6 Google upcoming Products you should try this year 2016

6 Google upcoming Products you should try this year 2016

At this year’s Google I/O conference, Google displayed the future way of Interacting with the technology. It started with Google Assistant to Google Home, which they believe to take on rivals like Amazon Echo and Facebook’s new Bot chat. So here are the 6 Google Upcoming products you should try this year 2016.

Google Voice Assistant:

Sundar Pichai, CEO of Google, started the keynote followed by he made big announcement about Google Assistant. He explained How Google Assistant is going to bring two way communication between you and Google Assistant and he also mentioned last year 20% searches were made via voice in U.S and that is why Google is gearing up to make Voice search as more friendly to its users.

Google Home:

So followed by Google Assistant, there was an another announcement which was more innovative (As they call it like that) Google Home. It will take the best properties from Chromecast and use them in the house and it also has the search function built-in, so people can make voice search.


It is a companion app for one-to-one video calling.  The goal of Duo is to make video calling faster even on slower network speed. Google is also adding a feature in Duo called Knock Knock, which allows you to make a live video of the other caller before you answer. It is coming live for this Summer on both Andriod & IOS.

Day dream:

Day Dream is going to be a new high-quality mobile virtual reality platform which allows manufacturers including Samsung, HTC and Huawei having smartphones capable of handling it. New hardware tools like headsets and a controller will be available for Daydream VR. Which is getting launched this fall and it will also include Google’s apps like YouTube, Street View, Play Movies , Google Photos and the Play Store.


To compete with popular chat services such as Facebook’s Messenger, which recently announced an artificial intelligence features and WhatsApp which also owned by Facebook, Google is launching Allo by bringing interesting features like stickers and whisper chat. Allo also uses smart reply, which is a suggestive conversational response. It will use Google’s computers to predict how you want to respond, saving you typing. It will also chat directly with Google to find information or navigate. In Google Allo one can search the web, watch YouTube videos and even play games. Google Assistant is embedded in app too. Allo will be coming to market this Fall.

Android Wear 2.0:

Android Wear 2.0 will have a revamped user experience and standalone apps that run right on the watch, no matter where your phone is or even if it’s off. Users can now mix and match watch faces with various apps on any Android Wear ready smartwatch. A better keyboard is also available on the Android Wear smartwatch.



How do you Track Offline Interactions in Google Analytics

How do you Track Offline Interactions in Google Analytics

Tom Capper, leading Analytics consultant gives information about Tracking Offline interaction with the help of Google Analytics and steps about how to integrate it.

The trouble with web analytics is the possibility of it telling you lots about your website but nothing about your business. A browser is not the same thing as a customer, and yet we forget this in the data that we use to optimize our marketing efforts. Using Google Analytics, part of the solution to this problem is User ID, which allows us to track users as they move between multiple browsers, as long as they log in along the way. However, a lot of the most important interactions in a customer’s journey might not take place in a browser at all – instead they’ll take place in a shop, or over the phone, at an event, or in the customer’s inbox. In these cases, it might be that you can draw together these interactions with your existing Google Analytics data using Measurement Protocol.

Introduced with Universal Analytics, Measurement Protocol is an alternative way of sending data to Google Analytics that gives you far more control than traditional on-page code – allowing you to send custom hits associated with specific users, even if no web pages were involved.

In this guide, I’ll look to explain what can and cannot be done with Measurement Protocol and how to deploy it in practice. Primarily this will be focused on the use case of lead tracking, but the lessons here apply to any application of Measurement Protocol. I’ll also offer some tips and caveats from our experiences deploying Measurement Protocol solutions with our clients.

If you’re not already confident with Google Analytics, you might want to check out Google’s own Digital Analytics Fundamentals before you read further, or at least this guide to how sessions are calculated.

The Importance of Offline steps:

Measurement Protocol stays within Google Analytics’ paradigm of hits, sessions, and users – it’s another way of sending a hit besides the more traditional JavaScript snippet approach.

