Google is rolling out a new report in Analytics which analyzes a website’s custom audiences.

This appears to be a quiet rollout with no official announcement, though Google is notifying users upon logging into Analytics.

Here is the notification that comes up for those who have access to the new report:

Clicking on “see report” will, of course, bring you to the report. It also triggers another notification with links to learn more about it.

The report can be accessed manually by opening “Reports,” expanding the “Audience” tab and clicking on “Audiences.” It’s clearly marked as “NEW” so you can’t miss it.

In order to collect any data in this report, you must first have audiences configured in your Google Analytics account. Otherwise, the report will appear blank.

A custom audience is a group of visitors that have met a pre-defined condition. For example, audiences can be created for new visitors, returning visitors, past purchasers, users who have visited a specific section of a site, and so on.

Once audiences have been created and published to Google Analytics, the Audiences report will begin to display the following metrics:

  • Acquisition: The volume of users an audience is sending you, and how well the audience works to generate potential new business.
  • Behavior: How well a site engages a particular audience based on bounce rate, pages per session, and time on site.
  • Conversions: How well an audience is performing in terms of goal completions and transactions.

Knowing how an audience is performing, or not performing, can help site owners determine how much of their time and budget should be spent marketing towards that specific segment of visitors.

Aside from a small amount of forum chatter I haven’t seen much information going around about this new report. That leads me to believe it could be rolling out on a limited basis. So if you don’t see this report in your Google Analytics, chances are it will be coming eventually.

Source: This article was published searchenginejournal.com By Matt Southern

Categorized in Search Engine

…and how to get the info you need

If you do anything online — a website, a blog, a mobile app — chances are you’re using Google Analytics. Somewhere between 30 and 50 million websites rely on it for tracking and measuring the metrics that matter to them.

It’s powerful. It’s robust. It’s free (and everyone loves free).

But it’s not perfect. Like everything else, it has its shortcomings. It’s flawed, occasionally misleading, and an outright failure in some ways.

Analyzing and exploring the data it collects can guide your decisions and help you transform your website into a conversion machine.

That’s good.

However, there are some things it can’t tell you. Information you need to make the most informed decisions about your business, your website, and your marketing strategies.

That’s bad.

Are there ways to bridge those gaps? You better believe it.

Man typing on computer

User Experience and Intent

The most consistent complaint against the platform is that it focuses too much on your success — traffic, clicks, downloads, and conversions — and not enough on your failures, which can be even more revealing.

Analytics excels at presenting the “what:” bounce rates, exit pages, traffic sources, session length, landing pages, site speed, and so on.

It’s not so good at giving you a “why,” and that’s arguably the more important question.

It’s great to know your conversion rate. It’s wonderful to see that Facebook sends a steady stream of traffic your way.

But what about the people that visit your site, explore a little (or a lot), and then leave? Or customers that abandon their cart on the last step? Wouldn’t it be great to have some data about that, to know why it happened (and not just that it did)?

You can. You just need to look beyond Analytics.

There are dozens of tools and services out there to give you that priceless insight:

Q&A

The easiest thing to remember in both life and business is that if you don’t know, ask. Simple. So if you don’t know why your visitors and customers are doing or not doing something, ask them. But how?

A service like Qualaroo can do it for you. They provide real-time opportunities to ask targeted questions at particular points in your funnel, on certain pages, exit surveys when they click to leave, or for segmented audiences (based on time on page, number of visits, and more). Their onsite surveys ask the right questions at the right time (while it’s happening), collating the responses and presenting them to you in easy-to-digest reports.

Qualaroo website homepage

These “voice of customer” insights lead to better, stronger business decisions, and that leads to a better, stronger business.

Heat Maps

Get a visual representation of how visitors are interacting (and actively not interacting) with each page on your site. A heat map like Crazy Egg or Simple Heatmaps provides tons of data on user clicks, attention, and scrolling.

See exactly where they do and do not click, look, scroll (and stop scrolling), and read. You can eliminate or improve dead zones, streamline pages by removing links, forms, and content that is being ignored, opting to move it or lose it. You can even color code those clicks and looks by the originating source of the traffic. Give your visitors the website they want, based on what they’re already doing and not doing on it.

Session Replays

Imagine being able to stand behind your visitors and watch over their shoulder as they explore and engage with your site. You’d see firsthand where they get confused, when the navigation is misleading, their path from arrival to ultimate conversion, and so on.

A valuable exercise, but unrealistic. Or is it?

