What is the most important customer group?

Digital Analytics – What is the most important customer group?

For years, many e-commerce managers struggled to understand online users’ behavior, so they could turn their portals into more efficient sources of revenue. At first, most of the activities and promotions were designed and focused on engaging both existing and new users, with the focus varying from time to time between the two groups; however the realty in most cases was that decisions were based primarily on personal opinions and current trends.

Despite spending hundreds of hours and several years analyzing web analytics, hoping to distinguish between these two groups, it has become clear that the more one learns about them, the more difficult it is to identify the difference between them. One of the main reasons for this is that overall, technology is evolving at a much faster pace than analytics technologies are, or at least it feels that way for most small businesses.

The “new visitors” segment can be a bit misleading at first. In theory, a new visitor should be a person who is visiting your site for the first time and a new customer should be a person who has purchased your product or service for the first time. In today’s world, however, it is very common for users to have multiple devices, such as a laptop computer, an iPhone, an iPad, and in many cases, multiple browsers installed on the same device. This makes it much harder for analytics tools to identify visitors as the same person. In my case, I have a laptop with multiple browsers, which I take from home to my office almost every day, therefore connecting on various networks (IP addresses). I often make online purchases and, depending on what I am buying, will use different credit cards and shipping addresses. Therefore, for most analytics tools, who am I? Am I a new or existing customer? Am I a new or existing visitor?

When Google released the Real-Time Data component to Google Analytics, I felt that most of my business dreams were about to come true. As a young boy I remember being trained by my dad about how to approach customers. He had told me to approach a customer that had just entered the store. I hesitated because I saw that there were other people that were also about to open the door and come in, so I asked him, “Who should I talk to first?” He replied, “The most important customer right now is the one inside of the store.” Along those lines, if you were to ask me today which customer group is more important I would definitely answer, “The one currently browsing your website!”

With Real-Time Google Analytics you can have real time data that will allow you to push content and specific data, in order to generate revenue. You can do this because you can effectively monitor the results of new campaigns and site-to-site content (prices, coupons, etc.) based on the traffic demographics. With Real-Time Data available it becomes much easier to see key data such as:

• The number of people currently browsing your site
• Their geographic locations and the traffic sources that referred them
• Number of incomplete orders (cart abandonment)
• Which pages or events they're interacting with, and which conversions goals are working best

In conclusion, there are no shortcuts when it comes to managing a successful e-commerce portal. The more time you spend understanding your customer base, the better businessperson you will become. Making the right decisions and minimizing your investment risk will depend on how much time you are willing to spend to understand your customers.

References:

•       http://www.practicalecommerce.com/articles/3771-Understanding-Segmentation-in-Google-Analytics
•       https://support.google.com/analytics/answer/1638635?hl=en
•       http://blog.net-results.com/identifying-website-visitors-the-naked-truth-part-1/
•       http://www.smashingmagazine.com/usability-and-user-experience/#c2
•       Harvard Business Review -  http://blogs.hbr.org/2012/07/to-sell-more-focus-on-existing/

Show Me the Clicks! - How to Make Your Web Analytics Outperform the Competition

Working at an advertising agency and helping clients manage their online purchased media campaigns, I've seen the allure and temptation of the click win out too many times. Forget about setting goals in Google Analytics, that takes too much time and effort! What about a campaign that is supposedly for "brand awareness"? No, no, no...show me the clicks! I'd like to discuss the shift from Web Analytics 1.0 to Web Analytics 2.0 and how businesses can take action to focus on those things that drive revenue and accomplish goals.

Web Analytics 1.0
In a day and age where being up to speed on the latest and greatest technologies is an extremely sought after position, it's hard to imagine that we would still talk about businesses lagging behind in any forward-thinking concept. Unfortunately, Web Analytics 1.0 is still widely accepted as an effective web analytics strategy.

