What are UTM Parameters and How To Implement Them Easily

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What are UTM Parameters and How To Implement Them Easily 

Using UTM Tags To Measure Your Marketing Efforts with Opentracker.

Q: How can you benefit from using UTM tags?

A: Using UTM tags will allow you to capture information from ALL your incoming traffic campaigns and put it directly in your traffic reports. Conversions, sources, returning visitors, etc. So you can get a complete insight.

In this how-to, you will learn what UTM 
parameters are and also the industry standards on how to use them. Using UTM tags and parameters, successful marketers are able to specifically measure how they’re hitting goals. As a result, a content editor will know that tweets from company accounts are driving traffic to the correct website if UTM parameters are being used..

What are UTM Tags/Parameters?

UTM is an abbreviation of Urchin Tracking Module. Previously, Google Analytics was named Urchin. Eventually, Google bought the technology but the abbreviation remained the same. Basically, UTM parameters are information which describe clicks, sources, mediums, and campaigns. This information is passed on to Google Analytics for segmentation purposes. Most importantly, as a marketer you can use these parameters in a wide range of online marketing products. Hence, this makes the use of UTM tags an important skill to master.

Why use UTM Parameters?

UTM parameters are a way to track traffic from different platforms and sources, and compare the results. As a result, with UTM parameters, you can also distinguish the different means by which your traffic is being generated. Furthermore in this article, you can learn how Opentracker helps you to easily keep track of UTM parameters in the form of graphs displayed on live dashboard.

How can you benefit from using UTM parameters?

Using UTM parameters will allow you to capture information from ALL your incoming traffic campaigns. This information is directly put into your traffic reports. As a result, you can get a complete insight of conversions, sources, returning visitors etc. This information is displayed on a single dashboard.

UTM parameters

Best Practice: Make it a habit to always include UTM parameters in every new traffic campaign.

How do you use UTM Parameters?

UTM parameters are added to the end of a landing page URL. Consequently, when someone clicks and lands on a URL which contains UTM parameters, those tags are sent back to your Google Analytics for tracking.

For example, let’s say I want to track clicks to a page called “mypage” from a transactional email that I send out after a month. I would then insert a link to my site in that email which looks something like this:

http://mysite.com/mypage?utm_source=tutorial&utm_medium=email&utm_campaign=User :: Send 1 month followup
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How To Create UTM Parameters For Your Pages

The simplest way to create UTM parameters for your links is by using the Google Analytics URL Builder. Furthermore, different types and functionalities of URL parameters are explained below:

Campaign Source (utm_source)

A required parameter used to identify the source of your traffic such as search engine, newsletter or any other referral. An example of Facebook being the source is highlighted in green below:

https://www.opentracker.net?utm_source=facebook&utm_medium=social&utm_campaign=blogpost&utm_content=headerlink

Campaign Medium (utm_medium)

A required parameter to identify the medium that the link was used upon. i.e. : email, CPC, or other method of sharing. The example below is using the word “social” to signify the efforts using social media:

https://www.opentracker.net?utm_campaign=blogpost&utm_medium=social&utm_source=facebook&utm_content=headerlink

Campaign Name (utm_campaign)

A required parameter used to identify a specific product promotion or strategic campaign such as a summer sale. Summer_sale is the type of campaign in the example below.

https://www.opentracker.net?utm_campaign=summer_sale&utm_medium=social&utm_source=facebook&utm_content=headerlink

Campaign Term (utm_term)

An optional parameter suggested for paid search to identify keywords for your ad. You can skip this for Google AdWords. If you have connected your AdWords and Analytics accounts, use the auto-tagging feature instead.

https://ga-dev-tools.appspot.com/campaign-url-builder/

Campaign Content (utm_content)

Optional parameter for additional details for A/B testing and content-targeted ads.

https://www.opentracker.net?utm_campaign=blogpost&utm_medium=social&utm_source=facebook&utm_content=headerlink

Furthermore, you can learn more about how to tag your links in Google Analytics Help. It also contains a handy chart view with an example of one campaign with different sources & mediums.

How are UTM parameters Displayed In Opentracker?

All the website visitors that click on on any link that contains your UTM parameters will show up on the graph of each parameter. In practice, this means your graph would look something like this:

UTM parameters

UTM parameters in Opentracker Interface

In the example above, firstly you can see that the most number of sessions come from google source. Secondly, IP tracking is the most successful campaign. Thirdly, cpc is the best performing medium. Finally, “ip address searcher” is best performing paid search term.

Note: UTM parameters are case sensitive. This means that if you use “abc” for your on one medium as utm_campaign or use “ABC” as utm_campaign in other mediums, they will show up as separate campaigns in your Google Analytics. Also, note that UTM parameters will be shown in the browser’s address bar. Therefore, be sure you’re not using any tags that you should not be made public.

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Definition & Differences Between Hit, Page, and Web Counters

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Definition & Differences Between Hit, Page, and Web Counters

Executive Summary and Article Navigation

In this article, you will find discussion and technical definitions of:
  • Hit counter
  • Page counter
  • Web counter
  • Tracking system
You will also find information about:
  • The difference between these 3 counters
  • Why you need a counter
  • Important questions to ask when choosing a counter
  • Determining what is counted
  • Paid vs. Free counters
  • Level of detail provided
  • Evolution of counters to tracking systems
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Hit, Page, and Web Counters –– the difference

All three are counters; devices which display the number of visits which have been made to a website or page within a website. Some important differences are:

  • how many pages are measured (single or multiple)
  • the cost of the tool (free vs. paid)
  • how you access your website or page data
  • how far back this data is available
  • security feature which prevents recording of repeat clicks

The main reason for having a counter is to let you and your visitors know how many people have visited your page or site.

