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Tag: Analytics

How to Filter out Bots and Spiders from Google Analytics

August 13, 2019 No Comments

A common misconception is that Google Analytics or any other JavaScript based Web Analytics solution filters out Spiders and Bots automatically.  This was true till few years ago because most of the spiders and bots were not capable of executing JavaScript and hence were never captured by JavaScript based Web Analytics solutions. As shown in 4 reasons why your bounce rate might be wrong, these days bots and spiders can execute JavaScript and hence are showing up in your Web Analytics reports.

Google Analytics has released a new feature that will let you filter out known spiders and bots.  Here are few things to keep in mind

  1. The data will only filter spiders and bots from the day you enable this setting. It won’t be allied to the data already processed.
  2. Since this will filter out bots, you might notice a drop in your visits, page views etc.

 

Here are the steps to filter out Spiders and Bots

  1. Go to the Admin section of your Google Analytics report
  2. Click  “View” section and choose the right report view
  3. Click  on “ View Settings” (see image 1 below)
  4. Check the box under “Bot Filtering” which says “Exclude all hits from known bots and spiders” (see image 2 below)
  5. Click “Save” button at bottom and you are done.

 

filter-spider-bots-google-analytics-1Image 1

filter-spider-bots-google-analytics-2Image 2


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6 Reasons Why Your Google Analytics Reports Might Be Wrong

August 7, 2019 No Comments

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  1. Missing Tags – This is the most common error of wrong data.  This generally happens when new pages are added or the exiting pages are redesigned/recoded and the developer forgets to include the tags.  Make sure all of your pages are tagged with Google Analytics code.  You can use a tool like GAChecker, to verify if the Google Analytics tags are missing on any pages of your site.
  2. Mistagged Pages – Incorrect implementation or double tagging leads to wrong data in Google Analytics.  Double tagging results in increased page views and a low bounce rate. If you bounce rate is lower than 20% then that’s the first thing you should check.
  3. Location of GA Tags – Placing the tag towards the bottom of the page could result in no data particularly for the users with slow connections or pages that are slow to load.  This happens when a user tries to loads a page and clicks on another link before the first page is loaded. Since the Google Analytics tag is towards the bottom of the page, it might not get a chance to execute.  To avoid this issue, put your Google Analytics JavaScript in the <head> section of the page.
  4. Incorrect Filters – Wrong Filters can mess up the data and distort the view.  Always create an unfiltered view so that you have correct data to fall back on.
  5. Tags Not Firing Properly – This can happen when your page(s) have JavaScript errors.  A JavaScript error on any part of the page can result in an error in Google Analytics code. Verify the JavaScripts on your site to make sure there are no errors.
  6. Sampling – Sampling happens on highly trafficked site. Sampling in Google Analytics is the practice of selecting a subset of data from your traffic and reporting on the trends available in that sample set.  For most purposes, this might not be a non-issue however it can be of concern in eCommerce sites where sampling can (will) result in wrong sales figures.   You can get more information about GA sampling on “How Sampling Works“.


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SQL for Marketing Analysis – All Google Analytics Analysts Should Know

July 23, 2019 No Comments

Marketers and Marketing Analysts generally depend on the tools or IT department to help them pull the data for marketing purposes. There comes a time when they can’t just wait around for IT to help them data pulls and manipulations.  They have to know how to do it on their own. This course is for those marketers who would like to know how to use SQL to conduct their marketing analysis.

The course uses MYSQL to show how SQL works but all the leanings and syntax are applicable to other databases as well.  Sign up for SQL for Marketers and Marketing Analysts

SQLForMarketersCoverImage


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Software development analytics platform Sourced launches an enterprise edition

July 2, 2019 No Comments

Sourced, or source{d}, as the company styles its name, provides developers and IT departments with deeper analytics into their software development lifecycle. It analyzes codebases, offers data about which APIs are being used and provides general information about developer productivity and other metrics. Today, Sourced is officially launching its Enterprise Edition, which gives IT departments and executives a number of advanced tools for managing their software portfolios and the processes they use to create them.

“Sourced enables large engineering organizations to better monitor, measure and manage their IT initiatives by providing a platform that empowers IT leaders with actionable data,” said the company’s CEO Eiso Kant. “The release of Sourced Enterprise is a major milestone towards proper engineering observability of the entire software development life cycle in enterprises.”

Engineering Effectiveness Efficiency

Since it’s one of the hallmarks of every good enterprise tools, it’s no surprise that Sourced Enterprise also offers features like role-based access control and other security features, as well as dedicated support and SLAs. IT departments can also run the service on-premise, or use it as a SaaS product.