In order to better understand what Web Analytics 1.0 is, I will give an example from my previous work experience. I won't name specific names, yet relate a story and call the business involved "Large Car Dealership Corporation A". While Large Car Dealership Corporation A has the resources to afford the most expensive of web analytics tools, they choose to focus on that which has been plaguing business decisions for years (see video above): clicks. The business is too narrowly focused on solely driving traffic to their website (which is not user-friendly nor attractive) and not on creating a funnel to allow customers to follow a path that leads them to making a purchase decision. This lack of a complete web analytics strategy leads to misinformed decisions by the client and inefficient results from their online marketing campaigns.

Web Analytics 2.0
While many businesses are still focused on what the click can do for them, a major shift has been made in the web analytics realm. There is a focus on other elements than just getting clicks or more visits to a website. The web analytics shift to a new philosophy causes businesses to ask the following questions: What are our customers saying? How does this affect how the website or how a path is set up? What actions do we take in order to meet our end goals of increasing revenue and reducing costs?

Avinash Kaushik, author and well-respected web analytics professional, wrote a book titled "Web Analytics 2.0: The Art of Online Accountability & Science of Customer Centricity"[1] (also see his blog for more great information on web analytics). In it, he explains the shift from Web Analytics 1.0 to Web Analytics 2.0. He divides the new web analytics philosophy into five different parts and explains what role they play in an overall web analytics strategy.

The following gives more details around the parts of Web Analytics 2.0.

The What: Clickstream
Clickstream provides the fundamental elements of every web analytics strategy - clicks, unique visitors, pageviews, bounce rate, traffic sources, etc. While all of these elements are extremely important, they do not paint the entire web analytics picture. They are a base to support decisions made from other parts of Web Analytics 2.0.

The How Much: Multiple Outcomes Analysis
Too often businesses become obsessed with reporting and seeing some fancy new graph. When this happens, often there is a failure to recognize the need to take action. Avinash explains that there are three purposes to every web analytics or website optimization. Every website should do the following:

• Increase revenue
• Reduce cost
• Improve customer satisfaction/loyalty

Everything that a business does with its web analytics strategy should push to do these three things. If any initiatives are not accomplishing these three goals, the business should reassess its strategy.

The Why: Experimentation and Testing

Why are we making this decision? This is a question that all businesses should make when it comes to web analytics. Many times the HiPPOs (Highest Paid Person's Opinion) are making all the decisions based on personal preference or due to feelings of power. 

HiPPO

Taking advantage of the opportunity that the online world provides to test at a low cost and high efficiency is something that many businesses do not leverage for their overall web analytics efforts. 

The Why: Voice of the Customer

While web analytics provide an amazing opportunity to see things from an absolute data driven perspective, it is important to not forget about qualitative results that can provide valuable information. By performing surveys and usability testing, customers can provide information that will give deeper insights into the quantitative data. 

The What Else: Competitive Intelligence

In his book, Avinash relates competitive intelligence to the following story: Compare not having any competitive intelligence to driving in a car with blacked out windows and only focusing on the speed on the dashboard. It's important to stay focused on it, but it can hurt you. On the contrary, when you have competitive intelligence it is like having clean windows and seeing how fast other cars, or your competitors, are traveling. This can help you make adjustments to your own speed, or web analytics strategy.

In a world that is still longing for more clicks, being able to move beyond this crutch and include the components of Web Analytics 2.0 in your business web analytics strategies will help you optimize efficiently. You will provide a way to communicate with customers and drive results.

[1] http://www.webanalytics20.com/

Social Psychology, Profiling Social Networks

When detectives begin investigating a crime they often lean on criminal profiling as a means of finding the perpetrator. “[Criminal profiling] is not a blueprint, as [the media] often suggests, against which people can be measured to see how they do or do not fit.  It's a list of suggested behaviors and traits derived from the specific behavior evident at a crime scene or series of crime scenes that helps to narrow down leads and diminish the potential pool of suspects.”1

Profiling has and is being developed in the FBI's Behavioral Science Unit (Investigative Support Unit). It is used by police departments all over the country -- especially those with officers trained at the National Academy -- as a tool in their crime-fighting arsenal.  The basic idea for a profile is to gather a body of data yielding common patterns so that investigators can develop a general description of an UNSUB (unknown suspect).  Profiling involves the psychology-trained expert using his or her knowledge in human behavior, motivation, and patterns of pathology to create a multidimensional report.

