Content is King

Content Is King: Taxonomy and Metadata Management in a nutshell. 

A lot of other things matter in building a strong website or blog, like user experience (UX), e.g. look, feel, flow, etc. But when it comes to building a solid user base, content is king. Sounds easy right? Well, not so fast. If you're a good writer, or you have a team of good writers, that's one thing. You may even have a great strategy and a solid set of guiding principles. All good. If you're really good at this stuff, you might even have a planned set of topics for the year? Likely not, but that would be fantastic. 

So, that's all great stuff, but let's get techie, or we could even say 'sciency' for a minute. Backstage there's something else going on that you may not have thought about. It's call Taxonomy. Oh, and there's metadata too, but we'll cover that in a minute. So what is taxonomy? Remember from Junior High Biology class: kingdom, phylum, class, order, family, etc.?

Well that's kind of what we're talking about here. Taxonomy is the study of and/or practice of classification. By definition, your website or blog taxonomy should basically organize and classify everything you're doing and planning to do. Sounds hard right? It's really not that hard. It's human nature to classify and categorize things. So that's what you break your annual content or editorial calendar down into, and these classifications are better implemented today as "hashtags". It's a magic word thanks so many of us know now thanks to Twitter. 

So there's a little more to Taxonomies that hashtags, but that's a great way to start. For the less-experienced, here's a hash: # and the word used just after that symbol is the tag. Get it? The hash denotes to an application coded to recognize it that the word directly following the symbol means something about the 'content' it's associated with. Here's an example from Twitter - see the (hash) #universityofutah: 

One key to this, is that you plan out ahead of time what your tags are going to be. You can add to your initial list, but it should be pretty solid. You can use existing, relevant tags, and you can create some of your own. The rule of thumb is that they're relevant, unique, and are aligned to your strategy and values (a quick Google search will come up with dozens of 'best practices'): http://www.dummies.com/how-to/content/how-to-use-twitter-hashtags-for-effective-marketin.html 

So you have a basic taxonomy, or organization, for your hashtag use? Awesome. You can now expand that. Organize your content into other categorical topics, like, attributes of your targeted audience: 

• age range 
• income 
• gender
• market or professional field
• reading level
• consumer type 

And there are many more, depending on what your site or blog does. These are a couple of ways to build up your content strategy and taxonomies. Each site, digital property, or blog might have it's own version or permutation of the original taxonomy. Having a hierarchy in your taxonomic structure can really help this stuff scale (go back to the kingdom, phylum, class example). 

Alright, so I said I would talk about Metadata, or data about data. So, this really sounds complex, but again, it's not too bad, and in the long run this stuff will give you tons of bang for your buck. Here's an example: So you have a photo you want to add to your blog post. The photo, if taken on a late model camera, will have some EXIF (meta)data. That's a whole bunch of stuff about your picture - more here:  https://en.wikipedia.org/wiki/Exchangeable_image_file_format. A couple of super useful pieces of information from that 'metadata' are date/time and geolocation. With today's site and blogging tools, you can create all sorts of interactivity and relevancy with your audience just from your time and locale. For example, if I know my audience is primarily in the Mountain and Pacific time zones, and I have an library of images I'm searching for the 'right' image to connect with them, I can 'search' on the metadata and find pictures of mountains, or desert, or ocean, or even Disneyland, but only if that content is properly categorized and managed via my taxonomy and metadata. A little work up front goes a long, long way. 

So having a metadata strategy coupled with a good taxonomy, will both provide organization and structure to your content, but it will also present opportunities to create interoperability, or more 'connections' between your site, other complementary sites or functions, and your audience. It can dramatically improve to the scalability and extensibility of content across digital properties. And lastly, it can prevent piecemeal or fragmented messages from your hampering your site goals. 