The company also tells me that the enterprise version can handle larger codebases so that even complex queries over a large dataset only takes a few seconds (or minutes if it’s a really large codebase). To create these complex queries, the enterprise edition includes a number of add-ons to allow users to create these advanced queries. “These are available upon request and tailored to help enterprises overcome specific challenges that often rely on machine learning capabilities, such as identity matching or code duplication analysis,” the company says.

Cloud Migration

The service integrates with most commonly used project management and business intelligence tools, but it also ships with Apache Superset, an open-source business intelligence application that offers built-in data visualization capabilities.

These visualization capabilities are also now part of the Sourced Community Edition, which is now available in private beta.

“Sourced Enterprise gave us valuable insights into the Cloud Foundry codebase evolution, development patterns, trends, and dependencies, all presented in easy-to-digest dashboards,” said Chip Childers, the CTO of the open-source Cloud Foundry Foundation, which tested the Enterprise Edition ahead of its launch. “If you really want to understand what’s going on in your codebase and engineering department, Sourced is the way to go.”

To date, the company has raised $ 10 million from Frst VC, Heartcore Capital, Xavier Niel and others.

Talent Assessment Managment


Enterprise – TechCrunch


Sisense acquires Periscope Data to build integrated data science and analytics solution

May 14, 2019 No Comments

Sisense announced today that it has acquired Periscope Data to create what it is calling a complete data science and analytics platform for customers. The companies did not disclose the purchase price.

The two companies’ CEOs met about 18 months ago at a conference, and running similar kinds of companies, hit it off. They began talking and, after a time, realized it might make sense to combine the two startups because each one was attacking the data problem from a different angle.

Sisense, which has raised $ 174 million, tends to serve business intelligence requirements either for internal use or externally with customers. Periscope, which has raised more than $ 34 million, looks at the data science end of the business.

Both CEOs say they could have eventually built these capabilities into their respective platforms, but after meeting they decided to bring the two companies together instead, and they made a deal.

Harry Glasser from Periscope Data and Amir Orad of Sisense.

Harry Glasser from Periscope Data and Amir Orad of Sisense

“I realized over the last 18 months [as we spoke] that we’re actually building leadership positions into two unique areas of the market that will slowly become one as industries and technologies evolve,” Sisense CEO Amir Orad told TechCrunch.

Periscope CEO Harry Glasser says that as his company built a company around advanced analytics and predictive modeling, he saw a growing opportunity around operationalizing these insights across an organization, something he could do much more quickly in combination with Sisense.

“[We have been] pulled into this broader business intelligence conversation, and it has put us in a place where as we do this merger, we are able to instantly leapfrog the three years it would have taken us to deliver that to our customers, and deliver operationalized insights on integration day on day one,” Glasser explained.

The two executives say this is part of a larger trend about companies becoming more data-driven, a phrase that seems trite by now, but as a recent Harvard Business School study found, it’s still a big challenge for companies to achieve.

Orad says that you can debate the pace of change, but that overall, companies are going to operate better when they use data to drive decisions. “I think it’s an interesting intellectual debate, but the direction is one direction. People who deploy this technology will provide better care, better service, hire better, promote employees and grow them better, have better marketing, better sales and be more cost effective,” he said.

Orad and Glasser recognize that many acquisitions don’t succeed, but they believe they are bringing together two like-minded companies that will have a combined ARR of $ 100 million and 700 employees.

“That’s the icing on the cake, knowing that the cultures are so compatible, knowing that they work so well together, but it starts from a conviction that this advanced analytics can be operationalized throughout enterprises and [with] their customers. This is going to drive transformation inside our customers that’s really great for them and turns them into data-driven companies,” Glasser said.


Enterprise – TechCrunch


ServiceNow acqui-hires mobile analytics startup Appsee

May 13, 2019 No Comments

In a carefully framed deal, ServiceNow announced this morning that it has acquired the intellectual property and key personnel of mobile analytics company Appsee for an undisclosed price. Under the terms of the deal, the co-founders and R&D team will be joining ServiceNow after the deal closes.

It’s worth noting that ServiceNow did not acquire Appsee’s customers, and the company is expected to wind down its existing business over the next 12 months.

Appsee provides more than pure numerical analytics. As the name it implies, it lets developers see what the user is seeing by recording an interaction and seeing what went right or wrong as the person used the program.

Appsee session playback in action.

