Your SEM Bid Management Solution: it’s a ‘Turk’

By Rich Devine | May 31, 2011 4:41:58 PM

 

Image via Wikipedia

In 1770, Johann Wolfgang Ritter von Kempelen invented an automaton chess-playing machine affectionately known in modern times as "The Turk". For more than 80 years the 'machine' toured Europe and the Americas, defeating most of its opponents -- including Napoleon and Benjamin Franklin.

In 1820, Surprise! As if anyone didn't know, the chess-playing Turk was exposed as a hoax, a parlor trick, powered by humans stuffed inside the machine -- not automated by the machine itself.

Bid Management software is a 'Turk'. It's not that Bid Management isn't necessary, or helpful, or effective -- but if an agency is trying to sell you based on how awesome their 'proprietary' bid management software is, or how they've cracked some special code and have super-top-secret algorithms that make their bid management software smarter than Ken Jennings, take a pass.

Bid Management is a Turk, only as effective as the human being who is inside the box pulling the levers.

Don't misunderstand me. I am a big believer in bid management software. I recommend it for most of our clients, and there are some really, really good solutions in the marketplace -- some of them almost as smart as Ken Jennings.

Bid management is attractive for two reasons:

First it has the capability of processing information really fast, smartly predicting bids, and executing real-time optimization decisions that can result in added efficacy for your SEM campaigns.

Second, it offers tremendous efficiency. Multiple publishers can be managed from one single platform. Thousands of keywords, budgets, and bid decisions can be automated based on configured rules and parameters.

Clients get excited by the prospect of added value to their business and increased ROI from their ad dollar. Ad agencies get excited because they can provide services at some fraction of the human resourcing cost that SEM would otherwise demand.

The problem is that bid management is really just a Turk. In order for Wolfgang's chess robot to beat most of it's opponents like a robot should, he had to find world class chess players to sit inside the machine. So it is with bid-management software: while useful and even superior to humans for many automated functions, unless it's powered by a skilled human operator -- it just doesn't work very well.

Sometimes (actually lots of times) agencies get a little over-enthused by the prospect of profit margin and they skimp on the quality of human resourcing necessary to make it work. They buy into the myth of the Turk.

So when you're ready to hire an agency here are some things to look for:

1. They should have a bid-management solution. If they don't, I'd move on. At ZAAZ, I've had my team build familiarity with multiple tools -- some of which are better solutions for some clients than others. I really believe that there's an 80/20 rule here: without bid management you spend 80% of your time doing admin functions for paid search, and only 20% of your time doing strategy. With bid management, it can be the reverse. But the operative word is 'can'.

2. They should talk about their people. They should spend more time talking about the value and intelligence of their people than the magical value of the machine. If it's all about automation, algorithms, and predictive intelligence -- I'd take a pass. I can't tell you how often I'm in a new pitch, and the incumbent agency has deployed a great bid management solution; but they've thrown in a low-cost intern or a project manager with no time to spare and no real search experience. It just doesn't matter how awesome that machine is, without a good human to operate it, the venture always turns into a big mess.

I have a basic rule that surprisingly isn't always obeyed by others: I don't hire people to play chess unless they know how to play chess. Yes it costs me more to hire good people, but I have significantly lower churn on my clients, and my clients are happy.

3. Pricing should be transparent. If you can't tell what you're paying for between human contribution and software contribution -- take a pass. Bid Management software is usually priced at a percent-of-spend fee. At ZAAZ I've elected to take whatever volume discount we earn as an agency from bid management partners and I pass-through the discounted fee directly to my clients. Then I'm extremely transparent about what kind and how much human effort is required to make that Turk work.

 

this blog post originally appeared at RichDevine.me

 

Your SEO Guy: Expert or Business Partner?

By Rich Devine | May 26, 2011 5:14:32 PM

My team had a call with a prospective client the other day. I sat in and listened as the client made some frank observations about ‘SEO people’. In essence, she said her company’s progress with SEO always seems to miss the mark because consultants can never get past their own knowledge. They spend too much time bragging about their elite technical competency or secret strategies; and too little time understanding her business.

