Jonathan Mendez's Blog

Landing Page Optimization Part 1 (cont.)

The Keyword Query and Transactional Landing Pages

Picking up where we left off in Part 1 we’re now heading downstream and focusing on experiences where the user lands closer to completing their goal. I refer to these as Transactional Landings. Here the keyword driver can be anything from a general query like “mortgage” to a more focused query like “30 year fixed APR.” It is also on these landing pages that the direct response nature of search leverages itself well.

If we examine the SERP (Search Engine Result Page) we can see a clear and interesting dichotomy and I would say optimization, emerge for delivering relevance. The natural results are leading to informational pages or as I talked about in my last post Reference Landings. For someone who has a Discovery>Information>Directed>Closed goal path this is a highly relevant landing experience. These pages help fulfill their goal by providing them with more information on the subject and then ideally steer them in the right direction if their goal advances from an “information” to an “obtain.” PPC is a different story. Most paid search results lead to transactional pages. For someone who has a Recovery>Resource>Obtain goal this is a highly relevant landing.

On a transactional landing the user has the ability to immediately engage in some type of transaction. These pages are usually radically simpler to gain understanding of than Reference Landings so there is much less thought involved. Also, and this is an important point as we look at landing page optimization in a holistic manner, the user has already achieved the secondary goal of Discovery>Information on the SERP, mostly likely from the Ad (this will be covered in detail on my next post). The flow of going right to a form page or right into engagement is natural. There will be a brief moment of recognition (hey, I’m on the right page/site) but that brevity is all that most users need. Anything else, heaps of content, even images could possibly interrupt the flow.

With any kind of campaign that has a CPA/CPL or COS goal these are the users you should be focused on. Prioritize you testing and optimization around them. Keep in mind, these users don’t need persuasion, they need reassurance and confidence. Simply all that needs to be done is to present relevant messages in context along the pathway to the completion of their goal. Coming full circle to what I mentioned earlier if your marketing initiative is focused on persuasion this is better done through a reference landing, ideally from natural link to a microsite.

Once again we will divided our targets into the two high level goal classes, recovery or discovery and then quickly find goal paths we can bucket users in for each experience. Armed with that, we can begin to explore aligning ad creative and messaging with their goals. So let’s take a look at a couple of queries that would have Transactional Landings and attempt to classify them.

“car loans”
Here is a generic query. High volume, high value and also very hard to define. The user could be looking for any number of things, rate information, names of loaners or actively be in market for a loan. As such, their goal can be recovery OR discovery. We have already covered in this post a good strategy for this type of query and if we are held to ROI metric we have no choice but focusing our efforts on users in-market with a Recovery>Resource>Obtain goal. This experience would be a form page that ideally would message to the goals stated in the query.

I also want to use this high funnel query to exemplify the dichotomy and optimization of the SERP that I mentioned earlier. Here’s a quick check of the landing experiences from the top 3 results on Yahoo and Google, natural and PPC for “car loans”:

PPC
Transactional Landing (6)
Reference Landing (0)

Natural
Transactional Landing (0)
Reference Landing (6)

Moving on…

“D and B report”
This is an interesting query because it is both a branded query and in some regards a generic one. The user is likely looking to obtain a D&B report on a company. Her experience would be one that is heavily brand benefit focused and where she could engage immediately in a form to help her complete her goal. Seems pretty clear that the goal would be Recovery>Resource>Obtain.

“Black Prada sandals”
This is a product search and a very specific one at that. The fact that the user has told us the color they are interested in is an amazing opportunity for optimization and one that is often overlooked by retailers. People shop by color. This experience would go right to a product page, Ideally the page will be optimized to have a number of other “Black Prada Sandals” styles or a mix of other brands black sandals. This goal is another Recovery>Resource>Obtain.

In Part 1 I hope I’ve shown how user goal discovery begins at the keyword and how a methodology around targeted your landing experiences to these goals is the way to provide contextual relevance to users. But this is only the beginning of our landing page optimization methodology. In those crucial moments when users are engaging with a search engine pulling information and even when users are interacting with other forms of digital media through push, there is another critical touch point along the pathway to goal fulfillment. Next up I’ll take a look at that important and often-neglected component of landing page optimization, the ad.