GIF courtesy of Appsee

ServiceNow wants to take that functionality and incorporate it into its Now Platform, which enables customers to create customized service applications for their businesses, or use mobile applications it has created out of the box.

The company sees this as a way to improve the UI and build more usable apps. “We’ll be able to use Appsee for our mobile app and browser analytics. This can be used across all three of our workflows, and with this level of visibility our customers will be able to see how customers or employees are engaging [with the application]. With these analytics, ServiceNow will be able to provide insights on user behavior. In turn, this will help us provide an improved UI for customers,” a company spokesperson told TechCrunch.

Just last week at its Knowledge 19 customer conference in Las Vegas, the company announced Now Mobile, a new tool for performing tasks like ordering a new laptop or searching for the holiday calendar, and a mobile on-boarding tool for new employees. Both of these will be available in the company’s next release and could benefit from the Appsee functionality to improve the overall design of these products after it releases them to users.

Appsee has always been focused on capturing user activity. Over the years it has layered on more traditional analytics like DAUs (daily active users) and crash rates, the kind of metrics that can give companies insight into their user experience, but they combine that with the visual record to help see more detail about exactly what was happening, along with myriad other features, all of which will be incorporated into the ServiceNow platform moving forward.

The deal is expected to close by the end of Q2 2019.

Mobile – TechCrunch


An SEO’s guide to Google Analytics terms

December 22, 2018 No Comments

We all know Google Analytics is a powerful tool for serving up actionable data. And one of the quickest ways to get that data is to be clear about what all those terms mean.

What does bounce rate mean and is it connected in anyway to exit rate? And how about sessions and page views?

If those questions sounds familiar but you’re not sure of the answers, read on…

Because as soon as you understand all the Google Analytics terms, you can begin to get closer to the actionable data you need, the kind of data you can use to increase visitors, sales, and sign-ups.

Google Analytics can show what pages you need to improve in order to rank higher in organic search. It shows you if your copy needs tweaking, keywords need updating, or meta-descriptions re-writing. It also tells you if your call to action button is converting or not.

See also: A guide to setting up Google Analytics for your WordPress site.

Bounce rate

What Google Says:

“A bounce is a single-page session on your site. In Analytics, a bounce is calculated specifically as a session that triggers only a single request to the Analytics server, such as when a user opens a single page on your site and then exits without triggering any other requests to the Analytics server during that session.”

A user could leave a site because they lost interest, were confused, didn’t find the answer to their query, or did already found the information they were looking for.

The right kind of thinking here is this: What was the person expecting to find after searching for a keyword or key phrase. And does my site provide it?

If the bounce rate is very high, this is an indicator the site has a significant problem. Here are some helpful tips on ways to reduce bounce rate.

Alternatively, if the content is awesome and people spend a long time interacting with it, then that is known as “sticky” content.

If you’re just starting out with GA, here’s something to help get you started:

Clicks

The number of times people click on your link from the search results page is the number of clicks that appears on Google’s SEO report.

Clickthrough-Rate (CTR) is the number of clicks to your site divided by the number of impressions. Impressions are the amount of times your search link is shown to a searcher. So if CTR is high, the meta description is doing its job and converting searchers to visitors. However, if CTR rate is low then it’s worth testing different headlines.

Note that these clicks are not related to Google Ads clicks. These appear in Google Ads reports.

Entrances

If your site has more than one page then it has different entrance points, and Google records those separate entries.

Perhaps a blog post is performing well and bringing in traffic. Great. It might also show pages you want to be traffic-heavy are not performing properly.

Events

Events are certain user actions that happen on the site, and are created in line with KPIs.

For example, a site might offer a free download after pressing a button. So an event gets recorded each time the button is pressed. Now we have an event, we can extract actionable data. We know how many visitors the page had, and we know how many of those people we converted into button pressers.

Exit page

If an entrance page is where people arrive at your site, an exit page is where they leave.

A visitor may click through from the SERP, read the article, click on an internal link to read another article, then leave. Are there weaknesses on the exit page? This is easy to spot if one page stands out with a high leave rate.

Exit rate (% Exit)

The exit rate is calculated by dividing the number of ‘exits’ made from the page by the number of page views. However, a page with a high % exit rate may not necessarily have a high bounce rate.

But — and we said front and center these terms are confusing — a page with low exit rate is more likely to have a low bounce rate. That’s because users are probably heading to other pages on the site rather than exiting.

Hits

A hit is a request made to a web server to show a certain file. This could be a web page, an image or other things.

An event is considered a hit. A page view is a hit. All of these hits are grouped together in what Google calls a session. A session is a group of hits from one user. Google uses hits to determine the interaction between the user and the web page.

If the user takes no action for 30 minutes then Google ends the session.

Impressions

We first spoke of impression when looking at clicks. Impressions occur when your link is served up in the search results.

According to Google’s SEO Reports, impressions do not include impressions by paid Google Ads campaigns, which are recorded separately.

In short, when the user can see your link in the search results, that’s counted as an impression. And as you know, we use impressions and clicks to calculate the CTR.

Landing or entrance page

Both of these terms are used by Google to indicate the very first page a user lands on at the beginning of each session. This means in GA you can check which pages users most arrive at your site.

Page views

Page views are the number of times a visitor lands on any page of your website – these are called screen views on mobile.

Within page views, we first have unique page views. Google does not count multiple views of the same page by the same person in the same session as individual views. Instead, it counts them all as one unique view.

Then we have pages per session, also called ‘Average Page Depth’.

APD is the average number of pages viewed by a each user in one session and inside the analytics it includes repeated views of a single page.

Sessions

We encountered sessions earlier on. You already know that a session is the complete amount of time a visitor spends on your website.

You also know that each action a visitor takes is recorded as a hit. And all those hits are recorded within the session. This means in a 24 hour period you might have 100 sessions and 300 hits. The hits figure is equal to or higher than the sessions number.

There is a time limit on sessions. With standard GA settings, a session is ended after 30 minutes of inactivity.

Average session duration is the average time of a user’s session and the calculation to get this is to divide the session duration by the number of sessions.

Time on page

Time on page is the average amount of time that particular visitor spent on the page. If a page is text-heavy then there’s much more chance of each session producing a greater amount of time on page.

Google records average time on page. This is a simple calculation of dividing time on page by the number of page views, minus the exit number.

Users, visitors, or traffic — which one do you need to know?

Each of these terms describes visitors who access your site. Google uses these terms as and when they want.

There is, of course, a self-evident distinction between a new visitor and a returning visitor. Traffic generally expresses the total volume of people visiting the website. But traffic is split down into categories…

Direct traffic is when someone sends you the full URL to a website and you click on that link to go directly to the site. No search has has taken place. Direct traffic is common when sending out a link to your email list. Each person would directly access the site.

Next, we have organic search traffic. Organic traffic is free and targeted, and comes about from SEO efforts to rank the site as high as possible in those all-important Search Engine Results Pages (SERPs). If the site is showing little to no organic search, then go back to the drawing board on the keywords in use.

Paid search traffic means the number of people who visited the site via Google Ads.

Lastly we have referral traffic. This means a search engine, another website or social media site has placed a link to your web page on their site and is referring traffic to you.

Further reading

Overview

Reports

Tracking

Analysis

Custom segments

Error pages

Beyond GA

The post An SEO’s guide to Google Analytics terms appeared first on Search Engine Watch.

Search Engine Watch


Podcast industry aims to better track listeners through new analytics tech called RAD

December 12, 2018 No Comments

Internet users are already being tracked to death, with ads that follow us around, search histories that are collected and stored, emails that report back to senders when they’ve been read, websites that know where you scrolled and what you clicked and much more. So naturally, the growing podcast industry wanted to find a way to collect more data of its own, too.

Yes, that’s right. Podcasts will now track detailed user behavior, too.

Today, NPR announced RAD, a new, open-sourced podcast analytics technology that was developed in partnership with nearly 30 companies from the podcasting industry. The technology aims to help publishers collect more comprehensive and standardized listening metrics from across platforms.

Specifically, the technology gives publishers — and therefore their advertisers, as well — access to a wide range of listener metrics, including downloads, starts and stops, completed ad or credit listens, partial ad or credit listens, ad or credit skips and content quartiles, the RAD website explains.

However, the technology stops short of offering detailed user profiles, and cannot be used to re-target or track listeners, the site notes. It’s still anonymized, aggregated statistics.

It’s worth pointing out that RAD is not the first time podcasters have been able to track engagement. Major platforms, including Apple’s Podcast Analytics, today offer granular and anonymized data, including listens.But NPR says that data requires “a great deal of manual analysis” as the stats aren’t standardized nor as complete as they could be. RAD is an attempt to change that, by offering a tracking mechanism everyone can use.