Looking at our attribution reports in Google Analytics with a purely on-site implementation, we might get the impression that a user:

  • Discovered us when our great content was shared on social media
  • Came back via organic and decided to get in touch
  • Later signed up to attend one of our meetups

If this is a lead generation site, we’d probably be very pleased to see a journey like this, but there are two problems with it. Firstly, it doesn’t actually tell us whether this turned out to be a good lead or a bad lead – should we invest more in content, or does this content just bring in leads that turn up to an event then go dead? Secondly, we risk seriously misunderstanding what it is that turns a website visitor into a likely customer – simply by failing to record steps in the process that might not have taken place on the website.

The journey above might actually look more like this, with offline interactions shown in blue:

  • Discovered us when our great content was shared on social media
  • Came back via organic and decided to get in touch
  • Was called by the sales team, who brought up the topic of relevant upcoming events
  • Later signed up to attend one of our meetups
  • Spoke with the team at the event
  • Arranged a contract over phone and email

Adding in these offline interactions, we have a far fuller view of what this customer’s path to conversion actually looked like, and we can confirm that this was a “good” lead of the sort that we might want to attract more of – rather than just ending the funnel at lead generation.

Used Cases:

The example above is probably the most common use-case – lead generation. However, we can actually use Measurement Protocol in any situation that meets the following criteria:

  • Users making themselves uniquely identifiable to CRM, e.g.:
    • Customer number
    • Email address
    • Username
  • Non-website interactions that happen after this fact but where the CRM could be referenced, e.g.:
    • Phone call
    • Email
    • Live chat
    • In person (store / showroom / branch / event)

More broadly, you could use Measurement Protocol for any of the following:

  • Conversions that occur away from your website
  • Steps toward conversion that occur away from your website
  • Engagement with your brand that occurs away from your website

In each of these cases, what you’d want to send to Google Analytics is a little different. For example, if you want to record steps towards conversion, you probably want to give them a medium, whereas if you want to record the conversion itself, you want to attribute that to the medium of a previous session. Which brings us neatly to the setup process.

Attribution using measurement protocol:

Measurement Protocol sends data to Google Analytics using a GET or POST request to a given URL. The parameters added to this URL are the data itself. There has to be a hit of some sort (such as a pageview, event or transaction), and the time of that hit cannot be overridden – for instance, you cannot place an additional hit into the middle of a session that occurred yesterday. Nonetheless, this facilitates accurate attribution of offline interactions, due to an oft-maligned quirk of Google Analytics – that it uses “last non-direct click” for everything, including the sources and mediums of sessions themselves. As Measurement Protocol hits are by default “direct”, “last non-direct click” attribution causes them to inherit attribution data from previous sessions.

So, for example, if we sent a hit to Google Analytics with no source (i.e. a direct hit) when we spoke to the customer at the event on the 12th of December in the above table, this session would be attributed by Google Analytics to “email”, the last known non-direct source for that Client Id. The only exceptions are if more than 90 days have passed since the last session with a non-direct source, or if you override attribution data in your Measurement Protocol hit.

The last missing component here is matching the customer at the event to his last known session. Typically, the way this works in practice is that wherever on the site a user can be added to the CRM, their clientId is added as an invisible field. Then if we want to send offline interactions recorded in our CRM back into analytics, or send website visits recorded in our analytics into our CRM, we have a unique value that we can use to match browsers to people.


Setup part 1: Prerequisites

Measurement Protocol requires a Google Analytics account that has been upgraded to Universal Analytics. While it’s been a long time since we’ve seen one that hasn’t been upgraded, you can check yours to be sure by going to the Admin menus and checking for Universal Analytics features like the “Referral Exclusion List”.

Setup part 2: Collecting client ID

Client ID is used by Google Analytics to uniquely identify browsers, and it’s a required parameter for Measurement Protocol hits.