You can get the same virtual experience with a tool like Jaco or Clicktale. They can record every user session in its entirety — complete with session transcript, advanced filters, and session scorecard — allowing you to watch at your leisure and see exactly what they’re doing, problems they’re having, obstacles, bottlenecks, hesitation, and more.

Jaco website homepage

See your website, product, or service through their eyes. Experience the buyer’s journey from their perspective. And then make it better for them. The best way to understand and appreciate the user experience is to experience it. These tools let you do that. Get the “why” to go with the Analytics “what”.

Call Tracking

We live in a mobile, digital, always-connected world. But to assume no one is using “older” technology like the phone is premature. People are still going to call for more information, or to make an appointment, or to request a quote, or to make a purchase.

You’ve most likely got your business number listed somewhere on your website and marketing materials.

Google Analytics can tell you when someone arrives at your digital doorstep via Twitter, or Instagram, or that guest post on another industry blog. That’s useful information that helps you allocate budget and resources (more to channels working, less to those that aren’t).

But what if someone calls you after getting your number from your Facebook Page? You have no way of tracking that point-of-contact. You just know they called you. Maybe you jot that down in the customer profile (if you create one), maybe you don’t. Either way, Facebook isn’t getting the credit it deserves for that new lead/customer.

Enter call tracking.

With it, you attach a unique phone number to each campaign or channel in order to track who’s calling and to which campaign they’re responding for each call you receive. That’s the kind of detailed attribution you need.

Why is this important? A phone call response typically converts in the 30-50% range (we only call when we’re really, really interested), compared to only 1-2% for online clicks, and up to 92% of calls coming through to a business originate from a digital campaign. That’s why.

Call tracking providers like CallRail or Call Sumo bridge the gap between your online marketing and real-world responses. They can record those calls, and offer call management, call attribution, and call analytics.

CallRail website homepage

Let Analytics handle the digital responses and traffic. But for the humble phone call, you need to look elsewhere.

Speaking of attribution…

Attribution Problems

Without a little extra work and tweaking, Analytics is notoriously mediocre at attribution. It’s a session-based platform that’s great at tracking a user during a single session: where they came from, what they did once they arrived, and where they exited. It is not great at multi-session visits.

Part of the problem stems from how GA tracks users. It needs access to someone’s tracking cookies, but if a user frequently deletes those cookies, for example, then you run into all kinds of problems.

No cookie, and a return visitor to your site will be cataloged as a new user by GA. If they visit, erase the cookie, visit again, erase again, and finally visit a third time and sign up for your newsletter, Analytics will classify them as a first-time new user, and that conversion will be credited to whatever channel brought them back that third time (most likely direct, which is why direct traffic numbers on GA are often skewed).

One way around this that provides at least better (though not perfect) attribution and session tracking is assigning a unique user ID to each visitor. You have to set it up on your Analytics view (you have to enable it and then implement in your code), but once you do, you’ll be able to connect multiple devices, sessions, and engagement for more accurate user and attribution data.

Another simple tweak to ensure you’re getting reliable campaign data is to use UTM parameters for each marketing campaign you have going.

Use Google’s Campaign URL Builder, fill in the required fields, and then see accurate and precise data for each individual campaign under Acquisition > Campaigns > All Campaigns. See which ones are bringing people in, converting, and growing your business (and by extension, which ones aren’t).

It’s an easy enhancement to GA, but there are a number of common mistakes people are making over and over again. Read through and avoid them.

With multi-channel marketing (and let’s face it, most of us are using several channels), proper user and attribution data is crucial. Give GA everything it needs to present the best data possible.

Keywords (Not Provided)

Last but not least, you already understand the importance of keywords to your digital marketing and SEO efforts.

Analytics is not much help here unless you connect your Search Console and GA accounts (enable it under Admin > Property > Property Settings > Search Console).

Once you do, you can see the search terms that are bringing people to your site under Acquisition > Search Console > Queries. You’ll see each search query along with its corresponding impressions, clicks, CTR, and Average Position.

Google Analytics Search Console

Useful, but you’ll also likely see the dreaded (Not Provided). Google is encrypting more and more of its keyword data, making your job that much harder.

But there are a few ways to glean a bit more information.

For starters, drill down to the landing page level and add keyword as secondary dimension. Head on over to Behavior > Site Content > Landing Pages. Scroll down to the bottom list, click on Secondary dimension, and type “Keyword” in the field to add that data set to the report.

Google Analytics Landing Pages

Now, for each page that people arrive on, you’ll see the search words that are bringing them in. If you see (Not Provided) for any page, you can take a reasonable guess as to the missing term by either a) considering the keywords you targeted with that page, or b) comparing it to the provided terms for that same page.