Already, RAD has a lot of support. In addition to being integrated into NPR’s own NPR One app, it has commitments from several others that will introduce the technology into their own products in 2019, including Acast, AdsWizz, ART19, Awesound, Blubrry Podcasting, Panoply, Omny Studio, Podtrac, PRI/PRX, RadioPublic, Triton Digital and WideOrbit.

Other companies that supported RAD and participated in its development include Cadence13, Edison Research, ESPN, Google, iHeartMedia, Libsyn, The New York Times, New York Public Radio and Wondery.

NPR says the NPR One app on Android supports RAD as of now, and its iOS app will do the same in 2019.

“Over the course of the past year, we have been refining these concepts and the technology in collaboration with some of the smartest people in podcasting from around the world,” said Joel Sucherman, vice president, New Platform Partnerships at NPR, in an announcement. “We needed to take painstaking care to prove out our commitment to the privacy of listeners, while providing a standard that the industry could rally around in our collective efforts to continue to evolve the podcasting space,” he said.

To use RAD technology, publishers will mark within their audio files certain points — like quartiles or some time markers, interview spots, sponsorship messages or ads — with RAD tags and indicate an analytics URL. A mobile app is configured to read the RAD tags and then, when listeners hit that spot in the file, that information is sent to the URL in an anonymized format.

The end result is that podcasters know just what parts of the audio file their listeners heard, and is able to track this at scale across platforms. (RAD is offering both Android and iOS SDKs.)

While there’s value in podcast data that goes beyond the download, not all are sold on technology.

Most notably, the developer behind the popular iOS podcast player app Overcast, Marco Arment, today publicly stated his app will not support any listener-tracking specs.

“I understand why huge podcast companies want more listener data, but there are zero advantages for listeners or app-makers,” Arment wrote in a tweet. “Podcasters get enough data from your IP address when you download episodes,” he said.

The developer also pointed out this sort of data collection required more work on the podcasters’ part and could become a GDPR liability, as well. (NPR tells us GDPR compliance is up to the mobile apps and analytics servers, as noted in the specs here.)

In addition to NPR’s use of RAD today, Podtrac has also now launched a beta program to show RAD data, which is open to interested publishers.

Mobile – TechCrunch


Better understand and reach your customers with new Cross Device capabilities in Google Analytics

July 24, 2018 No Comments

Today, we’re introducing new Cross Device features to Google Analytics. Analytics will now help you understand the journey your customers are taking across their devices as they interact with your website, giving you a complete view of the impact of your marketing so you can run smarter campaigns that deliver more tailored experiences to your customers.

Piecing together a more complete picture

Cross Device reporting in Analytics takes into account people who visit your website multiple times from different devices. Now, instead of seeing metrics in Analytics that show two separate sessions (e.g., one on desktop and the other on mobile), you’ll be able to see when users visited your website from two different devices. By understanding these device interactions as part of a broader customer experience, you can make more informed product and marketing decisions.

Say you’re a marketer for a travel company. With the new Acquisition Device report, you may find that a lot of your customers first come to your website on mobile to do their initial research before booking a trip later on desktop. Based on that insight, you might choose to prioritize mobile ad campaigns to reach people as they start to plan their trip.

In addition to the Acquisition Device report, you’ll soon have access to other Cross Device reports like Device Overlap, Device Paths and Channels. Our Cross Device reports only display aggregated and anonymized data from people who have opted in to personalized advertising (as always users can opt out at any time).

Reaching the right customers along the way

Analytics will also now help you create smarter audiences based on the actions people take on various devices. That way you can deliver more relevant and useful experiences.

Let’s say you’re a shoe retailer and you want to share a special promotion with your most loyal customers. You decide this means people who have purchased more than $ 500 in shoes on your website in the last 12 months using any of their devices. If a group of customers buy $ 300 worth of shoes on their phone and another $ 300 on their desktop, they’re just as valuable as another group who spend $ 600 on a single device, right?

Analytics now understands that these two groups of customers actually spent the same amount on your website, helping you create a more accurate audience list to reach the right customers. And spend isn’t the only way to segment and build audiences. You can also create remarketing campaigns to reach audiences based on how many times they visit your website across multiple devices.

Get started

To use these new Cross Device features, start by visiting the Admin section of your Analytics account and choose the setting to activate Google signals. (If you don’t see this setting, you will soon—we’ll roll it out to all Analytics accounts over the coming weeks.) There’s no need to update your website code or get additional assistance from a developer.

With these new beta features in Analytics, we hope you’ll quickly see that by better understanding the customer journey across devices, you can create more relevant and useful experiences for your customers.


Google Analytics Blog