It’s worth noting here that if you have multiple tracking IDs per page, users will generally have the same Client ID across all of them, so you don’t need to worry about getting the right one. You can confirm this yourself by following step five here and looking at the query parameters of individual Google Analytics hits on your site.


10 Basic Digital Marketing Metrics for Marketers

10 Basic Digital Marketing Metrics for Marketers

As you draft up your campaign or strategy, always ask yourself this question:

Can I measure this?

For the most important components of your project, the answer will likely be yes. So before you begin executing, make sure you’re laying down a solid foundation for how you will measure your success.

When you’re wondering if your efforts were worth it later, or speculating over whether you’ve done a good job, these metrics will be there for you, answering your questions, providing proof, and cheering you on to greater altitudes.

The metrics you’ll want to track will actually be dependent on your most important goals for a project or campaign. Although all projects are different, here are some great, mainstream metrics that I measure as a rule of thumb:

Screen Shot 2016-04-06 at 8.55.59 PM

Digital Marketing Staples

1. Overall Traffic Metrics


“All Traffic” (from Google Analytics) will show you how many people visited or engaged with your site in total. It can be broken up into source/medium, which describes where your traffic comes from.


Overall traffic will give you a bird’s eye view of where you stand. It’s a good idea to benchmark or keep an eye on your total traffic over time. You may begin to see similar patterns emerge—like seasonality—that can put you ahead of the game later. The rule of thumb here is that if you’re doing a good job, your overall traffic from all sources should steadily increase over time.

How to Measure:

First, enter your Google Analytics dashboard.

  1. Go to the Acquisition report section
  2. Go to Overview
  3. Look in the Sessions column in the table

10 Basic Digital Marketing Metrics for Marketers

2. Channel-Specific Traffic


These metrics depend on where people were immediate before arriving at your site. The channel is the type of door they used to enter your site.


Looking at your top mediums is important to measure for full-scale digital marketing campaigns. It allows you to see what’s causing a drop in visits (if you see dips in overall traffic) and where your campaign excels.

Channels to Watch:

  1. Direct: This is when people directly type in your URL to visit your site or who began to search in the omnibox but visited your site before. The omnibox automatically fills in because they’ve been there before.
  2. Referral: These are people who came to your site from another website. It’s external traffic. People followed a link on a different domain to get to you.
  3. Organic: These are people who performed a search on a search engine such as Google or Bing, and clicked on your website’s listing in the organic (non-paid) search results.
  4. Social: People who came to your site from a social media platform. It’s also a great indicator to gauge the general effectiveness of your SEO, social engagement, content, and integrated campaigns.

10 Basic Digital Marketing Metrics for Marketers

3. Total Conversions


Traditionally, a “conversion” is when someone evolves from a simple user visiting your site to a paying customer. However, in today’s digital world we want to track engagement and what our customers are doing on our website to get them deeper into our funnels.

More generally, it’s when users complete any desired action, such as filling out a form, clicking a download button, sign up for a trial, download an ebook, create an account, etc.


Source: Convinceandconvert.com & Rahul Alim



google 360

Google Logo

Google Launches New Universal Analytics Premium Data Tools for Digital Marketers

This tuesday, Online search engine giant Google unveiled a new suite of marketing analytics and data products. The offering, the Google Analytics 360 Suite, will compete with similar marketing “cloud” solutions offered by companies such as Adobe, Oracle, Salesforce and IBM.

The Google suite is compromised of six separate tools, some of which are new, and some of which are updated and repackaged versions of existing products. The idea is to provide marketers with a centralized platform to track and store information about customers and their behaviors.

For example, the tools might help an online retailer understand why a customer initially visited its site, enable it to track the customer’s purchases and actions, and help tailor future advertising and marketing efforts to that person based on that data.

“The suite is designed to give marketers a single view of the entire customer journey,” said Paul Muret, vice president of analytics, display, and video products at Google

One notable introduction is a data management platform, or DMP, called Google Audience Center 360. Google says marketers can use the tool to store and analyze customer data collected across multiple different devices and platforms. The DMP will also connect to ad-buying software offered by Google and others to help inform targeted ad buys.