Is it a perfect solution? Not at all. But it does give you a bit more to work with.

You might also consider using paid search a bit more, too. The keywords for your AdWord campaigns are not hidden from you like they are for organic search. You’ll see all the terms bringing in paid traffic.

Google Analytics is good, but it’s not without its flaws. The suggestions here can provide more of what you need, but it’s still not everything.

At a minimum, connect your GA account to Search Console for better organic search query data. Connect it to your Adwords account for query, sitelink, and cost data, as well as richer data sets in general. Turn on Advertising Reporting Features (found under Admin > Property > Tracking Info > Data Collection) for more visitor detailed demographics and interests.

And if you’re tired of just not “getting” Analytics in the first place, check out a beginner’s guide. There’s no shame in starting at the beginning. Even the experts among us were newbies at some point.

Finally, don’t forget that Google Analytics is not the only game in town. Alternatives include Adobe Analytics, Piwik, and Clicky (which very cleverly highlights the features either missing or inadequate in Analytics). Each has its own strengths and weaknesses, and might be a better fit for what you need from your analytics solution.

Clicky, for example, provides reports on every single person who visits your website, along with video analytics, search keyword rankings, and heat maps built right in. Adobe Analytics provides better data storage, and Piwik is open source.

Find the right tool for your job.

What data is missing from Google Analytics for your needs? What do you use to fill that gap? Leave your answers on social media.

Author : Aaron Agius

Source : https://www.searchenginejournal.com/google-analytics-cant-tell/187131/

Categorized in Search Engine

The holidays are all about tradition and bringing cheer to your family, friends, and clients. For me, that applies to the Google Analytics metrics I have come to know and love when sending my clients their monthly reports. For most of us, the holidays are the all-too-short-lived time where families gather ’round a tree, get and give gifts we may or may not use, and eat a harvest of homemade food. For others, the more data-driven geeks like myself, that slew of holiday treats takes second place to the festive findings of my Google Analytics dashboards.

Whatever you’re looking forward to this holiday season, I’ve got some easy Google Analytics reports for my SEO marketing friends that will make your extra two-and-half days off a little more om. Ahead, find 6 Google Analytics reports that brought me lots of cheer for this year during this cornucopias gourd filled fall season. Hint: You may want to add these to your wishlist!

Before I dive into the details of Google Analytics reports, I wanted to share an overview of factors and metrics I consider before building my report. These vary from person-to-person and brand-to-brand.

Before We Begin

First, what metrics align with your overall business goals? Google Analytics reports give you an overview of your website and business health. What metrics are important to your client? Here is a snapshot of what I take into consideration for the majority of my clients:

  • Organic Traffic tells you the number of users who have visited your site organically (unpaid) whether through Google, Bing, or another search engine.
  • Referral Traffic tells you the number of users who have visited your site outside of search engines. Referral traffic is also a good identifier of how your content and brand visibility is performing off-site.
  • Organic Conversions tells you how your content, landing pages, and user experience are performing.
  • Referral Conversions tells you the sites you are getting the most external traffic from. Yes, you can do this with UTM parameters, but referral conversions give you a wide scoping view.

Next, take a look at the timeframe you want to monitor. For example, I monitor reports on a 28-day period so each month is consistent. And, the same goes for quarterly. I use 90-day period for my quarterly reports.

Lastly, how do you plan to track your SEO growth? I prefer to track my progress week over week to compare a chosen period against the previous year. But, others prefer a snapshot view with no previous history data to compare.

Now, let’s dig in a little deeper to discover what SEO reports I use regularly to track my performance and show proof in SEO value.

1. Year-Over-Year Organic Traffic

How to Build This Report:

1. Go to Acquisition > All Traffic > Organic Search

yoy organic traffic_Google Analytics

2. Click Customize in the top left corner of the screen.

3. Create a new custom report named “Organic by Month.” The Metric Groups should read “Sessions,” “Goal Conversion Rate,” and “Goal Completions.” While “Month of Year” should be selected in Dimension Drilldowns. And, lastly, the Filters should include “Medium” + “Exact” + “Organic.”

yoy organic traffic custom report_Google Analytics

4. You should get a month-over-month (MoM) comparison.

MoM comparison in Google Analytics

5. Export each year to Google Sheets and combine the two sheets.

6. Then, you can create a Google chart to begin identifying trends and patterns year-over-year.

analytics year over year organic search in google sheets

What This Report Tells You:

The loss of organic traffic fear is real, especially when it comes to your personal website or client’s site. Surely, the best practice is to monitor your data regularly, checking real-time data, analyzing new vs. return visitors, or referral traffic. But once you see your organic traffic slowly drip into a downward pattern, are you sure you were monitoring the right data?

