Building Better Content By Improving Upon Your Competitors

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Building Better Content By Improving Upon Your Competitors Posted: 16 Jul 2014 05:17 PM PDT Posted by Bill.Sebald In rock n' roll music, stealing is expected. Led Zepplin allegedly lifted from lots of earlier blues and folk artists. The famous I-IV-V chord progression of The Wild One's song "Wild Thing" was used only a couple years later on "Mony, Mony." My favorite example of musical larceny - "Let It Be" by The Beatles, "Farmhouse" by Phish, and "No Woman, No Cry" by Bob Marley are built around the exact same chord progression. Yet in all these cases, the songs were tweaked enough to stand on their own in meaning, served as distinct entities, and inspired unique feelings from the listener. Granted record company execs often disapproved, but some artists were often flattered to see interpretations of their riffs and progressions. At the end of the day, this is what spawned (and advanced) the rock music genre. Sometimes stealing is the engine of innovation. "Your idea isn't new. Pick an idea; at least 50 other people have thought of it. Get over your stunning brilliance and realize that execution matters more." —Mark Fletcher of Bloglines.com. In marketing, we don't just "steal" the minds of consumers, we sometimes steal - and interpret - from our competitors. Sometimes we're lazy about it, and sometimes we're perceived as originals. Remember one of the immutable laws of marketing - always appear to be first. Well then why not be first to make someone's content strategy more effective (for your own gain)? Wait - so do I condone being a pickpocket, cat burglar, or politician? No. What I'm suggesting is reviewing what inspires you, analyzing why it was successful, and inspiring yourself to make something better. Better for us, better for our clients, and better for their customers. Oh no; is this another "Content Is King" post? I'm not a huge fan of that phrase anymore. SEO has gone through some serious developmental stages in its lifetime. Once the hype was all about "keyword density," then "anchor text," then "duplicate content;" now I feel like our latest bandwagon concept is the semi-vague "content is king." These are certainly all valid concepts in SEO, but without proper context, they often fall short of sound advice. They become blind directives. So here we are in 2014, with many business executives nodding along, "yes - content is king. I've read that a trillion times. We need to crank out 100 posts a month. Go, go go..." But I think this is a problem. Now that SEO is mainstream, there's so much "good content" that the noise ceiling has simply been raised. I've said it before, "Fair-quality copy is becoming the new Google spam." I go into pitches now where businesses can't understand why their legacy content isn't getting searches. In other words, they ask why "content is king" isn't producing results. It's usually because content was treated as a homogeneous tactic where a marketing or SEO strategy wasn't put in place to link the pieces together. I think it's time SEOs put that phrase to rest, and start thinking in terms of how a traditional content marketer would think about it. "Content that is unique in value, strong in expertise, provides a necessary point-of-view, and leads the pack in terms of usefulness is more than king - it's fundamental to success." A bit of a mouthful (and less sexy), not to mention harder to develop, but it really needs to be adopted. So if you would, please keep that in mind during this post. Continue on! What are your competitors doing? Content ideas come from lots of sources. Some are vapid (like content topic generators) and some are interpreted (like reviewing customer poll results). Often a simple interview with your sales or service team can teach you plenty about the mindset of your consumer. Studying on-page product reviews can also be inspiring. Focus groups, experiments; all this and more can help produce pieces of content that can be strung together and tracked in order to build a truly converting funnel. We all know the most effective content is inspired by data, versus "crazy ideas" with no concrete evidence quickly thrown against the wall. While this occasionally has some SEO benefit (arguably less and less with Panda updates), it rarely does much for your conversion funnel. It takes that extra digging that some aren't quick to execute (at least in my experience). But what happens when your competitor is willing to do the work? That's where you can learn some interesting things. Marketing espionage! Granted, most competitors don't want to share their data with you, no matter how much beer you try to bribe them with (believe me, I've tried). We have tools like SEMrush to estimate search metrics, and services like Hitwise and Compete to get more online visitor data. While that is certainly helpful, it's still directional. But we're marketers - so what do we do? We get creative. How to get a birdseye view of a content play (with common SEO tools) It's time to lift the hood. I like to start with  Screaming Frog. Most SEOs know this