What is “share of voice”? Share of voice (SOV) in marketing originated as advertising terminology, defining the percentage of media spend by a company compared to the total spend in the market. In essence, it’s meant to gauge visibility of a brand compared to its competition. In the SEO world, it measures organic visibility compared to the rest of the search landscape. Share of voice has been used in the SEO industry for years, but recently more SEO tools have begun incorporating it as an additional measurement alternative to simple rank tracking. Rank tracking is extremely valuable, but when it comes to reporting and speaking with stakeholders unfamiliar with the minutiae of SEO, rank tracking can get people confused and caught up on a specific rank for one term at one point in time. Not to mention that search engines are extremely sophisticated now, and many factors can influence why a brand may rank position #1 in one location and position #8 in another. Share of voice is an alternative measurement that brings rank tracking to a higher-level conversation about overall awareness performance. I’d be remiss not to mention that share of voice is just one metric to incorporate. Good SEO measurement dives deeper into the business impact of the channel, But including SOV can be a great way to discuss overall awareness, which is an important step in the funnel to sales and conversions. How is SOV calculated? Share of voice is typically calculated as (Position Click Through Rate X Search Volume) / Total Volume summarized for all keywords. This allows higher search volume terms to make a bigger impact than those with lower volume. For example, if you rank position #3 for a term with 1,000 monthly searches and position #1 for a term with 100 monthly searches, you would do the following math to get SOV: Keyword 1: Position 3 CTR 9.25% * 1,000 = 92.5Keyword 2: Position 1 CTR 34.76% * 100 = 34.76Total SOV = 127.26 / 1,100 = 11.57%Thankfully, tools can do this automatically for us. (2013 me was doing this at scale in Excel, and ain’t nobody got time for that anymore!) How to use STAT SOV STAT automatically calculates SOV within their tool. They do this at a few different levels: the overall project, a data view, and a tag. This allows for flexibility to report on SOV for the whole site, a certain section, or a certain topic. You can get as creative as you want when setting up the tags and data views. Just keep in mind what you would want to report as SOV for a website when creating your tagging strategy. There are plenty of resources already on how to set up tagging strategies. Here is a great article on the overview of using tags for analyzing data, and STAT resources have plenty of documentation on how to set up tags. Out of the box, STAT utilizes their own click-through-rate percentages, but you can customize them to match your industry if you have different metrics you’d like to use.’ STAT automatically calculates the SOV for the top competitor sites in a group of keywords. You can add your sites domain(s) and any top competitors you want to make sure are included as “pinned” sites within the SOV settings tab. Learn more about how to customize the SOV settings here. Once you’re all set up with your customization, you’ll receive daily updates to SOV and can use the helpful reporting dashboard to compare over time. Incorporating SOV into reporting dashboards You can always export data directly from STAT or utilize screenshots in your monthly report format of choice, but I prefer using the STAT Google Data Studio connectors. These allow for an easy data connection and the ability to add custom visuals to existing or new reports. It’s a shortcut to making client-friendly visuals that don’t require custom updates. Here is a great resource to start with if you are new to the STAT GDS connection. You’ll have to learn how to do simple API calls to get some of the data points you need, but I promise you’ll feel more powerful once you master. If the API instructions scare you, use this builder to input your own account metrics as a shortcut. Once you have your API details, go to this link to begin setting up the SOV data connection at the site level and use this link to set it up at the tag level. You should see a visual similar to the following. The site connector will have Site ID and the tag connector will have Tag ID. Fill in your fields and add to an existing or new report. Once you have the data in your report you can now build your ideal visuals. Visualizing SOV Share of voice in STAT is listed in an ongoing line chart or a table. I find that useful as an SEO, but a stakeholder tends to just need a quick snapshot they can read as “good” or “bad” quickly. People’s attention span is getting lower and lower with more things to distract them everyday. Good data visualization can get your point across faster and gain trust with stakeholders. There are a few options I tend to use as a starting point. These range from snapshot in time visuals to trending visuals. Bar chart Bar charts are extremely easy ways to visualize the SOV in a way that allows the audience to compare and see who is winning and who is losing in a snapshot in time. To visualize SOV within a bar chart use Site as your Dimension and Share of Voice as your metric. Ensure SOV is properly calculated as a percent of the total. You can either customize your date range to be a default time frame or use a date range filter on the page to allow it to be changed on the fly. Pie chart Pie charts are very controversial in the data viz industry. These are generally not a good option since you can’t easily compare the inputs to each other. I challenge that the share of voice is less of a comparison and more of a percentage of total, which is what a pie chart is meant to show, and therefore sometimes utilize them as a quick snapshot. I tend to include a bar chart next to this visual to dive in more just in case, but you do what you prefer. Follow the same instructions as the bar chart when setting up the visualization. Table Tables are simple and effective ways to easily read data. I wouldn’t suggest this as a visual by itself, but it’s great to have as a reference for a chart or for an analyst. By default the table settings will sum the share of voice metric so make sure you adjust it to be a percentage of total. Line chart This would be similar to the out-of-the-box visualization in STAT itself. The difference is that you can visualize in more of an aggregate format and make them a bit more in line with your reporting visuals. Add certain colors to draw attention to your sites or calls-outs as needed. When setting up a line chart, use a simple number versus a percent to make sure it aggregates properly. Again, these are just starting points, use what you need to tell the right story to your audience. Take it to the next level One of my favorite parts of GDS is the ability to interact with your data and customize it on the fly. These are just some quick tips to make your dashboards even more useful. Utilize filters Filters allow you to adjust data on the fly. There are two types of filters: a page level filter that can change multiple visuals while looking at the report and a visual level filter that pre-filters specific visuals. Use a page level filter when you want the report viewer to have the ability to dig into the data and use visual level filters for when you want the data to only display the filtered data you selected. Page-level filters You can add a filter under the “Add a Control” dropdown. The most common page level filters I use include date range control and dimension filters. You can set up dimension filters to be self-selecting or custom search options. Which you choose depends on what you want a report viewer to have access to use. For example, adding in a filter for Sites allows you to change the competitors listed in a visual. This can help you remove competition that is making the visuals hard to read (*cough* Google *cough*) or that the audience doesn’t care about. Visual-level filters There are different options to apply filters at the report, page and visual level, but all of these are filters that are applied to your visual before it’s created. This customizes the data in the visual to exactly what you want to show versus the report viewer having to self-select. For example, you could add a visual level filter to only show the sites you have manually added, in case you didn’t want to show the full landscape. I wouldn’t recommend using pie charts for filtered data, since it does remove key data points from the total. You can learn more about filter options from Google’s resources. Create competition groupings Calculated fields in GDS give the ability to layer data transformations on top of the raw data source. You aren’t modifying the data itself, but instead creating a new value to include in the report. There are plenty of resources to learn how to create calculated fields so I’ll just cover the high level steps here. Example: You want to visualize the types of competition with the top SOV by site type versus domain. Setting up the following calculated field will summarize the SOV by grouping so you can get an even higher level view of your top competition: To add a calculated field, open the data source and click “Add a Field” and then add in your custom code. Make multiple views Who says you only have to have one report? I’m a huge fan of an internal and external report view. This allows you to set up more details in your internal report while keeping an external report high level and focused on the visuals. Use the internal report to dive deeper and build your insights for the stakeholder-facing one. For a client-facing report I tend to keep the visuals focused on a specific time frame without the ability to filter. This allows the client to see what I want them to see. For my internal reports, I tend to include the ability to adjust timeframes, include multiple filter options, and include tables to support my visuals so I can easily download or see the raw data if needed. Get creative with your data With tools like STAT and Google Data Studio, you can combine data sources on a common data point. The SOV data source has “Date” as a field, so any other data source that includes a date can be combined. Want to visualize SOV on the same chart as traffic? Want to combine multiple tag SOV data sources into one? Want to layer published content dates over SOV changes? Get creative and try it out! Might as well start asking if you can visualize something and then see if you, can versus feeling limited to the basics. We’ve covered how to set up your projects to look at SOV with STAT and how to pull that data into the Google Data Visualization tool in this article. Now go forth and use your learnings to create something custom for your client or business. Remember to focus on the story you want to tell first, and let the data bring it to life.