The decision you must make when deciding what product to use is the cost you are willing to pay and the type of information that you are looking for.

As with many forms of technology, you generally get what you pay for. Counting and tracking options which you pay for give you more detailed information of a higher quality. Additionally there may be some work involved, in terms of generating and interpreting your stats, depending on which option you choose.

Why are many counters free? Many counters are free because in return for installing a counter on your page, you give the company who’s product it is a back-link. Back-links are used to obtain a high listing in search results.

Additionally, most services offer the bare minimum, a counter, for free. If you wish to learn about your traffic in any detail, an upgrade and payment is necessary.

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Hit Counter

A hit counter measures and displays the number of times visitors have viewed a single page on a website. Hit counters are typically displayed on homepages. Hit counters can be public or non-public. If they are non-public, or ‘invisible’, only the webmaster can see how many times the page has been viewed. Technically, hit counters measure requests sent by a visitor’s browser to a server. Each time a visitor’s browser requests to see a page on your site, this request is relayed through your server, and is called a hit.

There is a high potential for confusion here, because log analysis also involves the interpretation of ‘hits’. The hits recorded by log files are much more numerous, and do not individually represent individual human ‘hits’ or ‘clicks’. The hits recorded by log files each represent a single pieces of information (for example a graphic such as a gif) which, when taken together, make up page views. In log file analysis a single page view can generate dozens of hits, depending on how much information is being called up, in terms of graphics, etc. Therefore it is important to always find out the definition of a hit in the system that you are using.

The advantage of hit counters is that many are free, easy to install, and can be graphically altered to fit in with the feel of your site. Additionally, there are also numerous scripts available for free download that can be used to make your own hit or page counter, if you have the time and know-how. To have a look, type “hit counter script download” into your favorite search engine.

The drawback of hit counters is that they will not tell you how many unique visitors you have had. Nor do they always tell you the time period which has been measured. Often the data stretches back to the installation of the counter, which can be interesting, but will not help to analyze trends.

Page Counter

Essentially, a page counter is the same thing as a hit counter: a line of code and a graphic device used to display the number of visitors who have viewed a page on your site. A page counter only measures and presents statistics for the page it is installed on. Technically, a hit counter is a page counter, as it measures and presents the same information, the only difference being in name. Page counters often provide a service that measures page views on multiple pages of a website, as opposed to hit counters, which are typically used to count hits on a single page.

Web Counter

Much like a hit counter or a page counter, a web counter is a combination of code and graphic device that allows you to measure and display the number of visitors a web site has received. Web counters are typically used to measure multiple pages. A web counter is a step closer towards visitor tracking, as some web counters offer additional statistics, such as both the number of visitors, and the number of pages viewed, so that, for example, 200 visitors will have looked at 345 pages over a given period. Additionally, web counters offer analysis, for example, by providing a comparative overview to show which pages receive the most visitors.

Tracking systems

The next step is a tracking system. Tracking systems offer the additional feature of charting the progress that visitors make from page to page, by recording clickstreams. A tracking system can also tell you which search terms were used to find your site. Opentracker provides both of these services. Additionally, tracking services provide complete aggregate reports available for any given period during which data was being recorded. Tracking systems are designed to answer specific questions. For example, by matching click-streams and visitor profiles, to identify specific markets. If you have a product or service you are offering, you can determine where interested customers come from: a particular referrer, or ISP, and expand your efforts to reach that audience. You can go a step further and measure the effect of any changes you make, from the colors on your homepage to a new marketing strategy.

Using a tracking system, it is not necessary to guess what visitors are doing. If you know, to the click, what your visitors do, decisions about content management are much easier to make. Opentracker was designed primarily with this goal in mind: the ability to effectively analyze and respond to web traffic.

Opentracker is relatively unique in being a step beyond log files and log file analysis. We record highly detailed visitor activity and visitor profile data. We track unique visitors over the long-term. We host this data and make it easily available. There is no software to install, nothing to download, and no reports to generate. Your password protected statistics can be accessed remotely, only connection to internet is necessary.

To summarize:

Some important questions to ask when considering counters:

  • What do you want to measure, exactly?
  • Do you want to count a single page, or multiple pages?
  • Do you want to count unique visitors?
  • Do you want to make comparisons between pages?
  • Will you have easy access to your stats?
  • How far back will data be available?
  • Do you want that information to be public?
  • How is a ‘hit’ defined in the system you are using?

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Data Science in the Travel Industry

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Data Science in the Travel Industry

Summary

This article will focus on the use of data science in the travel industry. You will also learn more about:

  1. The travel industry and its global digital sales
  2. How data is collected for analysis
  3. How the collected data is used
  4. What this means for you, the consumer

Introduction

data science in travel industry

Our world is all about data; we consume data, share data and analyze data. It does not matter which part of the data industry you fall under- whether you are a consumer, or a producer, you are part of the data-centric world that exists today. With so much data available, it should not be a surprise that everything around us is influenced by it. From our likes, dislikes, influence; you might not realize it but every major decision you make can be and is being influenced by firms tapping into data science to sell their services. Because of this, there should be no surprise that Big Data is used in the travel industry to convince you to go to certain locations around the world. And yes, we realize that that might surprise you but there’s a lot more involved in the process of picking a location than an impulse to travel. Here’s how it goes.