Landing Page Optimization

Leading up to my panel participation Monday September 25th at OMMA New York on Search and Site Design: When Every Page is a Landing Page; I’ll be sharing a deep dive into some methodologies for landing page optimization. This post begins to explore the role of the keyword query and how that informs landing page optimization strategy by facilitating goal discovery. Next, I’ll look at how ads factor in the equation and ultimately the landing page design, experience and testing.

Part 1. The Keyword: It All Starts with the Search Query

The way marketers must ensure relevance in the digital medium is by targeting messages that are contextually relevant to the user’s goal. The groundwork for this should start by focusing attention on discovery of user motivations, intentions and emotions that drive their goal. Looking at the keyword query, we can begin to define search (and all pull media) goals in one of two ways. The user goal is either a recovery or a discovery search. From this determination, and using my search goal chart, we can begin to follow goals down distinct paths and gain more learning we’ll use to optimize messaging around the aforementioned motivations, intentions and emotions.

This is not however a scientific practice. The problem we encounter as marketers delivering relevance from a search query is the same one that the search engines struggle with everyday. Most user queries are not very detailed. Users tend to search using short keyword query strings (I believe the average is 2.3 words per query). Also, research indicates that generic keywords are used 75-80 percent of the time for high volume search behavior like product research. So successful goal discovery requires we get “behind the keyword" in order to understand those motivations. This is an assumptive process. However, as we go forward we will use testing to validate our assumptions or as often happens, be surprised by behavior we never assumed.

So how do we begin landing page optimization with the keyword? First we can divide landing page experiences into two types. What I refer to as Reference Landings and Transactional Landings.

Reference Landings: These are generally high funnel in nature and mostly occur with generic keyword queries and broad navigational queries. This landing could be anything from a page on a content site like CNET to a retailer’s category page. The user is seeking some form of information discovery.

Transactional Landings: These are where the user has the ability to immediately engage with the next click in some type of transaction. These are generally lead-generation and product pages.

From within these landing page experiences we can begin to further divided our targets into the two high level goal classes, recovery or discovery and then quickly find goal paths we can bucket users in for each experience. Armed with that, we can begin to explore ad creative and messaging that aligns with their goals.

So let’s take a look at a couple of queries that would have Reference Landings and attempt to classify them.

Reference Landings

“Houston flights”
This is what I would consider a navigational query. The user’s goal is likely to find specific flight information. However, because of the query his landing page experience will be one from which he has to navigate further to obtain the information. This is an important differentiation and bridging this gap between expectation and delivery is how we would strategically deal with this kind of query. The goal here is (macro) recovery (I know I want to go to Houston) or if you’re referencing the class chart, Recovery>Directed.

Back to optimization for a second…. As Matthew Roche pointed out to me, Kayak has a great example for this query of bridging the gap I just mentioned. They are targeting content into their form field via what seems to be URL parameter info. Now that’s a simple but great optimization strategy. Ok, back to keyword queries…

“Plasma TV reviews”
This is what I would consider a content query. We can presume the user’s goal is to find editorial content for decision-making purposes. His experience will be one from which he has to navigate through and absorb a good amount of copy. The goal here is discovery (not sure what Plasma TV to buy) or if you’re referencing the chart it can be further defined as Discovery>Informational.

“leather jackets”
This is what I would consider a recovery query. The users knows she wants a leather jacket and even though her overlying goal is likely to buy a leather jacket the underlying goal is first to find a leather jacket. Her experience will be one where she is presented with multiple options in the hope of delivering an option of interest. The goal here is Recovery>Resource>Obtain

Even if the user motivation behind the keyword is specific, goal discovery is only as good as the query. The better the query the more we can find out about the goal and the more relevance can be delivered. For SEMs this an important point because for many the overriding practice is to target ads and landing pages based on expanded match or broad keyword match. This strategy makes delivering relevance ad side and site side much more difficult hurting conversion rates.

Next, I’ll go a bit further down funnel looking at Transactional Landings. This is where is gets very interesting because of those darn generic queries. I’ll also look at how we can start to test and tailor our messaging by focusing on what we’ve learned about the user’s goal and the needs of the user to get closer or complete their goal.

Viral Vidiocy: The Agency.com Video

So I finally watched the agency.com viral debacle. What struck me was that all the smart people that used to work there must have left. Agency.com seems like...well, not the sharpest tool in the shed.