Another new tool called Google Optimize 360 will enable marketers to personalize their websites for different types of visitors, while the Google Data Studio is designed to turn marketers’ data into interactive reports and dashboards.

The suite will also include an updated analytics feature called Google Analytics 360, formerly called Google Analytics Premium, and an attribution product called Google Attribution 360, formerly known as Adometry.

Many marketers already use similar tools, but they often stitch together technologies from multiple vendors. According to Mr. Muret, marketers might benefit from having all of these tools under one roof, because of Google’s ability to integrate them so closely with each other, and with other Google data and technology.

“We feel like we’re bringing together best-of-breed systems that really help to get to the point where you’re taking advantage of these systems much faster and with much more precision”, Mr. Muret said.

The individual tools in the suite will integrate with non-Google products, however. For example, the Audience Center DMP can be integrated with online ad-buying tools provided by third-parties, as well as its own AdWords and DoubleClick ad products.

“We’re taking an open approach and working to make all the systems interoperable. We recognize we need to interoperate with other platforms to make things more realistic,” Mr. Muret added.

Google isn’t the only company attempting to be a one-stop-shop for marketers’ needs. In recent years companies including Adobe, Oracle and Salesforce have assembled similar suites or “stacks,” designed to help marketers closely track and measure their interactions with customers on the Internet and elsewhere.

Marketers might also be nervous about Google handling more of their data. Some say they’re already concerned with the power the online ad giant wields in the market.

By Jack Marshall


GA Custom Report

Google Analytics custom Report

How to Use Google Analytics Custom Report

In this article, Shanelle Mullin explains about How to use Google Analytics Report.

Many Google Analytics custom reports are configured incorrectly. More often, Google Analytics configurations are broken, rendering custom reports even less effective. Before you begin experimenting with custom reports, conduct a Google Analytics Health Check.

Once you’re sure your analytics are healthy, you can begin trying to understand the five key elements of custom reports: users, sessions, hits, metrics and dimensions.

  1. Users: A segmentation level option. This is the broadest level; each individual person is a unique user.
  2. Sessions: A segmentation level option. Most users make multiple visits, which is known as a “session”.
  3. Hits: A segmentation level option. Within each “session”, there are hits.
  4. Dimensions: Every report is made up of dimensions and metrics. Dimensions describe characteristics (e.g. geographic location or browser).
  5. Metrics: Every report is made up of dimensions and metrics. Metrics are quantitative measurements (e.g. sessions or conversion rate).

There are also three different report types: explorer, flat table and map overlay.

  1. Explorer: This is the basic report. It includes the line graph and the data table below, which you’re very familiar with.
  2. Flat Table: This is one of the most common custom report types. It’s essentially a sortable data table.
  3. Map Overlay: This is simply a global map with colors to indicate engagement, traffic, etc.

Of course, there is the Google Solutions Gallery, which allows you to choose from dozens of user-made custom reports, advanced segments and dashboards with the click of a button. However, for best results, you should understand how each report was configured and why.

So, why use Google Analytics custom reports? Primarily because there is a lot of data available to you. Sorting through it manually and trying to analyze it for insights can be incredibly time-consuming. Custom reports collect the data and present it in a way that makes it easier for you to analyze.

But what are you analyzing for? If you go into Google Analytics without the right questions in mind, you’ll get lost after hours of unguided searching. As W. Edwards Deming said…

If you do not know how to ask the right question, you discover nothing.

Start by conducting heuristic analysis. (For more information on heuristic analysis,read through the ResearchXL model.) After heuristic analysis, you should have a list of questions you need to answer. Like…

  • Does the site look good in all browsers? On all devices?
  • Why is the post-purchase page loading slowly?
  • Are button clicks being tracked?
  • Is anyone actually using XYZ?

Your list will be much longer. Use these questions to guide your Google Analytics exploration and give you purpose.

