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History of Search Engine Marketing

MM: What’s history of search engine marketing—in terms of current practice and vendors as well as what you anticipate in the future?

BK: Search marketing evolved in the mid-to-late-90’s as the number of search engines increased and marketers saw an opportunity to influence the search results on these engines. Today search marketing is defined by a couple of categories.

Search Engine Optimization (SEO), also referred to as natural search, is an effort by site creators to ensure the structure and content of their pages will properly “feed” the search engine spiders—so their company’s pages get top ranking. On most search engines, these results comprise the lower, left body of the results content.

Search Engine Marketing (SEM), also referred to as paid search, is an environment where keywords are bid on for ranking. These results typically display at the top, left and down the right hand side of the search results content and most often have a shaded background and even a “sponsor” designation title.

In my experience SEO is handled by a combination of in-house personnel and outside consulting or agency expertise depending on the importance of search rankings and the volume of keywords an organization is managing. SEM, by contrast, is almost always handled by an outside agency and sometimes by several agencies, especially when the client markets to unique industries, product lines, and / or geographies.

However, Covario represents a firm that provides a suite of software to help companies audit the effectiveness of their SEO and SEM processes, bridging SEO and SEM to create a new category—or so they intend! As the volume of keywords under management increases, the need for automation becomes increasingly important and eventually mandatory.

My impression of future state is one where technical solutions, consulting and services will be imperative to successful attraction of site visitors. More and more social network services such as Facebook, will play a role in site attraction success so look for an ever-changing landscape.

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Media-planning Agencies

MM: That parallels the evolving role of a media-planning agency—specifically, a group that understands the syndicated research, compiled data, and other types of primary research, slicing and dicing the data to achieve an optimum media mix—that includes SEO, SEM, and other forms of engagement services. Does it follow that the SEO-SEM trend will continue moving towards even more specialized agencies?

BK: I do think the trend is for companies to hand-off or out-source SEM to agencies with a specialization in Internet marketing. There’s a lot of money in play. Companies spending these dollars need to have a high degree of trust they’re getting proper positioning for the dollars invested and that this positioning is driving the desired visitors to their site.

I believe agencies must build or license technology to improve their ability to manage these processes. I also believe agencies or some form of service provider needs to “mentor” on-line marketing best practices to their clients for a couple of reasons.

If on-line marketing is viewed as a black art then it will be difficult to view it as a strategic initiative of the company. If the agency holds all the skill or knowledge about these practices then in-house champions can’t articulate value nor influence KPI’s that are span on-line and off-line initiatives.

Google and others are actively taking on this consulting role in competition with agencies and in support of company in-house plans so again the agencies need to transform from exclusive outsourcing to more of a mentoring partnership.

MM: Yes. This goes to a conversation I’ve been having with other innovation leaders now for several years. In one sense, Google really owns that whole keyword/adword space. And the organic search that makes it relevant.

The second thing it has as an ad network. Both adwords, as well as banner ads and rich media things, in terms of animation and things like that.

The challenge that Google has in terms of growing its business is that online only represents one portion. Granted, a significant and rapidly-growing portion, but a portion nonetheless of the total spend.

So there’s a still tremendous—many hundreds of billions of dollars—spent in print, broadcast, out-of-home as well as direct mail and catalogue and so on. They’ve made moves to say, “Let us create a marketplace kind of network for that.” Be they spot display ads in print magazines with a barcode reader in it, so that consumers can scan the barcode with their mobile phones and get a coupon or whatever.

This comes back to what Google just recently announced. I don’t know if it’s a formal announcement or a beta announcement, but essentially a dashboard by which to integrate the Google analytics or Google scene in terms of “What’s going on,” in my website, as well as in the marketplace as it relates to concepts and products listed on my website. With the ability then to buy things.

Now we’re talking about a market planning desktop.

Can you validate pushback? Refine that narrative? And then perhaps explain how you see it working in the realities of the clients with whom you work?

BK: I can’t really comment on those statements since this is outside my area of knowledge. In my opinion this plan makes a big assumption that the creative capabilities and the experience of an agency are of less value than the automation of those processes and the buying power of a market maker like Google.

MM: I think that heightens a narrower, deeper, slice of creativity. That would highlight the price premium that someone who really understands a very specific part of an overall engagement theatre.

I’m really talking more about disintermediating the traditional media planner who—for the most part—was the only one able to translate the analytic insights into concrete action items.

BK: Agreed.

MM: Can you summarize some of the vendors that are leading the way in terms of SEM? You mentioned Covario. Any others in that space?

BK: Covario’s the only software solution I know of that provides an automation and auditing solution for SEM versus the placement solutions offered by companies like Omniture and WebTrends.