tool. If you don't, it's a spider that emulates what a search engine spider might find. In my experience there's no better way to find the topics a website is targeting than with a "screaming" crawl. Filter down to HTML, and you'll find the URL, Title Tag, Meta Description, H1, and sometimes the Meta Keyword data. If you already have your own keywords and entities in mind, and want to see what a competitor is doing with them, it's as simple as searching for them in Screaming Frog (or an excel export) and scanning for it. Click for a larger image: Consider this totally random "shammy" example in the screenshot above. If I worked in the shammy business, through a quick scan I might be interested to know that at least one of my competitors found value enough in creating a section around an iPad cloth. Is that a segment I never considered? Don't have Screaming Frog? The site:operator is a less powerful option. You can't export into a spreadsheet without a scrape.  Ubersuggest or keywordtool.io can be used in clever "quick and dirty" way - put in a keyword you think there's opportunity for, and add "who," "what," "where," "why," or "how" to the query. Your fragmented query will often show some questions people have asked Google. After all, plenty of great content is used to answer a query. Search some of these queries in Google and see what competitor content shows up! At the very least, this is a nice way to find more competitors who are active with creating content for their users. At this point you should be taking notes, jotting down ideas, observations, potential content titles, and questions you want to research. Whether in a spreadsheet or the back of a napkin, you're now brainstorming with light research. Let your brain-juice flow. You should also be looking for connections between the posts you are finding. Why were they written? How do they link together? What funnels are the calls-to-action suggesting? Take notes on everything, Sherlock! Collect the right data Next, step it up with more quantifying data.Time to trim the fat. Search data By entering and measuring your extracted in Google's Keyword Planner, you'll see not only is there interest in an iPad cleaner (where an "iPad Shammy" might make sense with its own strategy), but some searcher interest in the best ways to clean an iPad. That could be fun, playful content to write - even for a shammy retailer. It could tie directly to products you already sell, or possibly lead you into carrying new products. Click for a larger image: Estimated searches don't tell the whole story. We know plenty of keywords and metrics from this tool are either interpolated or missing. I've found that small estimated searches can sometimes still lead to more highly-converting volume than expected. Keep that in mind.  Social data What searches enter into Google's search box isn't the only indicator of value. Ultimately if nobody likes a certain topic or item your content, they aren't going to share or link to it. Wouldn't it be great to have another piece of evidence before you get to structuring a strategy and writing copy? That evidence may lie with your competitors' social audience. At this point you have keyword ideas, content titles, sample competitor URLs, and possible strategies sketched out. There are some great tools for checking out what is shared in the social space. Topsy, Social Crawlytics, and Buzzsumo are solid selections. You can look up the social popularity of a given URL or domain, and in some cases drill down to influencers. If it's heavily shared, that may suggest perceived value.  Click for a larger image: Look at the image above. If my agency is a competitor of yours, you might be interested that one of my posts got 413 social shares. It was a post called "Old School SEO Tests In Action (A 2014 SEO Experiment)". You can dig in to see the debates boiling through the comments or the reactions through social media. You can go so far as see who shared the post, how influential these people are, and what kind of topics they usually share. This helps qualify the shares. With these social metrics I believe It's reasonably safe to infer people in the SEO space care about experiments, learning about things that move rankings, and that most believe older tactics aren't worth pursuing. With very little time at all, you might be able to come up with ways to improve upon this post or ideas for your own follow up. Maybe even a counter argument? Looking at who the post resonated with, you could presume my target audience was SEOs with a goal of providing industry insights. With a prominent lead generation form on this post, you might even suspect a secondary interest was as a source of new client leads. If you surmised any of these things from the social data, you're 100% right! This was certainly a thought out post with those goals in mind.    