An Overview of The Travel Industry

The travel industry is the fastest growing industry in the world- no one can contest to that fact. Globally, digital travel sales were at a staggering $500 billion in 2015 and they are predicted to exceed $800 billion by 2020. Naturally, this makes the industry very competitive and you can see that. Everything involved with the travel and tourism industry is super competitive. Start from your plane tickets. You’ve got airlines offering luxury services and single seats worth $15,000 or more and then you’ve got budget airliners that can get you a seat for as low as $50. Then look at the hotels you stay at; there are resorts worth $1000 a night and then there are hostels worth $30 or less. You can travel to locations all around the world for less than $1000 for a five to ten-day trip.

data science in travel industryWhen we see these deals, we genuinely think its amazing that prices are so low. Often, some of us even book a trip for the weekend or something just to make sure that we don’t miss out on this discount we’re getting. But don’t chalk out these prices as luck or chance, there’s more to the travel industry than you know.

How does a website know exactly which vacation advertisement to pull to catch your attention? How does a standard hotel or flight website know exactly what you’re looking for?
This is where Big Data comes in, and your experience is due to the use of data science in the travel industry.

How Data Is Collected for Analysis

You might not realize it but when you’re booking for your vacation, you’re actually leaving a massive trail of data on the internet. After all, everyone compares different websites, flights, hotels and more. You might even be checking that five-star hotel you’d love to stay at but can’t because you’re going on a trip with your family at $1600 per night is not very budget friendly. You’ll look at tourist spots, local markets, cuisines and so much more. It’s only natural that you would do at least some research about the place you’re going to because you’re going to want to experience the best that place has to offer.

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While this is something quite normal for you as a consumer, what you don’t realize is that this trail of digital information is sought after by major travel and tourism companies. The insights they provide can help form a package that would be ideal for you. It’s not a bad thing. If anything, we know that personalization is key in the travel industry. Every traveller wants a personalized trip which they can enjoy. Tourism based companies turn to this data provided by you to create a personalized package that you will not be able to resist.

However, while this may sound easy, it’s really quite difficult. After all, the only way a travel agency, for example, can get all sorts of information about you is if they have complete access to your online activity, which they don’t. So how do they go about it?

What Happens to Collected Data

Well, what they do is they set up a data analytics division, or maybe hire a data analytics firm to look at the patterns of searches in a particular area. This is easier to access and there are a lot of websites that do sell or share information such as airline and hotel accommodation and things like that. While there is no individual information about one person available, data analytics firm use this information to sort and then begin analysis.

The result is that they manage to come up with a list of preferences and tastes of the people living in a particular area. You might have noticed things like “People also liked…” at the end of an online store or a hotel website. This is the result of data analysis by firms who’re looking to capture your interest.

What the data analytics team does is that, based on the probability, create a list of things that might catch your attention. This information is found by looking at a lot of data and then forming patterns. People who don’t mind spending a lot of money on airfare, because they want luxury and comfort, also don’t hesitate to spend a lot on hotels, rental cars and more. Therefore, when you choose a very expensive airline to get tickets from on a flight booking website, you might also get recommendations to more high-end hotels. If you’re looking at budget airlines, you’ll be offered more budget-friendly hotels.

How This Affects You

Your entire travel experience depends a lot on the first few things that you type on the search engine of Google. You just don’t realize it. As consumers, all we see is the information given out to us instead of the back story that led to this information in the first place. Again, it’s a really good way of showing exactly how connected, how data-driven our world has become.
Following trends in your area, it can also be easy to predict the kind of places you might want to visit. Have you ever noticed that after a trip to a foreign country, you’re getting advertisements about that area? That’s because websites notice your geographical location. If you’ve been to a place for less than a month, it’s not hard to guess that you were there on vacation so the advertisements you see will be centered around going on vacation again because travel agencies are in the business of providing values around traveling. That’s just how it is.

Conclusion

In the end, data science has a massive impact on the travel industry. What’s more interesting is that even after using data analysis on so many fronts, travel agencies are actually looking to increase their budget for data science even more. This means that you will be seeing a lot more personalized travel packages and honestly, that’s great. Everyone should be able to travel and make the most of what the travel industry has to offer.

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5 Social Media Trends to Watch out for in 2020

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5 social media trends to watch out for in 2020

Ever since the world went digital two decades ago, businesses are still trying to figure out how best to leverage the power of social networks in the cyber world to engage with their customers.

In an ongoing experiment of sorts in establishing brand value and getting customers to positively review their brand, businesses are trying different things. Here’s a roundup of 5 social media trends to watch out for 2019.

What you will learn from this article:

  1. Learn how businesses are leveraging the power of social media.
  2. How technology meets social media to better customer experience.
  3. Importance of customer engagement by speaking out as a responsible and responsive business.

Reading time: 4 – 7 minutes

1. Bye-bye billboard advertising. Hello digital world!

Just because something has been done something for the last 30 years doesn’t mean that businesses should continue to pump resources into ineffective marketing techniques, especially when better options are available.

With a greater focus on engaging with audiences in the digital world, marketing teams are under pressure to review their existing basket of marketing levers and the ROI generated from them.

 

With the buzzword being, ‘’targeted marketing’’ broad-based, mass marketing techniques like billboards and, in some cases, radio advertising may soon fall out of favour.

2. Social Listening is gathering steam

Social listening is about picking up on what customers are saying about a particular product or a brand. It’s not about if they are saying nice things or bad things about the company. It’s about understanding their expectations and disappointments and looping it back while creating the next product or changing certain aspects of brand positioning to better appeal to customer tastes.

Social listening is not only meant to help businesses collect inputs for their next project but it also helps in content creation by understanding the exact words and phrases used by target audiences. Content created to drive traffic and conversions by tapping into the exact vocabulary used (in real time monitoring) by customers is the next leap forward for online marketing.