Social Analytics: Measuring How Much We Rock (or fail) at Social

       Everyone knows that social is here to stay. Sites like Facebook.com, Twitter.com, Google + and YouTube allow for communities of people to connect to one another at the click of a button. As these sites gather subscriber bases in the hundreds of millions, businesses are looking at ways in which they can leverage social to impact the bottom line. Marketers are diving head first in the race to obtain the most likes, +1’s, and re-tweets in order to provide stronger positions for their brands. An unfortunate reality of this strong push towards social media marketing is that marketers are ignorant of the means in which to quantify how every Facebook “like” or Google “+1” impacts their business. Instead of looking at how optimal their involvement in social media is, the organization focuses on insightful metrics that common place tells them are important.

What can we track?

      Marketing efforts on social media can be more than content saturation and posting pandemonium. According to Avanish [1], social media metrics can be reduced to four aspects that provide practitioners insight into the effectiveness of their social media brand promotion campaigns. These metrics provide analytical insights that allow you to understand who your audience is and how to effectively engage them.

1. Conversion Rate: # of Comments Per Post

    Where e-commerce conversions generally describe a completed sale, social conversions occur when subscribers to your social asset connect with you through comments or replies to the content that you have posted. Conversion rates are calculated by finding the amount of audience comments per posting. Achieving higher conversion rates can mean that content is engaging your audience and driving return visits and additional brand interaction. Beware posting content that artificially stimulates audience interaction and focus on obtaining genuine engagement with a message that is in line with your brand and organization.

2. Amplification Rate: # of Shares Per Post

   Many channels of advertisement provide only a limited amount of impressions per add. Social media has the added benefit of enabling audience members in your own network to provide additional exposure to audience members within their own networks. Amplification rate describes the rate at which people take your original content and distribute it through their own social networks. Amplification actions may go by different terms based on the social site (re-tweet on twitter, share on YouTube Facebook and Google +), but each action amplifies the reach of the original posting. Analysis begins by categorizing content which obtained the highest amplification rates and finding similarities in order to influence future postings.





3. Applause Rate: # of Likes/+1 Per Post

    All of today’s social media sites provide users a means to provide immediate feedback to content and comments from other user. Applause rate is the number of “kudos” (favorites, likes, +1s) per post. This metric allows marketers an insight into what content audience members like and dislike, while simultaneously notifying others in their social graph that they endorse your content. These endorsements follow your content and provide credibility to users who might have discovered it through search. 





4. Economic Value: Value Per Visitor

   Even though the previous metrics are an important way of quantifying how effectively your organization participates in social media, most high level managers need to be educated on the value that is derived from social efforts before allocating any additional resources. Social economic value is a combination of revenue generated and reduced costs that social media campaign’s produce. Before we are able to discover how social drives economic value, organizations need to define what their micro conversions are.

Micro Conversions

   Micro conversions are web site engagement actions taken by users that are not overall conversion goals for the entire site. For example, when a user comes to your site to research what comments people are leaving for your products, but fails to make a purchase (a macro conversion goal), that individual has participated in a micro conversion. Organizations who define and track these micro conversions are able to gain insight on how aggregated micro conversions influence macro conversions. (2)

   Micro conversions relate to social economic value in that once defined, our analytics tools are able to track how and quantify exactly how our micro conversions are influencing the money making conversions that mangers love. A micro conversions may look like any customer who looks at a support page, blog, or product info on our site. We then take that data and compare it to the amount of referrals from the social sites we participate in and the amount of macro conversions, we are able to prove that social participation can generate value to an organization.(3)




Take Away

   Social media analytics can and must be used as a means of objectively measuring how effectively organizations are able to leverage social media to add economic value. However, social media’s most effective role in any organization is how it allows us to define our marketing message, while providing a communication tool that allows us to build relationships with our customers. Social marketers usually don’t work for free. By correlating social media efforts to profits, social efforts can be seen as a revenue generator.

Some Social Analytics Tools

These tools can help keep track of social media efforts through the gathering and reporting of every interaction that occurs on an organizations social media assets. 