Backlink data Let's examine link popularity and return to the shammy industry. Specifically let's look at a pretty unique item - a shammy for Apple products -  https://www.klearscreen.com/detail.aspx?ID=11. Open Site Explorer found 1 link from a retailer. Ahrefs found 8 links from 8 domains, one being a forum conversation on Stackexchange.com, and the others from a retailer. Majestic found 13 links from 6 domains. Similiar to what Ahrefs found. WebMeUp found 30 backlinks from 9 domains. From this data it looks like the iPad shammy market isn't exactly on fire. Now it doesn't appear iKlear (or Klear Screen) is doing much marketing for this particular product - at least not according to Google. Their other Apple product cleaners seem to get more attention, but perhaps iKlear simply knows this isn't a high demand product. It could be true - after all it hasn't gone viral. It hasn't generated much in the way of online discussions. But it also hasn't been marketed much. This is why all the data needs to be collected, correlated, and analyzed.  You want the best hypothesis you can get before you start committing your time to a content strategy. Did this just kill a possible content strategy for an iPad Shammy, or is this a huge untapped opportunity? It entirely depends on how you interpret all the data you collect.  You've got some ideas; now what's the execution? You just did a lot of work. You can't go off half-cocked throwing up willy-nilly content. Jeepers, no! The next step is the most crucial! At this point you should have uncovered some great ideas based on your competitor's clues. Now comes the part where you thoughtfully determine how to implement these ideas and craft a strategic roadmap. The options are endless, which could provide a decision-making struggle. From new microsites to overhauling existing content, there's so much you can do with the gems you've dug up. Remember to examine what your competitors did. How did they plug everything together?  But sometimes your competitors don't have a discernible content strategy. Instead just fragmented content floating like an island. This is even better for you. Now you have opportunity to not only outshine in the actual content, but put together an actual experience that your users will value, thus providing a likely positive SEO result. Here are three options I tend to build a strategy around most often:  Create a new funnel Create content for off-page SEO Create emphasis content With fresh metrics, the new funnel is often necessary. Chances are you discovered uncharted territory (at least from your website's perspective). All future or existing content should have pre-conceived goals - there's a top and bottom to every funnel, and maybe some strategic off-ramps leading to forms, contact pages, or products. Remember, you're goal is to be driving the reader through an experience, eliciting emotions and appealing to their needs of which you've already built a hypothesis upon. This new funnel can dip into your current website or run parallel (ie, a microsite, sub-domian, or otherwise disconnected grouping). The greatest thing about digital marketing is that nothing is in stone. It's so easy to test these funnels and redesign with collected data when necessary. Off-page is also very common (right link builders?). Find something that is popular, and go share it with sites more popular than yours. Maybe you can even start generating new popularity and create a segment of its own. Build a strategy to take this burgeoning topic and let the widest audience know about it. Get branding, mind share, links, and ideally profit like a beast. The "emphasis content" (as I call it) has been a solid go-to plan for me when I discover small pockets of opportunity; notably the stuff that may have a smaller impact and isn't worth a month long content strategy. If I were to create my own iPad shammy play, based on what I'm seeing so far, I'd probably think about a page or two as emphasis content.  This content is like an independent port of entry or landing page, either to an existing funnel or a direct money maker. In a previous post I talked about  creating niche collection pages for eCommerce. That could serve as emphasis content to a parent collection, but I'm usually thinking of heavier use of text in this case. Where you really take your goal, slice it up, and provide nice, beefy communication about it. This play can be nuclear. By creating these one-off pages based on all the metrics discussed above, it's usually much easier to do targeted outreach and social marketing. A well placed page, providing well placed internal links (ideally off popular pages), can pass PageRank and context like a dream, A tool like  Alchemy API can help you see the relevance of pages and help you determine the best place to publish this page Summary A content strategy doesn't go far if it's phoned in. Take all the help you can get, even if it's from a competitor. Learn from businesses who took steps before you. They may have very well discovered the holy grail. Competitive research has always been a part of any marketing campaign, but scratching the surface only gets you superficial results. Look deeper to uncover more than just a competitor's marketing plan, but the very reason why the competitor may be beating you in search. Then, hopefully you'll become the rock star others are trying to copy from. That's a good problem to have. 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!