Unfortunately, “out of sight, out of mind” does not apply to tracking your organic traffic. Was the drop from seasonality? Or, did a competitor launch a new campaign?

As you can see from the example above, traffic is above the previous year, but it does decrease toward the end of the year. This helps us to normalize traffic each year. And, you can compare this year’s traffic as a percentage of last year’s traffic.

Here’s an example below:

Google Analytics Organic YoY Percentage Reports

The decrease in traffic has its surprise drops; it’s not very regular. There’s a significant decrease in May and again in October, which could be seasonality or SEO visibility. Regarding SEO visibility, this could be a change in J-SON, PPC, or keyword positioning. I’d suggest digging deeper to identify the concerns for your client.

Bonus Tip:

If you want to take your organic traffic year-over-year reports to the next level, upload your data from above into Distilled Forecaster tool. This tool will help you predict future traffic levels based on your historical data. And, it will help you map out your on-site technical SEO recommendations. For example, if you’re planning to redo the metadata in Q1 of next year, your changes may affect the overall site traffic.

Distilled_Forecaster SEO Organic traffic

2. Scroll Depth Tracking

How to Build This Report:

1. Your website must already be connected to Google Tag Manager.

2. Open Google Tag Manager, click “Add a New Tag.”

GTM Add New Tag

3. In Tag Configuration, click “Custom HTML.”

Custom HTML Tag Configuration in GTM

4. Copy and paste this code by Rob Flaherty.

<script>
/*!
 * @preserve
 * jquery.scrolldepth.js | v0.4.1
 * Copyright (c) 2014 Rob Flaherty (@robflaherty)
 * Licensed under the MIT and GPL licenses.
 */
;(function ( $, window, document, undefined ) {
   
  "use strict";
 
  var defaults = {
    elements: [],
    minHeight: 0,
    percentage: true,
    testing: false
  },
 
  $window = $(window),
  cache = [];
 
  /*
   * Plugin
   */
 
  $.scrollDepth = function(options) {
     
    var startTime = +new Date;
 
    options = $.extend({}, defaults, options);
 
    // Return early if document height is too small
    if ( $(document).height() < options.minHeight ) {
      return;
    }
	
     // Get some information about the current page
    var pageTitle = document.title;
	
    // Establish baseline (0% scroll)
    sendEvent(pageTitle,'Baseline');
 
    /*
     * Functions
     */

function sendEvent(action, label, timing) { if (!options.testing) { if (typeof(dataLayer) !== "undefined") { dataLayer.push({'event':'ScrollDistance', 'eventCategory':'Reading', 'eventAction':
action, 'eventLabel': label, 'eventValue': 1, 'eventNonInteraction': true}); if (arguments.length > 2) { dataLayer.push({'event':'ScrollTiming', 'eventCategory':'Reading', 'eventAction':
action, 'eventLabel': label, 'eventTiming': timing}); } } else { if (typeof(ga) !== "undefined") { ga('send', 'event', 'Reading', action, label, 1, {'nonInteraction': 1}); if (arguments.length > 2) { ga('send', 'timing', 'Reading', action, timing, label); } } if (typeof(_gaq) !== "undefined") { _gaq.push(['_trackEvent', 'Reading', action, label, 1, true]); if (arguments.length > 2) { _gaq.push(['_trackTiming', 'Reading', action, timing, label, 100]); } } } } else { $('#console').html(action + ': ' + label); } } function calculateMarks(docHeight) { return { '25%' : parseInt(docHeight * 0.25, 10), '50%' : parseInt(docHeight * 0.50, 10), '75%' : parseInt(docHeight * 0.75, 10), // 1px cushion to trigger 100% event in iOS '100%': docHeight - 1 }; } function checkMarks(marks, scrollDistance, timing) { // Check each active mark $.each(marks, function(key, val) { if ( $.inArray(key, cache) === -1 && scrollDistance >= val ) { sendEvent(pageTitle, key, timing); cache.push(key); } }); } function checkElements(elements, scrollDistance, timing) { $.each(elements, function(index, elem) { if ( $.inArray(elem, cache) === -1 && $(elem).length ) { if ( scrollDistance >= $(elem).offset().top ) { sendEvent('Elements', elem, timing); cache.push(elem); } } }); } /* * Throttle function borrowed from: * Underscore.js 1.5.2 * http://underscorejs.org * (c) 2009-2013 Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors * Underscore may be freely distributed under the MIT license. */ function throttle(func, wait) { var context, args, result; var timeout = null; var previous = 0; var later = function() { previous = new Date; timeout = null; result = func.apply(context, args); }; return function() { var now = new Date; if (!previous) previous = now; var remaining = wait - (now - previous); context = this; args = arguments; if (remaining <= 0) { clearTimeout(timeout); timeout = null; previous = now; result = func.apply(context, args); } else if (!timeout) { timeout = setTimeout(later, remaining); } return result; }; } /* * Scroll Event */ $window.on('scroll.scrollDepth', throttle(function() { /* * We calculate document and window height on each scroll event to * account for dynamic DOM changes. */ var docHeight = $(document).height(), winHeight = window.innerHeight ? window.innerHeight : $window.height(), scrollDistance = $window.scrollTop() + winHeight, // Recalculate percentage marks marks = calculateMarks(docHeight), // Timing timing = +new Date - startTime; // If all marks already hit, unbind scroll event if (cache.length >= 4 + options.elements.length) { $window.off('scroll.scrollDepth'); return; } // Check specified DOM elements if (options.elements) { checkElements(options.elements, scrollDistance, timing); } // Check standard marks if (options.percentage) { checkMarks(marks, scrollDistance, timing); } }, 500)); }; })( jQuery, window, document ); jQuery.scrollDepth(); </script>


