Featured in Colorado Biz
By Michele Kiss

It’s not just about collecting data.

The advent of digital brought with it the incredible measurability of the online channel. When coupled with a recession, where every dollar counts and profitability of every move is questioned, data-informed decisions have become critical to many companies. Analytics is not just reserved for companies at the top, but is becoming a cost of successfully doing business.

It’s not just about the collection of copious amounts of data, but on the integration and use of it. Ultimately, companies need the right resources in place to analyze, interpret and recommend new courses of action. A heavy investment in tools, without investment in people, is seldom successful.

Welcome to the new breed of analysts. Whether companies are hiring a “web”, “digital”, “cross-channel”, “marketing” or “business” analyst, there’s no doubt that it’s a great time to be a data geek.

The demand for analysts is directly related to the growth of online business, aided by the proliferation of mobile devices such as smart phones and tablets. The responsibility of the “Web Analyst”, whose role was initially focused just on behavior on a company’s website, has already expanded in scope, evolving to include online, mobile, social and traditional channels, as well as the integration of online and offline.

Those already working in digital analytics can attest to the barrage of recruiter calls to coax experienced analysts over to a new company, as the demand exceeds the number of analytics professionals available in the market.

Greater awareness at the college level

Growing awareness of the profession at the college level will help to (slowly) fill some of this demand. Educational institutions are starting to introduce courses tailored specifically at this new field. The University of British Columbia began offering an award program in web analytics in 2005, and other schools are following suit, with certificate programs or course work within marketing focusing on digital analytics.

The existence of these programs can help make students aware of a career in digital analytics. Programs such as Marketing, IT, Business, Economics, Mathematics and Statistics continue to lay a great foundation for a career in digital analytics, and still represent the majority of the entry points into the field, but these new dedicated courses allow students to learn enough to hit the ground running in a junior role.

An abundance of resources

For someone interested in joining this growing field, there are a number of ways to get involved. The Web Analytics Association (WAA) has chapters across the U.S. and provides local events, education, conference discounts, research, standards, training, awards, certification and great professional networking opportunities.

The Analysis Exchange is a program that provides a “student” of analytics with hands-on experience tackling the analytics challenges of a non-profit, supported by an experienced mentor. Another option to gain experience is to volunteer your services to a local charity or small business. The availability of free tools means anyone can get their feet wet in this industry.

For professional networking and to talk to those already in the industry, attend a Web Analytics Wednesdays or WAA local symposium, or getting involved via social media. There are digital analytics groups on Twitter via the #measure hashtag, Facebook, Linked In and Yahoo. Ask questions, and you’ll be surprised at who will take the time to answer them.

In addition, companies are creating more opportunities for those looking to break into the field. For example, Red Door Interactive created an internship program that helps students get hands on experience in a variety of areas, including analytics. The interns not only help collect and analyse data, but they learn how an agency works and how to be a part of a cross-functional team.

For companies needing to hire analytics professionals, it can be tough, and it’s not likely to change soon. Good analysts are typically happily employed and frequently recruited, so companies need to be open to developing entry-level or junior analysts on the job, consider internal candidates with compatible skill sets, allow flexible working arrangements (like remote employees) or make an offer too good to refuse. As long as demand continues to exceed the availability of resources, it will continue to be an analyst’s market.

Read the full article here.

Michele Kiss, Director of Digital Analytics, Red Door Interactive
San Diego, February 2012

I work in Digital Analytics. We are a relatively new field (or at least, a relatively new application of analytics) and one where I sometimes feel we don’t leverage enough of what’s been done before. Rather than re-invent the wheel, I headed off to the Predictive Analytics Innovation Summit in San Diego, to learn from a wider variety of industries, and see what they were doing with predictive analytics.

Here were a few of my key takeaways:

It’s not about the tools

I honestly thought this was just an affliction of the digital analytics industry, but it turns out, this is an issue in all area of analytics.
It’s not about the tools, it’s about two things –

1. The talent. Talent matters more than the tool. The “best tool” is one that you can hire great people to use. People are what will make analytics successful, not the tool.

2.Your needs. The “best tool” is the one that suits your business needs – not the most popular, the most expensive, or even the one with the most features. (If you don’t need those features, what’s the point?)