With the recent onslaught of Social Networks we are preparing for a scene rich with evidence to begin profiling potential target markets for commerce. This has been attempted using predictive analytics and user generated content from Social Networks but has often missed the mark. What I am referring to is the marriage of Big Data Market Research and Social media profile data. There is a proliferation of data that each of us unknowingly and knowingly share on social network sites. This data is littered with pieces of evidence that tell our story; who we are, what we like, what we dislike, what makes us tick and what turns us on. All pieces to a bigger puzzle that is us. This data can tell companies exactly what they need to know in order to sell their products or services. Highly focused targeting for advertisers, marketers, product development and research and development. This is not to say that the content that social network users are creating is of no value but that the true gold is below the surface.

A new field of social psychology could emerge. Social networks like Facebook sit on data that are the fabric of our lives. This data could be some of the richest information into what each of us really want or even need. If corporations could begin mining this rich data and couple it with the already rich market research data that is out there the social psychologist could begin profiling each of us. Providing valuable insights and directives. Below are just a few suggestions on how this new field may prove profitable.

1.    Keys to purchasing habits and prediction

           A profile is based on the idea that people tend to be guided by their   individual psychology and will inevitably leave idiosyncratic clues. These   clues will better serve advertising directives including but not limited to the best time, format, medium, location and content for these ads. As this       continues to get more accurate in its profiling specific and even custom advertising experiences could become the norm. Ever experience with a down to delivery.

2.    Advancement of new Advertising Methodologies

           For instance, product sponsorships based on individual’s social influence and profile categorization. Imagine getting paid in cash or free shawg because you fit a profile for a company and have an above average influence based on your social network interactions? Teenagers become walking billboards, and cheap ones at that. With far reaching grass roots styled effects in their ability to market, promote and sell products or services. No longer do companies have to lean on Hollywood’s elite to promote their lines. (Hollywood actually released a film not to many years ago all about this very thing. The Joneses)2

 

3.    New Business Models/Opportunities - Digital Grooming

           Surrounded by digital content, profiles, categorizations, social clout and influence new necessities with our digital selves will get put in the spotlight. Consultants will now work with you to build a better digital self. It won’t be enough to shave and shower in the mornings in the privacy of your own bathroom. You will need your digital self to be cleaned, trimmed and groomed in to not lose the promotion, get an interview or even keep your job. All this will bring on new ventures, backed by new technologies to make it easier and efficient to manage.3

These ideas aren’t new, nor are they far from completion. We are already beginning to see products that will begin to merge our interaction of our digital selves and our physical world. How we are viewed, classified and even profiled will continue to become integral. With it come new concerns for privacy, civil rights and even discrimination. All of which will need to be sorted out. Needs for fact checking will long pass by just being needed for politicians or journalists but your next-door neighbor and even child or parent, not to mention employer and employee. With each of these concerns more new opportunities for business models, laws and enforcing agencies with come as well. Proving Hollywood movies like The Joneses or even Minority Report closer to realities than not.

References:

--> http://www.trutv.com/library/crime/criminal_mind/forensics/forensic_psychology/10.html 

http://www.imdb.com/media/rm3528560384/tt1285309?ref_=tt_ov_i

-->

http://www.web-strategist.com/blog/2012/04/25/how-%E2%80%98social-profiling%E2%80%99-will-work-in-the-real-world/

 

Metrification Autometrically!

Metrics! Metrics! Metrics!  If I have to hear that word one more time I think I might just scream like Doc Brown at the end of Back to the Future II. 

GREAT SCOTT!!  I thought I sent Metric McFly back to the future!

But, that's the life of a web analyst.  They look at metrics everyday.  They read metrics everyday.  They dream about page view percentages and average time on a site.  They search through blogs and books about how to improve their SEO.  They attend conferences and workshops with names like the eMetrics Summit or any of the following:  SearchFest, Social Media & Web Analytics Innovation (try repeating that five times really fast!), or Webstock (which is like Woodstock, just without all of the drugs, half-naked people dancing everywhere and the legendary Santana and Jimi Hendrix).