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Voice of customer

MM: Great. I’m going to use this opportunity, Bob, to circle back on a topic that you introduced earlier. The term that you used was, “Voice of the customer.”

BK: Yes.

MM: I’m familiar with the term from my exposure into Six Sigma and Lean Six Sigma. More of a formal quantification of customer satisfaction and utilization rates and things like that. What do you mean, when you’re using “Voice of the Customer,” as it relates to customer experience management? What does that entail? Where’s it been and where’s it going?

BK: “Voice of the Customer” speaks to technologies that allow for direct customer dialog in an online environment. Primarily this takes the form of surveys and direct customer feedback. In particular there are two companies leading in this solution space: iPerceptions and ForeSee Results. Both have compelling solutions and back it up with consulting from business analysts helping clients to take action on the data collected.

Another emerging opportunity for customer feedback is mining content in social media environments including Blogs, Chat rooms, Facebook and MySpace, etc. Gaining access to this data and being able to aggregate remarks into categories could provide online marketers with tremendous insight about brand perception and loyalty, competitive and complimentary products or services, and many other associations.

The bottom line is companies need to get direct customer responses to add with statistics gathered in other interactions so they have a complete 360-view of their online visitors.

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Journey of Customers

MM: Yes. Early in our corporate history we did a lot of surveys. There were several almost axiomatic truths that have distilled from having surveyed over 50,000 people. I personally have interviewed probably 3,500 or 4,000 people.

Surveys are highly structured, scientific collections of bullshit. They give you top-of-mind associations and more specifically speak to the expectations of the person asking the question.

Most of the survey data rarely comes back to anything meaningful or insightful in terms of buyer behaviors. This really relates to the superficial, although necessary, task of understanding what your customers are thinking about. Understanding that what customers think very rarely correlates to what they actually feel and do.

BK: So in this on-line context you not only ask the question and get the response but you correlate this Q&A to what they were doing during the session and what they did after the question was asked and answered. Perhaps this will provide valuable insight for Customer Experience Management.

MM: The thing that I’ve tracked now for going on a year and a half is that companies have begun to do extended, open-ended interviews with customers at various stages of what I’ll call the “customer journey to success.”

In some cases, they’re not yet customers. In some cases, they’ve just bought something but they haven’t really yet made an emotional commitment to buy it again or to use it. All the way through arm-waving evangelists.

These interviews then get transcribed. Often, verbatim—with all the broken grammar and syntax that it often entails. These transcripts then move into a specialized content database, using a text-mining engine. We start doing semantic tagging, so as to identify topics and trends and topics. And some more advanced text analysis. We start to understand and to quantify things like sentiment. Keywords and phrases that are positive, negative and neutral, as they relate to a particular policy, program, product, technology, market, demographic segment.

So these text-mining and special voice-of-the-customer databases have really started to document and crystallize the taxonomy of awareness, consideration, trial, purchase and advocacy.

I say the taxonomy of that meaning that there are specific keywords and phrases. Some of them are related directly. Some of them are only indirectly related. This taxonomy of satisfaction then becomes the basis for social media monitoring, by which to start tracking the conversation about your product market customer segments, relative to those keywords that you’ve identified—and then starting to really build more meaningful dynamic day-to-day dashboards.

The idea is then to identify who in your market really has emerged as an advocate for a particular type of application or for product usage.

BK: This sounds much like the interaction you would want in a BLOG or social media interview. To get the best perspective you should engage with Jerry Tarasofsky (iPerceptions), Larry Freed (ForeSee Results) and even Rand Nickerson (OpinionLab).

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Driving the R in CRM

MM: In my conversations with folks in Europe who really seem to be ahead of us, in terms of really understanding the “R” in CRM, really understand that first of all, you need to have a lifecycle model for what it means to be in a relationship with a brand. But also, do we have an explicit data collection model for collecting what I call “brand interaction data,” very early on in the awareness and consideration process?

Something else that I’ve seen in this area that’s really been a startling breakout success for some of the digital agencies is the use of viral videos that are part of a guerilla-marketing program. Viral videos explicitly designed for presentation and consumption at YouTube, FaceBook and some of these other video-sharing sites.

Then, tracking who actually downloads or posts or syndicates in those videos of their Blogs and writes about it. Then making an outreach to the people that posted favorable things about these humorous product placements. Almost like a paid feeding of viral videos.

BK: I’m sure it won’t surprise you to know that Coca-Cola spends a lot of time and energy monitoring that very thing. Feeding that very engine. You didn’t mention it, but I’m sure you’re aware of Second Life. Burger King in particular spends a great deal of time and money on Second Life, which doesn’t immediately correlate back to store sales, but certainly does speak to that lifetime brand.

