SEO & Social Media: What is the Relationship? Finally, we have the Answer!

There are so many ways to answer this question. I've been trying to answer this question for at least a year, in terms of how we position our agency services and capabilities -- and I think I have the answer.

But first, lets discuss why it's so difficult to consistently and concisely define SEO/Social kinship and fit it neatly into a box. There are many reasons -- a few of of them include:

1. Subjective Definitions of Social Media:

While we most folks generally agree on what SEO is, why it's important, how it's generally done, and what the benefit can be -- no two people have the same definition for Social Media. For some, it's about blogs. For others it's about social networks like Facebook, and perfoming community management. Yet for others, it's about having conversations using Twitter. Some look at Social as a means for outreach, public relations, and awareness. And others view it plainly and simply as another visitor acquisition channel. Then there are those that view Social as a means to understand sentiment and tonality related to a brand or product. Is it limited to just digital? Or does it include any kind of social effort and behavior that exists online or offline?

Because there is no generally accepted definition of Social Media, how we understand the relationship between Social and Search is just as fragmented. Likewise the way we execute strategy based on Social/SEO synergy is inconsistent.

2. Lack of Standard Process

Because there is no widely accepted definition for Social Media -- how the medium is applied by marketers varies widely. This is where we can get in trouble. From an agency perspective, this is maddening because I want to hone our method, and define our capabilties and offerings. But the more we try to add structure and process to the execution of social media -- the more risk we face in missing new and innovative ways to harness the potential of social media.

For SEO & Social -- the same challenge exists. Any standardized process to realize synergy between the two may limit potential from that synergy.

3. Rate of Change:

Trying too hard to standardize process is risky because of the rapid onslaught of new tools, technologies, fads, and practices. The rate of change we see requires a reset in our understanding of what Social is -- monthly or even weekly. I won't even try to recite all of the variables that go towards 'change', but just think about how Twitter has impacted how we view social just during the last 6-12 months. Think about the emergence of local-social phenomenons like Foursquare and now Facebook Places. Think about the impact of Mobile and Mobile Apps. Think about all of the ancillary tools, widgets, and nic-nacs that strike social resonance and inspire sharing.

For SEO specifically, consider the impact of unviversal search. A SERP is no long just a SERP. Both real-time and seasoned social content continues to be more and more prominent -- both in its display within search results as well as its contributing impact on site authority and rank potential.

3. Organizational Boundaries:

However you define Social, there is considerable overlap between SEO & Social. But all too often, those that are responsible for SEO aren't always the ones assigned to manage Social Media efforts. Naturally, whatever potential synergies may exist between both disciplines aren't realized as well as they could be if managed by separate teams or resources.

So with so much ambiquity and fragmentation, how do we make sense of the connection between SEO and Social? Well, I'm glad you asked, because I have the answer. But before I tell you, you need to pay me. For such an invaluable answer, why would we give it away for free?

Don't worry, all you have to do is Pay with a Tweet (one of my favorite little social nic-nacs). Here's the deal: we want more traffic for ZAAZ Blogs. And there's a couple of ways we can get it: through increased SEO visibility, and through viral Social Media distribution of our blog.

So here's how this works: my ground-breaking answer and the remainder of this riveting blog post can be accessed after you tweet a nice little tweet. Your tweet tells your followers all about this clever blog post written by yours truly, and how it changed your life. Your tweet inspires further sharing of my post and blog to others, and their interest in accessing my 'answer' incents further tweeting and social sharing.

But it doesn't stop there! Many of those that take interest in my post and our blog will lead to a viral cascade of links (blogs/sites/tweets/etc.) Google then sees these links and adds authority to our blog, increasing our search engine rank potential.

Believe me people -- the answer is worth it. Seriously. But even if you don't care about the answer, do me a solid, and just tweet this damn blog post, okay? Just click the link below. (Oh, and follow me too!)

  

    

#shamelessselfpromoter

SXSW Interactive

ZAAZ has three submissions in the SXSW PanelPicker. We guarantee education, entertainment and surprises. Voting ends August 27th! Look at our ideas, ask us questions, vote for us, and let's take 6th street by storm!