Demystifying Data Visualization for Marketers Posted: 16 Jul 2014 07:05 AM PDT Posted by Annie Cushing I presented on wrangling and demystifying the data visualization process for marketers at MozCon this year, and it turns out there was far more to talk about than could fit into that half-hour. For the sake of those who couldn't make it and those who could but want to learn more, I pulled together this overview of my presentation, offering more detail than I could in the slides. To see all of the links shared in this post, check out my MozCon Bitly bundle. Demystifying Data Visualization for Marketers from Annie Cushing You may want to open the SlideShare file in another tab or browser window, so you can easily toggle between the post and the SlideShare. I'm going to go through the presentation slide by slide to bring the narrative to print. Slide 3 I have a confession: Although it's probably safe to say I'm a fairly advanced Excel user — at least among marketers — until recently I had no real charting strategy. In fact, I signed up to do this presentation partly to force me to carve out a strategy, particularly with Google Analytics data. Slide 4 In this presentation I have focused on Google Analytics data for a couple reasons: If you can wrangle Google Analytics, other marketing data is a walk in the park. It has naming conventions that map beautifully to Excel, making it an ideal tutor. Slide 5 My approach may seem a bit Karate Kid-esque, but if you can grasp the interplay between Google Analytics and Excel, you'll never be left wondering how to visualize your data. Although there are many aspects to data visualization, I focus primarily on charting. Slide 6 In Excel there are two components to charts that are critical to understand: data series and categories. They are always used together. Think of categories as buckets for your data and data series as the data itself. Slide 7 If you dumped a pile of Legos in front of a group of kids and told them to organize them by color into their corresponding, labeled containers and then count them, the containers would be categories. And the data series would be the count of Lego bricks. Slide 8 First let's peek under the hood on a PC by cracking open the Select Data Source dialog. You get to it by right-clicking on your chart and choosing Select Data. Slide 9 Excel for Mac also has data series on the left and categories on the right. And that's about all they have in common. Slide 10 But, as with most features in Excel for Mac, the functionality of the Mac's Data Source dialog is far inferior to that of the PC. Slide 11 This sort option is helpful if you have a stacked chart and want to sort the individual data series. I like to put the larger series on the bottom and smaller ones on the top. But if you have a stacked chart on the Mac and you want to reorder the data series, you actually have to delete the series you want demoted and manually add it back in. It's kind of like that game, Hand on Hand, you might have played as a kid where kids go around in a circle putting their right hands in the middle, followed by the left hands. Then they go around the circle moving the bottom hands to the top of the pile as fast as possible. Although in this case, you're moving the data series to the bottom of the pile. Slide 12 To move the Sessions data series to the bottom of the pile, first select it from the Series list. Slide 13 Then click the Remove button to delete it from the list. Slide 14 Then click the Add button to add it back to the list of data series. Slide 15 Click the data selector button to the right of the Name field and select the series name, as directed in the screenshot. Slide 16 Click the data selector button to the right of the Y values field and click-and-drag over the values. If the column is long, just click the first cell and press Ctrl-Shift-Down Arrow (Mac: Command-Shift-Down Arrow) to select the entire column without scrolling. (We are nothing if not efficient.) Slide 17 And finally you need to click-and-drag over the category axis labels. Which brings us to the Mac's other issue …. Slide 18 In the PC version, there's one place for the category axis labels. On the Mac you have to choose the axis labels for each series. It's counter-intuitive. Slide 19 Categories end up along the horizontal axis — or the vertical axis for horizontal bar charts. Slide 20 The data series ends up in the legend and is usually a metric (from GA). But there are a couple exceptions, which we'll get to in a minute. The categories populate to the horizontal axis label or vertical axis label with the bar chart. Slide 21 Transition to Google Analytics. Slide 22 The two major players in Google Analytics – that we'll be mapping to Excel – are dimensions and metrics. They're (practically) inseparable. Slide 23 Dimensions are the buckets your data is broken up into. These come into Excel as text – even if they're values – like you get with the Days to Transaction dimension (which you can get from Conversions > Ecommerce > Time to Purchase). They are always the far-left column of the table. Add a secondary dimension in any report (standard or custom). Create a custom flat table with two dimensions. Learn how in this post. Use the API. This is the only option that will allow you to use more than two dimensions. You can pull up to seven dimensions in one API call. Slide 24 Metrics are anything that can be measured with a number. Slide 25 If you're in a custom report (or have clicked the Edit link at the top of most standard