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3. Chatbots are getting smarter and ubiquitous

When bombarded by similar questions (that sometimes run into the thousands) on a daily basis, how do you handle it? Chatbots are an intelligent answer for most B2C companies that interact with customers on a regular basis. They help customer service staff by relieving part of their work burden by acting as the first line of defense for customer queries and complaints.

Chatbots have been deployed in a range of sectors like fintech companies looking to help people keep a tab on their expenses, investments and creditworthiness to online medical counseling to help people combat loneliness and depression.

Although there is a long way to go before they can completely replace frontline staff in online customer service, they are getting smarter and more ubiquitous by the year.

4. Influencer marketing: The verdict is that it works.

Well established brands have bigger marketing budgets, a greater degree of visibility and brand attraction in the social media sphere that makes it easy for them to connect with audiences, run marketing campaigns and connect better with prospects and existing customers.

But what if you’re a newbie on the block? Well, the truth is, it doesn’t matter so long as you have some money to spend. When endorsed by the right person, your business could receive all the retweets, likes and shares it needs – to be seen, heard and remembered by customers. It’s important that the person who endorses your brand shares the same values as your business does.

Tip: An athlete endorsing a fast food brand is a bad idea.

5. Taking a stance and making it known to the public

50 years ago businesses could brush aside allegations of having lax environmental standards,

Unsafe working environment or claims of employment discrimination. Times have changed. People want to be associated with companies that reflect their own values and this has led to businesses proactively responding to the social environment in which they operate—that means taking a firm public stance and speaking out when wrongs are committed.

These are some of the broad trends that were witnessed this year and most experts expect them to continue well into 2019. Taking a cue from these trends, your business can pick and choose any of these methods to help you better your marketing and branding exercise. But remember, nothing happens until you choose!

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Queries, Keywords And Search Terms

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Queries, Keywords and Search Terms

In this article we discuss the loss of search terms, explain the current relevance of queries within Google, and outline our current strategy for building content based on focus keywords. November 2017.

The goal is to understand how your choice of words influences your Marketing and Sales efforts.

Executive Summary – Bullet Points

  • ‘keywords’ and ‘search terms’ are now called Queries, by Google
  • you can no longer see which visitors used which queries
  • you can still see which Queries bring you traffic, but only via Adwords – for bidding (and rank) purposes
  • the queries or keywords you use when building webpages are still central to your success
  • take-home message: the point is to use words that will lead visitors to your site (via search engines)
  • Access this data via the ‘Search Analytics Report’ within the Search Console in Adwords
  • the solution? smaller Pages and highly relevant content
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Search Terms No Longer Available

About 10 years ago, in the heyday of SEO, search terms, and keyword ranking, the Marketing Dept. had it better than they knew. It was possible to see, for every visitor coming into a site, which words they had typed into a search engine. This information, coupled with their clickstream gave direct insight into buyer needs, wants, thinking, and personas.
Search term encryption began slowly, and today, search term and keyword data are only available for paid search (non-organic) traffic within Adwords.

Google (via Chrome) was not the only player involved – Mozilla (Firefox) and Apple (Safari) also encrypted by default.
Google obviously needed a way of keeping search terms visible for their advertising clients, so you can still see and buy Queries via Adwords, but they are anonymized, and used for ranking and conversion, as opposed to visitor tracking. It is important to keep in mind, however, that the overall statistics for any query are front and center. In other words, queries and click-through rates are the key determinants in deciding how relevant content is, and how much traffic costs.

The point of this article is to summarize what we have learned from encryption and the disappearance of search terms and keywords, 5-10 years on.

Definition: (focus) keyword. The focus keyword is the keyword, or query, you want to lead visitors to your page from Google. In other words, the search queries, terms, and phrases you want your page to rank (display) for.

Google’s Search Analytics Report

Google Webmaster Tools has been replaced by the Search Console, within which you will find the Search Analytics Report, and this description:

…for example, choose “Queries” to group data by search query terms…
The Search Analytics Report shows how often your site appears in Google search results. Filter and group data by categories such as search query…to improve your site’s search performance, for example:
1. See how your search traffic changes over time, where it’s coming from, and what search queries are most likely to show your site.
2. Learn which queries are made on smartphones, and use this to improve your mobile targeting.

Take-Home Message
[bottom line] See which pages have the highest (and lowest) click-through rate from Google search results.

In English, please? Smaller Pages and highly relevant content

When the loss of search terms first hit home, SEO experts were at a loss to see the bright side – less just means less in this case. The upside is that your most embarrassing searches – “cashew stuck in child’s nose” or “how to get my iphone to do that thing where the screen tilts again” (portrait orientation) -remain private.

So there is a ‘void’ where search term information is concerned.
How have we responded to the change? By reverse-engineering content to drive traffic. In other words we target the language (products and services in our case) and write content which speaks to that topic. The required/ recommended keyword density (number of times query or phrase appears, is 1-3%), meaning that the surrounding language also plays a role.

In the past – you could check how people coming in to a site behaved, based on search terms. Now, you can see how your Google advertisements behave, based on queries. Obviously there are still (conversion) metrics involved, but there has been a definite shift.

The solution

Specifically, what we do is write small concise descriptions of what we do (sell), and publish these on separate pages. In this way – we can see which pages bring in traffic – and that way, we know what our audience is really interested in. That’s the bottom line.

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What are UTM Tags and How To Implement Them Easily

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What are UTM Tags and How To Implement Them Easily 

Using UTM Tags To Measure Your Marketing Efforts with Opentracker.

Q: How can you benefit from using UTM tags?

A: Using UTM tags will allow you to capture information from ALL your incoming traffic campaigns and put it directly in your traffic reports. Conversions, sources, returning visitors, etc. So you can get a complete insight.