Rich Devine "Mobilizing Performance From Search"
By 2012, 20 percent of all search queries will come from a mobile device. While there is growing focus on creating mobile site experiences and applications, not enough businesses focus on their mobile search experience. Just because you’ve optimized search for the desktop doesn’t mean it works on a mobile device. Mobile search is different than desktop search—and for many businesses, it’s a critical step toward customer success. Our discussion focuses on three core actions: how to identify unique business opportunities for mobile search, how to optimize for mobile search, and how to measure the performance and value of mobile search.

Anders Rosenquist and Katlen Tillman "How Mocial Apps Help Dorothy Kill the Witch"
What if Dorothy had had access to social, mobile, and location-based services on her journey to Oz? How would that have changed her experience getting back to Kansas? This panel will explore that very question with the aid of an innovative case study from Alaska Airlines. Location-based services can build customer loyalty, provide value and support a brand. We’ll discuss how the marriage of mobile with social can integrate real world places through mapping and destination content. Connecting conversations based on location, these "mocial" apps can help people like Dorothy understand where to go and what to do during the journey while avoiding the witch, or the perils of air travel.

Jason Carmel "Privacy vs. Relevance: Who Smells the Tension?"
Generic, digital experiences suck for both users and businesses alike. People expect to be treated as individuals with unique perspectives and needs. When executed appropriately, everyone benefits from more targeted content. But when does personalization go too far? With digital technology collecting data at an unparalleled rate, there is a risk of this information being breached, mishandled or assumed incorrectly. This session delves into the cost and benefits of using digital and offline data to create a more personalized experience, and investigates the best ways to build these data-driven experiences without trampling over the privacy rights of the public.

The WSJ's Datapocalypse 2010

The Wall Street Journal has an amazing interactive piece entitled "What They Know" that focuses on the data that is collected and used for tracking and reporting by 50 of the most visited sites on the Web. Play around with it for a while- you get a sense of the massive amounts of data that popular sites such as ebay and CNN.com collect about you behind the scenes and how that data might impact your privacy online.

Unfortunately, the good people at the WSJ couldn't leave it alone with a powerful display of information. Instead of representing an informed understanding of what data companies are tracking, the risks and benefits of collecting and using that data to the end consumer, and an assessment of efforts that are or should be made to improve the system, they got all "DATAPOCALYPSE 2010" on us. Let's unpack a few issues I had from this little suitcase of drama, shall we?

Issue #1: Marketers are spying on Internet users"

This is how the author starts off the article (note the bold was their emphasis, not mine), and it's an exaggeration of the grossest order. "Spying" is not a term one should thrown around lightly. In fact, unless it is literally applied to the act of assassinating someone with an umbrella tip or swallowing something on microfilm, the only people who use the verb "spying" in this context are those who are trying to create controversy. Are marketers "spying" on you as you navigate the web? Of course not. Collecting anonymous data to inform how successfully an audience is consuming certain content is a far cry from sending someone with an accent to open up your home safe and take pictures of your offshore bank account numbers with a very, very tiny camera. Using the term "spying" when you mean "sharing aggregated web data" is from page 12 of the Fox News Handbook of Journalism, and the WSJ needs to be better than that.

Issue #2:  I'm not even going to justify the graphic of the dude with the binoculars with a comment.

"Watchers?" Honestly. The WSJ makes Web Analysts and Data Miners sound as if they are video taping you in the shower.

Issue #3: Exposure Index?

The Exposure Index is the grade that the WSJ folks give to each site to inform the reader of how worried she should be about her data being traded around like prison cigarettes. The WSJ explains its methodology obliquely at best. Volume of trackers and opt-out options are interesting circumstantial factors, but they pale in comparison to an analysis of 1) what information is being shared 2) with whom 3) for what purpose, which this index appears to lack:

• More tracking isn't necessarily more sensitive tracking - The fact that a site collects 200 pieces of information doesn't make that information particularly relevant or sensitive, in aggregate. There is a false assumption permeating the data as it's presented that each data tracker leads to information of equal value. Think about how patently untrue this is. Information concerning which articles I read on espn.com and how ESPN would share that information in an aggregate way, even to 100 third party advertisers is in the grand scheme of evil out there in the world fairly low on the totem pole. Compare that to the very sensitive financial data that is collected and used by PayPal, which gets a better score on the exposure rank, in part because it has significantly fewer trackers.
• Define your terms - I think the infographics would be a lot more telling, and consequently a lot less sensationalist, if they included a key explaining what these 3rd party sites are that get your data and what they are doing with it. When a site shares information with Microsoft, for example, it likely has to do with the Bing! search terms used to get to the site. The trackers are not sniffing your machine to see if that copy of Outlook 2010 is registered. Similarly, "Coremetrics," will sound a lot less ominous if you know that it is a standard web tracking tool that monitors anonymous visitor behavior on site, rather than a collective of Nigerians trying to steal your daughter's college tuition.