While they were spending their time learning how to make sandwiches and use a cash register, a smart agency would have be pouring over metrics from Nielsen, comScore, Hitwise, Google & Yahoo.

While Agency.com was chatting up people coming out of St. Pat’s and questioning a Hasidic Jew (isn’t it obvious that Subway isn’t exactly a kosher deli) a smart agency would have gained understanding of Subway's brand conversation by exploring audience segmentation and behavioral preferences.

While Agency.com put time and effort into editing and scoring a viral video a smart agency would have been buying a few keywords, running sample creative and testing messages.

Had they been smart with all the time an effort they spent clowning (or was that real;), they would have learned enough about Subway’s customers to deliver a great pitch. They even could have put it on a video and spread a crafty viral message showing the world why Agency.com should be your interactive AOR. Instead, like most of the people that star in their own UGC, they have showed themselves for what they are while at the same time trying to be something they're not.

By the way the 413 (that’s right) YouTube comments on this are priceless.

The State of the State: Afterthoughts on SES San Jose

Online marketing and in particular search is still very much a nascent insurgency. I try to remember that. But at the end of this latest SES, after I had the chance to talk with the leaders in strategy, technology, analytics as well as reps from the engines themselves I walked away (once again) with a sinking and frustrating feeling that few if any large companies or ad agencies are playing this game on the highest levels. As upstarts continue to make road kill of the old media world of publishing & entertainment and search has forever changed the auto and real estate industries (among others) I wonder what these woolly mammoths are waiting for.

Certainly most of the large consumer businesses are lost. As I exemplified in my presentation on Branding and Search, P&G and Coca-Cola clearly don’t get it. Here are two companies with the resources to do ANYTHING they want online and through search yet their marketing efforts are lame attempts at the CGM flavor of the day.

The good news is that the naivete, cold-feet, or whatever is at play here with the masters of industry, has no effect on us. As an industry we have an insatiable desire to keep accelerating the pace of innovation. So while some companies just leech off of search, others truly innovate around it, behind it, through it and with it. Possibly the most innovative of these businesses in the past few years is Kayak. Clearly the best vertical search engine because of its use of the 2.0 technologies available to developers and marketers to improve user experience and deliver relevancy, Kayak is changing consumer behavior. That only means more road kill is on the horizon.

Because of Kayak I’ve purchased flights on a few airlines I had never even heard of, not knowing before Kayak that they flew routes to the cities I was going to. So airlines and users benefit from Kayak’s great functionality and ability to deliver relevant information. The unfortunate part for me is that I still need to go to Kayak when ninety percent of the time I fly on Continental. I would think by now, with all that Continental knows about me and my Elite Gold status I could just go to Continental.com and feel like they would provide me the most relevant and easiest user experience in finding and booking flights. They don’t. All those partner airlines Continental has, well they don’t even link to them from their site.

But I can't get Coca-Cola out of my mind and as I'm flying home from SES I'm thinking...maybe it's my problem? I know I'm ahead of the game, they'll catch up in a year or so. Then, as I get off the plane from SES and check email I come back to my senses. Sure enough there was an RFP waiting for me in my inbox. A relatively new site, but one that you may have heard of, is about to launch paid marketing initiatives for the first time. Their RFP calls for what I would call an agile marketing platform (based on the concepts of agile design) to enable user segmentation, A/B testing, multivariate testing and targeted content delivery to be embedded from scratch into new landing pages and the conversion flow experience. I hope we get the job not because it is a great company, or that it is a large project, but because I get excited and passionate about working with companies that are smart enough to play this game at the highest levels…and will reap the highest rewards.

But I'm still left to wonder how long will it be until the Coke's and P&G's of the world step-up? Maybe the better question is, how long until an upstart or rival employs some highly strategic online marketing to cause serious hurt to one of their business units? Time to wake up big fellas. The game is on.

The Quality of Web Analytic Data. Or, why you need to be doing High Impact Segmentation

Avinash Kaushik of Intuit had a great post recently on the poor quality of web analytic data. A side story to me was how much better the amount and quality of data we have for online marketing is over every other measured medium. As we look more and more towards this data and the quality of it to define audiences and behavior there is an important optimization concept that emerges. There is also a lesson of failed web 1.0 thinking and 2.0 simplicity.