I’m not always the smartest dude, but I steered the remainder of our conversation toward questions and ideas about her business.

Her point is valid. Without question there is a tremendous amount of nuance, technical implication, and know-how required to do SEO right — it’s not a discipline for fakers, you’ve got to know your stuff. But is that really what sells SEO? It shouldn’t be.

SEO should be about about the promise of performance. I’m not talking about rankings or traffic — I don’t care about rankings, and I don’t care about traffic. You heard me. What I do care about is performance.

Too often SEO professionals equate rankings and traffic with performance. That’s a mistake. Certainly rank success and traffic contribute to performance, but rankings don’t make me money. Traffic…believe it or not…isn’t a recognized currency that can buy lunch.

SEO professionals can be really smart within their discipline, but it’s rarer to find SEO folks that also have strong business perspective. It’s the difference between the Expert and the Business Partner.

So what are you getting from your SEO person — an expert or a business partner? Hopefully both. Here’s some basic questions to help you determine what kind of SEO you’re talking to:

1. Does he spend lots of time talking SEO jargon — algorithms, robot.txt files, canonical redirects, etc., etc? EXPERT

2. Does she ask questions about your business and products? BUSINESS PARTNER

3. When you talk about success measurement, does he talk in terms of rankings and traffic? EXPERT

4. When you talk about success measurement, does she talk in terms of behaviors and goals tied to specifically to your business? BUSINESS PARTNER

5. Do you understand what he’s actually doing, and why it’s important for your business? No: EXPERT. Yes: BUSINESS PARTNER

7. Does she speak transparently about the process, and try to match unique strategies to very specific business objectives? BUSINESS PARTNER

8. Does he try to steer you away from other marketing efforts like paid media, creative & UX, or traditional advertising — in favor of just focusing on SEO? EXPERT

9. Does she want to coordinate SEO efforts with other marketing channels and stakeholders, including creative, paid search, display media, web analytics, traditional advertising? BUSINESS PARTNER

You get the idea.

Now don’t get me wrong. There is nothing wrong with being an expert. But if you’re hiring an expert for SEO, be aware that strong business perspective isn’t always included.

 

this blog post originally appeared at RichDevine.me

SEO & Social Media: What is the Relationship?

By Rich Devine | Aug 30, 2010 2:59:13 AM

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

Google Encrypted Search: Curious George or War Games?

By Rich Devine | May 26, 2010 4:48:45 PM

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

By Dmitria Burby | May 20, 2010 2:15:50 PM

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.
   

Google getting Bingy with it.

By Rich Devine | May 6, 2010 2:53:04 PM

Silly Google. Their new search results look remarkably similar in functionality to what Microsoft rolled out with Bing. At the time Google said they're just fine standing pat. Now they're saying that they've always been adjusting the presentation, usability, and functionality of their results.

Come on Google, it's okay to admit that Microsoft did something well -- and now you're making an effort to follow suit. http://ow.ly/1HW56

What is your delivery vs. demand ratio for search marketing?

By Rich Devine | May 4, 2010 3:36:05 PM

Despite my best efforts, graduate school taught me all about financial ratios. Financial ratios are key indicators of a firm's overall financial health and performance. Drawn from financial statements, our nerdy finance friends polish their thick glasses, find two numbers from a financial statement and divide one number by another to arrive at a simple ratio. They look at liquidity ratios, asset turnover ratios, profitability ratios, dividend ratios, etc.

Similarly, many of us use analytics data to inform 'key performance indicators' related to our digital marketing efforts. KPIs are great, but they generally carry relevant meaning only for my business, not necessarily yours. How we derive formulas for KPIs is also very specific to our own business and data sources. For example, your definition and formula for 'conversion' is probably much different than mine.

Financial ratios, however, are basic enough to be relevant across businesses. All finance professionals use the same basic ratios. Because they are meaningful across the board, they are particularly helpful for comparing businesses within industries.