I don't want to be misinterpreted here as saying that we shouldn't be concerned about what data is being collected about us on the Web and how it is being used. Privacy policies are impossible to understand, a lot of unnecessarily sensitive data is being collected and stored indefinitely for no discernible advantage to the end user, and, let's be frank here, businesses can't always be trusted to act in good faith when an opportunity to make a killing arises, and the only thing standing in its way are the sanctity of a few words on a web page that no one really reads anyway. I work in the industry and know full well that it needs to change. I applaud the WSJ for releasing its findings and recognizing Internet privacy as an important issue.

My concern here is that the language used by the WSJ inspires panic (check out the results of their poll) rather than conversation, and panic invariably results in knee-jerk reactions and ineffective legislation- both of which are on the way.

Facebook Open Graph Coming to a Phone Near You

Facebook is pushing the mocial envelope these days. At the MobileBeat 2010 conference in SF earlier this week, Facebook announced that it will be extending its Open Graph platform to mobile, moving away from an individual mobile app strategy and moving into a let's-allow-facebook-to-be-connected-into-everything strategy.

What does this mean?  App makers will now be able to connect into the Facebook platform and incorporate data into their own apps, leveraging information such as friend recommendations.  It's easy to imagine a scenarios that combine information from your friends with location-based services - say Foursquare but with your whole Facebook community and history.

For marketers this means greater opportunities to serve offers at the right time and place, but with the added benefit of having the backing of your friends. A hotel chain's app that leverages a user's Facebook community could connect friend-recommended POI's and restaurants with discounts to stay in at a nearby hotel property.  Or a retailer could show you your friend's reviews of the product you are looking at while on the showroom floor.  Pretty cool.

Facebook also stated that they have 150 million mobile users of Facebook and are growing.  A nice plus that they just implemented too is the ability to sign up for a new Facebook account completely on your mobile device.  Good call, and good move toward further breaking mobile's tether to the desktop.

More info check out:  http://social.venturebeat.com/2010/07/13/facebook-mobile-platform/

The News Could Be You: Managing Your Brand Reputation Online

Online reputation management has become an increasingly hot topic as mass adoption of social media progresses. There are no shortages of issues or drama that overtakes blog posts, trending topics and social commentary, the new reality is that no brand – whether consumer or personal – is exempt. I know I am stating the obvious here, but it’s for this reason that engaging in social media is tenuous for companies and individuals, since there is always a potential for risk; however, whether or not you choose to participate, if something is going to happen it will whether you’re ready or not.

Looking at the new ‘news’ consumer which uses multiple platforms to access the news, with approximately 72% of U.S. news consumers indicating they do so “because they enjoy talking with others about what is happening in the world” (source: Pew, www.pewinternet.org/Reports/2010/Online-News.aspx) suggests that people do so to follow the dramatic narrative that may directly or indirectly touch their lives – and reality can be stranger than fiction.

News isn't just produced in the newsroom anymore.
With the onset of citizen journalism, seemingly innocuous encounters between people in public have the ability to become a 'news' story that is disseminated and shared at a local and global level. The power to elevate an issue is now in the hands of anyone who has something to say. There is happenstance and momentum that can quickly build - catching fire through social channels when fueled properly.

Categories of developing 'news' that have recently inspired conversation waves across the social Web have included:

• Consumer watch groups and commentary on corporate business practices -- such as Nestle and the case with Greenpeace
• Business decisions that can impact consumers -- such as Apple vs. Adobe and the exchanges that ensued once Apple announced that Flash would not be supported on their iPhone and iPad products
• Businesses making decisions or causing situations that impacts society or stakeholders -- such as BP and their focus on traditional media to communicate and then engaging in social media a day late 
• Perception, perspective, or situation related to an individual that spirals out and causes a gossip cycle -- such as Tiger Woods and his long period of silence while social commentary was running amuck on blogs, the Twitterverse, and across Facebook and other social networks.

It can happen to you.
Looking at these scenarios it’s very easy to fall into that place of thinking that ‘it can’t happen to me.’ But you never know when you might find yourself in a situation where a person might misconstrue an interaction and choose to take it online. Brand or personal brand, everyone is at risk at some level.