In this how-to, you will learn what UTM 
tags are and also the industry standards on how to use them. Using UTM tags and parameters, successful marketers are able to specifically measure how they’re hitting goals. As a result, a content editor will know that tweets from company accounts are driving traffic to the correct website if UTM parameters are being used..

What are UTM Tags/Parameters?

UTM is an abbreviation of Urchin Tracking Module. Previously, Google Analytics was named Urchin. Eventually, Google bought the technology but the abbreviation remained the same. Basically, UTM parameters are information which describe clicks, sources, mediums, and campaigns. This information is passed on to Google Analytics for segmentation purposes. Most importantly, as a marketer you can use these parameters in a wide range of online marketing products. Hence, this makes the use of UTM tags an important skill to master.

Why use UTM Parameters?

UTM parameters are a way to track traffic from different platforms and sources, and compare the results. As a result, with UTM parameters, you can also distinguish the different means by which your traffic is being generated. Furthermore in this article, you can learn how Opentracker helps you to easily keep track of UTM parameters in the form of graphs displayed on live dashboard.

How can you benefit from using UTM Tags?

Using UTM tags will allow you to capture information from ALL your incoming traffic campaigns. This information is directly put into your traffic reports. As a result, you can get a complete insight of conversions, sources, returning visitors etc. This information is displayed on a single dashboard.

UTM parameters

Best Practice: Make it a habit to always include UTM tags in every new traffic campaign.

How do you use UTM tags?

UTM tags are added to the end of a landing page URL. Consequently, when someone clicks and lands on a URL which contains UTM parameters, those tags are sent back to your Google Analytics for tracking.

For example, let’s say I want to track clicks to a page called “mypage” from a transactional email that I send out after a month. I would then insert a link to my site in that email which looks something like this:

http://mysite.com/mypage?utm_source=tutorial&utm_medium=email&utm_campaign=User :: Send 1 month followup

 

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How To Create UTM Parameters For Your Pages

The simplest way to create UTM parameters for your links is by using the Google Analytics URL Builder. Furthermore, different types and functionalities of URL parameters are explained below:

Campaign Source (utm_source)

A required parameter used to identify the source of your traffic such as search engine, newsletter or any other referral. An example of Facebook being the source is highlighted in green below:

https://www.opentracker.net?utm_source=facebook&utm_medium=social&utm_campaign=blogpost&utm_content=headerlink

Campaign Medium (utm_medium)

A required parameter to identify the medium that the link was used upon. i.e. : email, CPC, or other method of sharing. The example below is using the word “social” to signify the efforts using social media:

https://www.opentracker.net?utm_campaign=blogpost&utm_medium=social&utm_source=facebook&utm_content=headerlink

Campaign Name (utm_campaign)

A required parameter used to identify a specific product promotion or strategic campaign such as a summer sale. Summer_sale is the type of campaign in the example below.

https://www.opentracker.net?utm_campaign=summer_sale&utm_medium=social&utm_source=facebook&utm_content=headerlink

Campaign Term (utm_term)

An optional parameter suggested for paid search to identify keywords for your ad. You can skip this for Google AdWords. If you have connected your AdWords and Analytics accounts, use the auto-tagging feature instead.

https://ga-dev-tools.appspot.com/campaign-url-builder/

Campaign Content (utm_content)

Optional parameter for additional details for A/B testing and content-targeted ads.

https://www.opentracker.net?utm_campaign=blogpost&utm_medium=social&utm_source=facebook&utm_content=headerlink

Furthermore, you can learn more about how to tag your links in Google Analytics Help. It also contains a handy chart view with an example of one campaign with different sources & mediums.

How are UTM parameters Displayed In Opentracker?

All the website visitors that click on on any link that contains your UTM parameters will show up on the graph of each parameter. In practice, this means your graph would look something like this:

UTM parameters in Opentracker Interface

In the example above, firstly you can see that the most number of sessions come from google source. Secondly, IP tracking is the most successful campaign. Thirdly, cpc is the best performing medium. Finally, “ip address searcher” is best performing paid search term.

Note: UTM parameters are case sensitive. This means that if you use “abc” for your on one medium as utm_campaign or use “ABC” as utm_campaign in other mediums, they will show up as separate campaigns in your Google Analytics. Also, note that UTM parameters will be shown in the browser’s address bar. Therefore, be sure you’re not using any tags that you should not be made public.

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How Big Data is Transforming the Aerospace Industry

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How Big Data Is Transforming the Aerospace Industry

Summary

This article provides information on the aerospace industry and how it is making use of Big Data. Additionally, you will also learn about:

1) Big Data’s impact on the industry

2) The use of IoT and sensors

3) Big Data’s role in the Race to Mars

big data and analytics

Introduction

In the twenty first century, it is a consensus that data is important. Websites need data to optimize and tailor your experience, businesses need data to understand what their consumers want, even your smart devices at home use data so that they can cater to your needs. In a world where data is so important, it’s actually given rise to a new phenomenon: Big Data.

Big Data is quite literally just a name for an extremely large set of data which can be analysed on a computer and then subsequently reveal patterns and trends. As you can tell, everyone wants Big Data to analyse the market and their target audience.

So, it’s really no surprise that Big Data is getting bigger and reaching out to almost every major industry in the world. As it is getting cheaper and gaining more momentum, we find that every day newer industries are making use of it to make their daily processing easier.

 

The Industry So Far

The aerospace industry as a whole has always been ahead when adapting new technologies so it’s really no surprise that it too is using Big Data to improve its overall performance across a range of different operations. While we find big names in the industry such as Boeing and Airbus using data sensors to understand not only how they can further develop more efficient aircraft, we also see that smaller, newer companies like SpaceX also joining in on the trend and using data sensors to further improve rocket technology.