It is about strategy, and culture …
Success with analytics isn’t driven by the tools you buy, the process you implement, or the technology you have – it’s about culture.

The creation and hoarding of data is not what will make you successful with analytics. What matters is the consumption of analytics by the organization, and allowing data to challenge beliefs and theories. It’s not about big data – it’s about using it to make big decisions.

Case in point? Improving the efficiency of a predictive model is only worth a few percentage points in your model’s accuracy. But nailing your fundamental strategy? That’s where success comes from.

… and about communication …

Analytics is also destined to fail if it’s not communicated well. This is often where hiring for analytics fails: too often, analysts are hired who can’t communicate with others in the organization. If anyone walks out of a meeting after an analytics presentation and doesn’t know the outcome or the next steps, that’s not their fault – it’s our fault.

Businesses today are in a difficult situation – we have too much data, yet too little knowledge. Analytics is critical to helping to understand what’s important, draw insight out of volumes of data, but without the right people and the right communication, you’ll never see that value.

iMedia
Mikael Greenlief, Online Media Planner, Red Door Interactive

Having been entrenched in some aspect of online and digital marketing since the start of my career, I have heard countless times from clients and colleagues, “show us the numbers,” “show us the analytics,” “show us the stats”.  These requests are valid and quite important.  The data often help us glean insights upon which we can develop strategies and execute them. However, there is another reference point that is of equal importance; unscripted, observable research.

Most traditional forms of research are typically conducted with a few premises that present some gaps in understanding human intention and behavior, including:

1. Asking a select group of people to provide their true opinions about a brand or product.
2. Surveying a large sample size of randomly-selected people a large volume of questions, hoping to get a “true” understanding of their behavior.
3. Posing real-time questions about their experience post interaction or purchase (in-banner surveys in web forms).

Looking at some of the principles of psychology and sociology, people often don’t know why they do what they do, or say what they say and find it difficult to answer such questions in a group setting. Most times they act on feeling, impulse or habit.  It’s the way they’ve always done it or what they’ve always thought. To provide some context, think about the last time you brushed your teeth. Did you think through the process of getting your toothbrush, rinsing it off, grabbing the paste, opening the lid, putting it on your brush, closing the lid and then start brushing your teeth? It’s safe to say that you probably did not. It was habit, instinctual. Another good example might be the last time you went to a restaurant, had a wonderful (or awful) experience and wanted to share it with your friends on Facebook. Did you put a lot of thought into what you said then wrote and rewrote it while fine tuning your position throughout? Most likely you wrote what came into thought, shared your true and honest opinion as a result.

The unaided, unbiased, qualitative information provided from watching consumers in action in their own environment can be extremely useful – sometimes more so than web analytics – in driving both online and offline marketing strategy. Brushing your teeth may seem like a mundane, habitual act, but for companies that are able to watch, it can offer numerous insights that can drive product design (how do they hold their brush), packaging (is the tube easy to open) and product type (is there too much foam in the paste, do we need to alter the ingredient mix) just to name a few.

All forms of research are valid and can provide brilliant ideas. That means organizations can’t become narrow-minded in their approach and not see the bigger picture that comes from getting too mired in digital numbers and prompted questions. In order to fully understand the consumer, marketers must also observe actual behaviors, listen to their unaided opinions and understand the context of the situation. Taking this into account along with the more popular forms of research (survey, focus groups, statistics) will help companies understand the complete picture of human behavior in order to develop the most effective plan.

Read article on iMedia here>>> 

For anyone who missed the fantastic WAA LA Symposium, here is everything you wanted to know (and were too ashamed at missing such a fabulous event to ask!) 

The future of analytics: Jim Sterne’s keynote was a great opening to the day and focused on the possibilities of the future. Here’s how the road to success looks: 

• Data will let us predict the future, and data modeling will let machines help us make better decisions.
• The future of analytics is collaborative analytics – getting the information out there and getting input from the entire company.
• Ultimately, the future of analytics is up to us, and it’s not the technology that will make it happen – it’s the people who know how to use it.