When managing a company or a personal brand do differences exist?
No way. Both are equally as important in terms of how the crisis is handled, and the same guiding principles are applicable since the damage to reputation can be just as detrimental. A Pew study found that 44% of adults online have searched for information on people who they seek services or consult with professionally. (source Pew: http://www.pewinternet.org/Reports/2010/Reputation-Management.aspx?r=1) Brand, personal or not, managing your reputation online matters.

Here are 6 basic steps for reputation management during a crisis:

1. Listen - Whether you implement a full strength monitoring tool or use something as simple as a Google alert, knowing that something has happened is the first step in moving towards a resolution and not missing a critical development that can be more damaging if left unaddressed.
2. Act quickly yet deliberately - The goal is to address the situation with the right reaction, making decisions from a place of emotion rather than logic in these instances can prove destructive to your brand.  How you’ll act or respond naturally will depend on the situation and the impact, but being deliberate instead of rash is the key, and responding quickly shows responsiveness.
3. Assess whether it’s true or false – If it’s true, face it head on in a professional manner and work to find a resolution, demonstrating that you are listening and acknowledging the situation. Many times taking it offline is helpful. If it’s false, contact the individual through Twitter, their blog or e-mail and in a friendly manner request that the information is corrected. But the main thing here is to be   professional and take the high road, remember that your customers/potential customers are watching.
4. Engage responsibly and with integrity – These are especially important values when engaging online since the repercussions for not being truthful or inappropriate can be long-lasting.
5. Counter pages with pages in search – The more content you put out there, the better you can balance the pages that are in search results. You are definitely in control of the content you create whether it’s on your site, your Twitter or Facebook pages or in forum or board posts.
6. Wash, rinse and repeat, if needed – Some brands are more targeted for attacks than others, and this might be an ongoing process.

Today’s digital world has made aspects of marketing and professional communication more complex than ever. But by starting with monitoring your brand – corporate or personal – it’s that first step towards decreasing risk of not being ready for when a crisis arises.

Machine? Tell me what to do

Recently I went to get a sandwich and had an experience which my friend and colleague Kat Tillman said- “hey that would be a great blog post.” So, alas this social media strategist is finally walking the walk and posting to the ZAAZ blog. Ok, so here’s the deal – I ordered my sandwich on a super handy kiosk and even paid with the handy-dandy swiper dealy.  Then, decided after a couple minutes of standing in the way of everyone for my completely automated order that I wanted an iced coffee. So I walked over to the adjacent coffee bar (inside the sandwich shop). Did I mention that they give you a vibrating sandwich notifier thingee? Anyway, I waited at the coffee stand for nearly 10 minutes (not exaggerating). Then, Kat (on my behalf) asked one of the 20 plus staff if there was a coffee person around? Their answer back was “did you place the order on the computer?” Hummmmm. No! Why would I think you could order both sandwiches and coffee on their friendly kiosk?  Then it dawned on me ­– technology doesn’t take the place of good customer service. Of the 20 people making sandwiches and managing screens, no one noticed I was waiting to order the old fashioned way. It’s an issue when we spend all our time looking at screens waiting for them to tell us what to do next.  As a gadget girl and social media DB I am here to say – “look up and take notice. There are people (and potential customers) all around you. Are you really engaging with them anymore or are you expecting your technology to take up the slack? Your brand should be enhanced and extended by technology not ruined by it.” I believe no amount of technology, automation or social media can replace good customer service.

Social Media Bill of Rights - Do You feel Covered?

At last week's 20th annual Computers, Freedom & Privacy (CFP) summit in San Jose, participants and practitioners debated and proposed a Social Network Users' Bill of Rights, designed to represent the denizens of the social ecosystem out there (in here?). Facebook, Google Whatever, Twitter, this is mostly about you guys. You can tell that these principles weren't written by politicians or (exclusively) lawyers, since they are clear, intelligible, and brief enough to be included in their entirety below:

We the users expect social-network sites to provide us the following rights in their Terms of Service, Privacy Policies and implementations of their system:

1. Honesty: Honor your privacy policy and terms of service.
2. Clarity: Make sure that policies, terms of service and settings are easy to find and understand.
3. Freedom of speech: Do not delete or modify my data without a clear policy and justification.
4. Empowerment: Support assistive technologies and universal accessibility.
5. Self-protection: Support privacy-enhancing technologies.
6. Data minimization: Minimize the information I am required to provide and share with others.
7. Control: Let me control my data and don"t facilitate sharing it unless I agree first.
8. Predictability: Obtain my prior consent before significantly changing who can see my data.
9. Data portability: Make it easy for me to obtain a copy of my data.
10. Protection: Treat my data as securely as your own confidential data unless I choose to share it, and notify me if it is compromised.
11. Right to know: Show me how you are using my data and allow me to see who and what has access to it.
12. Right to self-define: Let me create more than one identity and use pseudonyms. Do not link them without my permission.
13. Right to appeal: Allow me to appeal punitive actions.
14. Right to withdraw: Allow me to delete my account and remove my data

Many of these are spot on and so obviously RIGHT, that it makes me a little sad we have to actually tell these business that we expect them. Specifically, Honesty, Freedom of Speech, Predictability, Empowerment, and Protection are complete no-brainers. Clarity is another pet peeve of mine that is well placed on this list- putting your privacy policy in 8 point font and using language indigenous to the British House of Lords circa 1740 is a cheap-ass way of protecting yourself for any skeezy behavior you do after the fact. Any company that fails repeatedly on the above doesn't deserve our attention, let alone our engagement or dollars.

Some principles, thought, are admittedly less clear to me. Data Minimization is an example here, where the intent seems to be something like "Listen, stop asking me for my birth date for a service that doesn't require that data." I get that, and support it. But the flip side is that everyone has a different understanding of what is "necessary," which I kind of also get (does Facebook need your birthday to work? No, but I would guess a lot of people like getting wall posts on their birthdays with well wishes). My take on Data Minimization is that so long as the other principles are adhered to, businesses should feel free to ask anything they want: if their registration form is bloated with irrelevant, overly personal questions, then registrations will suffer as a result. The market will reward the most optimal form with the least friction between click-to-form and registration.

Some principles may actually contradict each other, as well. I look at the Right to self-define as particularly tricky here. If a customer chooses to have 16 unlinked accounts, it arguably puts a significant burden on the business to insure that portability is manageable. If all those accounts are anonymous, does it render the Right to appeal meaningless? (why do I need to appeal a punitive ruling if I can just open up another 16 anonymous accounts)

Still, any critiques of the Bill of Rights are minor, and should be viewed in proper perspective. This is an effective (though certainly not the first) barometer of customer expectations in a digital world where data is aggregated 24/7.

What happens next is always the really interesting question. Will these (or other) principles be legislated? Or will businesses understand which way the wind blows and self-regulate?

What your website says about your brick and mortar sales

 

What can your website activity tell you about your brick and mortar sales?  Ever wondered when your website metrics go up, if it means you’ll actually sell more products offline?  

While ecommerce activity continues to grow in all categories, for many companies the majority of online shopping activity still results in a purchase being made through an offline (brick and mortar) retailer.  As part of our Monetization Modeling practice we analyze this relationship so that we can better understand the role of online actions in the purchase process, and how to optimize the site experience to drive conversion. 

Following is an example of this research, what we learned, and the actions taken as a result.  The products in the example below are high consideration consumer product traditionally sold through a network of retailers (for confidentiality, we’ve anonymized the data).

Methodology and data:

Our research methodologies were correlation analysis and linear regression.  In order for these techniques to be meaningful we needed at least 30 months of both website activity and offline retail sales. For both datasets, we had ‘rolled up’ data (e.g. total site visits, total retail sales) and also product level data (e.g. product ‘A’ web visits, product ‘A’ retail sales). 

HIGH LEVEL SALES ANALYSIS:

With the datasets assembled our first step was analyzing high level relationships.  We ran a series of correlations between online KPIs and offline sales. We started by analyzing site visits, as this represents one of the highest level indicators of consumer interest.  Visits to the website show a fair, but not excellent correlation with offline sales:

Correlation between Website Visits and Offline Sales:  .70

The story becomes more interesting when we begin to look at visits to specific research tools on the site.  In this next graph we are looking at total visits to a group of 5 ‘upper funnel’ product information pages on the site.  These pages contain basic information about the products that a first or second time visitor might rely on to better understand the features of the product.  In this case we see the correlation with offline sales has improved over basic site visits.