Let me rephrase that, they devour metrics like 30 year old's devour Alphabits cereal.

Is that a bowl of Alphabits?!  NO, fool it's an ice cold bowl of metrics! Eat up!

Metrics are like the blood that pumps through the veins of web analysts.  They devote hours to scouring metrics with a combination of tools like Omniture, WebTrends and Google Analytics, just to name a few.  They bust out metrics at a party like ghostbusters bust ghosts.  They have Photoshopped pictures of themselves hanging out with Avinash Kaushik....what you don't know who that is?!  Click here for some edumication.

LET'S GET METRICAL!

To further educate yourself in the ways of the web analyst there are is little metrics lingo that you will need to brush up on so you don't look like a complete maroon when attending those really neat conferences I previously mentioned above.

For example, you should know a little about the following:

• Page Views - the amount of times a page on a website has been viewed.  These can be viewed by new, repeat or a return visitor.
• Entry page - which is generally the very first page on a website that is viewed.  For example when you visit Walmart.com, that first page is the entry page.
• Exit page - is the opposite of the entry page!  Exactly!  It is the last page you left from a website.  
• Bounce Rate - is basically the rate of how many times a visitor exited a page on a website versus those that have stayed on the page.  For example, say you go to the Walmart.com link and search for motor oil.  Then you decide that Autozone has motor oil to and for a better price, so you type in your address bar www.autozone.com.  You bounced from the Walmart page to the Autozone page.
• Conversion - this is a measurement of how many visitors have performed or completed some action on the web page.  For example, purchasing an item from Amazon.com or initiating a download from a website.  
• Count - which is a measurement of how many visitors have entered a page on a website
• Average time on Site - How long did visitors stay on your site.

Now with some lingo under your belt, your almost ready to get started into the world of web analytics.  The next step is to understand exactly how some of these measurements are categorized.  Generally there are 3 categories that metrics fall under:

1. Individual - Activity of a single web visitor for a defined period of time.
2. Aggregate - Total site traffic for a defined period of time.
3. Segmented - A subset of the site traffic for a defined period of time, filtered in some way to gain greater analytical insight.[1]

The next step to understand, is that all of these metrics are the results of visitors...visiting a website.  This brings us back to another set of important metric lingo...visitors...

Not these visitors!

These visitors....

There are three types of visitors in the web analyst lingo.

1. New Visitors - Are visitors that have visited a website for the first time.
2. Return Visitors - Are visitors that have returned to the website.
3. Repeating Visitors - Visitors that have repeatedly visited a website during a specified time.
4. Unique Visitors - Wait didn't I say that there are 3 types of visitors?!  I did, and I am glad you caught that, because that means you are actually reading this post!

The three types of visitors: New, Return, and Repeating, are considered part of  Unique visitors.  Unique visitor is defined as "the number of individuals within a designated reporting timeframe, with activity consisting of one or more visits to a site.  Each visitor is only counted once in the unique visitor measure for the reporting period."[2]

So...uh..What Does All This Mean?

Now that you understand some of the basics it's now time to jump into the why of web analytics?  One metric to notice when you are testing out some analytics tools on your website, is the Average Time on Site.  For example, why were the visitors on your site so long?  

Were they engrossed in a web article like this one 

V-Day Special, How Web Analytics is a lot like Dating or were they staring off into space?  It's a good idea to figure that one out.  

If you have a shopping cart on your site, it's a good idea to ask yourself how long did it take for a visitor to get there and make a purchase.  How many of those visitors were new visitors?  There's a metric for that too!  

So what do you do with all of these metrics?  Like any good web analyst you search for patterns.  

Do you see a pattern? Hmmm...keep looking.

Web analysts are excellent at finding patterns within their metrics.  They can see why visitors spent too much time on their website or why they bounced out after 30 seconds off a specific page.  All of these metrics set patterns and trends that are used to figure out how to improve conversion rates on a website...which is that completed event thing I mentioned before.  