More brands than ever are investing and producing quality journalism to drive their earned media strategy. They recognize that it’s a valuable channel for simultaneously building authority while finding and connecting with customers where they consume news. But producing and distributing great content is no easy feat. At Stacker and our brand-partnership model Stacker Studio, our team has mastered how to create newsworthy, data-driven stories for our newswire. Since 2017, we’ve placed thousands of stories across the most authoritative news outlets in the country, including MSN, Newsweek, SFGate, and Chicago Tribune. Certain approaches have yielded a high hit rate (i.e., pick up), and one of our most successful tactics is helping add context to what’s going on in the world. (I mentioned this as a tactic in my Whiteboard Friday, How to Make Newsworthy Content: Part 2.) Contextualizing topics, statistics, and events serves as a core part of our content ideation process. Today, I’m going to share our strategy so you can create content that has real news value, and that can resonate with newsroom editors. Make a list of facts and insights You likely have a list of general topics relevant to your brand, but these subject areas are often too general as a launching point for productive brainstorming. Starting with “personal finance,” for example, leaves almost too much white space to truly explore and refine story ideas. Instead, it’s better to hone in on an upcoming event, data set, or particular news cycle. What is newsworthy and specifically happening that’s aligned with your general audience? At the time of writing this, Jack Dorsey recently stepped down as CEO of Twitter. That was breaking news and hardly something a brand would expect to cover. But take the event and try contextualizing it. In general, what’s the average tenure of founders before stepping down? What’s the difference in public market success for founder-led companies? In regard to Parag Agrawal stepping into the CEO role, what is the percentage of non-white CEOs in American companies? As you can see, when you contextualize, it unlocks promising avenues for creative storyboarding. Here are some questions to guide this process. Question 1: How does this compare to similar events/statistics? Comparison is one of the most effective ways to contextualize. It’s hard to know the true impact of a fact when it exists stand alone or in a vacuum. Let’s consider hurricane season as an example. There’s a ton of stories around current hurricane seasons, whether it’s highlighting the worst hurricanes of all time or getting a sense of a particular hurricane’s scope of destruction or impact on a community. But we decided to compare it another way. What if we asked readers to consider what hurricane seasons were like the year they were born? This approach prompts a personal experience for the readers to compare what hurricane seasons are like now compared to a more specific “then” — one that feels particularly relevant and relatable. I’ll talk more about time-based comparisons in the next section, but you can also compare: Across industries/topics (How much damage do hurricanes do compared to tidal waves?)Across geographic areas (Which part of the ocean is responsible for the most destructive hurricanes? Where has the most damage been done around the world?)Across demographics (Which generation is most frightened of hurricanes?)There are dozens of possibilities, so allow yourself to freely explore all potential angles. Question 2: What are the implications on a local level? In some cases, events or topics are discussed online without the details of how they’re impacting individual people or communities. We might know what something means for a general audience, but is there a deeper impact or implication that’s not being explored? One of the best ways to do this is through localization, which involves taking a national trend and evaluating how it’s reflected and/or impacts specific areas. Newspapers do this constantly, but brands can do it, too. For example, there are countless stories about climate change, but taking a localized approach can help make the phenomenon feel “closer to home.” We put together a piece that illustrated significant ways climate change has affected each state (increased flooding in Arkansas, the Colorado River drying up, sea levels rising off South Carolina, etc.). You could take this a step further and look at a particular city or community if you had supporting data or research. If you serve particular markets, it’s easy to implement this strategy. Orchard, for example, does a great job publishing real estate market trend reports in the areas they serve. But if you’re a national or international brand that doesn’t cater to specific regions, try using data sets that have information for all countries, states, cities, ZIP codes, etc., and present all of it, allowing readers to identify data points that matter to them. When readers can filter data or interact with your content, it allows them to have a more personalized reading experience. Question 3: What sides of the conversation have we not fully heard yet? The best way to tap into the missing pieces of a story is to consider how other topics/subject areas interact with that story. I’ll stick with our climate change theme. We did the story above on how climate change has impacted every state, which feels comprehensive about the topic, but there’s more to dive into. Outside of just thinking how climate change is impacting geographic areas, we asked ourselves: How is it affecting different industries? Now we have a look at a more specific angle that’s fascinating — how climate change has impacted the wine industry. When you have a topic and want to uncover less-explored angles, ask yourself a set of questions that’s similar to the compare/contrast model: How does this topic impact different regions? (E.g. What is wine’s cultural role in various countries?)How does this topic impact different demographics of people? (E.g. Who profits most from wine making?)How does this topic impact different industries? (E.g. How have wineries/vineyards impacted tourism?)How is this topic impacted by these various things? (E.g. How is the flavor of wine impacted by region? Who buys the most wine, and where do they live?)This should create a good brainstorming foundation to identify interesting hooks that aren’t often explored about a really common topic. Conclusion Not only will taking the approach of contextualizing differentiate your story from everything else out there, it will also allow you to re-promote it when a similar event occurs or the topic trends again in the future. Contextualized content is often this perfect blend of timeliness and evergreen that’s really difficult to achieve otherwise.
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