Success in large organisations: Jorge Laguna from HP and Matt Wright from Keystone Solutions presented a joint client session on the keys to successful testing in large companies: 

• With a successful A/B and Multivariate testing program, a full site redesign is essentially dead. You are continually iterating to improve the experience and your bottom line.
• Build relationships within and with other teams – you can’t succeed alone.
• Recruit the right people internally, but don’t be afraid to bring in external talent that you need to ensure success.
• Document best practices.
• Communicate your success.
• Build a methodology that works for your organisation.
• Allow the necessary agility to move quickly on opportunities, and the flexibility to allow testing to work for different departments globally.
• Future-proof your investments, for when you move to new technologies.

Shawn Hushman from Kelley Blue Book talked about the requirements of successful enterprise analytics, including: 

• Commitment of the organisation, technical alignment and organisational clarity on what was important.
• At KBB, results in analytics drove further demand, until it became a part of the company’s DNA.

Understanding the Multi-Channel Customer: Kristin Shanks from Petco not only succeeded by featuring her adorable puppy in her presentation, but by sharing Petco’s success in understanding their multi-channel customer. Petco’s analytics found that:

• Multi-channel customers (for example, those who shop both in-store and online) are more valuable, spending 3x that of a single channel shopper.
• Petco didn’t just measure the overall lift due to shipping prices and policy changes, but segmented to see the impact on shopping behavior and the shift from in-store to online, to truly understand the incremental lift.
• Shanks readily admits this kind of analysis is not easy for them – they too struggle with data silos. But understand, and rewarding the loyalty of, their multi-channel customer was crucial to their business.

Succeeded in Your Career: Thuy Kim from Experian Consumer Direct shared some of her tips for a successful career in analytics:

• Keep in mind the different roles you have as an analyst. You should be creative and an information architect, presenting data in a way that is understandable (and, in the case of executives, digestible in under 5 minutes) but also act as a project manager, and of course, an analyst.
  • Red Door Interactive Project Manager Malani Shubin added to this that an analyst should also be a sales person. Whether you are on the client, vendor, agency or consulting side, you’re selling your capabilities, and the benefit that you can bring to the business.
  • Don’t forget about building the foundation. Your credibility is based on the success of things you’ve done before.
  • Analytics leaders, stop to think – why should anyone be led by you? What are your team seeing you do, even if you don’t say it? How can you create an impact and earn the right to lead?  

Success in Education: June Dershewitz from Apollo Group (Univ. of Phoenix) and Scott Rutherford from UCI discussed some of the challenges faced by the use of analytics in education. (For example, imagine trying to measure the long term impact of whether use of a mobile app leads to higher grades and graduation!) Some of the successes they shared included:

• UCI’s use of data to decide go/no go on courses ensures that they remain profitable in the face of state cutbacks.
• Education is able to learn from other industries (for example, finance) in how important the investments in analytics facing them will be to their future success, and justify accordingly

Success in data accuracy: Jon Narong from BeachBody.com discussed the importance of data quality, and how the right team structure has helped their organisation to succeed. 

• Analytics is considered a critical production data source, not a secondary concern and its accuracy is a top priority. Of course, you can never truly ensure 100% accuracy, but it is crucial to make the data as accurate as possible and understand why there might be some inaccuracies, not to mention understand their impact.
• Splitting their analytics team into Business and Technical Analytics has allowed deep immersion, less distraction from the team’s core focus and organisational confidence in their data.

Success in Social: Social was definitely a focus at the event, with not only a social media panel but also a great closing keynote from John Lovett at Web Analytics Demystified. Success in social for 2012 is going to involve:

• Moving from “what can we measure?” to “what should we measure?”
• Leveraging learning from different channels – social is not so new or different that we can’t learn from the past. For example, success in social, as in email, isn’t based on the size of your “list” (email addresses, Facebook fans) but on what you do with it from there. How do you market to the audience you’ve built? It’s not enough to have Facebook fans – you need to market to them, and do it well.
• But we are at the whim of the social channels – what metrics they’ll provide, and what they’ll allow to be tracked. You may need to find the right tools to complement your social strategy and even develop your own metrics to measure the impact on your business.
• Focusing on proving value, instead of just experimenting and defining basic metrics. Companies will have to move from the “hype” to truly considering their objectives.
• As John Lovett pointed out, “it’s frickin important to set goals” and you must align your strategy and goals with your corporate culture – “corporate culture will eat strategy for breakfast.”
• Make sure the social work you are doing is actually right for your customers. Twitter and Facebook and YouTube might not be right for your customers, but what about your support forums where customers help each other? (After all, you wouldn’t use television to market to the Amish, would you?)
• Never forget that social customers are just a percentage of your customers – keep it in context with your other initiatives!