What do these trends tell you?

This is the Bounce rate of this blog.

This is the Number of Visits to this blog.

This is the Percentage of New Visits on this blog

The peaks tell us that there were quite a few that visited this blog on that specific date while the valleys are the opposite.  The same can be said of the bounce rate and the % New Visitors.  Since this blog first got started in January we have had 3,771 visitors, 2,067 of them unique with an average bounce rate of 60.81%.

From these trends we can also see from where our visitors are coming from:

The darker green = where most of the visitors are coming from.

Here you can see the the United States is the main visitor demographic with India in second place.

So far what does all of this tell us?  The majority of our visitors are from the United States and let's see what page is the most viewed....looks like with a total of 10,039 page views that the post in the lead is customer analytics incorporating with 264 page views.  Ah, but look at the unique visitors!  The blog post about the problems with google analytics is leading the pack.

SO....with all of this new information swirling around your brain, it's a good idea to let it sit for awhile.  And while you're at it, read some other more interesting posts like these for our blog site:

Adventures in Ghostery

Yesterday's Web Analytics is Today's Digital Analytics

The time has come to end this post before I get a higher bounce rate!  Please read other posts while on this site to get those rates up!  

Related Resources

[1] http://www.kaushik.net/avinash/web-analytics-standards-26-new-metrics-definitions/

[2] http://c.ymcdn.com/sites/www.digitalanalyticsassociation.org/resource/resmgr/PDF_standards/WebAnalyticsDefinitionsVol1.pdf 

“Show me the Money!” - Making Your ROI on Analytics

"Right now, the [Web analytics] industry places far too much value on the measurement side of our work, especially compared to the output side," says Evan LaPointe in an intriguing post at the Atlanta Analytics blog. Measurement, he argues, "probably accounts for just 5-10% of the total value of analytics."

Evan then goes on to explain what Web analytics really is. Essentially, web analytics is the answering of these basic questions, “not individually, but holistically:”[1]
    1.    Who is coming to my web site?
    2.    What are they doing (or better, what are they trying to do)?
    3.    What is the gap between what they are doing and the ideal? (and do we mean ideal for the business or the customer? good question!)
    4.    What are some concrete ways we can close the gaps?
    5.    How can we get more of these people?
Not a far cry from questions any business finance department is asking; what is the company worth? Are they going to grow?, What does the market think? and How does that compare with its worth?. The point Evan is trying to make is that Web Analytics is about making the company as a whole better and that the Web Analyst is positioned to most effectively do that by being the analyst and not the specialist.

If you ask the question “what’s the best next step?” IT will give you and IT answer, marketing a Marketing answer and so on. The web analysts answer should be subjective. Evan even goes as far to suggest that good analytics when done correctly doesn’t mean that the website is better. You can't be afraid to embarrass your management. The really great web analyst makes the company better by making recommendations through “un-tinted glasses”  on the overall process efficiency and how well the company delivers on its goals. A true contribution to profitability, or ROI.

Web analytics must “generate added value through the losses that it identifies and the opportunities that it creates...Online measurements should allow companies to update how and to what extent online investments form part of the company’s overall development.”[2]

Here is where context can make a difference. It isn’t good enough to simply collect data with your web analytics tools[3]. You need to understand that data in context to the business questions, goals, outside influences etc. It is only when you slice and dice the data that context of other data matters. The ROI of getting the right story is monumental.

So don’t simply collect data. Get an ROI from your efforts, empower your web analyst to be hated by all but loved by all. Your web analyst needs to use the data as the hard evidence for decisions in the right context. Telling the right story and positioning the company in the right direction. That’s where the money is and that is where the ROI is played out. Now go out and “Show me the MONEY!"

[1] http://www.atlantaanalytics.com/
[2] http://www.atinternet.com/wp-content/uploads/2012/07/AT_Web-Analytics-ROI_EN.pdf
[3] http://www.searchengineguide.com/mike-fleming/web-analytics-the-roi-of-why.php