Now, there are two things to remember when choosing or creating a custom report: choose representative, useful metrics and everything is better with segmentation.

You should have acquisition metrics, behavioral metrics and result metrics no matter what. You want to get a full end-to-end picture, so create custom reports that give you that.

Also, segmentation can be applied to custom reports the same way it can be applied to the basic Google Analytics reports. Take advantage of that to make your custom reports even smarter.

(For an in-depth guide to Google Analytics segmentation, click the below Read more Button.)


6 Email Marketing hack Metrics & KPIs You Should Be Tracking

In this article, Lindsay Kolowich explains about Email Marketing Metrics and Key performance Indicators which should be tracked by Email Marketers.

1) Clickthrough Rate

  • What It Is: The percentage of email recipients who clicked on one or more links contained in a given email.
  • How to Calculate It: (Total clicks OR unique clicks ÷ Number of delivered emails) * 100
  • Example: 500 total clicks ÷ 10,000 delivered emails * 100 = 5% clickthrough rate

(Using either total clicks or unique clicks in the calculation above works, as long as you use the same approach consistently.)

Clickthrough rate (CTR) is likely the first answer you’ll get when you ask an email marketer what metrics they track. It’s what I like to call the “day-to-day” email marketing metric, because it lets you easily calculate performance for every individual email you send. From there, you can track how your CTR changes over time.

CTR is also frequently used for determining the results of A/B tests, as these tests are often designed with the intention of finding new ways to get more clicks in your emails. Clickthrough rate is a very important metric for all email marketers to be tracking, as it gives you direct insight into how many people on your list are engaging with your content and interested in learning more about your brand or your offer. Read this blog post to learn what a “good” clickthrough rate is, according to industry benchmarks.

2) Conversion Rate

  • What It Is: The percentage of email recipients who clicked on a link within an email and completed a desired action, such as filling out a lead generation form or purchasing a product.
  • How to Calculate It: (Number of people who completed the desired action ÷ Number of total emails delivered) * 100
  • Example: 400 people who completed the desired action ÷ 10,000 total email delivered * 100 = 4% conversion rate

After an email recipient has clicked through on your email, the next goal is typically to get them to convert on your offer — in other words, to take the action that your email has asked them to take. So if you’re sending an email to offer your audience the chance to download, say, a free ebook, you’d consider anyone who actually downloads that ebook to be a conversion.

Because your definition of a conversion is directly tied to the call-to-action in your email, and your call-to-action should be directly tied to the overall goal of your email marketing, conversion rate is one of the most important metrics for determining the extent to which you’re achieving your goals. (We’ll discuss more specific goal-related metrics later.)

In order to measure conversion rate on your emails, you’ll need to integrate your email platform and your web analytics. You can do this by creating unique tracking URLs for your email links that identify the source of the click as coming from a specific email campaign.

3) Bounce Rate

  • What It Is: The percentage of your total emails sent that could not be successfully delivered to the recipient’s inbox.
  • How to Calculate It: (Total number of bounced emails ÷ Number of emails sent) * 100
  • Example: 75 bounced emails ÷ 10,000 total emails sent * 100 = 0.75% bounce rate

There are two kinds of bounces to track: “hard” bounces and “soft” bounces.

Soft bounces are the result of a temporary problem with a valid email address, such as a full inbox or a problem with the recipient’s server. The recipient’s server may hold these emails for delivery once the problem clears up, or you may try re-sending your email message to soft bounces.

Hard bounces are the result of an invalid, closed, or non-existent email address, and these emails will never be successfully delivered. You should immediately remove hard bounce addresses from your email list, because internet service providers (ISPs) use bounce rates as one of the key factors to determine an email sender’s reputation. Having too many hard bounces can make your company look like a spammer in the eyes of an ISP.

