Web Analytics, When You Need It?

Web Analytics: When You Need It


Web analytics have been around for a long time. It has been used ever since the companies began using the internet for marketing purposes, or in other words, e-commerce. With the rise of e-commerce, Web analytics came into subtle existence.

The OLD Analysis

Web Analytics before made use of certain tools to analyze how well websites perform. Page Views and Hits counter are one of the most tools used by companies before to determine how popular their website is. Of course, before, it was the only thing dependable.



Weaknesses of the OLD Method

Although some would argue before that website popularity is measured by the number of site visitors, most people do not really understand the depth and implications of "hits". I, for one, believe that although having a number of "hits" in one's site isn't bad, it cannot be accounted for everything. For instance, as Avinash Kaushik said in his book, Web Analytics: An Hour a day, we need to measure both the "what" and the "why", quantitative and qualitative, or simply, the numbers and motivation behind the website.



Before, websites are deemed a success when it reaches a million hits, or a million page views. This is because of the assumption that the more people who view it, it must mean its helpful. In some cases, it is true, but considering there are more than a million people world wide who have access to the internet, and the fact that page views and hits counters neglecting the fact that web visitors always have a tendency of going back to the same site over and over again, that million hits may be as good as 20,833 people going back and forth from to the website everyday, for the whole year.

In a nutshell, what old method lacks is the ability to give substantial data as to "why" people visit the website. People may just happen to see the website, but leaves almost immediately. That would count as a hit, but you have no way of knowing whether or not they found the website helpful.

Introduction to the NEW Analysis

Now, there is little need to panic. Even though the old Web Analytics tools are somewhat becoming obsolete in this age of information, there are new replacement for them, most of which can and will give companies a more substantial data to work on. Web Analytics should be like the following: (note: the following, and more, are listed in Avinash Kaushik's Web Analytics: An Hour a day.)

1. Click Density Analysis: This tool is simple enough to grasp. It measures which links get the most amount of traffic from web visitors. This is much better than "hits" counters, since it lets you know which of you links are actually being used, allowing you to remove underused, or obsolete links.

2. Visitor Primary Purpose: A survey, or a simple question to your online visitors, either by sending to their e-mails, or interviewing them in person. The idea is to gather answers as to what your visitors' primary purpose in visiting your website. This will provide you that much needed "why" or qualitative data. With this, you can further improve the website with the things your target customer needs.

3. Task Completion Rates: This provides an analysis of how "successful" visitors are after visiting your website. By "successful", it simply means they completed the task they have by visiting your website. Things such as "Did you find our website helpful?" every time a user exits the site will give you a good overview of how useful your website was to your customers.

The one's mentioned above are the ideal use of Web Analytics today. They provide a certain degree of data that the old Web Analytics cannot provide.

Measuring Both the What and the Why

Avinash Kaushik states that: "Combining the 'what'(quantitative), and the 'why'(qualitative) can be exponentially powerful."

Most of you will ask why? To put it simply, you need not only the "numbers" when determining how productive your website is. You also need to know the "motivation" of the people using your website. Why did they visit your site? Why did they stayed in your website? or Why did they leave your website? Why are some of your links overused/underused? These are some of the "Why" questions most e-commerce website owners should be asking.

Methods To Use?

There are several methods to use to gather qualitative (why) data. The following are examples of the methods used (note: can also be found in http://www.webanalyticshour.com/):

1. Lab usability testing

2. Site visits, follow-me-homes

3. Experimentation/testing

4. Unstructured remote conversations

5. Surveying

Web Analytics, When You Need It?

Overall, Web analytics is needed NOW, by companies and businesses with websites. The need for efficient, and productive website is a must, not only to maximize the use of websites, but also to help customers get what they need. A good website is always a welcoming experience for both old and new customers.

Building Reputation in the Internet Streets

Online Reputation

most people don't recognize how important this is until the day they find themselves staggering underneath a mountain-load of bad reputation in the internet.

While building your real life reputation isn't bad, (and in most cases, it's very important to build your real life reputation) this isn't the only thing that will matter nowadays. Not when consumers can literally peek in the web, type your company name on a search engine, and basically read about anything there is to know bout your company. This also applies to employees and job seekers, especially with the rise of social networking sites such as friendster and facebook. You might even find yourself being featured in a website you thought was unaccessible.