GitHub has some additional data on coding your scroll depth.

2. Choose how to display your scroll depth. Some users prefer percentages (10%, 25%, 50%, 75%, 100%) and others choose labels like Article Loaded, Start Reading, Content Bottom, etc. This particular code uses percentages, but you can change the naming conventions if needed. Here is the scroll tracking code for that by Justin Cutroi:

<script>
jQuery(function($) {
    // Debug flag
    var debugMode = false;

    // Default time delay before checking location
    var callBackTime = 100;

    // # px before tracking a reader
    var readerLocation = 150;

    // Set some flags for tracking & execution
    var timer = 0;
    var scroller = false;
    var endContent = false;
    var didComplete = false;

    // Set some time variables to calculate reading time
    var startTime = new Date();
    var beginning = startTime.getTime();
    var totalTime = 0;
    
    // Get some information about the current page
    var pageTitle = document.title;

    // Track the aticle load
    if (!debugMode) {
        ga('send', 'event', 'Reading', pageTitle,'Article Loaded', {'nonInteraction': 1});
    } else {
        alert('The page has loaded. Woohoo.');    
    }

    // Check the location and track user
    function trackLocation() {
        bottom = $(window).height() + $(window).scrollTop();
        height = $(document).height();

        // If user starts to scroll send an event
        if (bottom > readerLocation && !scroller) {
            currentTime = new Date();
            scrollStart = currentTime.getTime();
            timeToScroll = Math.round((scrollStart - beginning) / 1000);
            if (!debugMode) {
                ga('send', 'event', 'Reading', pageTitle,'Start Reading', timeToScroll, {'metric1' : 
timeToScroll}); } else { alert('started reading ' + timeToScroll); } scroller = true; } // If user has hit the bottom of the content send an event if (bottom >= $("#authorTemplate").scrollTop() + $("#authorTemplate").innerHeight()
&& !endContent) { currentTime = new Date(); contentScrollEnd = currentTime.getTime(); timeToContentEnd = Math.round((contentScrollEnd - scrollStart) / 1000); if (!debugMode) { if (timeToContentEnd < 60) { ga('set', 'dimension1', 'Scanner'); } else { ga('set', 'dimension1', 'Reader'); } ga('send', 'event', 'Reading',pageTitle,'Content Bottom', timeToContentEnd,
{'metric2' : timeToContentEnd}); } else { alert('end content section '+timeToContentEnd); } endContent = true; } // If user has hit the bottom of page send an event if (bottom >= height && !didComplete) { currentTime = new Date(); end = currentTime.getTime(); totalTime = Math.round((end - scrollStart) / 1000); if (!debugMode) { ga('send', 'event', 'Reading', pageTitle,'Page Bottom', totalTime, {'metric3' : totalTime}); } else { alert('bottom of page '+totalTime); } didComplete = true; } } // Track the scrolling and track location $(window).scroll(function() { if (timer) { clearTimeout(timer); } // Use a buffer so we don't call trackLocation too often. timer = setTimeout(trackLocation, callBackTime); }); }); </script>

3. Choose how you want the scroll depth to work. Do you want to send an event after the user scrolls 200 pixels? You can change the value to whatever works best for you. If you’re comfortable with coding, you can edit this in code in this area above (just be sure to select the remaining areas):

ga('send', 'event', 'Reading', pageTitle,'Article Loaded', {'nonInteraction': 1});


4. Under “Triggers,” add “All Page View.”

GTM triggering for scroll depth tracking
6. Go to Variables > New (under User-Defined Variables) > Data Layer Variable. Then, add eventCategory. And repeat this step for eventAction; eventLabel; eventValue.