How do we find our customers in their place of preference and continually reinforce the brand? There are certainly some forward-thinking companies that don’t necessarily interact and sell stuff on the web, but they’re certainly using those mediums to solidify that brand loyalty.

Game Theory and Coke Promotions

MM: I’m glad you mentioned Coca-Cola. They were one of the early adopters of this smart promotional platform from a company that’s since gone out of business. It’s part of ePrize, now.

It was an interactive, smart promotions platform. It had mathematics underneath it that came from two PhDs in mathematics and game theory. Preference options would be similar to when you get an e-mail from Amex or Delta Airlines and they say invite you to make a bid on these four packages.

They invite you to make a bid, combining n-number of airline frequent-flyer points, membership points as well as hard dollars. They will choose five people over all the contest participants who got those packages.

BK: Cool.

MM: The net result is they end up collecting a lot of data from you. After you do several of these preference options they know, for example, that you’re single and that you have a proclivity for fun in the sun.

There are probably three or four more meaningful things they’ve learned from you as a function of your preference options or preference bids. It goes to the underlying game theory of how you elicit truthful information from anonymous actors.

So, game theory is just the mathematics or science of incentives to induce a particular behavior.

Coca-Cola was one of the very first adopters of this very sophisticated gaming platform. The challenge of course of that otherwise elegant concept is that it takes real rocket science. It takes somebody who’s got a PhD in quantitative methods and game theory to really understand how to construct and design these interactive promotions such that it produces the desired result.

BK: Agreed.

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Skill sets in predictive modeling

MM: As web analytics goes from more or less forensic reporting of anonymous behavior to now predictive models of what customers are likely to respond to, the underlying analytic discipline shifts from quantitative methods to things that are more forward-looking—be they game theory and predictive modeling.

When we talk about, “Who has skill sets in predictive modeling and econometrics?” Aside from analysts that are working at hedge funds and in New York City, and getting paid $300,000 to 500,000 a year, it seems to me that agencies will step forward into that opportunity with a founder or some equity participant. Secondly, it seems to me that there’d be a natural gravitation toward the largest concentration of PhDs in mathematics—India. And India may emerge, in fact, as the center of excellence for more prescriptive analytics and modeling of games, promotions and brand interaction through a lifecycle.

BK: I guess in response I’d say that the challenge the web analytics vendors play or have right now is that by and large, customers—people using web analytics tools—are implementing 20 to 25% of the capability of the solution to begin with. Limiting their use to data collection, analysis and reporting.

So, the more advanced, predictive modeling that you’re speaking to … while it might be something that they’ll ultimately build towards, the question is, “Will a majority of companies take on the task of implementing this capability?”

MM: I think that the agency will make that an opportunity and will invest in the tools and technologies to automate the tagging of your pages, and the reporting that comes from that, as well as the interpretation of what that means with very specific prescriptive outcomes in terms of what we need to build next.”

BK: I totally agree with you. I think it’s going to have to be a service provider. It’s not going to be the end company that’s going to try to have that expertise in-house.

MM: Yes.

Increasing Conversion Rates

BK: That argument could be fought from the other side, you should talk to SAS Institute where they have hundreds of Analytic PhD’s on staffs that are building very robust predictive models. The question is, “How many commercial companies are sophisticated enough to take advantage of that technology.”

In traditional modeling, companies continue to struggle with defining appropriate and action-able conversion funnels. Marketing is typically concerned with getting more visitors to the site and at the top of the funnel. And Marketing tends to be satisfied if somewhere between 2% and 4% of this top-of-funnel visitors make it all the way through since that meets with “industry standards.”

But who in the organization is focused on increasing that conversion percentage? It seems to me it would be more cost effective and more brand desirable to get a larger percentage rather than focusing on drawing more visitors in. Particularly in an environment of great noise, over lapping options, and fickle consumer behavior!

MM: Yes! The Miller and Heiman folks that came out with that canon of sales management strategic selling that came out in the ’80s—Miller recently wrote an article in Brand Week in which he describes the sales funnel. You call it the conversion funnel, which I guess is a little further down.

He said that most companies—especially younger companies—have these wicked peaks and valleys in their monthly revenue, as a function of spending too much time in the bottom third of the funnel—which he characterized as “closing.” In his model, he simply trisected it into prospecting, nurturing and then closing.

He said it’s very common for a company to spend most of its time-resource-money on the closing function – which leads to these wicked swings in revenue on a month-to-month basis. He said that ideally, you want to have an equal distribution of time, money and resources.

He was advocating—to contradict you a bit—to put more people into the funnel so that some number of them will bust the rate and zip right down to the transaction, because they’re so desperate to do something.