For search marketing, we often conduct performance audits that directly assess site health or campaign effectiveness for SEO and SEM respectively. These deep-dive evaluations are important, but like financial ratios, search ratio analysis helps us understand the comparative search performance of clients within an industry or competitive set.

One ratio we typically use to help clients understand existing performance compared to potential is the Delivery vs. Demand ratio. We use this ratio for both Natural and Paid Search.

Demand refers to the estimated keyword volume relevant to your brand or business. You can look at forecasted  or historical volumes -- doesn't matter.

Delivery reflects the estimated traffic comes to a brand's web site from SEM and SEO sources.Competitive analytics tools like Compete.com are great resources for this data.

Let's look at an example of Delivery/Demand ratios:
The graph above shows delivery/demand ratios for furniture web sites. If all sites were equally optimized for SEO, we would expect to see Traffic from SEO scale up or down with demand. Likewise, if each business valued paid search marketing equally, we'd expect to see delivery from SEM scale with each brand's respective search demand.

Notice, however, the discrepancy in delivery/demand ratios between brands -- both for SEO and SEM.

The SEM ratio is simply a reflection of investment -- we can see that both Crate and Barrel and West Elm have committed investment to paid search. Comparatively, the other companies are considerably under-invested. So if I'm Dania, I need to ask myself, "Why is West Elm willing to outspend me by 6x even though search demand for my brand is almost 3x that of West Elm?"

On the SEO side, the ratio clearly demonstrates the lack of delivery compared to demand for Dania and to some degree Room and Board. Based on estimated keyword demand, Dania should be earning more traffic than all competitors except for Crate and Barrel. But Dania is barely scraping any delivery from SEO, and it's not even close.

Of course the ratio doesn't tell us what is wrong with Dania's SEO efforts or lack thereof, nor what needs to be done -- but the ratio provides a quick-hit red flag that Dania should seriously evaluate their site for SEO.

So now that we see a red flag, let's see if there really is a difference between Dania's on-site SEO compared to West Elm who is seeing much more delivery.

As a really basic example of SEO effectiveness between brands, let's compare Dania's title tag usage to West Elm's:

 
 

Sure enough, Dania is not well optimized for title tags, and West Elm really seems to be consciously optimizing their tags effectively. And if you take a deeper look, beyond just title tags, West Elm has done a fairly nice job of SEO across the board, while Dania has some clear opportunities for improvement.

Whereas SEO audits and SEM assessments provide introspective insights -- ratio analysis provides comparative value for clients to understand, unequivocally, how they fare against industry standards or competitors.

Performance ratios are also ideal metrics for your scorecards, either as top level KPIs or side-bar indicators.

Here are some helpful rules for using ratio analysis:

1. Keep them simple: Remember it's one number divided by another.

2. Internal and External Relevance: Ratios should be meaningful not just to your own business -- but ratio formulas should be widely relevant and usable across businesses or industries.

3. Estimates vs. Accuracy: Much of the data you use for ratio analysis can be drawn from free or paid competitive sources. There is wide discrepancy in forecasted demand, and delivery data between sources -- but accuracy isn't really our objective -- as long as you can get a sense for proportion, that's all we need to generate a valid ratio.

4. Actionable: As with all analytics, focus on ratios that provide actionable insight and avoid ratios that are just nice to know.

So now that I've shown you mine, show me yours. What other simple ratios can you use for search marketing?

 

Search Engines and Brand Lift, part 2

By Erik Koto | Mar 11, 2010 3:28:30 PM

As we discussed in our previous post, ZAAZ recently conducted research on whether and how the use of different search engines affected the perception of the actual brands searched. We discovered that the search experience on different search engines yielded different results, with some results being more relevant to the consumer than others. 

The research concentrated on loyal search users of Yahoo, Google, and Bing. We looked specifically at the correlation between brand awareness and search efficacy, and how search engines are changing consumer behavior.  Researchers and analysts from ZAAZ, Compete, and BrandAsset Consulting collaborated on the research.  Compete and BrandAsset provided behavioral and attitudinal datasets, respectively, and ZAAZ led the analysis portion of the study by combining attitudinal and behavioral data, to draw a more complete picture of consumer search behavior.
 
The findings indicate that if the results of a search query satisfy the needs of the consumer, then the search engine has greater appeal to that potential customer— and he or she will also have a deeper connection to the brand searched.  In other words, the search engine can provide different degrees of “brand lift” to a destination site.  The user’s experience on the destination site is shaped by the search engine that the user takes to get there, and that experience has an impact on the parent brand.
 
For example, while researching the wireless industry, we found that while Bing loyalists tended to have a higher visit rate to Sprint's site, Yahoo loyalists had a higher rate of conversion or purchase behavior on the Sprint site. So Sprint sees a higher rate of online purchases from people coming from Yahoo search compared with other search engines.  In the retail category, Walmart.com saw the highest rate of online visitors, shoppers, and converters from Bing loyalists. Amazon.com, on the other hand, saw its highest rates in all three categories from Google users.

We also discovered varying profiles among different search engine loyalists.  If you’re a Bing user, you’re far more likely to be an innovator or early adopter, compared with Yahoo or Google loyalists.  The research also provided rich psychographic details about each loyalist group.
 
The attached deck (pdf, 850kb) goes into greater detail on the differences between the industries analyzed: wireless, retail, travel, and automotive.
 
Some potential implications for marketers from this research include:

Resource allocation models among search engines could change depending on the brand. In other words, brands devoting funds to search advertising must take into consideration which engines are going to do the best job for them behaviorally and provide the highest brand lift.

Advertisers’ sites could be optimized and targeted based on referring search engine.  As marketers become more informed about what the referring search engine says about the visitor’s brand perceptions and likelihood to convert, dynamic targeting programs can be developed to speak to each audience and serve relevant actions that are most likely to increase value.

This study is a jumping-off point for deeper research and monetization modeling of how interactions across the digital channel affect brand perception and conversion.  Search activity does not exist in a vacuum, and is influenced by a brand’s mix of bought, earned, and owned media.  Using data from this study, in conjunction with social media listening, other bought media activity, and deeper site side analytics, will help marketers create more effective outreach and engagement strategies across the digital channel.

By Anders Rosenquist and Erik Koto

Search Engines and Brand Lift

By Anders Rosenquist | Feb 24, 2010 3:50:07 PM

Adweek recently published the results of a new study conducted by ZAAZ, Wunderman, BrandAsset® Valuator, and Compete that explores the relationship between the search engine that consumers use to find a brand’s website and the consumer’s perception of that brand. The study found that loyal users of Bing, Yahoo!, and Google have distinct characteristics that benefit some brands more than others.

“This research demonstrates that marketers have a real choice to make when formulating search strategies,” said Shane Atchison, CEO of ZAAZ. “The search engine acts as a kind of ‘train’ on the Internet. Each train provides a different set of unique results or ‘destinations.’ Consumer preference for a specific train demonstrates a unique demographic and psychographic profile.” That preference, the study found, can have enormous impact on any brand a consumer searches for.
 
ZAAZ led the analysis portion of this pioneering research study, which combined attitudinal and behavioral data to draw a more complete picture of consumer search behavior.  In this two-part post, we’ll first discuss our methodology;   in the second post, we’ll discuss the findings and how marketers could put these findings to use.  (Note: this research was independently conducted, and was not funded by any of our clients.  You can view a version of the results presentation here: Search Engine Research (pdf, 850 kb)
 
Our team combined two extensive databases from BrandAsset Valuator (BAV) and Compete. Both BAV and Compete own the largest databases in their areas of expertise.
 
BAV’s databases contain a range of attitudinal information – focusing on 72 brand metrics – and use the world's most comprehensive database of brands. Its BrandAsset Valuator model has measured brands since 1993; today, over 35,000 brands have been evaluated, and over 600,000 respondents in over 50 countries have been surveyed. To find out more about BAV data, try comparing a few of your favorite brands using the ZAAZ-built interactive tool: http://thebrandbubble.com/explore/.
 