The thing is, online reputation is becoming an essential part of being our modern day world. If you neglect proving yourself over at the internet, you might find yourself getting a harsh whiplash from reality.

So first things first, Why bother building your online reputation?

According to Andy Beal and Dr. Strauss: Radically Transparent, "The power is with the people. Companies and CEOs previously controlled their reputations in both business and consumer markets, aided by public relations (PR) firms and crisis-management plans. Individuals monitored their reputations via feedback from clients and people in their personal and professional networks. The switch from traditional media and corporate monologues on websites to social media on the internet makes every internet user a journalist. People will judge
you, your company."

As I've said earlier, online reputation is essential nowadays. For companies, the days of traditional media has long been forgotten. Consumers nowadays won't just stick to listening to commercial advertisement. The internet is their way of verifying whether or not your company really offers what you were advertising for. As an added bonus (or problem), online journalist or "bloggers" will write about your company, with or without your knowledge. Of course this shouldn't hurt if its all praises and positive things, but these journalists will be one of the most critical people to write about your company. Why? Because most of these people are consumers.

This meant that if they don't like your services or products, you can expect they will write about it fearlessly, especially within the anonymity of their blogs.

The same thing can be said for individuals looking for work. Social networking sites and blogs that are about you will have significant impact on whether or not you will get hired for a specific job. According to Job Star, 80% of all positions are filled without employee advertising, meaning, companies doesn't advertise for vacant job positions all the time. Most of the time, they look for candidates online.

With that said, if you've got a bad online reputation, expect a nasty turn of events in real life.

So How do we build online reputation?

That is where an Electronic Portfolio, or an E-Portfolio comes in. An E-portfolio is a cohesive, powerful, and well-designed collection of electronic documents that demonstrate your skills, education, professional development, and the benefits you offer to a hiring organization. A very good example of an E-Portfolio is a BLOG.

Yes, a Blog. Professional blogs should contain information about oneself. This include, but are not limited to:

• Important Contact Information: Provide E-mail addresses and necessary phone numbers so that you can easily be contacted.
• Keywords: Place keywords or keyword phrases that will easily be spotted by employers using automated resume tracking systems.
• Powerful Objective Statements: Specifies where you want to go and what you want to do.
• Qualifications, Education, Work Experience (if any), Activities: This will give employers a heads up of what you can do for them.

Stack your resume in a chronological manner, placing your most marketable skill on top of the list.

Aside from what are written above, your E-Portfolio should also contain an E-Gallery. This gallery should showcase your accomplishments, examples of previous work you've done, examples of activities you've participated in, and other related events/things that will boost your credibility. Always remember to use only original works, keep examples short, keep confidentiality, focus on obtaining Job, and keep things organized.

Why bother with an E-Portfolio?

Aside from the fact that it will help boost your online reputation, here are other reasons why you should have and E-Portfolio:

• An E-Portfolio can give you instant credibility
• An E-Portfolio gives instant access to you and examples of your works.
• An E-Portfolio shows you are current and up-to-date.
• An E-Portfolio expands your exposure and increases your visibility worldwide.

How about for Corporate Online Reputation?

Ah yes, corporations aren't immune to bad online reputation. But it doesn't mean they can't do anything about it.

Companies should learn:

• How to monitor their brand on the internet
• How to react to an online crisis
• How to repair your reputation should you suffer a crisis
• Why monitoring is vital to your reputation management efforts.

Having said that, companies need to monitor their own brand(s), their company name, their products and services, their executives and spokespeople, their marketing campaigns, the current industry trends, competitors, and most of all, the companies known weaknesses.

Nothing helps a company protects its reputation more than honesty. As Andy Beal and Dr. Strauss wrote in their book, Radically Transparent, "Show what you are doing, and reveal your processes. Acknowledge your mistakes and participate fully in conversations that concern you."

Of course, a little help from modern technology won't hurt as well. Google Analytics and Technorati can help companies find out what people are saying about their brands. Knowledge is power, as they say, and with it, comes responsibility. If a company can vigilantly keep tabs on what's going on around it, chances are it can prevent itself from any serious damage, reputation or otherwise.

So in a nutshell, Online reputation is important, both for Companies and Individuals alike. Quoting from Andy Beal and Dr. Strauss' Radically Transparent, "Reputation is NOT what the company or the individual thinks about itself, but what OTHERS think.... -you have no reputation at all because no one cares."