Did you miss the WAA LA Symposium? Don’t forget about the great ways that the WAA can help you succeed in your career, by providing local events, education, research, standards, training and certificates, not to mention building your professional network. Check out some of the upcoming Symposiums to find one near you: http://www.webanalyticsassociation.org/?page=symposiums

Michele Hinojosa, Director of Digital Analytics, Red Door Interactive

I  just returned from ACCELERATE, the Web Analytics Demystified FREE conference, in San Francisco.

The next ACCELERATE conference will be held in Chicago in April 2012. If you are interested in the digital analytics industry, I seriously recommend going. It was one of the best events I attended all year. 

Given the event was centered around short, “Top 10 Tip” style sessions, I thought I would return with my Top 10 Takeaways.

Top 10 Takeaways from #ACCELERATE

1. There is no ROI in Facebook fans or Twitter followers. There’s only ROI in how you market to them once you have them. (Justin Kistner)

2. Integrate, integrate, integrate. Customer feedback data + web data + CRM data + behaviour data + testing tools … and more. (Michael Gulmann,Expedia)

3. Not the first or last time we’ll hear this – tell a story with data. (Michael Gulmann, Expedia)

4. There’s an art and science to analytics and testing, but protect the integrity of your work – don’t ever fudge numbers. It’s okay to roll out something that didn’t perform statistically better for other reasons – that’s the art. But don’t deceive. (Michael Gulmann, Expedia)

5. Mobile or die. Web traffic from mobile just continues to increase. You need to give users a choice how to engage with you – desktop, tablet, mobile devices. (And remember their choice!) (Eric Feinberg, Foresee.)

6. There are things you can do for a better relationship with your vendor. Don’t bully, communicate fully and often, and help them to help you. (Ben Gaines, formerly of Omniture.)

7. To hire a great team, prioritise your requirements, understand that you can’t have everything, and actually sell candidates on your role. (Corry Prohens, IQ Workforce.) And from Adam Greco (Web Analytics Demystified) hire the right people for what you need right now. Don’t hire a chief if you need an indian.

8. Quality is key. You should be willing to put yourself on the line, to vouch for the quality of your data. Monitor quality and continually consider the appropriateness of your implementation and reports – things do change over time! (Adam Greco, Web Analytics Demystified)

9. Your data is dirty. Deal with it. (June Dershwitz, Apollo Group.) 

10. Learn. Learn the lingo, how to cope with (and still make use of) dirty data, understand your sources of data and any acronymns. (June Dershwitz, Apollo Group.)

eMetrics was held in New York City for the first time this year, and co-located with a number of other conferences, including Predictive Analytics World, Conversion Conference, Google Analytics’ GAUGE and more.

Among some of the takeaways:

Big Data:

• Companies like eBay and Expedia have been dealing with “big data” for some time now, and the volumes continue to grow. In fact, looking back at the data volumes they had just one year ago, eBay now laughs at the volume.
• However, we’ll all start dealing with this more, in all areas of business, as companies continue to gather more data from a variety of channels.
• This brings us to deal with the challenges of data integration and attribution, and we don’t want to – they’re hard! (-Bob Page.)
• People are still a focus, we need analysts, but we also need technology and machines to support us. The needles are getting smaller, and the haystacks bigger. Machines will need to learn for us to keep up. <Insert Skynet comment here>

Attribution:

• You will never get it right, your aim is to keep getting closer, and to make your models less wrong. (And if it seems too good to be true, it probably is.)
• Not up to attribution modeling yet? Even just starting to combine your data sources in Excel is better than nothing.

Know your customer:

• Your customers are telling you what they want and giving you feedback. LISTEN!
• More than that, your customers are now in control. They can switch to your competitor at a drop of a hat, and most carry a “store in their pocket” via their mobile device.
• And in case you’re curious, YOU are not your customer. Stop thinking you know what they want, and listen to them.