We also used behavioral data provided by Compete. Compete combines site and search analytics and surveys on a diverse sample of more than 2 million users in the U.S. to understand what people are clicking on and why. Compete manages the largest pool of online consumer behavior data in the industry.
 
The datasets from BAV and Compete  both contained information on the same brands across verticals including retail, travel, wireless, and automotive.  Additionally, both data sets contained a field with information on a consumer’s primary search engine. Taken independently, each data set provides insights into search engine use.  However, when ZAAZ combined and mined the data sets, we found a much more powerful and complete story.
 
At ZAAZ, we live in a world of disparate data sources; we have data for Web analytics, social media, usability, optimization testing, surveys, and more.  Almost always, this data is supplied through different tools and in different formats.  Most online marketers will be familiar with this scenario: too much data, too few connections, limited insights and action.  We’re constantly looking for new and innovative ways to combine data and tell a true 360-degree story of the customer.
 
The research published by AdWeek is certainly not the first time we’ve been through this process.
 
Working with Ford we’ve joined attitudinal survey data to behavioral Web analytics data, and analyzed this data by unique user.  With this combined approach, we are able to map how different user journeys affect customer’s brand perception and likelihood to purchase a Ford vehicle.  As a result, we have quantitatively identified what areas of the Ford site and types of content are most effective at driving sales – an insight we never could have gained by analyzing the data sets in isolation.  Ford has used this data to channel media, redesign site architecture, and run a data-driven optimization program.
 
Working with Dell, we combined site optimization testing with in-person usability testing to understand why a particular creative treatment won. For a particular campaign, we found from our optimization tests which page variants generated the greatest interaction with the page. In addition, our analytics data showed that there were several key places in the purchase path where users were abandoning at an alarming rate. To gain insight into why this was happening, we conducted usability tests in our Seattle lab with Dell consumers, having them step through the purchase path and describe their process. We were able to uncover how participants’ attitudes toward the site and the brand changed through the process, why parts of the site became annoying, and why they decided to jump out of the purchase path—either to find a different product, or to go  a competitor’s site.  The insights gleaned from combining optimization and usability test data helped generate  site changes focused on improving user attitude and increasing conversion.
 
With the search engine research, the objective was to understand the relationship between a customer choice of search engine and the brand perception of products being searched.  Once we had the data sets combined we set to work looking for trends.  Using a series of aggregations, drilldowns, and data visualizations, we were able to observe trends in the data common across attitudinal and behavioral data sets. Once the trends in the data were clear, we pulled together stakeholders from BAV and Compete to build consensus on the interpretation of the data as well as actionable strategies.
 
Next week we’ll discuss some of the findings from the research and how to take action on these findings...

By Erik Koto and Anders Rosenquist

How to Develop a Consistent Targeting Strategy

By Shane Atchison | Mar 2, 2009 3:51:04 PM

Targeting, a hot-topic marketing practice, deserves digital marketers' attention. Targeting can help marketers deliver the right content or message to the right person, at the right time and in the right space. But targeting can be an ambiguous concept. Often it means different things to different people.

Most digital marketers divide their efforts between offsite and onsite targeting. Offsite targeting comprises advertising and demand-generation activities like search, display, and e-mail. They drive performance by sending traffic to your online real estate. Successful marketers recognize that traffic by itself won't guarantee success, so they apply site-side strategies to maximize performance once a visitor lands on the site.

Today's holy grail for targeting requires the integration of off- and onsite targeting efforts. This happens too rarely, however. Ask yourself these questions: How often does your paid-search team seek data and insights from the person who manages Web site analytics? How often do your site-optimization efforts employ data and insights from the teams that manage search and display media?

Below are the most typical and effective forms of off- and onsite targeting, as well as tips for how businesses can successfully bridge the divide so targeting represents one consistent marketing strategy, rather than separate parts of a disjointed and sometimes ineffective effort.

