How one company lost 42 million Pounds and what this means to be GDPR compliant.

How one company lost 42 million Pounds and what this means to be GDPR compliant.

With the constant stream of sound bites surrounding GDPR, one could be forgiven to assume that most companies would have taken care to update their privacy policies and inform their customers about this transition.

 

Shockingly, according to a ISACA survey, not only are most companies unprepared, but only around half of the companies surveyed (52 percent) expect to be compliant by end-of-year 2018, and 31 percent do not know when they will be fully compliant!

 

Let that sink in…52% of companies, as of this very moment, do not comply with the (GDPR) General Data Protection Regulation.

 

Some of the biggest Tech and social media giants like Google, Facebook, Instagram, and WhatsApp have already been slapped with lawsuits for violating the GDPR law that went into effect on May 25, 2018.

 

If found guilty, EU regulators can impose fines upto 4% of global annual revenues; numbers that could easily run into the billions.

 

In 2015, TalkTalk, a British telecom company failed to securely store customer data and in the aftermath of the loss of data due to a cyber attack, not only was the company fined around £400,000 by British regulators, but it also lost more than 1,00,000 customers and 42 million pounds.

 

Such instances of data breach or data mishandling tell us the devastating impact of under -preparedness – lost revenues, dwindled customer base, negative publicity and heavy regulatory fines – enough to bring any company down to its knees.

 

India with an active customer base of 240 million was the largest audience country for Facebook. In the wake of the scandalous Facebook-Cambridge Analytica affair, Facebook revealed that personal data of 5,62,455 Indian users was improperly shared.

 

What was the effect of this revelation?

 

Velocity MR, a market research company, released a survey that

that found that after the Facebook security breach, 24% of users started sharing ‘’lot less’’ data, while 7% stopped sharing data altogether.

 

Let’s take a moment here and do some quick back-of-the-envelope-math and what this might have cost Facebook.

 

7% of 240 million works out to 16.8 million people avoiding Facebook. Losing

17 million customers roughly translates to Facebook shutting down operations in both Sweden and Austria!

 

That’s a lot of advertisement money to go down the drain.

 

Not only this, CEO Mark Zuckerberg had to endure negative publicity and a televised Q&A grilling session with legislators on both sides of the Atlantic.

 

With the latest lawsuit over GDPR non-compliance, Facebook with its deep pockets could survive another round of missed opportunities in advertising revenues and regulatory fines.

 

But honestly, how many businesses can afford incidents like this?

 

A study by Ensighten revealed that one of the reasons firms seem unprepared for GDPR, could be the lack of consensus over who is responsible for data protection within a business and how to go about it. What should be the first step?

Ryan Wain, chief marketing officer at Unlimited Group, advised decision makers to undertake a full audit on data held by a business.

He added: “Possibly the most important consideration is to avoid viewing GDPR compliance as a process with a hard and fast endpoint. Rather, it will be an on-going journey as you gather and process new data moving forward.”

It’s time to be GDPR compliant

For more than 15 years, we have been helping companies take smart decisions using data analytics. Now, we are also helping small & medium sized businesses stay compliant with the GDPR law.

The GDPR law runs to 11 chapters and 173 recitals and let’s face it, who has the time to sit down and pour through the contents with a magnifying glass?

 

But the good news is that we have you covered. Here are 3 things that you should absolutely know.

 

  • Geographical location: Businesses in the EU are subject to GDPR—even if the data they’re accessing is processed outside of the EU. The reverse is also true. If you’re a company processing the data of EU citizens (either to offer goods and services, or to monitor behavior taking place in the EU)—it doesn’t matter where you’re based, or where you’re processing the data. You still have to comply with GDPR.
  • Greater Penalties for noncompliance: The maximum fine for noncompliance with GDPR is up to 4% of annual global turnover, or 20 million euros—depending on which is greater.
  • Explicit Consent required: Consent has to be given in an easy, accessible way before processing a person’s data. You also have to disclose the purpose for that data processing and make it as easy to withdraw consent as to give it.

 

(Insert video link – null/video/gdpr-what-is-it-and-how-might-it-affect-you/2A0C50F6-6248-49EE-AAFC-A505CB425705.html)

 

Here’s a quick 3-min guide of how GDPR affects your business.

 

At a one time fee of just €395, OpenTracker’s Quick-scan Analysis can do a thorough Data audit and help you identify non-compliant features and help you keep avoid the dangers of expensive regulatory fines.

With an expert team at your disposal, we can help you identify the loopholes and shortcomings in the present data handling regime in your company, the state of preparedness of your business to deal with the GDPR provisions and also chart out a custom plan to help your business become and stay GDPR compliant.

We have already helped hundreds of companies with GDPR-compliance. Have any questions? Why not ask? We would love to hear from you.

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Other titles for your consideration:

-83% of companies are in trouble due to GDPR non-compliance. Where do you stand?

-Facebook and Google are facing GDPR lawsuits. Is your company GDPR compliant?

 

Articles & White-papers

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

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

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

 

Other possible headlines

 

1.     Here’s how one organisation saved €10Bn in costs and what it could mean for you.

 

2.     Enjoy higher savings of 30-40% more by reducing frauds and errors..Here’s how!

 

Articles & White-papers

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
Start your free trial!

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.

Start your free trial!

Articles & White-papers

Start your free, no-risk, 4 week trial!
IP-Adresse verfolgen

Queries, Keywords, And Search Terms

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

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.

IP-Adresse verfolgen

Queries, Keywords, and Search Terms

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

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.

Start your free, no-risk, 4 week trial!

1-click User-Tagging

1-click User-Tagging

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Tag and add notes to Visitor Profiles

We are very pleased to finally release User-Tagging, which is now available.

User tagging allows you to actually edit the Visitor Profiles for each and every visitor with a simple mouse click.

User-tagging demo video from Opentracker on Vimeo.

This new feature turns Opentracker into a very powerful CRM system – you can combine contact information with actual website browsing history.
Example: send out an email and combine response to your newsletter with insight into what each recipient (email address) actually looked at on your website.

user tagging username in Opentracker clickstream

 

Here are the fields that you can add/ edit:

  • Email address
  • Title
  • First name
  • Last name
  • Description
  • Gender
  • User name
  • Phone number
  • Mobile nr.
  • Fax nr.
  • Source
  • Currency
  • Website
  • Conversion
  • Rating
  • Email opt-out
  • Age
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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:

You will also find information about:

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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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Definitions of Big Data

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Definitions of Big Data

Q: Can you please provide me with a definition of Big Data?

A: The definition of Big Data is a moving target.

Opentracker big data definition

In order to make it possible to follow the discussion, as it evolves, we see have started a list of definitions, as we read them on the internet.

Author names: Andrew Brust (ZDNet), Bill Franks (FCW article), PCmag encyclopedia,  John Rauser (Networkworld), John Weathington (TechRepublic Blog), Cory Janssen (Techopedia.com), Mike Gualtieri (Forrester),  John Ebbert (Adexchanger), Edd Dumbill  (O’Reilly Strata), Boyd & Crawford (cited by Leslie Johnston on the Library of Congress), Tim Gasper (cited on TechCrunch), Margaret Rouse (TechTarget), Mike Loukides (O’Reilly Radar), Jimmy Guterman (O’Reilly), Wikibon,  Steven Burke (CRN), Urbandictionary .com, Slashdot (SAP survey), George Dyson (personal correspondence Tim O’Reilly), Doug Laney (Stackexchange), Brian Hopkins and Boris Evelson (Forrester), Bob Gourley (Smartdatacollective),  SAS,  Stephane Hamel.