Think of any time you’ve compared data sources measuring the same metric. How many times do the numbers match? Never. How often are they within 10%? Probably, not too often. It is because of the questionable quality of data that you can’t too sharply define, cluster or segment for personalization and targeting. Data discrepancy dictates that segmentation must be done at high source levels to ensure confidence and reduce margin of error.

No problem here though. The greatest value in segmentation is found at higher levels in the food chain. Test where the impact is greatest. It’s likely that segment will be pretty large. An additional benefit is that with all that traffic at those higher levels you need a relatively short amount of time to get signal. It is a fast and simple way to test and lends itself to continued iteration forming the backbone for Relevant Design and Agile Marketing methodologies that I encourage you to think about for your business or clients.

So what was the lesson here? Take a look at all those personalization companies from the .com bubble. Where are they now? The first issue is that they had no testing platform. They weren’t agile. So all the great personalization ideas, well nobody knew how effective or relevant they were to users. But really I think it was that they sliced their ideas and concepts to thin, focusing and delivering personalization on meaningless and non-relevant micro levels (Welcome back Rick!) when larger issues like delivering content users have told you interests them from their click path were simply not possible (beyond Amazon and a few others) with this large, heavy 1.0 enterprise software.

New ways of thinking always encounter resistance. But more and more of the smartest people in optimization are moving toward agile strategies using high impact segmentation. The web is undergoing a revolution in the delivery content and experiences will continue to become more and more relevant. Anyone who is optimizing media by segments and sending and testing targeted content delivery has a competitive advantage. For how long is unknown. What I do know, is at some point in the next few years we’ll wonder how we ever delivered relevance without segmentation.

Testing and Optimization for the Holidays

It's over 100 degrees today in New York City however my mind is thinking about freezing cold mall parking lots that don't have a parking space. What does that mean? It means that now is the time to start optimizing for what will likely be the largest online shopping season ever. So, where and how do we begin our efforts?

I’m often confronted with companies that want to get the answers to many questions in a single test of their landing page or ad. Of course, there are companies out there pitching that methodology and it may seem like a great idea. It’s not. The best testing should be simple, iterative and focused on answering a single question. This will naturally lead to more questions. That’s great because testing should be an ongoing and fundamental part of online business.

Testing should also be isolated as much as possible. Everyone from scientists to programmers has long understood the benefits of isolated environments for testing. This helps separate the signal from the noise…a phenomenon of outside and often uncontrollable factors influencing the test. The more outside factors you can remove from the test equation the more confident you can be that your findings are accurate. And if you can get a large enough data set in an isolated setting you can be confident with the answers to even the most difficult questions.

Let's say an online retailer wanted to optimize their customer funnel to increase conversion and revenue. They probably have an extensive site hierarchy that includes top-level pages, category pages, sub-category pages and product pages…and then of course the checkout process. This is a long funnel and there are many factors (noise) that influence a conversion.

The best strategy for them would be to divide each step in the funnel-flow process (and forget checkout at the moment) and create test plans for each page with a single question to be answered. What works best getting the person one more step closer to conversion? So instead of one big multi-page test we would run four separate tests.

Additionally, if we take each step of the funnel and optimize it in isolation we will make a greater impact by not only improving it an overall manner but also optimizing the funnel for where and how users are entering it. This is very important.

For example, will users coming to these pages on deep linked PPC ads behave differently than users coming from the homepage? Which pages from what AdGroups and keywords does the search traffic like best? These are great questions. By segmenting out our test groups we’ll have answers to these questions and more in only a few weeks. Best of all, should we find that not every segment likes the same messaging, creative and content, we already have our JavaScript in place from the tests to deliver targeted content.

It’s important to mention again, and this really the takeaway I hope you get…testing is an iterative process. Start out with a simple A/B..N test and then move into a multivariate test on the winners. Test results down to the keyword level against different traffic sources (search, direct, media) and user stage segments (first time visit, return, customer, etc.). Once satisfied with a great page dynamically deliver the winning content for each source and segment. Sound simple? It is.

The results of this testing and optimization process will have a huge impact on conversion. For large retailers we would be looking at millions and millions of dollars this Holiday season in additional online revenue. Now that’s a simple result everyone can understand.

Here's another great post on Holiday Shopping optimization courtesy of Matthew Roche: