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Google Streamlines Analytics Experience

Yesterday, I went into Google Analytics to set up a new website. Once again, it took me several tries to make my way to the proper section. I don’t load things into Analytics all that often, but still, you’d expect a tool this sophisticated to be a little more intuitive.

Hopefully, that’s what we’ll all find when we log on to the next generation of Google Analytics which they call “dramatically streamlined.”

analytics update

When you go into the Admin tab, this is what you’ll see going forward. Google provided several screengrabs on their blog but what they don’t show are the options under the drop-downs and this is where I’m confused.

[Infographic] In a Mobile World Customer Reviews Matter More Than Ever Before

customer-feedback-matters-previewThe Internet world is indeed a mobile world. There is no longer proof needed for that to agreed to amongst any marketers.

What that mobile world has created, however, is a brave new world for the consumer who now wields more power than ever. That power comes mostly in the form of reviews of a business’ products and services. It all leads to a customer who can voice great joy or great dissatisfaction with a business and that is power.

According to Gib Olander, CEO, Local Viewpoints,

Word-of-mouth advertising has long been recognized as the primary factor behind 20% to 50% of all purchasing decisions; in today’s mobile friendly, digital world, consumer testimonials and online reviews have become the default way within search results for consumers to judge the viability of a business to meet their needs.

The folks at Local Viewpoints put together an infographic to help further explain this reality of today’s online world.

Here it is.

4 Steps to Move from Insights to Action

This post is presented by Marketing Pilgrim’s Analytics Channel Sponsor WebTrends. It was written by Stephen Eide, Training + Development Specialist at Webtrends.

If you’re like most digital marketers, you track a set of website metrics—measurements such as site visits, time on site, referring sites and the all-important purchases, conversions or downloads. While tracking and reporting on these metrics is fairly straightforward, do you know how to use them to make improvements?

While it can be challenging to move from reporting on results to driving action, it’s a critical transition. It can help transform your organization and put you on the path to marketing glory.

Here are four steps to get you started:

Five Questions You Must Answer Before Testing Your Landing Page

WebTrends Landing Page White PaperThis post is presented by Marketing Pilgrim’s Analytics Channel Sponsor WebTrends. It was written by Karen Wood, Sr. Product Marketing Manager at Webtrends.

It’s a cold, hard reality that your landing page has just four seconds to capture a visitor’s attention. Not only that, landing pages are the stage in the campaign funnel most vulnerable to customer abandonment—converting, on average, just three percent of visitors.

This so-called success rate begs the questions: Is three percent acceptable to your bottom line? And what is it about your marketing efforts the other 97 percent rejected?

The Hard Truth on “Gut-Feel” Marketing

All too often, poor campaign performance is rooted in human condition. Many marketing decisions aren’t based on data, but rather on opinion—and often, that opinion is just the highest paid person’s gut feeling. As a result, the marketing team is sent down a path without any certainty that what they are doing will produce results.

Twitter Acquires Social TV Analytics Firm Bluefin

Twitter logo 6-12Coming off the success of another Super Bowl where Twitter was an increasingly important part of the experience of the game from the play to the ads, Twitter announces that it’s relationship with TV is getting deeper.

The microblogging site (Ok, does anyone actually call Twitter that anymore? Could use a little help here) has purchased Bluefin Labs which is a social TV analytics platform. From their blog post we get

Today we’re happy to announce that we have acquired Bluefin Labs, a leading social TV analytics company that provides data products to brand advertisers, agencies, and TV networks. We believe that Bluefin’s data science capabilities and social TV expertise will help us create innovative new ad products and consumer experiences in the exciting intersection of Twitter and TV.

Seeing the Future: Sentiment Analysis and Predicting Trends

ibm-steampunkAs marketers we spend considerable time looking at analytics.

Much of the analytics has to do with prior performance. We look at what has happened, determined why we think it happened that way then we adjust accordingly.

In a real-time sense we look at analytics and we hope to learn what is happening “on-the-fly” and adjust accordingly.

So what else is there? Well, there’s always predicting the future. Yeah, that’s right. Predictive analytics are getting attention. I suspect that we are in the heavy hype phase where it sounds cool but will the delivery match the anticipation? We have enough of an Internet industry track record to know that hype often outpaces reality by a sizable margin (how many “This is REALLY the year of mobile!” claims were made starting in about 2000?).

Just How Big is Big Data?

Big data is a term you hear bandied about a lot these days, but what exactly does it mean?

Big data refers to any collection of information that is so large, you can’t use normal means to process it. For example, I can list all of the kids in the local elementary school on a spreadsheet then use conventional sort methods to find out how many are girls, how many are born in December, how many have siblings in the same school. Easy.

Now, suppose I want to mine that same information, but with all the kids in every elementary school in the US. That would require a very, very large spreadsheet and better tools for sorting and quantifying.

In online marketing, we’re looking a big data sets connected to internet usage. We begin with a simple slice from Monetate’s new Infographic “The Retailer’s Guide to Big Data.”

Then we add in other types of data collected by retailers on the internet. Names, addresses, birth dates, phone numbers, email. Then we move beyond personal identifiers into personal preferences; what did a person buy, how often did they buy, did they buy the blue one more often than the red one. From there we expand to product reviews, and Likes and Pins on Pinterest, shared links, photos and blog posts. Each of these items tells us something about the person who interacted with each of these experiences.