reports), metrics always show up to a party in blue. Slide 26 And dimensions show up as green. You can learn more about custom reports from the video tutorial I created to help marketers. Now it's time to marry Google Analytics and Excel. Slide 27 In most cases dimensions in Google Analytics map to categories in Excel. Slide 28 And metrics map to data series in Excel. Slide 29 I'm going to break this down systematically, based on the number of dimensions and metrics you're wanting to visualize. Slide 30 Dimensions: 0 Metrics: Multiple You want this if you want to know aggregate numbers, e.g, sessions for the month, or revenue, or goal completions. Slide 31 I hate to start on a downer, but you need the API to do this. The GA interface requires at least one dimension. Slide 32 As with most things, if you prod enough, you'll discover hacks and workarounds. But the name of the game here is to come up with a dimension that will only have one bucket. Going back to the Legos analogy, it would be kind of like saying, "Put all the plastic Legos in this bucket and count them." Slide 33 Workaround: Set dimension to something that will encompass all of your data, meaning you'll only have one row in the report. One example of that would be the User Defined dimension (under Audience > Custom > User Defined). As you'll see in the screenshot, all of the values are consolidated as (not set) since this profile (now called view) doesn't use the User Defined dimension. Slide 34 If you're still using the User Defined dimension (and, therefore, have multiple rows reporting), you really need to update. If you're using classic GA, you should be using custom variables and custom dimensions if you're using Universal. Slide 35 Another option is to use the Year dimension with a custom report. This is ideal if you are gathering data for a single month. You can aggregate data beyond one month, as long as the date range you choose doesn't straddle more than one year. Slide 36 Here's what the custom report looks like under the hood. Learn how to  create custom reports in Google Analytics in a video tutorial I did. Slide 37 You can access this report  here while logged in to Google Analytics. Slide 38 This data isn't conducive to charting, but you can sexy up a table with sparklines and conditional formatting. Slide 40 Dimensions: 1 Metrics: 1 An example of this might be revenue segmented by country or bounce rate segmented by device category. Slide 41 Pie Chart Basics Here are some highlights about the pie chart: They use angles to show the relative size of each value. You should put data in descending order to put the most significant data point at 12:00 and radiate clockwise. Avoid 3D pie charts. They distort data. Data points must add up to 100%. So you can't take traffic from 5 of your 8 campaigns and chart them. Microsoft says no more than seven categories; I say no more than five. None of the values in your data series can be negative. Learn more Pie Chart Tricks Ways to trick out your chart: You can grab a piece of the pie to isolate it and drag it out slightly to draw attention to it. This is called exploding pie pieces. You can also change the values to percentages in the data labels or even add the categories, thereby negating the need for a legend. Slide 42 Donut Chart Basics Here are some highlights about the donut chart: Donut charts show data in rings, where each ring represents a data series It uses the length of the arc to indicate the size of the value. You should put data in descending order to put the most significant data point at 12:00 and radiate clockwise. Data points must add up to 100%. So you can't take traffic from 5 of your 8 campaigns and chart them. Microsoft says no more than seven categories; I say no more than five. None of the values in your data series can be negative. Learn more Donut Chart Tricks Ways to trick out your chart: You can put the title or the value you want to highlight in the center.  I don't recommend using the donut chart for multiple series or dimensions. They're more difficult to interpret.  Like the pie chart, you can pull one out to draw attention to it. You can use a donut chart to create a speedometer chart. You can fill it with an image that resembles the surface of a donut to make it look like a … Okay, yeah, never mind … Slide 43 Column Chart Basics Should sort in descending order. The axis should start at 0. Categories don't have to add up to 100% Learn more Column Chart Tricks You can add a trendline to make trends stand out. Consider going totally minimalist with the techniques I demonstrate in this video tutorial. (You can skip to the 15:53 mark.) Don't be afraid to move the legend around. Excel's default axis tends to be dense. I typically double the Major Unit, so if the major unit is set to 100, I typically up it to 200. Learn more about the major unit from the Microsoft site. (But I also show how in the above-mentioned video tutorial. You can use a column chart to create a bullet graph to show current data vis-à-vis goals or projections. You can use a column chart to create a waterfall chart. You can add a target line to your chart. If you have many categories to chart, you can use a scrollbar. You can use a column chart to create a thermometer chart. Just remember safety first when working with column charts. Slide 44 Bar Chart Basics You need to sort your data in ascending order to put the longest bars at the top. Bar charts are good for categories with longer labels. You shouldn't use bar charts if your dimension is time based (date, month, etc.). Learn more Bar Chart Tricks You can use all of the tricks (except the last two) listed in the Column Chart Tricks list. Slide 45 Radar Chart Basics Category labels are at the tip of each spine. You can use a fill with your radar charts. Radar Chart Tricks Radar charts can be compelling when you compare multiple entities at once. For example, I saw a set of 50 radar charts that compared metrics like crime rates for different types of crime for each state. If you don't want the axis labels to show, you can set the number formatting to ;;; to hide them altogether. You can then include an annotation on your chart that lets viewers know the intervals.  