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  1. “Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization.” Cited from Wikipedia
  2. “Big data is the term increasingly used to describe the process of applying serious computing power – the latest in machine learning and artificial intelligence – to seriously massive and often highly complex sets of information.” Cited from 4/2013 the Microsoft Enterprise Insight Blog
  3. “We can safely say that Big Data is about the technologies and practice of handling data sets so large that conventional database management systems cannot handle them efficiently, and sometimes cannot handle them at all.” Cited from 1/2012 ZDNet Blog by Andrew Brust.
  4. “An easily scalable system of unstructured data with accompanying tools that can efficiently pull structured datasets.” Cited from a 4/2013 post on the FCW Blog.
  5. “The definition of big data? “Who cares? It’s what you’re doing with it,”” Cited from 3/2013 FCW article, quoting Bill Franks.
  6. “The definition of big data refers to groups of data that are so large and unwieldy that regular database management tools have difficulty capturing, storing, sharing and managing the information.” Cited from yourdictionary.com
  7. “Big Data refers to the massive amounts of data that collect over time that are difficult to analyze and handle using common database management tools. Big Data includes business transactions, e-mail messages, photos, surveillance videos and activity logs (see machine-generated data). Scientific data from sensors can reach mammoth proportions over time, and Big Data also includes unstructured text posted on the Web, such as blogs and social media.” Cited from the pcmag encyclopedia
  8. “Any amount of data that’s too big to be handled by one computer.” John Rauser cited 5/2012 at networkworld.com
  9. “To define big data in competitive terms, you must think about what it takes to compete in the business world. Big data is traditionally characterized as a rushing river: large amounts of data flowing at a rapid pace. To be competitive with customers, big data creates products which are valuable and unique. To be competitive with suppliers, big data is freely available with no obligations or constraints. To be competitive with new entrants, big data is difficult for newcomers to try. To be competitive with substitutes, big data creates products which preclude other products from satisfying the same need.”
    Cited from 9/2012 John Weathington on the TechRepublic Blog
  10. “Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.” Cited from a Cory Janssen post on Techopedia.com
  11. “Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data.” Cited from IBM.com
  12. “A more pragmatic definition of big data must acknowledge that:
    Exponential data growth makes it continuously difficult to manage — store, process, and access. Data contains nonobvious information that firms can discover to improve business outcomes. Measures of data are relative; one firm’s big data is another firm’s peanut. A pragmatic definition of big data must be actionable for both IT and business professionals.The Definition Of Big Data: Big Data is the frontier of a firm’s ability to store, process, and access (SPA) all the data it needs to operate effectively, make decisions, reduce risks, and serve customers.”
    Cited from a 5/2012 Mike Gualtieri Forrester Blog post
  13. “The world has always had ‘big’ data.  What makes ‘big data’ the catch phrase of 2012 is not simply about the size of the data.  ‘Big data’ also refers to the size of available data for analysis, as well as the access methods and manipulation technologies to make sense of the data.” Cited from 12/2012 Adexchanger.com article by John Ebbert
  14. “Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it.” Cited from 1/2012 post by Edd Dumbill on O’Reilly Strata
  15. “We define Big Data as a cultural, technological, and scholarly phenomenon that rests on the interplay of:
    (1) Technology: maximizing computation power and algorithmic accuracy to gather, analyze, link, and compare large data sets.
    (2) Analysis: drawing on large data sets to identify patterns in order to make economic, social, technical, and legal claims.
    (3) Mythology: the widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity, and accuracy.” From Critical Questions for Big Data Boyd & Crawford (2012) as cited by Leslie Johnston on the Library of Congress website
  16. “The definition of Big Data is very fluid, as it is a moving target — what can be easily manipulated with common tools — and specific to the organization: what can be managed and stewarded by any one institution in its infrastructure.  One researcher or organization’s concept of a large data set is small to another.” Cited from 10/2011 Leslie Johnston Library of Congress
  17. “Big Data is presently synonymous with technologies like Hadoop, and the “NoSQL” class of databases including Mongo (document stores) and Cassandra (key-values).” Tim Gasper cited 10/2012 on TechCrunch
  18. “Big data (also spelled Big Data) is a general term used to describe the voluminous amount of unstructured and semi-structured data a company creates — data that would take too much time and cost too much money to load into a relational database for analysis. Although Big data doesn’t refer to any specific quantity, the term is often used when speaking about petabytes and exabytes of data.” Cited from a 3/2011 post by Margaret Rouse on TechTarget
  19. “But I do like Roger Magoulas’ definition of “big data”: big data is when the size of the data becomes part of the problem.” Cited post by Mike Loukides 2/2013 post on O’Reilly Radar
  20. “Big Data: when the size and performance requirements for data management become significant design and decision factors for implementing a data management and analysis system. For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration.” Cited from 6/2009 Jimmy Guterman O’Reilly
  21. Big data has the following characteristics;
    1. Very large, distributed aggregations of loosely structured data – often incomplete and inaccessible:
    2. Petabytes/exabytes of data
    3. Millions/billions of people
    4. Billions/trillions of records
    5. Loosely-structured and often distributed data
    6. Flat schemas with few complex interrelationships
    7. Often involving time-stamped events
    8. Often made up of incomplete data
    9. Often including connections between data elements that must be probabilistically inferred,
    10. Applications that involved Big-data can be:
    11. Transactional (e.g., Facebook, PhotoBox), or,
    12. Analytic (e.g., ClickFox, Merced Applications). Cited from Wikibon.org
  22. “We think at the end of the day, big data is not just about analytics, it is about data-centric applications. It is about driving some experience to a customer and causing them to do things in realtime.” Paul Mauritz quoted in a 4/2013 Steven Burke article on CRN
  23. “Modern day version of Big Brother. Online searches, store purchases, Facebook posts, Tweets or Foursquare check-ins, cell phone usage, etc. is creating a flood of data that, when organized and categorized and analyzed, reveals trends and habits about ourselves and society at large.” urbandictionary.com
  24. “A new survey by SAP suggests that nearly 76 percent of executives see “Big Data” as an opportunity. However, respondents’ definition of “Big Data” varied to a considerable degree. Nearly a quarter of the 154 C-suite executives felt that “Big Data” was the technologies designed to handle the massive amounts of data swamping organizations. Another 28 percent defined “Big Data” as that flood of data itself. Still another group (19 percent) equated “Big Data” with storing data for regulatory compliance. Around 18 percent viewed “Big Data” as the increase in data sources, including social networks and mobile devices.” slashdot 6/2012 citing an SAP survey
  25. “Big data is what happened when the cost of storing information became less than the cost of making the decision to throw it away.” Tim O’Reilly quoting personal correspondence via email from George Dyson 20 March 2013, regarding Dyson’s talk at the Long Now Foundation 19 March 2013.
  26. The Big Data Landscape:
    1. Apps
      • Vertical Apps
      • Ad / Media Apps
      • Business Intelligence
      • Analytics and Visualization
      • Operational Intelligence
      • Data as a service
    2. Infrastructure
      • Analytics Infrastructure
      • Operational Infrastructure
      • Infrastructure As A Service
      • Structured Databases
    3. Technologies

    big dataDerived from an informational diagram on