Mobile:

• Mobile isn’t the future. It’s now. (-Bob Page – and with eBay doing $5 billion in mobile in 2011, you can see why!)
• What was most interesting at this eMetrics was to see mobile become less of a siloed topic, as it has previously, and more just an aspect of the business.

Privacy:

• User privacy is a challenge for all, but especially in Europe, as countries try to interpret the European Privacy Directive. For lack of a better way to describe it? It’s a mess.
• There is no real way to summarise all the current views on privacy, because everyone who speaks of it differs. However, there’s one thing we can be sure of – privacy will be different, and perhaps unrecognisable, in ten years, because the current system is not manageable.

We are more than “web” analytics:

• Multi-channel, attribution, holistic view of the customer – we should no longer be pure “web” analysts. In fact, when Bob Page from eBay talked about the types of analytics they do, there was no mention of web analytics. It is just a channel, and one place in which the company may look at customer analytics, loyalty analytics, etc.

Lessons for analysts:

• From the mouth of an executive: If the business doesn’t care about the data or metrics you’re providing, it’s because you’re not providing anything that actually matters to the business. (Or in other words, “I don’t care about bounce rate!”) Executives don’t want your metrics, they want your recommendations. They’ll only take so much of, “This is interesting.” Tie it to revenue.
• Translate data into actionable terms, and then you’ll get action. Don’t just count. Make decisions. Make mistakes. But DO something! There is, of course, a fine line between mistakes that impact your credibility, and mistakes that move your business forward. Make mistakes and learn, just keep moving forward. (-Joe Megibow)

If you’re like to read more, feel free to read through the archive of tweets.

Livia Gibbons, Digital Analyst, Data Insight & Strategy, Red Door Interactive

The 2011 Semphonic X-Change Web Analytics Conference did not follow the traditional style of conferences I’ve attend. It was not a place with 150 people in a room reading a PowerPoint. Instead the annual X-Change Conference utilizes a small group (10-15ppl) “huddle” format which allows participants to engage in open discussions, debates and collaborative problem solving. Being the first time I attended, I wasn’t too sure what to expect. From the Key-Note address through the Analytics Challenge for Non-Profits and all the huddles in-between, every detail was thought out  and taken care of by the Semphonic team so that all us analyst could focus on the good stuff- data.

During the keynote presentation, Elea McDonnell Feit of the Customer Analytics Initiative at Wharton (WCAI)* took us on a brief history of the collection of consumer behavior data. From the 1800’s when store owners kept goods behind the counter so buyers needed to ask assistance to view products. This allowed store owners to collect data on their customers’ specific behaviors; from what the most popular items were to what price point turned them off. Through this method, on a small scale, business owners could use that data to make profitable business decisions.

This approach to data collection was abandoned as a result of the growth of mass media and the migration from small “Mom & Pap” stores to large chains. This shift to managing customer expectation and demand for a large scale audience took the data collection power away from the business owner and created a gap in data collection.

Now in 2011, the internet marketing industry has developed numerous tools and strategies to capture the consumer data we need to analyze to provide the most valuable decisions for our clients. However, due to the large volume of consumers that advertising platforms are trying to reach and business owners are trying to use to benefit their businesses, there are still gaps in our data collection methodologies and practices that we are working to close.

This theme of gaps / challenges in data collection came up frequently across the huddles I attended. Participating in the small group, discussion based huddles it became clear that most of us were facing challenges in data collection (it’s not just me!). While we didn’t solve all the data world’s problems in 3 days, the X-Change conference allowed us to discuss and debate the issues.

Key Challenge Themes:

1. Integration of Qualitative & Quantitative data

In today’s landscape, because no business can succeed solely online or offline, analysts are seeking to tie multiple data source together to better understand the true impact of specific marketing efforts and how they impact the whole picture. It is through access to offline marketing or demographic data or behavioral data from surveys and studies that analysts can start to bring it all together. Seems logical; yes. So why isn’t this done more?

