Improve your media’s content and business strategy with simple Google Analytics techniques


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    Buzzfeed publisher Dao Nguyen recently revealed in an interview how the publication uses data to plan and promote publications.
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    Tao Nguyen, Buzzfeed Publisher


    I do not think that Buzzfeed has a monopoly on data. I think we just use them correctly.



    We've translated a Publishing Executive article that describes Google Analytics tools that help media analyze data, draw conclusions, and adjust editorial policies.

    Short retelling:
     

    Demographic indicators


    To expand your audience, write content based on user interests. Talk about the cities in which they live.

    Unique visitors and conversion


    What percentage of people subscribe to your newsletters and watch your ads?

    Bounce rate


    How many users continue to use your site after reading one article. How to engage them with personalization?

    Average check


    How to apply e-commerce metrics to a media platform.

    Content Grouping


    Find out which articles and sections of your site generate more money and subscriptions.

    Publishers are fiercely competing for traffic from sites and services that distribute content (read Facebook, Google News, Flipboard). Media seeks to better understand what benefits the content brings, and what needs to be done to earn more on the content. The time has come for analytics.

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    Surely your editors and marketing team are already analyzing the content in some way. Most likely you are using Google Analytics. And, most likely, you do not use all the tools.

    Content analysis is methods and metrics that show what each page of content does for the business. How does it affect advertising revenue, sales of subscriptions, newsletter subscriptions, and any of the many ways to monetize content.

    Content analysis is an invaluable strategic tool. It gives a detailed picture of whether a particular article or section was needed for the business. It is also a tool for identifying insights that help you make the right business decisions.



    Comment by Relap.io

    There is another point of view. Our Bigpicture.ru customers have abandoned Google Analytics. According to the editors, GA does not give all the answers that the media manager needs.
    “Google Analytics is good, but it’s not giving a complete picture in all slices. We have created our “Monitor” tool. ”
    Read more about how Bigpicture.ru analyzes content in an interview:
    How Bigpicture.ru Blog Team Sells Longreads for 1 Million Views and Opens SALO Agency




    Read a brief overview of metrics and methods that publishers can take in their arsenal. Content analysis is an extensive topic, so treat this information as a basis.

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    Define goals


    How do you earn? As an example, take these goals:

    • You want to increase the number of email newsletter subscribers, but there are fewer subscribers than you want.

    • You want to increase your advertising revenue by increasing traffic.

    • Subscription is the most profitable channel, but only 1% of visitors are ready to issue it.


    Let's see which metrics come in handy in each case, and outline why you need to pay attention to them.

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    Demographic indicators


    GA collects detailed information about visitors: age, gender, geographical location, language settings of the browser, and, most importantly, their area of ​​interest (sports, cooking, etc.)

    How to use


    SEO consultant Stephanie Chang advises paying close attention to demographic indicators in GA: where they live, how old they are, what they are addicted to.

    Chang suggests creating content based on readers' interests. For example, if GA shows that many visitors were to culinary sites last week, write articles on culinary topics as part of your publication. Geographic data will help you plan your content pointwise: if most of your readers are from the Midwest, a few articles about Chicago are a good idea.

    All three of the above business goals involve increasing audience. See who comes to your site right now. Demographic data is much more useful than analyzing old content.

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    Unique visitors


    Unique visitors (or "unique") - the number of people who came to the site or page.

    How to use


    Sites that sell display ads rely on unique visitors statistics, so for business goal 2, this metric is simply necessary.



    Comment Relap.io

    See what percentage of your visitors convert to clicks on ads or subscriptions. A low score means you need to try new ad formats or better engage your audience .




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    Conversion


    Conversion rate indicates the percentage of visitors who have performed a certain action - as a rule, made a purchase. There is a conversion by goals, it indicates the number of people who left an email, for example.

    How to use


    Conversion rate may vary depending on what you want. If you sell an annual subscription for $ 12,000 on a highly specialized topic, the rate will be lower than if you were offering readers a less expensive subscription to versatile topics.

    75% of e-commerce sites have a conversion of less than 5.3%; Content-oriented sites tend to have lower rates.

    If articles on a specific topic have lower conversion rates than on other topics, this is a clear signal that the content is not working.