Hootsuite: 
http://hootsuite.com/features/social-networks

Tool Demo

Google Social Reporting
http://www.google.com/analytics/features/social.html

Tool Demo

References:
1) http://www.kaushik.net/avinash/best-social-media-metrics-conversation-amplification-applause-economic-value/

2) http://www.kaushik.net/avinash/excellent-analytics-tip-13-measure-macro-and-micro-conversions/

3) http://www.marketingsherpa.com/article/how-to/5-tactics12

Analysis through Visualization

Data Visualization & Analysis

The majority of companies are sitting on a treasure trove of data, but without being able to see or visualize the data, what good does it do us? Enter data visualization tools. Seeing the data allows decision makers to put the data in context, and then make important business decisions. Aaron Koblin, lead of Google's Creative Labs in San Francisco, says "It's not about clarifying data, it's about contextualizing it." 

For any business with valuable data, (it could be argued every business,) data visualization should be a large part of their business culture. Every Decision Maker in the company should have a Business Intelligence Dashboard, that allows them to see KPI's and Scorecards in a visual format. However, data visualization goes so much further than that. With the proper tools businesses can use historical or live data to make every major decision.

How should Google Instant change your next campaign?

Probably, but not how you might have expected.

For those of you who don’t use Google as your default search engine...Click Here

Anyway, Google Chrome instant search is a real-time search tool that allows users to more rapidly search for things on the internet . Extremely convenient, as you can see below, the search uses algorithms to auto predict your search results based upon

the most commonly typed in phrases or words. In fact, Google states that it can save 2-5 seconds for every search on Google. For me, someone who has more than 200 searches a day (i know, i have counted), that is a substantial amount of time. Here is a cool link that shows how the search works.

In the search below i just typed in the query ‘wher’ and this is what is returned:

Because it is in grey in the search box, the search results will have ready been presented in the window below:

It is May 6, when i am writing this so you can see why the “Where’s my refund check,” may be the most frequently searched phrase. Popularity, within context, is one of the main reasons for the higher results, but Google asserts that all suggested results, impressions, are based upon ‘real-user searches.’ But i didn’t want to search for “Where’s my refund check,” but rather “where to buy Lime Green Jackets?” So did i just give an impression for “where’s my refund check?”

While a great example of instant searches,  let’s take another example of an instant product search. If you open up your browser to google.com and type in the “Nike air max 201” you will see a suggested list like 2013 and 2012, but what is really interesting are the results that are presented below. Remember, we haven’t hit enter yet, but our results are still being displayed. If you drop select the “2012” in the suggested list, you should get a result list like this:

Any results that lists Nike in the domain is third in our organic searches list. Now instead of selecting the “2012” result in the search bar, select the “2013” and watch how your results differ. Now we see “nike” domain in the top slot. Is Nike paying extra for the keyword “2013” or is google instant search playing with things? If we just search for “nike air max”, Nike is the top two results. It is noteworthy, that is your were searching specifically for 2013 Nike Air Max shoes, you would have seen the results for the 2012 shoes first. Is this an incorrect impression?

After researching several sites, including Google, it is said the Google Instant will NOT be affecting your PPC data or your analytics data. Impressions, for instances, are only counted when a search term is clicked, the greyed suggested term is selected with an ‘enter’, or if you stop typing on a search query for more than three seconds. Google also believes, naturally, that instant search should actaully improve your impressions data over time because it will lead to less incorrect search or impressions, as users will see the results beforehand and be able to adjust their search terms appropriately. 

Seems like a reasonable way to ensure quality impression data, but where things may see a difference is in the AdWord campaign that you may be using. Google admits that your AdWord campaigns will need a tweak from your original campaign purchases. One thing that is always a question, is do you buy “hotel” or “hotels”? Before, you may have wanted to purchase “hotel” as it was shorter, but now it seems like Google Instant prefers “hotels” over “hotel” in the suggested 

results.

What is strange is that Google Trends shows that “hotel” is a much more frequently searched term than “hotels”.

So it would seem it is hard to pinpoint exactly which AdWord term would be a better fit. Of course, if you have the funds, you could always purchase both.

Throughout my research on this topic, the article by David Iwanow, on SearchEngineJournal.com was by far the most thorough. If you plan on reading more on this topic I highly recommend it. Link

So how does this change the way you prepare for your next campaign?

Is that my picture? A Closer Look to Online Privacy

Our privacy is not what it used to be. I remember back in the day when we were so careful about the things we’d share online; now it’s hard to keep our information safeguarded.