But it doesn’t stop there. The aerospace industry is expanding its use of data to understand and improve its current technologies. It uses analytics to enable suppliers to behave more efficiently and connect Original Equipment Manufacturers (OEMs) to further optimize the supply chain in the market. OEMs make further use of data analytics in order to perform predictive maintenance, track performance, optimize processes and more.

 

The Aerospace Industry & IoT

The industry also makes use of the Internet of Things (IoT) and related devices and sensors to collect vast amounts of data and analyse them to learn about all sorts of things. This covers a range of tasks- from the analysis of operation data from the shop floor, required to understand how quickly and efficiently work is done in the workshop, to simulate conditions the aircraft might need to withstand in order to survive in extreme cases of turbulence and weather. Big data is helping the aerospace industry improve for the better. Furthermore, we find that IoT and sensors are able to save operators time-consuming disassemblies which might occur due to an error in assembling as it is able to provide regular updates on the assembling process of an aircraft or rocket; through this, it is easier to look into issues that the shop floor may be facing and dealing with it before the problem gets too big. It also helps operators and supervisors make targeted decisions that improves the overall effectiveness of the assembling process.

But that’s not it.

With the help of IoT, the aerospace industry is able incorporate intelligence into the very components and devices used in the process of both creating a craft- from the boardroom to the workshop- using complex flight data which was previously not available. By making the devices ‘smart’, it is much easier to see what’s happening, to monitor both the shop floor and business side of things taken care of in the boardroom, so that critical components can be monitored and analysed so that they improve both machine productivity and reliability.

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big data and analytics

Data Has A Big Role In Aerospace

Productivity, as you know, is very important in the aerospace industry. Companies want results and there is only one way to deliver: analyse as much data as possible to showcase possible short term and long-term progress. In the aerospace industry, time is money and Big Data can help companies keep track of their progress.
Traditionally, the use of data has always existed in the aerospace industry. After all, you need a copious amount of data to correctly analyse and simulate a flight on simulators. From its very conception, the industry has making use of data to be able to perform. It’s not really practical building an aircraft or rocket worth billions of dollars without having the data to support that what you’re doing will not have any long-term consequences. Because of this, it’s really no surprise that the aerospace industry is making use of Big Data and related technologies. In fact, given the current industry climate, it was inevitable.

Why Big Data is Particularly Attractive to Aerospace Companies Today

This decade has probably been one of the most exciting decades for the aerospace industry. There’s a race for who can land a manned spacecraft on Mars and you have companies like Boeing, NASA, SpaceX and other companies from all around the world wanting to make their mark. Because of this competition, there’s really no surprise that aerospace companies have turned to digital technologies to increase efficiency- because that is important; a mistake is not affordable- and be able to deliver in a smaller amount of time.

The United States, though previously a pioneer in the industry, is actually finding itself in hot waters as China, Japan, India and other countries are coming into the field to put their mark. As recently as 2013, China launched a manned expedition to the moon. India plans on doing the same. Meanwhile Japan has partnered with various aerospace countries to make it Mars before SpaceX or Boeing.

It’s a race against for these companies and so it makes all the more sense for them to use a growing number of sensors on infrastructure and assets, to monitor and analyse their progress. After all, sensors are able to massive amounts of data in a small amount of time. This data is then used to map out assembly time on the shop floor, models of aircrafts made on computers based on this data can help create virtual situations which the aircraft might experience in real-time and more. In fact, using Big Data actually saves the costs of developing prototypes as every scenario is tested on the virtual model of the craft to ensure that nothing goes wrong. This way it’s easier and more cost-efficient to directly jump into developing a real-life model, based on analysis. It saves time, increases efficiency and companies are able to cut back on manufacturing costs and use it for Research and Development (R & D).

Conclusion

The aerospace industry is doing well with its use of Big Data and other technologies. Of course, much work can still be done in the field, but it’s great that the industry is leading the way in innovation. In fact, following the aerospace industry’s example, we find a lot of automobile and marine companies also turning to the use of Big Data. Therefore, in the end, it is safe to say that Big Data has not only improved, but it has also changed the game in the aerospace industry. It’s going to be very interesting to see just how far the industry will come along in the next few decades as it continues to use these technologies.

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Data Analytics can help grow your business: A low-down on growing your business in the cyber age

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Data Analytics can help grow your business:A low-down on growing your business in the cyber age.

C-suite executives of Fortune 500 companies have the luxury to tackle one business problem at a time. They usually have billion dollar budgets, an army of managers and other levers at their disposal. Lucky for them, because they are not in the trenches of the battle that so many small and medium sized businesses constantly find themselves in.

This article can help you

1.     Appreciate the importance of Big data and why it matters

2.     Why you should use Data Analytics and how it can solve your business problems.

 

Article length: 500 words

Reading time: 3- 7 minutes

 

For most businesses, there are a million problems – human resource mismanagement, ineffective marketing, poor customer retention – and they all demand immediate attention.

Now, you may not be able to solve all of them. But, what if you could maybe manage them better?

*How about not having to guess anymore about what your customers want or think about your product?

 

*How about deciding on your staffing requirements or tracking employee productivity to gauge the impact of such factors on a project?

 

*How about better overall outcomes for your business because you choose to use hard quantifiable data to make business decisions?

You would like that, wouldn’t you? No more searching in the dark for answers.No more making decisions based on gut feeling. The answer to all these problems is simple. The answer is Data Analytics.

How does Big Data Work?