Slide 46 Notes about the Heat Map Learn how to create a heat map in this video tutorial I did. Slide 47 And now let's look under the hood at a typical chart that uses 1 dimension and 1 metric. Let's say we have this table of analytics data …. Slide 48 If we create a column chart from this table, this is what it's going to look like (with some cleanup). Slide 49 Now if we look at the data source this is what we'll see …. Slide 50 The mediums show up over here in the categories … Slide 51 And the sessions values show up here in the data series … Slide 52 Which populates to the legend. But you can delete the legend when you only have one metric (or data series). You'll then want to include the metric in the chart title. Slide 53 And the mediums populate the horizontal axis labels. A little piece of Excel trivia: The Select Data Source dialog still says Horizontal Axis Labels, even for bar charts where the labels are on the vertical axis. #pedantic Slide 54 Example of 1 dimension and multiple metrics: Sessions, goal completions, and revenue broken down by Device Category (mobile, tablet, desktop) BTW, the Device Category dimension is one of the most important in Google Analytics. By itself it's pretty useless, but in the context of other data, it's very useful. You should be segmenting all of your data by it. Slide 55 Notes about the Clustered Column Chart Clustered column charts are good for showing comparisons (e.g, sessions vs revenue for each month or ROI vs Margin by campaign (or keyword). You could transform the clustered column chart into a combination chart by adding a line chart on the secondary axis that adds a percent value. Slide 56 Notes about the Stacked Column Chart The stacked column chart is good for showing how each data series contributes to the whole. An example might be revenue broken down by medium. If you want to order the columns by overall height, you can create a total column for the series. You just won't chart that column. Slide 57 Notes about the Clustered Bar Chart All of the notes in the above-mentioned stacked column chart. Like the [single] bar chart, the clustered bar chart is better for categories with long labels. You can hack the clustered bar chart to create a double-sided bar chart. You can view a video tutorial I did on how to do this. Slide 58 Notes about the Stacked Bar Chart If you want to sort the bars so that the longer bars are on top, create a totals column and sort it in ascending order. You shouldn't use the stacked bar chart if your dimension is time oriented (date, month, etc.). Slide 59 Notes about the 100% Stacked Column Chart Use the 100% stacked column chart when you are working with percentages. The data series must add up to 100%. For example, if you wanted to see what percentage of social referrals came from desktop, tablet, and mobile devices. Slide 60 Notes about the 100% Stacked Bar Chart All of the notes under the 100% stacked column chart apply here. Slide 61 Notes about the Radar Chart Category labels are at the tip of each spine. You can use a fill with your radar charts. Radar charts can be compelling when you compare multiple entities at once. For example, I saw a set of 50 radar charts that compared metrics like crime rates for different types of crime for each state. If you don't want the axis labels to show, you can set the number formatting to ;;; to hide them altogether. You can then include an annotation on your chart that lets viewers know the intervals. See the screenshot under the Slide 45 note above. Slide 62 Notes about the Combination Chart Learn all about combination charts in this post I wrote on the Search Engine Land site. Slide 63 – 69 Self-explanatory as they follow the same dialog as slides 46 – 52. Slide 71 Notes about the Line Chart In a line chart, category data is usually distributed evenly along the horizontal axis and value data is distributed evenly along the vertical axis. Line charts can show continuous data over time, so they're ideal for showing trends in data at equal intervals, like months, quarters, or fiscal years. You can add markers and set the lines to none to use them in ranking charts. Avoid using stacked line charts. It's not always apparent that the data series are stacked. If you want to stack, use an area chart instead. You can add interesting line markers like the ones I created in this video tutorial to replicate the charts in Moz's tool set.  