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    Bounce rate


    When someone comes to the page and leaves without taking action, GA marks this visit as a “opt-out”. The lower the bounce rate, the better. A low score means your content is interesting to readers. SEO blogger Avinash Kaushik once mentioned (somewhat deceivingly, as we will see later) that the bounce rate is “Come, Vomit, Go.”

    How to use


    If some page collects more traffic than others, but at the same time it has a higher bounce rate or lower conversion rate - do not worry. Something on this page attracts the audience, but does not involve. A high bounce rate may be due to interface problems. Or there is nothing interesting on the page besides the content of the page itself.



    Comment Relap.io

    Your media is what is around the article. It depends on the frame around the content whether the reader remains or leaves. To engage the reader, personalize the blocks around the article. So each user will find on your site what interests him. When RIA Novosti started using the personalized Relap.io block , the number of referrals on recommendations increased by 101%, and the time on the site - by 19%.
    Read the details in the case: Relap.io will collect the “Main” on Ria.ru




    From time to time, you will see pages with a high bounce rate and high traffic. This is not always bad - if you sell ad impressions, such a page is useful, regardless of failures.

    The failure rate, by definition, is not self-sufficient: it does not indicate the course to action. You did everything right to attract readers if the traffic is high. It is worth paying special attention to the bounce rate if no one is subscribing to your newsletters or does not issue a paid subscription.

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    Average check


    AOV (Average Order Value) - indicates the average income from each visitor.

    How to use


    AOV is a key indicator in e-commerce. It is useful for media with selling pages, and for those trying to increase the number of subscriptions or selling tickets to conferences. Using AOV you can evaluate the effectiveness of discounts. Therefore, if you are offering a discount for a second or third subscription and want to know if the system is working, AOV is a necessary metric.

    Set Goals


    In GA, you can configure triggers - the so-called Goals, which record the fact of event X on the site. An event may be a click on an advertisement, or if someone stayed on the page for more than 5 minutes, or someone bought a subscription, or reached the page "confirmation of purchase", or subscribed to an email newsletter and others.

    Frequent script


    You create a page where the user lands when he performs an action - the purchase confirmation page, or the “Thank you for sharing email address with us” page. The goal is configured to visit such a page, and you can track which ways users get there most often.

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    Content Grouping


    Have you ever wondered why posts about fish drive more email requests than posts about cats? Readers who see the Comic Sans font subscribe less often than those who see Helvetica? Want to find out which author has more fans?

    How to use


    Grouping content in GA allows you to compare one piece of content with another. Grouping is perhaps one of GA’s most useful features.

    Categories can be formed by date, author, subject. Compare pages and see which text contributes to conversion. Or you can see which users have a higher average check (or number of subscriptions) depending on their conversion path.

    Content grouping is organized into three levels, so each group will have a subgroup and each subgroup a set of pages.

    Example:



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    Anna and Bob worked together on Article 1 — a useful feature: each web page can belong to more than one subgroup.

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    The disadvantage of grouping by content is the need to plan everything. If you want to add a new author or topic within the next 6 months — say, your fishing site will publish a series of articles on deer hunting — the results will be distorted if you do not add a new category in advance. So think ahead.

    Content grouping will not show how effectively your previously published articles about fish and cats attracted an audience and converted traffic. Data begins to be collected from the moment you configure categories. Therefore, the effective use of grouping involves the accumulation of information.

    What conclusions can you draw?


    For example, fans of Karlita's articles are more likely to buy a subscription than fans of other authors. Set the Goal on the subscription confirmation page, set up the author groups, and after several hundred visits to the page, you will receive answers.

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    Consider sample size


    The larger the sample, the better. Tracking conversion or bounce rates with 1,000 unique examples is better than 100, and 10,000 is even better. The required sample size depends on what actions you expect from visitors. If you sell something for $ 50,000, the conversion will be lower than if you collect email addresses for mailing.

    Instead of thinking about sample size from a unique visitor’s point of view, think about the time it takes to measure data: will you wait a week to find out if articles on agriculture stimulate more subscriptions than articles on grill? Will you wait six weeks? Two month? Often, strategic thinking over time is more useful than in the quantitative indicator of visitors.

    The more time, the more accurate the results. Accuracy is when the numbers stop jumping sharply. If you track how a new article affects conversion, it’s better to wait until the quantitative indicators stabilize on it and draw conclusions based on the data you’ve received. This is more reasonable than falling into euphoria and changing the design or content strategy just because 20% of 10 visitors to a new page bought a subscription.

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