Correlation between Upper funnel actions and Offline Sales:  .80

Lastly, we looked at the correlation between a group of 5 ‘lower funnel’ pages and offline sales.  The ‘lower funnel’ pages are actions a website visitor would typically engage in once they are close to the purchase decision, this actions include; finding a retailer, financing options, online inventory search, and requests to be contacted by a sales consultant. The correlation between these actions and offline sales proved to be very strong.

Correlation between Lower funnel actions and Offline Sales:  .90

 

 

High level conclusions and findings:

This analysis immediately yielded insights into shopping behavior.  Clearly, ‘lower funnel’ actions on the web site are a very important part of the purchase process. Their correlation of .90 with offline sales is proof of a very strong relationship between these actions and the purchase decision. 

Another important insight gained from this analysis is the lead time between online research and offline sales.  Prior to this analysis, the client believed users engaged in detailed online research 45 – 60 days prior to product purchase.  In our analysis all three web metrics (visit, upper funnel visits, and lower funnel visits) all show their strongest correlation with same month offline sales. This clearly demonstrated that online research takes place within 30 days of purchase, much closer than previously believed.

PRODUCT SPECIFIC ANALYSIS:

Our next step was to drill down into the data and analyze more specific relationships.  We started by looking the relationship between website actions and offline sales for specific products.  The company had 4 distinct product families.  Within each product family there were 2 to 4 unique products (or SKUs).  We knew from the analysis above that ‘lower funnel’ visits had the best correlations with offline sales, we began by rerunning the same analysis at a product level.  Once again we observed very distinct relationships.

The following table shows the results of product level analysis.  In this case we ran correlation of product specific sales against product specific web activity.  Here we see a distinct difference in correlations between Product Category A, and Product Category B.  Category A shows very strong correlations with offline sales, indicating that online research is particularly important and highly related to the purchase event for these products.  Category B shows the opposite effect, these products show very little relationship between web visits and offline sales.  Indicating these customers are not highly engaged in the web for researching their purchase.

Product Category	Product	Correlation with offline sales
Category A	Product 1	0.79
	Product 2	0.91
	Product 4	0.84
Category B	Product 1	0.40
	Product 2	-0.10
	Product 3	0.52

More specifically, this information can be used to target visitors who have completed specific research activities in Product Category A with timely offers to incent offline purchase.  Since we know these visitors are in market and likely to purchase in the next 30 days, this is a key opportunity to convert sales.

To further illustrate the strength of the correlation between online research and offline sales, we analyzed a single product through a promotional period.  In the chart below, you can clearly see the spike in both online research activity and offline sales during this period.  Knowing the strength of the relationship and the temporal proximity of online research to offline purchase is instrumental in developing timely targeting strategies.

Product specific correlation between Lower funnel actions and Offline Sales:  .91

REGRESSION ANALYSIS:

Our final analysis was to determine which specific online actions were the best predictors of offline sales.  It is important to note, our objective was not to predict product sales on an ongoing basis, but rather understand what actions were the best predictors of actual sales.  Understanding the predictors of offline sales gives us a key insight into the importance and influence of specific online actions.

We built a series of multiple regression models to determine what group of online actions could best forecast actual sales. This was a highly iterative process where we analyzed multiple groups of different KPIs and assessed their R-squared values.  The R-squared metric tells us how well a group of online actions explains the variability of offline sales.  The higher the R-squared, the better that group of online actions are at predicting sales. 

After a series of regression models, we narrowed in on a group of online actions that predicted offline sales with an R-squared of .71 (in this particular application, a very good fit).  Back-testing this model showed a very strong ability to forecast sales based on web site actions.

With the regression model in place and back tested, we had identified a group of 6 online research actions that predict offline sales with a high degree of accuracy.  The completion of these actions signal that a highly qualified visitor is on the site, and should be targeted with specific messaging.  Additionally, since we now had quantitative insight into the most important site actions, modifications to site architecture, on site advertising, and even offsite display advertising, were made to promote these key activities.

ONGOING ANALYSIS

The findings shown above provided the first quantitative insight into the relationship between online actions and offline sales.  These findings provided the rational for changes to content strategy (both onsite and bought media), promotional offerings, and targeting strategies.  The findings also helped to change commonly held notions about how and when consumers interacted with the digital channel. To ensure this was not a “one and done” analysis, we built the capability for easily updated, ongoing correlation analysis into our standard monthly performance reporting.  As the site evolves we can now monitor the correlations between online actions and offline sales, providing us with a new and powerful way to continually optimize the digital channel.