Slide 72 Notes about the Stacked Area Chart Ideal for showing stacked data series over time, especially if you want to demonstrate a fluid trend. Stacked column charts should be used if you want to keep each of the categories more disparate. You should order the data series so that the larger series are at the bottom of the stack with the smaller series being clustered together at the top because people's eyes naturally travel from the horizontal axis upward with stacked area charts. If you keep the gridlines, make them significantly lighter. A light gray works well. Make sure you have adequate contrast between contiguous data series. Sometimes Excel puts two colors next to each other that blend. If you have smaller data series that are difficult to see, use stronger colors to make them easier to view. If you have all larger data series and you want to add some finesse, give your data series a line (what would be called a stroke in graphic design programs) that's slightly darker than the fill. You can create a combination chart with a stacked area chart. Just don't use a line chart for the other style. I like to use a chart style that stands out from the area chart, such as a column chart. You may want to increase the transparency of its fill so that you can easily see through to the stacked area chart. Slide 73 Notes about the Clustered Column Chart You use the clustered column chart to show comparisons between data series (as opposed to how they contribute to the whole). The clustered column chart is especially effective for showing year-over-year data. The categories would just have the name of the month (I abbreviate to three letters, which you can learn how to do in this tutorial), and one column would be used to show data from one year and the other colored column would indicate the previous year. To show the month from each year as a disparate data series, you would have to make each year a separate column in your data. You can add a line chart on the secondary axis that highlights the percent change between values. You can play with the gap width and overlap settings to adjust the series. You get to those by selecting a column, pressing Ctrl-1 (Mac: Command-1), and navigating to the Series Options (Mac: Options) area of the Format Data Series dialog. Excel doesn't provide the option to add a data label that indicates the total of all the data series for each column. You can hack one by adding a total column that you include in the clustered column but then change to a line chart. From there, remove the line and add data labels above the line. Slide 74 Same as Slide 60. Slide 75 Same as Slide 58 Slide 76 – 77 Self-explanatory. Slide 78 Things get more complicated when you want to chart two dimensions. There are three ways to get 2 dimensions: Slide 79 So here we have two dimensions (Device Category and User Type). I picked these dimensions to demonstrate because they have a finite number of options. I LOVE the device category dimension and use it frequently to segment my data in Google Analytics. Note: When you chart two dimensions, you can only use one metric (or data series in Excel). Slide 80 Here's an example of what a clustered column chart might look like. Slide 81 We now have a dimension in the legend — or category in Excel. Slide 82 Using the Switch Row/Column button …. Slide 83 This is what the chart would now look like. Notice we now have three data series and two categories. Slide 84 Now let's take a peek under the hood. Slide 85 Again, here you see we have dimensions, not metrics, in the data series. The metrics should be included in the chart title. Slide 86 And now the Device Category dimension is in the category area. Slide 87 Your chart options are the same as when you had one dimension and multiple metrics. These options are not exhaustive. Slide 88 Slide 89 The data in this table is in report format. If only marketing export data came in this format. (It doesn't.) Slide 90 This is how marketing data actually comes out of different marketing tools. It's called tabular format. Slide 91 Just as in a database, rows in tabular data are called records. Slide 92 Columns are called fields. Slide 93 And the column headings are called field names. But if I were to select two dimension columns and one metric and select a chart, here's how Excel digests the data … Slide 94 Gross, I know. I'm a child. Slide 95 Here's what it actually looks like. A royal mess. Slide 96 Excel requires that data be in a report format in order to chart two dimensions. And the one metric (sessions, revenue, impressions, whatever) goes into the green area. There's only one way to corral an export with two dimensions and one metric into report format ... Slide 97 Pivot tables sound scary and intimidating but not if you think about what pivot means. Slide 98 When a soldier pivots, s/he very simply goes from standing facing one direction to turning at a 90 degree angle. That's what a pivot table does. By moving one of your dimensions into the Columns field (Mac: Column Labels field), Excel puts that dimension's values across the top of your data.  Once you have your data in report format, and you can chart it. You typically want to put the dimension with fewer values into the columns area. Learn how to create pivot tables in this comprehensive video tutorial I did. Slide 99 Although pivot tables come with a lot of junk in the trunk, you can see the pivot table puts the data into report layout, which Excel can then use to chart the data. If you're on a PC, you can create a pivot chart. If you're on a Mac, you can create a static chart from the pivot table because Excel for Mac still doesn't support pivot charts. Still. Ridic. Slide 100 Now you're ready to look at GA data — nay, all marketing data — with a more strategic eye… And spend less time tooling around in Excel trying to figure out how to visualize your data! 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!

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