attribution Modeling

Posted by:  /  Tags: , , , ,

Posted by RuthBurr

Guys, we need to talk about attribution modeling. It’s a hot issue in our industry and most of us (SEOmoz included) aren't doing it as well as we want to be. It's tough stuff. Mike P from Distilled gave a great MozCon presentation on the topic, but most of us aren't anywhere close to that sophisticated – and even his model is impacted by Google Analytics' limitations.

It’s been covered in far more detail elsewhere, but in a nutshell: attribution modeling attempts to solve the problem of which channel gets credit when a user touches multiple channels prior to converting. Many marketers simply throw up their hands and say the last touch gets all the credit – but then we have to live with the knowledge that some of our efforts are far more effective than we give them credit for.

Not-so-super modeling

dog model
Supermodel by Soggydan on Flickr

Unfortunately, attribution modeling is very hard to do well for a lot of reasons: 

  • Any site to which users return daily (like, for example, quickly fills up with touches that may or may not be related to conversions.
  • Channels like social media and community building are often a first touch but rarely the only touch before conversion, meaning they tend to get less credit than they deserve.
  • Attributing offline sales to online efforts can be very painful, not to mention tracking one user’s conversion path as she uses multiple devices during her buying decision.
  • In our post-Panda world, we’re spending a ton of time and effort on content that may end up on third party sites, opening us up to the near-impossible task of tracking view-through conversions.

In my opinion, however, the biggest problem with the attribution models available to us today is that their roots lie in web analytics tools like Google Analytics. This means that attribution models tend to be biased toward on-site efforts. The bulk of our marketing efforts doesn’t happen on-site, so why should our measurement? Our competitors certainly aren’t doing things on our site, so why should we content ourselves with on-site data?

Web-analytics-based attribution models also tend to break up sources at the channel level: organic search, social media, direct traffic, etc. Anyone who’s worked for months on driving traffic from Twitter and then had one tweet from Rand break their site can tell you not all social media touches are created equal, so why lump them all into Social Media?

tweet from @randfish

Finally, attribution models are incredibly difficult to implement for success metrics beyond conversion (more on that later).

Marketing analytics is about campaigns, not channels

Here at the MozPlex, we’ve been talking a lot about marketing analytics: the way we measure and optimize our marketing activities. I think Joanna put it best in her post: “Marketing analytics is the act of looking past mere website results, and asking yourself, ‘How did that marketing campaign really go?’”

Marketing analytics means going beyond the data we can get from our web analytics tool so you can measure off-site and even offline activities. Capturing that additional data about how your off-site and on-site marketing activities are performing allows you to test with greater confidence, and as marketers, we should always be testing. It’s probably not as simple as “social media doesn’t drive as many conversions as organic search.” Instead, we can test how to spend our time and money – which levers to pull at which time and in which way – to attract, keep, and delight our customers. At the same time, we can take a cross-channel, holistic view of our efforts to see what messages are resonating best.

All conversions aren’t created equal

Of course, one thing we want to do with our marketing efforts is make more money. ROI-driven modeling is always going to be part of what we’re measuring. However, modern marketers are driving for more than just the lead or the sale or the free trial. We’re looking at micro-conversions like newsletter signups. We’re watching and participating in conversations about our brand. We’re investing in customer happiness. We’re tracking shares, tweets, mentions, and views – and we’re keeping an eye on how are competitors are doing, too.

In addition to major conversions, marketing analytics is about tracking customer loyalty.

customer loyalty
Forever Friends by dprotz, on Flickr

We can often gain as much revenue from keeping our existing customers happy as from getting new ones. What happens after the conversion?

Marketing analytics is also about tracking brand identity. This is becoming more and more important as the major search engines focus more and more on brand strength as a quality indicator. This is another area where typical attribution models just don’t go far enough. Brand-centric campaigns are as much about generating conversation and positive feelings as they are about directly causing more conversions – this makes it harder to prove value if conversions are your only KPI. Branding has an influence on direct traffic, but it also has a big influence on organic search traffic from branded keywords.

So, should that traffic still count as organic search, if branding efforts are what inspired the search in the first place? This is another area where a more campaign-centric view can provide more insight than simply attributing conversions to channels.

Getting closer to marketing analytics

We’re still in the early days of true marketing analytics, which means we’re still mashing up data from a bunch of different tools and struggling to find the right ways to track campaigns. In the meantime, we can start hacking our web analytics’ attribution monitoring tools to go beyond simple channel attributions:

Advanced metrics for attribution modeling

  • Top referrers (separated out from the rest of referral traffic)
  • Top keywords (separated out from the rest of the keywords)
  • Long-tail keywords (same deal)
  • Top partners and/or affiliates
  • (not provided) search traffic
  • Branded and non-branded search traffic
  • Individual social networks (A friend and a follower may not be the same!)
  • Individual feeds
  • Individual paid advertising sources

We can also start thinking of (and tracking) our data with a marketing analytics mindset:

Advanced metrics for marketing analytics

  • Messages
  • Type of touch (Branding? Promotion? Retention? Happiness?)
  • Type of product
  • Audience
  • Time of day
  • Conversations

In the end, marketing analytics is more useful than straight-up attribution modeling, because it allows you to view your marketing efforts holistically. When you view individual customer touches as part of a larger whole instead of siloed by medium, you can take a longer and more customer-driven view of your marketing efforts.

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

SEOmoz Daily SEO Blog