We leave a pile of Data every time we are logged onto the Internet—which is pretty much 24/7/365 now. Every click, every transaction, the hover of a mouse, and even the time spent surfing each page is tracked, recorded and stored. Mountains of such data captured every single day can be deployed to make sense of habits and patterns of consumers, employees and the wider market allowing you unprecedented insight into the minds of your target audience.

So, whether it is about introducing a new product in the market or retaining existing customers, Big data can help you make decisions that are backed by hard quantifiable proof. The Data is there to back you up!

Now, a good data analytics toolkit should be armed with a few must-haves and so here’s a quick glance at the most popular tools used at Opentracker.

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What benefits does Opentracker offer?

=>OpenTracker’s real-time monitoring tool privileges its users to study traffic and data, minute-to-minute, from all sources and devices, to make vital decisions in real time!

=>In a single click, categorise data by every conceivable metric and tabulate in an easy-to-understand chart.Easy to set-up and easy to use with an elegant user interface for tackling strategic online marketing problems fast.

                                 Categorise and compare data from all sources!

 

=>Need to share reports and insights with your colleagues or employees? No problemo! Create individual accounts with the option of customising access for every single employee.

=>OpenTracker’s advanced API allows you to write data and create reports just the way you like them.You can chain, link, mashup or combine API data to create reports which are customized or more advanced than those available, at a fraction of the price, in the market.

=>Identify visitors by their geographical location, IP address, specs. of the device, nature of the visitor (company/govt. body/individual), complete visitor history and a comprehensive profile of every visitor.

Wait, But there’s more! You didn’t think that was it, did you?

 

Open tracker’s has many more features that cater to the diverse requirements of businesses and you can get a sneak peek of them right here. Our products have worked and worked well for over 17 years for 5000+ customers and now is your chance to give your business a guaranteed shot at harvesting intelligent data to power your business.

 

Here’s an exclusive offer for a free 30-day trial pack only because we believe that you should try our products for free before you buy them.

 

We would love to hear your queries and help you pick and customise our product offerings to suit your business needs. Click here and answer just two simple questions, and one of our experts will reach out to you to guide you.

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A sneak peak at increasing sales by 30% and much more

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A sneak peak at increasing sales by 30% and much more

 

From time to time, every CFO or HR personnel has had to answer a perplexing question: What is the ROI here? Am I getting the best bang for the buck?

There’s a lot Big Data can do: It can help organizations shore up their bottom lines by helping them review the performance of their departments, gauge the outcomes of their services, track loyalty of their customers and even help weed out non-performing human resources.

Here’s a look at hard numbers on what it means for manufacturers, retailers and pretty much anyone who has a company to run.

Cutting costs and keeping your organisation lean using Big Data

An early adopter of the technology, Germany’s Federal Labour Agency or ‘’BA’’ in short, is tasked with the finding jobs and providing support services for the unemployed.

Armed with a 54 Bn budget and 1,00,000+ employees, it has cut more than €10Bn in costs by employing big data strategies by identifying and eliminating inefficient programs, creating new targeted programs and pitching them to segmented audiences and helping disseminate and adopt best practices.  

Image Source:  Mckinsey Report

Surveys reveal that customers of BA highly appreciate the relevance and efficiency of their services. No matter the size or type of organisation, understanding where to direct your resources is crucial to profitability and the continued market-viability of any organisation.

Image source: Mckinsey Report

The above image illustrates the savings accrued in the form of increased tax collection, detection of fraud and increased operational efficiency by deploying Data Analytics. Such gains are achievable and relevant even for private businesses.

Government’s, NGO’s and businesses can all build capabilities that allow them to deploy Data Analytics to make better sense of how their resources are utilised and how well they connect with their target audience.

Data Analytics can successfully lead innovation in your company. 

Launching a new product or service always carries with it a high up-front cost in terms of time and money spent on recruitment, R&D, product development, marketing & publicity and other costs. Sometimes, with millions invested and the survival of the company at stake, here’s how some companies are using Big Data to get it right.

Pramad Jandhyala, co-founder of LatentView, had this to say,’’ Earlier, a food company would go to panel of chefs or focus groups to see what product to launch. In that model, people didn’t tell you anything until you asked a question. Now, you don’t ask any questions, only study trends.

Tapping the power of social media and data analytics, her firm helped a client decide to start a restaurant in favour of flavours from Peru, Thailand, Korea and Nepal.

She added,’’We listened in on social media conversations around which restaurants people ate at, their recommendations etc. Now companies want to see what they can learn from what people are saying rather than merely understand if they are saying good or bad things about a product’’. 

Understanding and capitalizing on trends is important to stay ahead of the game. Introducing the right product at a wrong time or marketing incorrectly to the wrong customer-set is a sure-shot way to burn cash.  

Lesson to learn? Simple: Your customers are leaving digital clues. Learn to read them.

What do the experts have to say on this?

Image Source: Mckinsey Report

 

Every single figure in the above image stands as a business opportunity for avenues of growth.

A  Mckinsey Report explained, ‘’Big data can help manufacturers reduce product development time by 20 to 50 percent and eliminate defects prior to production through simulation and testing. Using real-time data, companies can also manage demand planning across extended enterprises and global supply chains, while reducing defects and rework within production plants’’.

 

Notice, (in the above image), how costs can be slashed and revenues shoot up, regardless of where Big data is deployed in the value-chain.

In sectors like retail, some retailers like Wal-Mart have developed the capacity to mine petabytes of data on customer preferences and buying behavior, giving them the leverage to win important pricing and distribution concessions from consumer product goods companies.