The huge amounts of data provided every day by online users, the tools to mine these data and the eagerness for companies to buy/sell online data, have changed the way users interact with the internet and the way companies try to lure online users to share as much as they can about their customer’s lives [1].

Let’s take a look at how the Digital Analytics Association encourages digital analysts to provide privacy, transparency, control, education and accountability.

Digital Analytics Data Protection  

The Digital Analytics Association (DAA) defines in its code of ethics, five points to guarantee that the Digital Analyst will provide a great job at protecting the data [2].

Privacy

The analyst agrees to hold consumer data in the highest regard and will do everything in his/her power to keep personally identifiable consumer data safe, secure and private.

Transparency

The analyst agrees to encourage full disclosure of clients/employer consumer data collection practices and to encourage communication of how that data will be used in clear and understandable language. It’s important to keep the company’s privacy policy up-to-date, just so the analyst can provide a clear and truthful reflection of the data collection.

Consumer Control

The analyst agrees to inform and empower consumers to opt out of his/her clients/employer data collection practices and to document ways to do this.  

The consumer control option gives the consumers the ability to opt out, making sure that they are removed from the data collection when requested.

Education

The analyst agrees to educate his/her clients/employer about the types of data collected, and the potential risks to consumers associated with those data.

This one encourages analysts to inform peers of the commitment to data privacy and the education of senior management, of current data collection capabilities, data definitions, and potential data risks.

Accountability

The digital analyst agrees to act as a steward of customer data and to uphold the consumers’ right to privacy as governed by my clients/employer and applicable laws and regulations.

This one makes the analyst accountable for use and misuse of the data collected. It encourages the analyst to comply with all practices governing ethical use of consumer data.

While the analytics' world serves the purpose to tailor data based on a given company needs, it can also provide nightmares to online users if this information is not safe.

A Living Nightmare

In 2012, hackers gained access to Wired.com Senior writer Mat Honan’s “complete digital life in the span of an hour” [3]. Everything happened because of a tool, widely used by hackers, called social engineering [4]. The hackers were able to gained access to his Gmail, Twitter and Apple accounts; in the process, his mobile devices were wiped out losing all of Mat’s documents, messages, emails and pictures.

Stories like Mat’s are very common nowadays. I’m terrified every time my friends share status in Facebook and their profile has been set to public. I also get concerned when my family members tell me that they haven’t changed their passwords in years.

We are exposed to online data every day. It’s our duty to prevent hacker attacks by following simple rules like frequently changing passwords, making sure our online profiles for the different social media networks [5] is not set to public, clearing web browser cookies, and staying away from harmful websites.

The Bottom Line

Digital analytics can be intimidating to online users because of the tactics and tools used to mine, extract, transform and load the data collected. It can also be intimidating because errors in the process and the lack of privacy from different companies could expose holes that can be exploited by hackers.  

Digital analytics provide awesome tools to optimize the efforts to drive business results. It’s our responsibility as online users, to keep our personal information away from hackers to avoid headaches. It’s also the data company’s responsibility to make sure our data is kept safe.

What are some of the things you do to keep your personal information secured?

References

http://image.shutterstock.com/display_pic_with_logo/576460/576460,1271023722,10/stock-vector-eye-spy-telescope-50715340.jpg

1. http://www.nytimes.com/2012/07/05/business/retailers-lure-online-shoppers-offline.html?_r=0

2. http://www.digitalanalyticsassociation.org/

3. http://www.wired.com/gadgetlab/2012/08/apple-amazon-mat-honan-hacking/all/

4. http://www.social-engineer.org/

5. http://dauofu.blogspot.com/2013/05/social-psychology-profiling-social.html

Six Big Trends for Digital Analytics in 2013

We’ve all heard the both the hype and truth of Big Data and Digital Analytics. With so much information available to companies regarding their customers, it’s considered a catastrophe for companies not to be on-board the data bandwagon.  The concepts of Big Data and Digital Analytics, along with the numerous applications, are infiltrating throughout multiple industries and have made significant influences in business strategy.