I think to your point Bob, most companies do a mediocre-at-best job of nurturing deals already in their pipeline.

BK: I would fully agree with you.

MM: I concur that for incremental investments, it would seem to me that if you could reduce your attrition rate by just 10%, you could in effect double a conversion rate.

BK: Yes.

MM: In terms of gain-for-pain, it seems to me that getting the easily implemented solutions done first would probably result in a very noticeable and tangible return on investment.

BK: Agreed.

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Hearing the Voice of Customers

MM: So as a way of starting to summarize these points—what are the things that a proactive eBusiness manager would want to do in terms of maximizing the efficiency of their nurturing process? Clearly we need to monitor what’s going on. Right?

BK: Yes. I think we need to monitor it at a very tactical level. Internet managers should spend more time answering the “why” questions that come from campaign reports, analytic reports, voice-of-the-customer responses, social media pages, etc.

“Why aren’t we getting the response that we expect on campaigns?

“Why are lengths of visits, page views, returns by recent visitors surprisingly up or down?

“Why is customer feedback so infrequent?”

MM: I’ve got data that says, “Oh. I’ve got a user experience or a user interface problem here; I’ve got fuzzy, indistinct content and product descriptions here; I’ve got an SLA that needs to be improved because I’ve got too many timeouts or I’ve got a server overload.” Something like that, right? So, in monitoring, you want to identify some number of things to do. Right?

BK: You’re right. In the beginning it’s about structural and technical issues that tend to be the “fires” that keep most organizations in perpetual reaction mode. Next the organization will focus on product, segment, campaign and other sub-groups to improve interaction and success.

At some point it should become important to transition from being reactive to being proactive. At some point in the life cycle companies will proactively focus on customer experience and improved satisfaction with an eye on turning customers into “raving fans.”

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IT Service Management as Model

MM: This mirrors what we’ve seen in the IT service management area. Specifically around self-managing autonomic computing, advanced by IBM and other vendors. The core building block concept of self-managing systems is something that they call the “MAPE” loop. That’s an acronym for Monitor Analyze Plan Execute.

If I can apply the MAPE loop to your conversion funnel, we need to do a better job of monitoring what’s going on in the conversion funnel.

The analyze part then really starts to ask—to your point—”Why are we only getting 3%? Why not 10%? Why not 20%?

This will go back and forth between the IT service management and the equivalent of a service level agreement. What set of ongoing benchmark scorecards can we establish with the idea that, “If we can measure it, we can improve it?”

Having really good performance indicators or performance benchmarks as part of that analysis becomes critical.

The other part then entails understanding what the data’s telling me. Back to the MAPE loop—the “P” of “planning.” Planning really entails having a framework by which you can execute. So it seems to me that once I’m monitoring customer experience and engagement success, now it shifts.

From, “Okay. Here’s what we need to do,” to, “Now, let’s do it.” That puts emphasis on engagement systems. Some of that maybe entails some sort of a dynamic messaging system. But it’s driven by some sort of analytic profiles or personas, and it has a bunch of content in the newsletter that was really optimized for the intended person, given their customer profile or session behavior.

That then suggests that as I start to react almost in second cycles, as they begin to receive these bounce-back or outreach confirmation e-mails, there are click URLs in the newsletter that if they click, basically validate, “Yes. We’re on-target.”

So there’s a closing of the loop between something that happened, some behavioral data generated, some analysis of that data in terms of, “Here’s what it likely means. Let’s go probe and test it—either as a function of something that was served on in the session, or something that was served by means of a messaging system subsequent to the session.” Closing that loop and then also validating that, “Yes, you are who you are, and you’re still interested in Category X or Y or whatever the criteria is,” that you’ve associated with a particular persona.

Then ultimately, we’re talking about maintaining that data in a useful way. Such that when you come back and visit again, there’s even a further tighter loop. Ultimately driving us all toward individualized content, where every page is my home page. Where all the search engines in a faceted search framework reflect the needs or the taxonomy of awareness, consideration, desire and satisfaction of, “me.”

Based not only on my transaction, but my brand interaction histories. That thereby closes the loop of what I’d call an overall engagement cycle.

I know that was a lot to listen to, but does that make sense?

BK: That makes sense. In my experience, the handicap to implementation or improvement is a culture of change. It’s an environment where you can be agile enough to ask those questions and then make the appropriate changes. That might be something as simple as, “Why is this page not optimizing correctly,” and then having an infrastructure where you don’t have to wait weeks or months for a web development team to make desired changes in order to have an impact.

I think the desired environment is something everybody would sign up for. Automating it or having technologies to support it would be a desire as well. Now it’s a matter of, “Can I get any bang for the buck if I spend moneys on systems?”

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