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Uncovering Information through Data Mining

Data Mining

This term is being thrown a lot nowadays. In this information-driven age we live in, trawling through terabytes of data and figuring out what to do with the data obtained is essential in making businesses work. That is where our good old Data Mining tools come in handy.

But what is Data Mining?

According to Kurt Thearling's Introduction to Data Mining, the term is defined as the "extraction of hidden predictive information from large databases".

Extraction of hidden, predictive information sounds like a mouthful to some, and even more cryptic to decipher to most. But this short phrase says a lot. For instance, lets say your business is about selling cakes, and you have a compilation of customers who have bought products from your store before. You might want to know what product appeals to your customers on a given, say, holiday event. That's where data mining comes in with a charm. Not only does it tell you what product to sell, it also helps you determine to which person to sell to using the database you've compiled.

Works like a charm, right? Kind of reminds of Statistics, don't you think?

According to Kurt Thearling, Data Mining and statistics aren't really far off each other. In fact, according to him, "there is little practical difference between a statistical technique and a classical data mining technique".

So why is there so much hype for Data Mining than Statistics?

Kurt Thearling states that data mining tools are more robust to dealing with messier real world data, and more robust to being used by less expert users. Simply put, these tools are more reliable in that they are capable of performing without failure under a wide range of conditions.

But that's not the only reason he has stated.

Data Mining is timely during this information age. "If there was no data, there would be no interest in mining it." In this age where computers are running rampant, and information is being stored in large quantities, data mining has a lot to offer, not just locating data amongst
millions of files and folders, it also translate those data into information, and that information into business intelligence, which then in turn, helps in the decision making process of a company.

So why again is Data Mining timely? Well, in my point of view and understanding of what Thearling has said, Data mining simply makes the task of finding "hidden" data that much easier. In this information age we live in, traditional find and grind would not be as efficient as before. Not to mention that once you've found the data, analyzing it in hopes of finding what its relevance to the current issues would take long period of time using traditional manual methods. Data gathering nowadays continually grow in size and complexity, requiring more sophisticated means of safely storing them, finding them when the need arise, and analyzing them in the quickest, yet thorough manner.

Databases nowadays have grown to contain information that are very large in quantities and possibly larger in quality. But not all data stored in them will be useful at a given time. Databases can be larger in both depth and breadth:

• More columns. Analysts must often limit the number of variables they examine when doing hands-on analysis due to time constraints. Yet variables that are discarded because they seem unimportant may carry information about unknown patterns. High performance data mining allows users to explore the full depth of a database, without preselecting a subset of variables.

• More rows. Larger samples yield lower estimation errors and variance, and allow users to make inferences about small but important segments of a population.

Data Mining is without help anyway. Listed below are some of the more useful techniques Data Mining has to offer:

• Artificial neural networks: Non-linear predictive models that learn through training and resemble biological neural networks in structure.

• Decision trees: Tree-shaped structures that represent sets of decisions. These decisions generate rules for the classification of a dataset. Specific decision tree methods include Classification and Regression Trees (CART) and Chi Square Automatic Interaction Detection (CHAID) .

• Genetic algorithms: Optimization techniques that use processes such as genetic combination, mutation, and natural selection in a design based on the concepts of evolution.

• Nearest neighbor method: A technique that classifies each record in a dataset based on a combination of the classes of the k record(s) most similar to it in a historical dataset (where k ³ 1). Sometimes called the k-nearest neighbor technique.

• Rule induction: The extraction of useful if-then rules from data based on statistical significance.

While these techniques offer help, another question lingers. How exactly does Data mining help you tell the information you do not know, and what is going to happen next?

Answer is simple: Modeling. Thearling defines Modeling as simply the act of building a model in one situation where you know the answer and then applying it to another situation that you don't. Basically, you find patterns using pre-existing records to predict the data you need.

For instance, a marketing manager for a novelty product institution could "mine" their data warehouse for data of what customers prefer to purchase given a specific holiday. Using a model table containing demographic information such as age, and gender of customers who have purchased novelty items from the store at a given holiday event, you could easily know what products to promote, and what products to omit during a specific holiday event, thus efficiently promoting products while eliminating unnecessary costs.

Over all, we see the potential successes data mining offers to businesses in different industries. Not only does it help in decision making processes, it also makes the "decryption" and prediction of valuable information easier in today's information age.