4) List Growth Rate

  • What It Is: The rate at which your email list is growing.
  • How to Calculate It: ([(Number of new subscribers) minus (Number of unsubscribes + email/spam complaints)] ÷ Total number of email addresses on your list]) * 100
  • Example: (500 new subscribers – 100 unsubscribes and email/spam complaints) ÷ 10,000 email addresses on the list * 100 = 4% list growth rate

Aside from the call-to-action metrics (CTR, conversion rates), you’ll also want to be keeping tabs on your list growth and loss. Of course, you should be aiming to grow your list in order to extend your reach, expand your audience, and position yourself as an industry thought leader. But believe it or not, there’s a natural decay of your email marketing list, and it expires by about 22.5% every year — which means that it’s more important than ever to pay attention to growing your subscriber list and keeping it at a healthy size.

5) Email Sharing/Forwarding Rate

  • What It Is: The percentage of email recipients who clicked on a “share this” button to post email content to a social network, and/or who clicked on a “forward to a friend” button.
  • How to Calculate It: (Number of clicks on a share and/or forward button ÷ Number of total delivered emails) * 100
  • Example: 100 clicks on a share/forward button ÷ 10,000 total delivered emails * 100 = 1% email sharing/forwarding rate

The rate at which your email recipients forward or share your email with others may not seem all that significant, but it’s arguably one of the most important metrics you should be tracking.

Why? Because this is how you generate new contacts. The folks on your email list are already in your database. So while conversion is still a primary focus, this doesn’t help you attract newleads. Encourage your readers to pass along your email to a friend or colleague if they found the content useful, and start tracking how many new people you can add to your database this way.

Keep a careful eye on your sharing rates to discover which types of articles and offers tend to get shared the most, and use that insight when you plan email campaigns in the future.


Two methods to track your customers lifetime value in Google Analytics

In this article, Mr. Jim Gianoglio, Senior Analytics Consultant explains about tracking customer lifetime value in Google analytics for online shopping websites.
In marketing, customer lifetime value (CLV), also referred to as lifetime value (LTV), is a prediction of the value a customer will have over there lifetime with your company or brand. This is often estimate, or averaged, sometimes with complex formulas. This topic has been thoroughly covered by some excellent posts, and several books,  so I don’t intend to regurgitate what’s already been written. My goal is to introduce another method of tracking CLV with Google Analytics.

Instead of estimating CLV with simple (or complex) formulas, I’ll have you recording the actual lifetime value of each and every customer by the end of this post.

Two Methods: Custom Dimensions and Custom Metrics

You might think that a value like CLV should be tracked as a custom metric, because it’s a number. And you’re right, partially. But there are some limitations and pitfalls to be aware of when using this method.

Custom dimensions can also be used to track CLV, and should be used in conjunction with custom metrics. Each option has benefits and drawbacks.

Custom Dimensions


  • Can be used with Data Import
  • Can reflect the CLV of a user at any time (not dependent on the data range of the report)
  • Easy to get a distribution of users by CLV


  • Can’t easily segment by users with greater than or less than a certain CLV
  • Can’t report the average CLV per channel, region, etc.

Ed Brocklebank of Metric Mogul has written an incredibly detailed and complete post on tracking CLV with custom dimensions. I highly recommend reading through it and setting those up.

However, there is still some benefits to be had by tracking CLV with custom metrics. That’s what I intend to show you.

Custom Metrics


  • Can be used to show average CLV of users
  • Can be used to show average CLV by segment (channel, region, etc.)
  • Can be used to segment users with greater than or less than a certain CLV


  • Can only report CLV for date range selected. If you have a long date range and a lot of traffic, your data is likely to be sampled

New Big Data Platform Designed to Solve Digital Analytics Challenges

Webtrends Infinity is a new big data platform for capturing, processing, storing and interrogating unlimited datasets for companies that want actionable customer intelligence to fuel their marketing programs. It’s a new approach that takes the promise of big data and transforms it into a tangible, meaningful and practical solution for the endless seas of digital information that companies have struggled to take full advantage of.