There were several topics of discussion including:
The pieces don’t play well together. Agency A is running offline efforts and Agency B is running online efforts and neither wants to share data with the other, in an effort to keep the business. Different pieces also use different methodologies to collect their data; combining and comparing them is not apples to apples, or do not have a “common key” to tie them together. Or maybe the implementation of the data collection tools had errors and the data we’re seeing doesn’t look right. We all recognize the need to integrate qualitative and quantitative data for the best full picture of what’s working and what’s not with regards to our client’s marketing efforts. Each organization is working to navigate the challenges in ways that best suit their needs.

1. Attribution

Attribution is a process for crediting a lead, purchase, or a conversion to a specific set of marketing efforts. Your monthly report may show you that your email campaign conversions increased 10%, your PPC campaign efforts increased 23% and your display campaign efforts increased 15% but overall sales were still down. This dispute over true attribution leaves us asking: How do you assess which marketing channel deserves the credit? The number and diversity of marketing channels is growing making attribution even harder. Understanding each marketing channel through correct tagging and tracking as well as finding the right attribution model for your company is key. Gary Phillips of Semphonic did a great presentation on attribution models you can view here: http://semphonic.com/resources/2011-tt-pdf/Attribution%20with%20Paul%20Legutko.pdf

1. Communicating Business Value with Data

How do you get the non-analyst minded individual to care about the data? The short answer is…You don’t. Metrics need context; you can’t just show total page views; need to show a story. The stakeholders want to see a success story, not data.

• Know your stakeholders – that will help you decide who needs to get what, who to go to for different needs/ideas, who do they share their data with? How is success of a project determined in their mind? What type of information are they using to make decisions? How can your data support the information they care about?
• For each project set a target and measure success against reaching that target. Keep your reporting simple and focus on the analysis of the data.

The Semphonic X-Change conference was a one of a kind conference. Working side by side with and learning from some fabulous minds at the 2011 X-Change Conference was, for this digital analyst, best describe as therapy. I am looking forward to attending again!

NOTE: WCAI is the preeminent academic research center focusing on the development and application of customer analytic methods. We all listened with envy as she described their process for analysis: get the data sets from companies, and then spend close to a year analyzing in. Many of us are lucky to have 1 week let alone one year! You can view a list of the Wharton School white papers here.

Michele Hinojosa, Director of Digital Analytics, Red Door Interactive 

I had the pleasure of participating in Keystone Solution’s first ever Speaker Series in Austin TX this week, and wanted to share a few takeaways from the day.

The focus of the event was on privacy, or, more specifically, how we can create relevant experiences for users without stalking. It was a great opportunity to hear different viewpoints and consider my own, and I took away a number of valuable takeaways:

1. Education of users is critical, to allow them to make informed decisions about whether the benefits they’re receiving are sufficient for them to consent to tracking. It is important that decisions not be made out of misinformation and fear.

2. But the crux of users’ issues with privacy tends to center around control. Users are made to feel they are being “held ransom” (“We have your data!”) and the uproar that takes place normally follows removing control from users. (For example, Facebook changes that make information (retroactively) public by default, or persistent cookies that override user choice to delete.)

3. Not too long ago, there was fear about buying online. While privacy concerns may never disappear, over time (and with education and control options) people may start to get more comfortable with tracking, just as they did with online shopping.

4. No one had the “magic bullet” for easing user privacy concerns, but there were really two threads emerging – 1) Concern about government regulation, due to the nuance of the issues. If legislators are not educated enough to distinguish between types of tracking, types of data, and the distinction between collection and use, blanket measures are likely to result. 2) Industry self-regulation will require a widespread commitment, as one company, vendor or individual can create a great deal of negative publicity. (And likely then lead to regulation.)

5. Tracking and personalisation get creepy when you’re doing it for the brand’s benefit, not the consumers. The best brands use data to make you feel special. However, too many companies don’t trust that doing things the right way will pay off, and try to take shortcuts or rely on the “magic bullet”.

6. Those collecting data and members of the analytics industry need to act as stewards of the data (and signing the WAA Code of Ethics is a great start!)

7. Most seemed to agree that while the issue has become tracking, the focus should be on data use rather than collection. (You don’t arrest someone for murder because they have a gun and motive… they have to take action.)

8. Similarities to offline were discussed (for example, grocery store loyalty/discount cards, cable box and ISP tracking.) But the question is, are users aware of all of this tracking? The internet is not necessarily causing privacy concerns, but online tracking is simply more public. In a way, online tracking might even be raising awareness of the offline tracking that takes place.