GTM variables data layer variable

data layer variable in GTM

7. Head back to the Tags > New > Google Analytics (choose depending on Classic or Universal). It should look something similar to the below:

google analytics tracking code in GTM

9. Under that same Tag, go to Triggers > Custom Event. Then, give it a name.

GTM custom events scroll depth

To make sure your GTM code is firing view, go to Behavior > Events > Top Events > Scroll Tracking in Google Analytics. It should look something like this:

event tracking percentages in Google Analytics

If this sounds like mumbo-jumbo to you, then stick to something like Crazy Egg’s Scrollmap tool.

What This Report Tells You:

Let’s just come out and say it — do you know if people are reading your content? Or, looking at all your products?

Once you add Scroll Depth tracking, you can identify if users are making it to the bottom of your page. Scroll Depth tracking is essential if you have a one-page website or a super long great homepage. Knowing your scroll depth can help structure and prioritize relevant site information at the top if the majority of users aren’t scrolling down. For example, if your higher priced products are at the bottom, you may want to reorganize them to mingle with the lower priced items. Scroll Depth tracking allows you further develop your pages with proper content placement.

Bonus Tip:

You want to pair Scroll Depth tracking with other metrics like advanced click event tracking, pageviews, bounce rate, time on page, and other engagement metrics to track interactions and performance. You can set this up with micro conversions in Google Analytics. Your goal should look something like this:

Now, you can see that every session (or visit) that a user scrolls more than 75% is now recorded as a conversion. This tells me these users are engaged in site design and content.

3. Micro Conversion Tracking

How to Build This Report:

  1. Identify your micro conversions. This is different for every site. I would suggest creating micro conversions if you have downloadable files, a newsletter, create an account or an add to cart function. You may need to create a ‘Thank You’ page to begin tracking these conversions. Here’s an example from SEJ.
  2. Set up goal tracking in Google Analytics. Again, depending on your micro conversion, this process will be different.
  3. Analytics Set Up Goals
  4. Verify your goal and watch the numbers start rolling in.

What This Report Tells You:

Micro conversion tracking shows you the steps a user takes before converting. It will allow you to see patterns that users frequently do before they purchase your product or contact you.

Measuring micro conversions are just as important as measuring macro conversions (the purchase). The more know what the users are doing before they buy, the more you can give them and optimize your site further.

Here are a few examples of micro conversions:

  • Comment on an Instagram post
  • Sign-up for your newsletter
  • Read a blog post
  • Download a size chart

Here are some ideas of macro conversions:

  • Purchasing a product
  • Contacting us

Micro conversions help lead you down the conversion funnel more accurately. Glenn Gabe talks more about conversion goals in Google Analytics.

Bonus Tip:

Once you have a good grasp on micro conversions, start assigning a dollar value to the micro conversions.

For example, if 100 users are signing up for your newsletter and 50 users to watch your product videos, but users who watch your product videos are more likely buy your product, they have a higher conversion rate. Once you have the conversion rate, you can attach an average order value to determine where to spend your budget.

Here’s an example of the formula I would use:

Average value of watching a product video = Revenue generated by users who watched the video / number of videos.

4. Organic Landing Page Traffic

How to Build This Report:

  1. Head over to Google Analytics > Acquisition > Channels > Organic Search.
  2. Add the secondary dimension of “Landing Page.”

google analytics landing page

What This Report Tells You:

When you’re able to match up your keyword terms with your landing pages, you’re able to work around the (not provided) issue. Now, instead of compensating for keyword data, you’re getting a holistic view of how pages on your website are performing. If your click-through rate is low and your bounce rate is high, you may want to consider working with a web designer to update your site. Or, if your bounce rate is high (depending on the site, I’m looking for anything over 75%), then you may want to consider rewriting the page to reflect more accurate search queries.

Bonus Tip:

If you take this a step further by using the “Landing Page” as your primary dimension. Then, add “Page Depth” as your secondary dimension. With this view, you’ll have an even better perception on which pages are driving high-quality traffic. Understanding what pages are pushing users to click around your site more will help you grasp what type of content your users want.