Big data has matured rapidly in the last 10 years,” said Steve Earl, senior director of product marketing for Webtrends. “The big data ecosystem provides a set of open source technologies that enable us to take advantage of massively parallel processing at a reasonable cost. Now, we’re able to use it to solve real problems for the broader market. Webtrends Infinity leverages big data technologies to uncover actionable customer intelligence needed to deliver truly personalized experiences.”


How to align User personas with content grouping in Google Analytics

In this article, David Kutcher  explains about aligning user personas with help of Google Analytics.

The purpose of your content is not to feed the content beast or the empty space in your website, but to reach, connect and convert your target audiences to your business.

As content marketing and intent-driven micro-moments evolve, defining your organization’s Buyer Personas and then strategically creating content that is aligned with one or more of those Personas provides a way towards the most effective content.

The main reasons for this strategy are that

  • you can create content that is written for specific audiences, tailored for them and their situation
  • highly tailored content will perform much stronger with the target audience than generic content as you speak their language to their needs
  • you can evaluate how you are connecting, satisfying, and converting individual personas, and compare them to other personas or the site average

Once you’re using Personas for your content creation, the next step is seeing how the Personas perform and gaining actionable intelligence from those metrics. To see how your Buyer Personas are performing in Google Analytics we’re going to use a little-discussed featured called Content Groupings to get us there.


Something that we often see in regards to Google Analytics and Buyer Personas is the idea of using Analytics as a way of formulating your Personas. This strategy uses data, most commonly found in the Demographics reports of Analytics, as a way of learning about their audiences.

In our opinion this is often a backwards approach. Demographics make awful Buyer Personas. They’re good at expanding your knowledge of a persona, but are a poor way of defining your personas.

For example, the website of a pilates studio might have the following personas:

  • A person seeking physical rehabilitation
  • A person seeking a “beach body”
  • A triathlete working on keeping flexible
  • A high school athlete
  • A senior citizen trying to keep injury free

In this example the Personas would be virtually indistinguishable or overlapping through Google Analytics’ demographic data, but these definitions provides the most value to the business. Each Persona needs to have content and messaging attuned to their individual needs and desires in order to be effective. How the business frames/targets a blog post on using pilates to recover from an accident will differ significantly from a blog post on getting fit using pilates, and the content loses efficacy when written generically.


Thanks: Moz.com

Six Google Analytics Reports to add on your Website Content Audit

In this article, Daniel Hochuli explains about six basic Google analytics reports to be added tracking your website content.

I’m a big believer that every good content marketing strategy begins with a comprehensive audit of the website’s current performance. The simple reason is that you cannot plan ahead if you do not already have a great understanding of where you currently are.

In this article, I will show you how a content audit with six important Google Analytics reports can help you make some smart decisions about the health of your current site, what your audience wants from your content, and how you can benchmark your performance for future content marketing efforts.

The six reports include the following:

  1. Channels report
  2. Landing Page report
  3. New vs Returning Visitor report
  4. Frequency & Recency report
  5. Site Search report
  6. Behavior Flow report

Now, these aren’t the only reports you should use in your content audit, and you don’t need to be a Google Analytics doyen to gather insights from these reports, you just need to know what you’re looking for.

For the above-mentioned reports, we will aim to answer the following questions about content on your website:

  • How is my audience finding my content? (Channels report)
  • Which content piece is performing the best in terms of traffic, engagement, and conversion? (Landing Page report)
  • What should my content performance benchmarks be? (Landing Page report)
  • Do I need to prioritize building an audience; or should I nurture my existing audience? (New vs. Returning report)
  • How many pieces of content do I need to create a month? (Frequency & Recency report)
  • What are the topics I should be talking about, but are not? (Site Search report)
  • Is my content successful at driving business transactional goals? (Behavior Flow report)
  • What is the value of my content? (Behavior Flow report)

First, though, some housekeeping: In order to create a comprehensive content audit in Google Analytics, you need to create some Advanced Segments.