9. There is often an argument of, “If you don’t like tracking, don’t visit the website.” However, is this reasonable? Is it truly consent if you don’t really have a choice? For example, you either submit to TSA procedures or never fly, which may even be required for a person’s job. Similarly, reading Terms and Conditions of software gives you only the choice to not use it – you have no option to negotiate with the company about those terms.

10. There is a gap between user privacy concerns and the amount of social sharing that users are doing. The responses to Facebook changes really show the kind of ownership that people feel over their Facebook experience, and that users forget that ultimately, they’re playing in Zuckerberg’s sandbox, not their own. Users will need to keep in mind that no matter the network, if it’s on the internet, it could be public, and exercise caution in sharing.

11. In the end, users want more control over their privacy, but the appropriate mechanism for that has not been figured out. Users may be willing to share data with some sites and not others, and allow personally identifiable information to some companies and not others. (For example, maybe I trust Zappos but not ShoezWarehouze.) But how do we allow control of these levels of privacy without creating acomplicated, unusable system of permissions?

In the end, no one had the solution, but that’s not really the point. This will be an ever-evolving process, and it’s important we talk through the issues, to ensure we don’t over simplify in our desire to solve for the benefit of all.

September 2, 2011 – Welcome to another RDI Click! post. Click! is a weekly collection of digital news highlights from Red Door’s most inquiring minds.

Click, enjoy and learn.

We’ve done the hard work for you.

Audience Targeting Strategies for LinkedIn Ads  - Search Engine Watch
“The current targeting options within LinkedIn are robust and well-suited to the audience on LinkedIn: they focus on professional affiliations, rather than personal attributes/interests/likes such as Facebook. Unlike Facebook, where you determine the targeting at the ad level, within LinkedIn, your audience targeting is established at the campaign level.”
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Supercookies: What You Need to Know About the Web’s Latest Tracking Device - Mashable
“Recently, online properties like Hulu, MSN and Flixster have been caught using a tougher version of the common cookie. These “supercookies” (aka “Flash cookies” and “zombie cookies”) serve the same purpose as regular cookies by tracking user preferences and browsing histories. Unlike their popular cousins, however, this breed is difficult to detect and subsequently remove. These cookies secretly collect user data beyond the limitations of common industry practice, and thus raise serious privacy concerns.”
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What Google Must Do To Not Make G+ Evil - Social Media Explorer
“If Google chooses to weight its own content greater than that of its now social competitors, it crosses the line and becomes what it set out to avoid becoming: Evil. Prioritizing Google+ activity in search results would, by definition, make Google+ a more important social network than others. This would inevitably drive more activity on Google+.”
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Fashion Brands Have Started to Air Grievances About Fashion-Hungry Tumblr - New York Magazine
“For the second season in a row, Tumblr is sending bloggers to Fashion Week, where, with the help of some partner brands, the young writers and photographers will get to do fun things with designers, like meet them or go to their shows or eat scones at their apartments. Then they can put posts about their frolics on their blogs, making them look like they hit the big time and giving Tumblr an edge in positioning itself as the blogging platform you use if you want to post about fashion. So the bloggers win, Tumblr wins, and the brands — do they win?” 
Read More

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Michele Hinojosa, Director of Digital Analytics, Red Door Interactive

Perhaps you’ve been working in digital measurement for a few years, or maybe you’re new. You keep hearing about Twitter and wondering whether you should jump on the bandwagon. Well, you’ve come to the right place.

Why should I join Twitter?

1. To learn: Step outside the sandbox of your own company, your own analytics solution, and your own challenges. Your eyes will be opened and you’ll start thinking about the bigger picture, and bring your what you learn back to your organisation.
2. To engage with others: It’s a fantastic opportunity to meet and build relationships with others in the industry. You can debate, discuss challenges, throw ideas around and form connections that may benefit you in the future.
3. Get help and help others: The web analytics community on Twitter is an amazingly generous group of people. Take @usujason or @VABeachKevin, who respond to fellow analysts’ Omniture questions on a daily basis. Oh – did I mention neither of them even work for Omniture?! Having a problem with Google Analytics? Throw it out. Others may have tackled this already and can give great advice.

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