Google Encrypted Search: Curious George or War Games?

If you are a search marketer, and you haven’t been locked in your basement playing Dungeons & Dragons while your ranking reports run, you’ve probably heard -- and either shrugged or freaked out – about Google’s announced launch of 'encrypted search'.

In a nut-shell, this secure version (https) of Google is supposed to allow users to freely search without fear of their search behavior being ‘observed’. Google’s own Search-Spam-Czar (not an official Obama administration post), Matt Cutts, issued a congratulatory blog post extolling the ‘inspiration’ of encrypted search. Cutts cites an example of working from your laptop on public Wi-Fi at the coffee shop – he celebrates the option of using Google’s encrypted search so that the coffee shop can’t oversee what you are searching.

Seriously? Unless you are Jason Bourne or Jack Bauer, do you really think the pimpled-teenager serving your venti mocha caffe latte con panna gives a decaf about your searches for the latest Chuck Norris jokes?

 

Is this a big deal?

Let’s talk about what this means for search and digital marketers. All respect to Matt Cutts (who is deservedly loved and revered -- especially by ZAAZ’s own Ryan Jones, our resident Matt Cutts serial tweet-stalker), but this is not about coffee shop Googling. Matt's blog didn't include an example of the poor search marketing manager trying to optimize her site only to find that Google’s encrypted search won’t pass the search referral data that is so central to her efforts.

And that’s the crux of the issue for us as search marketers: whether we will or won’t get that lovely referral data. For a rather fatalistic treatment on referral data implications, check out this blog by the equally revered Danny Sullivan.

Clearly, there’s a wide range of opinion and speculation over what this may or may not mean. Where do you fall? Let’s go back to business school and break out the trusty-rusty 2x2 box matrix to plot the wide range of sentiment on the topic. If you’re a search marketer, you should fall into one of the following quadrants. We’ll call this the Google Encrypted Search Freak-Out Matrix (GESFOM):

How freaked out we should or shouldn’t be is based on two big unknowns as reflected by the variables in our GESFOM (rolls off the tongue doesn't it?). First, how widely will Google scale its encrypted version of search? Will it truly remain as an opt-in only feature for the paranoid and cautious who are adept enough to add an ‘s’ to http://google.com? Or will Google scale this much more widely, either offering opt-out or no ‘opt’ at all?

Second variable is the impact to your search marketing efforts. How will you perform keyword research? How will you analyze the impact of referred keyword searches to your site? How will you attribute success to your search marketing efforts?

For now, I’m somewhere in the lower right quadrant of the Matrix. I’m Curious George. This is interesting enough for me to take notice and wonder about the monkey-mischief that could result – but as of now, this simply isn’t scaled widely enough to affect referral data to the point where I can’t take effective optimization action as a search marketer.

However, what happens if Google does widen the scale of encrypted search? What if they go bananas and just make this the default search experience? Well friends, then my GESFOM status goes to DEFCON-5 status, I go Matthew Broderick-crazy, and I start playing tic-tac-toe with a chimpanzee named Virgil.

 

Why is Google doing this?

On its face, this really is all about privacy for Google. But as we discussed above, this is not about protecting your Chuck Norris searches from the Starbucks dude. This is about Google more than it is about you. Google is proactively (or reactively) addressing potential legal and regulative vulnerability and ultimately trying to protect its own business interests and maintain shareholder value. Nothing wrong with that -- its what businesses do.

Ironically Google, for all the  not-so-veiled enmity they’ve had for Microsoft – is Microsoft in 2010. They are a dominant force in a relatively un-trodden and un-regulated industry. And dominant businesses are prime targets for stone throwing governments and lawyers.

This may be as simple as Google being mindful of the prolonged mess that Microsoft was mired in with the Department of Justice, the even more ridiculous battle Microsoft fought with the European Union, and the recent trouble Facebook has ‘Faced’ with privacy. Google has enjoyed a long run with relatively minimal trouble on the regulatory or legal side -- considering how dominant they really are. Providing encrypted search, could be nothing more than a bases-covering business decision.

 

Moving forward

As noted, there are just too many unknowns that need to become knowns before we can determine where we’ll end up with this, or how truly impactful this will be to long-term search marketing efforts, especially as related to referral data. Hopefully Google will be mindful of our small, humble community of search marketers who rely on sources of referral traffic data to do our job -- data which we use in ways that do not infringe upon individual privacy.