5. Multi-channel Funnels Assisted Conversions

How to Build This Report:

  1. In Google Analytics, go to Conversions > Assisted Conversions.

google analytics assisted conversions
2. Create a new segment including any interaction from Organic Search and excluding the last interaction from Organic Search.

google analytics organic search segment

What This Report Tells You:

Multi-channel Funnel (MCF) reports helping you identify first and last click attribution. In a short version, MCF reports show you what interactions your customers are taking before they complete a goal.

MCF reports are impressive for direct traffic since direct traffic isn’t correctly attributed in the main channel reports. They give you a wider scope of what is happening on your site. As an SEO consultant, I want to know what campaigns are contributing to the success or failure of my client’s website. SEO converts users, but it also assists in conversions, so I want to know what’s working and what’s not, especially for my e-commerce clients. Typically with e-commerce, I won’t see a first-time visitor convert, but with MCF reporting I can more accurately evaluate what channels are working.

When you add the new segment to determine the true value of organic search, you can see the assisted conversions and the assisted conversion value.

Bonus Tip:

It’s important to note that MCF tracking only gives us 30 days while Acquisition reports give you way more data. To fix this, change your default settings to 90 days. It will give you more data to work with and let you look at the bigger picture.

90 days google analytics assisted conversions

6. Organic Traffic Keyword Value

How to Build This Report:

  1. In Google Analytics, go to Behavior > Site Search > Search Terms and export the data. If you have Google Search Console connected, you can also check out Acquisition > Search Console > Queries to connect the dots in your data.
  2. Go to Google Keyword Planner and upload your data under “Get search volume data and trends.”
  3. google keyword search and google analytics
  4. Use the “Suggested bid” to give value to your search terms.

What This Report Tells You:

Giving a dollar value to your keyword terms that are already driving traffic to your site helps your client visualize the worth of your SEO strategy. It’s one thing to tell a client about their domain authority, traffic, and conversions from organic traffic, but it’s a whole other ball game when you can show your blog post positioned around a keyword term brought in the majority of money last month.

Bonus Tip:

To display this data, create a spreadsheet listing impressions, clicks, cost-per-click (from the ‘Suggested bid” above) and total value.

Keyword Organic Value

Your Turn

Okay, you know the drill: It’s the last month before the end of the year, holiday marketing campaigns are rolling in. And yes, this is a thrilling time, but there is a certain level of stress that comes with analyzing the Q4 data. It can be especially stressful for those who aren’t familiar with all the tips and tricks of Google Analytics reporting, which, let’s be honest, was all of us at some point.

These Google Analytics reports are available for free and are perfect for all of my favorite fall holidays. Because, supposedly, holidays are all about giving thanks. From tracking SEO performance to assisted conversions, I am thankful for these Google Analytics reports and all the delicious data they send my way. The reports above are just a few to help you get started.

Thanks so much for reading! I hope that gives you something to be cheerful for this holiday season. I’d love to know what reports and metrics you look at in Google Analytics. What’s important to you? What reports do you clients find most beneficial? I’d love to hear from you in the comments below.

Pinterest Graphic: 6 Google Analytics Reports That Will Bring Every SEO Lots of Cheer

Author: Anna Crowe
Source: https://www.searchenginejournal.com/google-analytics-reports-holiday/179077

Categorized in Search Engine

Fraudulent transactions can occur for most any ecommerce company. Larger companies can invest in sophisticated fraud protection services. But smaller merchants sometimes attempt to detect fraud themselves.

Back in 2014 we addressed do-it-yourself fraud detection. The article, from columnist Erica Tevis, owner of an online gift store, has helped many smaller merchants.

But Google Analytics can help detect fraud, too. I’ve used it for my own niche ecommerce site (selling imported food products), which occasionally encounters fraudulent orders.

In this article, I’ll explain how to use Google Analytics to examine three characteristics of suspect transactions, to help detect fraud.

Use Google Analytics to Identify Fraudulent Orders

Characteristic 1: The transaction was not recorded in Google Analytics. If you suspect fraud, see if the transaction was reported in Google Analytics. If not, it could be that the purchaser is using a browser add-on or he disabled JavaScript to block the sessions and transactions in Google Analytics.

To find a transaction in Google Analytics, go to “Conversions > Ecommerce > Sales Performance” and view the list of Transaction IDs.

Go to “Conversions &gt; Ecommerce &gt; Sales Performance to view Transaction IDs.

Go to “Conversions > Ecommerce > Sales Performance” to view Transaction IDs. Click image to enlarge.

Select a date range that should include the suspect order.  If you see potential transaction matches, enter the Transaction ID in the search box for more details.

If you see potential transaction matches, enter the Transaction ID in the search box for more details.