The report went on to add that, ‘’Retailers across the industry are becoming more sophisticated in slicing and dicing big data they collect from multiple sales channels, catalogs, stores, and online interactions. The widespread use of increasingly granular customer data can enable retailers to improve the effectiveness of their marketing and merchandising’’.

 

Did you know? Here are 3 real-life examples of increasing revenue using data mining.

 

1. Amazon.com employs Data Analytics to generate “you might also want” prompts for each product bought or visited. At one point, Amazon reported that 30 percent of sales were due to its recommendation engine. Another example of this lever is using big data analyses to optimize in-store promotions that link complementary items and bundled products

 

2. Location-based marketing targets consumers who are close to stores or already in them. For instance, as a consumer approaches an apparel store, that store may send a

special offer on a sweater to the customer’s smartphone.

 

The startup PlaceCast claims that more than 50 percent of its users have made a purchase as a result of such location-based ads. Nearly 50 percent of smartphone owners use or plan to use their phones for mobile shopping.

 

3. Retailers can use big data to integrate promotions and pricing for

shoppers seamlessly, whether those consumers are online, in-store, or perusing a

catalog.

 

Example, Williams-Sonoma has integrated customer databases with

information on some 60 million households, tracking such things as their income,

housing values, and number of children.

 

Targeted e-mails based on this information obtain ten to 18 times the response rate of e-mails that are not targeted, and the company is able to create different versions of its catalogs attuned to the behavior and preferences of different groups of customers.

Source: Mckinsey Report

 

 

 

Use Data to your advantage!

 

 We help firms, of all sizes, unlock their potential by helping them adopt big data strategies.

 

Click here for a zero-cost, risk-free trial or get an absolutely free – no strings attached- consultation with one of our experts

 

 

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Three Examples of Business Models Based on Innovate Technology. How do big data analysis and artificial intelligence play a role in this process?

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Three Examples of Business Models Based on Innovate Technology.

How Do Big Data Analysis And Artificial Intelligence Play A Role In This Process?

Welcome to the 2nd part of the previous blogpost : The Secret Sauce That Could Help Your Business Grow where discussed about why some businesses are better than others.

Emerging technology allows us to both A) send signals and communicate with users (clients) AND B) to analyze the large amounts of data generated in today’s digital world.

Here are three concrete examples of companies who are using (new) technology to discover and develop new markets. Another way of saying “new markets” is “new products and services”.

There is a lot of complexity involved. Here are the main ingredients:

1. Identifying ‘futuristic trends’ – innovation

2. Making these new innovative services and products available on the market

3. Using digital channels to deliver the products and services

4. Measuring all digital activity in order to look for trends relative to your business goals

So let’s get right down to it. To recap, to the part 1 of the blogpost : marketing gets you customers, but a well-oiled Operations department keeps your customers happy. And at the crux of operations is the agility to take risks and capitalize on growing trends to stay ahead of the race. Don’t believe me? Here are 3 examples of how acting on ‘futuristic trends’ are transforming industries.

Example 1 : Healthcare

Castlight Health is a company that analyzes Big data to make available to patients in large health plans, data on health care pricing that they don’t normally see, helping them choose the most appropriate healthcare plan. That’s not all, analyzing patient clinical and behavior data has helped doctors create customized, preventive care programs targeting the most appropriate groups of individuals ensuring higher rates of success in preventive healthcare.

For the pharmaceutical companies, the opportunities for breakthrough in discovery of new drugs based on large segmented data sets has presented them with a gold mine of opportunities for the discovery of next generation drugs.

Hospitals across the country are now harnessing the combined power of Big Data and artificial intelligence to better evaluate the benefits of drugs and define optimal treatment plans, saving on insurance costs and helping rapid patient recovery.

Targeting services or marketing to meet individual needs is already familiar to many consumer-facing companies. Segmenting and analyzing their customers through combinations of attributes such as demographics, customer purchase metrics, and shopping attitudes and behavior is firmly established.

Example 2 : Retail

Retailers, especially those that operate online but increasingly also those with physical stores, are adjusting prices and promotions in a bid to experiment with which combination best drives traffic and sales. One example is where, you may have bought a product online and walked by a physical store of the same brand, only to have been alerted on your smartphone, by the retailer, about a new product or a discount that has been customized and appeals to your tastes, based on your past shopping history which is nothing but a combination of Big Data and Artificial Intelligence.

In retailing, real-time price comparison services give consumers price transparency to a degree never before enjoyed and generate significant surplus for them. The likes of Amazon and e-bay have allowed us to compare products in real time from the comfort of our homes providing us the best possible choice of goods and services in the market.

It’s a win-win for both retailers and consumers!

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Example 3: Manufacturers and Service Providers

Manufacturers and service providers are using data obtained from sensors embedded in products to create innovative after-sales service offerings such as proactive maintenance.

Imagine your car reminding you that your car has reached 10,000 miles of its first run and needs a fresh pair of tyres or that its braking system needs to be fixed. Cars fitted with sensors provide real time data to automakers to help understand the performance of their cars, identify potential manufacturing defects for recall and help engineer the next generation of cars.

The emergence of real-time location data has created an entirely new suite of location based mobile services from navigation applications to people tracking.

The real time application of location based services have been capitalized not just by the likes of Uber or Lyft but by a wide range of industries from logistics and food delivery services to crime prevention by the police.

IOT, big data and artificial intelligence are going to change the economic landscape of the world and along with it, the fortunes of millions of people and the future of businesses and how they operate.

It’s an exciting time to be a part of the future. Whatever the industry and no matter what the product or the service, Big data can help recast your business to be more organizationally-agile, responsive to the ever changing business environment and most importantly, profitable!

It is time to make a decision!

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