Offsite Targeting

Most ads are served contextually, meaning that if you visit auto site Edmunds.com, you'll probably see a lot of ads related to cars. But offsite targeting is more precise. Here you rely on a huge network, or networks, to provide different ways to serve traffic based on user behaviors or profiling. The targeting can happen by any number of factors. For example:

• Geotargeting. Only shows ads in states or regions where a business has retail stores. This is common for both display and paid search campaigns.
• Interest group. Only shows an ad to someone who has visited a Web site on a specific topic (such as autos) in the last month.
• Prior view. Shows someone who viewed but didn't click on the first ad a second ad with a free-shipping coupon.
• Demographic targeting. Loosely targets display ads to network sites that fit a general demographic profile. Paid-search platforms like Microsoft adCenter offer user-based targeting and allow for incremental bidding where demographic criteria like gender and age can be identified.
• Day-part targeting. Serves an ad during specific times of the day and days of the week.

While results vary greatly depending on product, business, season, and so forth, the industry has pretty much proven that targeted ads consistently outperform their generic and even contextual counterparts.

A popular form of offsite behavioral targeting is search re-targeting. Here, an ad-serving platform can identify a person who has performed specific searches in the past. A corresponding display or text ad can then be served to that person across select network sites they visit. So if you've searched for "new cars" or "hybrid cars" on Google, don't be surprised to see display ads for the Ford Fusion Hybrid or Toyota Prius when you start browsing other sites later in the day. (You might want to think twice about what you're searching for, because if your spouse reads this column and sees a bunch of unsavory display ads on your home computer...well, you get the picture.)

Onsite Targeting

Onsite targeting relies on a more focused array of characteristics to align a Web site to what a visitor should experience. In addition to offsite parameters (geography, interest group, etc.), as well as other general parameters, such as referring source, you can use any authenticated data (i.e., information kept behind a login) to provide a personalized site engagement for each visitor. As with offsite targeting, there's no industry average for how a targeted Web site improves business. But anecdotally it isn't hard to see how a customer will more likely return if the Web experience closely aligns to what she's clicked on, viewed, or purchased before. At my agency, our site-side targeting test programs are among the most effective ROI (define) proven services we provide for clients.

Amazon and eBay are industry leaders of onsite targeting. Each individual eBay or Amazon user could experience a completely unique site, depending on their past behavior and profile. If you've been looking at auctions for Xbox consoles, then the next time you visit eBay, you'll probably experience a site that features Xbox games, Xbox accessories, and related products. Whether you sell or buy, how much you pay, what types of products you buy, and what time of day you tend to buy certain products are factors that drive onsite targeting.

Fortunately you don't need to be an eBay or an Amazon to take advantage of site-side targeting. Tools like Omniture's Test & Target and Optimost allow companies to deliver targeted site experiences.

Bridging the Divide

Bridging the divide between off- and onsite targeting efforts will be unique for every business, but here are some recommendations:

• Define success. You may think this is obvious, but at my agency we consistently find that separate teams and stakeholders have different definitions of success. It's critical that your teams work together and toward the same goals.
• Understand targeting mechanisms. Different ad-serving technologies offer different types of targeting -- behavioral, geographic, demographic, and so on. Make sure you understand their capabilities. Test and use them. I'm particularly excited by new targeting technologies that allow for search re-targeting.
• Use one consistent targeting strategy. Even though this sounds logical, it's more difficult than it sounds. Onsite and offsite folks don't talk to each other often. You will need to establish a process to ensure this happens.
• Share data. Once you get your teams and stakeholders playing for the same goal, encourage them to share data. And not arbitrarily. At my agency, our search team consistently delivers keyword trend and performance data to our onsite optimization team. This allows our optimization team to design tests and targeting strategy based on offsite opportunity. Likewise, our analytics team shares behavioral and attitudinal data with our media teams. Everyone has a consistent standard for what success looks like. There is no divide between offsite and onsite.
• Test, measure, execute. Repeat. Don't assume you're getting it right. Validate your strategy with consistent testing. For onsite, A/B and multivariate testing are excellent programs. Don't stop when you get promising results. Execute, measure, and repeat the process.