If you see potential transaction matches, enter the Transaction ID in the search box for more details. Click image to enlarge.

Characteristic 2: The geo-location of the transaction does not match the billing address. Follow the instructions above to find the transaction in Google Analytics. If it is present, click on the Transaction ID to display the products in the order, then click on “Secondary Dimension” and enter “Country,” “Region,” and “City” to identify where the purchaser was located.

Selecting country of the transaction can identify the location of the purchase, to match against the billing address he provided.

Selecting country of the transaction can identify the location of the purchase, to match against the billing address he provided.

Example Results When “City” is Selected as the Secondary Dimension

Example results when “City” is Selected as the Secondary Dimension. Click image to enlarge.

Google Analytics uses IP addresses to identify geo-location. It is not precise. But it can provide clues to the actual location of the purchaser at the time of the transaction.

People frequently purchase gifts, so that their billing address is different from the shipping address(es) in the order. That’s why it’s important to compare the billing address, not the shipping address, to the Google Analytics geo-location.

Erica Tevis, in her aforementioned article, stated that expedited delivery requests can be suspect. Couple expedited delivery requests with a geo-location in Google Analytics not matching the billing address and you may want to flag the order.

Geo-location information in Google Analytics that is “(not set)” could also be a suspect. In Google Analytics, “(not set)” means the location of the IP address cannot be identified. But“(not set)” could also be a legitimate sale. So “(not set)” alone should not be the sole determining factor.

These transaction IDs with “(not set)” as the Region are, in fact, legitimate.  

These transaction IDs with “(not set)” as the Region are, in fact, legitimate.

Characteristic 3: Purchaser spent much time on the website — especially on the payment page. If you find a suspect transaction, create an advanced segment for that Transaction ID, as follows.

First, click on “All Users” at the top-center of the reports to open the advanced segments window.

Click on “All Users” at the top-center of the reports in Google Analytics to open Advanced Segments

Click on “All Users” at the top-center of the reports to open advanced segments.

Next, click on “New Segment,” give it a name (such as the Transaction ID) and click on “Conditions” on the left-hand side. Select “Transaction ID” for the Filter and enter the Transaction ID in the box, then save.

Select “Transaction ID” for the Filter and enter the Transaction ID in the box, then save.

Select “Transaction ID” for the Filter and enter the Transaction ID in the box, then save.

There are two locations to view a user’s activity.

  • User report. This is a new report that shows all sequential steps and timing of the session(s) for a user. Find this report under “Audience > User Explorer.” Click on a “Client Id” in the list.
To see the sequential steps and timing for each user, go to “Audience &gt; User Explorer.”

To see the sequential steps and timing for each user, go to “Audience > User Explorer.”

You can see how the user arrived on the site. In the example below, the user was on a desktop device and arrived via paid search. Click on the arrow next to the time for the beginning of the session for more details.

Click on the arrow next to the time for the beginning of the session for more details.

Click on the arrow next to the time for the beginning of the session for more details.

You will see all the actions taken in the session in descending order of timeframe.

You will see all the actions taken in the session in descending order of timeframe.

You will see all the actions taken in the session in descending order of timeframe.

In this transaction, which was fraudulent, the person spent 22:36 (22 minutes, 36 seconds) on the website, which is much longer than a typical purchaser. He did not spend a lot of time – only one minute — on the payment page, however, which is highlighted above. If he had spent much time on the payment page, that could indicate he was trying to enter a credit card numerous times.

Looking down the session details, I see that the user spent three minutes on the customer information page, which is where purchasers enter the shipping and payment addresses. Three minutes is excessive.

The purchaser spent three minutes, an abnormally long period, on the customer information page, which is where they enter the shipping and payment addresses. 

The purchaser spent three minutes, an abnormally long period, on the customer information page, which is where users enter their shipping and payment addresses.

  • Content report. This is the second option for viewing users’ activity. Go to “Behavior > Site Content > All Pages” to view all pages that were visited in the session. I have highlighted, below, the address page, which this person spent 3:30 on. I also highlighted that he had two page views for the payment page, indicating that he had trouble on that page and it reloaded once.
Go to “Behavior > Site Content > All Pages” to view all pages that were touched in the Session.

Go to “Behavior > Site Content > All Pages” to view all pages that were touched in the session. Click image to enlarge.

The data from these two reports — User and Content — was not convincing that the user was a fraudster. But the reports are worthwhile to see the details of the suspect transaction.

Author : MORGAN JONES

Source : http://www.practicalecommerce.com/articles/132357-Using-Google-Analytics-to-Identify-Fraudulent-Orders

Categorized in Internet Ethics

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