Google may limit the scale of encrypted search, or pass data in a more formal way to marketers and analytics vendors. Too soon to tell just yet – but let’s have some faith that Google avoids anything that would drive us into GESFOM/DEFCON/Matthew Broderick/Chimpanzee insanity.

Searching for 10,000 Missing Kittens

Recently, the conversation of matching paid search clicks (from Google or Dart) to paid search site side reporting (Omniture or WebTrends) came back on the radar. I have had this same conversation many times in the past and have given many good reasons, but the truth of the matter is that the two sets of numbers will never match and we as a collective group should stop trying to get them to match. The two systems are both correct, it is not so much that there is a data ‘discrepancy’ - which implies error, as it is data ‘difference’ – meaning that there are different purposes for the two data sets. There are also implications with how the data is passed and measured (which we discuss below).
   
Data from paid search providers is concerned with reporting on individual actions (clicks), because it goes to how investments are made on individual keywords. Web analytics is generally concerned with data corresponding to individuals – which is why referral sources are often reported in terms of 'visits' or ‘visitors’ – and so if there is multiple search queries occurring from one ‘visitor’ web analytics will generally only report that single visitor as the referral.
   
Take for example that you have bought the keyword, "Kittens" (don't ask why I chose this word, I couldn't come up with something more appropriate). Google is reporting that you have 30,000 paid clicks on the keyword "Kittens," yet your site side reporting shows that you only have 20,000 paid click-throughs on "Kittens." Where are the other 10,000 clicks going?
   
I know that is hard to believe that both systems are correct when your clicks are 30% or even 40% higher than the click-throughs that are captured site side, but it is true. Think about it this way, the click is the intent to view content on your site and the click-through is the actual action of seeing content on your site. A lot can happen between the click of a content targeting link or keyword and browsing through site content.
     
Think about the fundamental differences in log file based tracking and javascript/tag based tracking. When the transition to javascript/tag tracking started we had several clients that wanted to compare the numbers from both sets of data. More often than not, we saw that the javascript/tag based tracking was between 20% and 50% lower than the log file based tracking. This shouldn't be surprising as tag based tracking was a much more accurate count of what visitors were doing on your site. The point of this statement is that there is a fundamental difference in the amount of content that servers serve up and the amount of content that is consumed by true consumers or visitors. Take the same approach with media reporting, there is a difference in the amount of content that is served up and reported as "clicked" versus the number of "click-throughs" that reach your site.
   
Some items that are noteworthy and difficult to change, but give some explanation of where those 10,000 clicks are:

• In addition to focusing on clicks vs. visitors, paid search assumes ‘match’ caveats for it’s keyword referral data. In other words "Kittens" may be the bidded term, but if matching parameters are tied to that term (broad, phrase) the data corresponding to that term would include dozens or hundreds of specific queries that included the word “Kittens”. Whereas site side analytics report on the actual keywords typed by the user, say "pink kittens," "stuffed kittens", etc.
• If paid search is using ‘content networks’ that click data will be reported as paid-search clicks, whereas web analytics tools will report those as site referrals like http://www.pinkkittendanceschool.com/blog/ (again, I apologize for the direction this example has taken)
• Some of the clicks on banners and paid search bounce from the site (or never reach the site) before the site side analytics tag fires. This happens more than you would think since the click is tracked on the search side before the redirect takes place.
• Every so often the tracking tags are dropped by the search engines.
• Filters on site side metrics can exclude clicks. Examples of this may be exclusion of internal traffic, spiders, etc.
• First Party Cookies and Third Party Cookies are handled differently by browsers.

     
With all of that being said, there are still ways to ensure that the numbers being reported are as close as possible.

• Ensure tags are placed on all of your paid search activities and all pages on your site.
• Ensure that the reporting attribution windows are the same in both tools.

   
Once you have taken the steps to ensure the data is as accurate as possible, do an audit to gain a baseline understanding of what the discrepancy is for your company. Understand, acknowledge and educate the consumers of the paid search data on why the data sets have a discrepancy and agree within your organization which source of truth you are going to use. Since most organizations are looking at behavioral data through tools like Omniture or WebTrends, it often makes sense to use these tools are the primary source of data to understand what people do once they land on the site.