While it’s true that the future of business belongs to those individuals embracing the big data concept, it’s even more advantageous to understand how 2013 will be shaped by new trends in analytics. Here are six trends in Digital Analytics and how they’ll shape the way business are run.

1.       Rise in Data Applications

The demand for easily accessible/user-friendly data applications has risen due to the influx of customer data and the need for non-IT professionals to utilize data analytics and consumer insights in their business decisions.  

This new group of applications, from well-known competitors like Hadoop and MapReduce, to emerging players like Qlikview and Kognitio, will be expanding big data insights across numerous industries. This will drive a huge competitive advantage enabling businesses to clearly see new opportunities for engaging with their consumers.

2.       Growth in Mobile

According to a recent Business Insider article, by the end of 2013, there will be roughly 1.4 billion smartphones in use around the world and mobile devices will overtake personal computers as the most widely-used web access tools.

So what does this mean for the world of data analytics? It means better access to customer information and thus quicker/more efficient business decisions. With the ability for CEOs, Project Managers, or any individual for that matter, to access customer information no matter their location, equates to boundless opportunities. Mobile technology affects every individual whether they’re the CEO of the company utilizing the analytics or the customer providing the information.

3.       Locality of Analytics

Location-based data is providing enormous possibilities for companies seeking new ways to engage their customers. Having the ability to not only understand their customer’s buying behavior, but also realize where they’re at during any given time, provides the opportunity to create “hyper-local” offers. (per Wikipedia: HyperLocal content refers to content intended primarily for consumptions by residents of that area)

Outside the common direct marketing users, location-based data is helping many different industries excel in their line of work. With so many individuals utilizing location-based features on sites like Facebook, Google, Yelp, and Twitter, there is now useful data outlining customer preferences that companies can take advantage of in their marketing schemes. There’s also the increasing usage of local data-based searches on search engines like Google and Bing, which provide customer insights on buying behavior.

4.       Data Governance and Best Practices

With so much consumer information being available 24/7 to hundreds of different companies, the issue of data security has become a popular topic of conversation. The concept of Data Governance refers to the overall management of data being exploited by a company. This particular data management includes issues in data accessibility, data integrity and data security by those applying analytics.

Data is becoming increasingly valuable for competitive industries and so is the practice of guarding customer information. If a company wants to gain the competitive edge while also maintaining its integrity and reputation, it’s an enterprise-wide duty to create best practices to protect different types of data such as financial information, trade secrets, and even patient health information. An effective best practice plan will generate an increase in data quality and thus create new business while also maintaining existing customer bases

5.       The Socialization of Data

Social Media is becoming a universal movement across various platforms. With such a prevalence of users across sites like Facebook, Twitter, LinkedIn, and Google+, there is an exuberant amount of opportunity for companies to engage with their customers, while also gathering valuable insights on their buying behavior, personal preferences and product opinions.

Obtaining these valuable consumer insights is the ability to analyze data within social media sites and subsequently transform it into knowledge. One of the issues surrounding social media analytics is understanding what to measure. Often users that are seeking social media data, have the goal of identifying upcoming trends. The secret however to gaining this much sought-after status is to know what you’re looking for, but also using technology that will provide valuable insights that may not have been sought after. These applications will therefore gain popularity as companies understand the importance of social media-derived data.

6.       Evolution of Business Intelligence

The concept of Business Intelligence is absolutely vital for all companies across various industries. Obtaining customer data is only the first step in the right direction. Having the ability to understand and visualize significant business metrics via a dashboard and thus generating strategy is the key behind business intelligence.

So where is Business Intelligence headed?  There are three important directions that Business Intelligence is headed. The first is Unstructured Data, which is data outside a database and that can be easily accessible by anyone within an organization. The benefit unstructured data holds on business intelligence is the opportunity for individuals across various departments to understand their company’s data analytics and thus make efficient business decisions.

The second route Business Intelligence is going down is the idea of Cloud-Based BI. Despite the fact that many companies would want to purchase BI systems, they’re often expensive to install and can require continuous maintenance. Building a BI system as a Saas (Software as a Service) creates the opportunity for more individuals to access key analytics while also allowing for easy BI software updates.

The third route in which Business Intelligence will venture is Mobile BI Applications. As noted above, mobile usage has dramatically increased and will soon takeover PCs as the main web access tools. Therefore having the capability to access business intelligence anytime, anywhere, and on any device, creates massive opportunities for business large and small.

Resources Used

-Adler, Steven. Six Steps to Data Governance Success. May 31, 2007. CIO. http://www.cio.com/article/114750/Six_Steps_to_Data_Governance_Success

-Badlani, Amman. Driving Consumer Insights with Mobile Analytics. April 19, 2013. Search Engine Watch. http://searchenginewatch.com/article/2262641/Driving-Consumer-Insights-With-Mobile-Analytics

-Brandon, Amanda. Four Trends in Business Analytics and Data Analytics. September 8, 2010. Spotfire.

http://spotfire.tibco.com/blog/?p=3303

-Howson, Cindi. 7 Top Business Intelligence Trends for 2013. January 25, 2013. Information Week. http://www.informationweek.com/software/business-intelligence/7-top-business-intelligence-trends-for-2/240146994

-Jordano, Lou. Future Uses for Data Analysis and Location-Based Data. October 16, 2012. Spotfire.

http://spotfire.tibco.com/blog/?p=15166

Working Smarter with Tag Management

Working Smarter with Tag Management

What is Tag Management?

In the beginning of e-commerce, the only analytics tool available was a simple page-view counter. Similar to the infamous McDonald’s billboards which advertised the number of hamburgers purchased each day, the little web counter was visibly displayed at the bottom of the homepage for everyone to see.

Today, web analytics has reached layers of complexity with tags associated with each button, link, and often even images. Each of these tags informs Customer Intelligence (CI) professionals how often a user is selecting an item, viewing a section of text, or completing an online process. 

Should We Use a Tag Management Tool?

Because the level of complexity has greatly changed, the method to manage tagging also needs to enhance. The CI can choose to manage each of the tags manually, but a number of challenges could occur.

Downfall in manual tag management:

• High Error Rate – A complex site will have hundreds of tags buried inside layers of JavaScript. Each tag will be associated to a particular area of interest. If the tag is placed in the incorrect place, the data gathered may be incorrect or irrelevant.
• High Cost – In order to manually change each tag, a web engineer will need to spend development time coding and deciphering proper placement. This time could either result in high operational costs or be viewed as excessive and dropped altogether.
• Long Time Frames – In order to ensure the tags are coded in the best, possible place, continual research and testing would need to be performed. If a decision is waiting on CI results, this may cause a delay and loss in profitability.
• Ongoing Process – Since this process will need to be repeated over and over again, the continual cost and length of time may jeopardize the benefit of analyzing online customer interaction.

In order to determine when a company should invest in a tag management tool, Forrester has created the following chart₁.

Determine your company’s score for each of the questions above. Total all of the individual numbers together to understand your tag audit score. Use the following table to establish if your company meets the level of CI complexity to benefit from a tag management solution.

 Common Tag Management Tools

• Google Tag Manager
• Free
• Integrated with Google Analytics
• Key Features: Easy to setup, unlimited number of tags, simple portal
• Adobe TagManager
• Included with Adobe Analytics suite
• Integrated with Adobe SiteCatalyst
• Key Features: Unlimited number of tags, secure administration portal, emergency rollback, ability to schedule start and end dates
• Tealium IQ
• Demo available
• Corporate Pricing
•  Key Features: Automatically adds code from vendors, turnkey vendor integration
• QuBit OpenTag
• Free – Open Source Version
• Enterprise Version
• Key Features: Universal variable, container tag for managing third parties
• Ubertags
• Hosted Service
• $50 Monthly Fee
• Key Features: One single tag on website manages all other tags

Learn More about Google Tag Manager 



Learn About Adobe Tag Manager

 Read More From Sherrie Cowley

Time Spent:

Research - 5 Hours

Write-up - 2 Hours

References:

1Stanhope, Joe. "How Tag Management Improves Web Intelligence".  Forrester. 2010.

2Stanhope, Joe. "Understanding Tag Management Tools and Technology”  Forrester. 2011.