Over the past couple of weeks I took on the role of SEM madman. We hadn’t focused on our own paid search in far too long, so I took it upon myself to dive in. In the process, I applied many of our age-old best practices and made up a few new ones along the way.
Here’s a recap of my experience in narrowing the top of our search funnel and matching messages through the post-click experience:
Getting (Strategically) Organized
First and foremost, we had to define and codify what we were looking to accomplish with our paid search campaigns. We were armed with tons of data, but needed to parse that down to something usable and actionable. I tapped our own site analytics, Google Trends, Wordtracker, and our historical paid and organic keyword performance to form a picture of where we were and where we need to go.
Since we are, to some extent, defining the post-click market, our panorama of potential terms and messages is wider than most. We have to look under more rocks.
I ended up with seven high-level buckets of terms. Within those seven buckets were 40 unique messages. For each message, I wanted to test a minimum of two ads and two post-click experiences (landing pages).
At the highest level, our objective was to improve the quality of respondents from paid search. This included the understanding that fewer people would click, but that better people would convert.
I created an Excel workbook with a sheet for each of the seven campaigns. Each sheet included four columns: keyword; ad; character count; and click-through URL. Each keyword had its own row and there were many keywords within a message. (A message is simply a group of keywords related enough that they can have the same ads and the same post-click experiences hooked to those ads.)
Whenever I wrote an ad, I split the ad-column row into four so I’d have each Google line in its own row: headline; description line one; description line two; and display URL. I then used a formula to automatically count my characters in each row and warn me whenever I exceeded Google’s maximums.
Each message was delineated from the others by blank black rows. With this workbook as my canvas I set out to write my ads. On average, I wrote three ads per message (about 120 altogether).
A page from the workbook can be seen above right.
Taming Chaos with Consistency
What happens in a lot of search marketing campaigns is that the pre-click message gets separated from the post-click message. This is often because the two camps are entirely separate departments or even organizations, but it can happen even within one department. One way to minimize the chance for that disconnect is to name the messages and carry those names through the campaigns. So that’s what I did.
Each message name was used as the name of the Google ad group and the name of the LiveBall traffic source. This way the ‘landing page software’ ad group hooked up with the ‘landing page software’ traffic source and the gods smiled. It’s now quite easy to see the flow from keyword to ad to landing page and visualize the participant’s context. It also makes it easier to process the analytics. Regardless of the number of ads within an ad group or the number of landing experiences tested on an ad group, the message is top of mind.
So, at this point I created a (message-named) LiveBall traffic source for each message and included its URL in my master spreadsheet. I had keywords, ads and URLs — everything I needed to load up Google. And that’s what we did next — creating a one-to-one relationship of campaigns-to-campaigns, and of messages-to-messages. Everything was paused until we got the post-click pieces in place.
Matching and Making Landing Pages
Like I said, I wanted to test at least two experiences per message, so I needed around 80 conversion paths. Of course the resources necessary to create 80 original landing experiences from scratch are enormous. I needed an unfair advantage. (Of course I already had LiveBall which is a huge advantage, but I needed another one.)
Enter my favorite shortcut — the Flash object. Using a Flash file that is built around variables (placeholders) instead of real images and text let’s you take control of everything within the Flash without ever going back to Flash development. In a nutshell, you can make incredibly polished looking ‘graphics’ without ever touching Flash, Photoshop or anything else resource intensive. You just associate images and type text — the Flash object applies fonts and behaviors for you and like magic you have perfect graphics.
Note that Flash has only recently become Google quality score friendly for landing experiences. Google and Adobe recently got together to make Flash more ‘Google friendly’ and Flash developers can now make Flash in a way that lets its text be read by Google (just like ordinary HTML). Google now crawls these Flash files and can read their content — making a quality score determination possible.
An illustration of two landing pages based on one Flash object can be seen above right.
My prototype conversion paths used two different segmentation alternatives. My initial (A) paths tested product segmentation (for us that’s platform vs. services); while my (B) paths tested solutions interest vs. ROI interest (softer than the product-segments).
For the record, our top-line mission here was to narrow the funnel and get higher quality prospects to engage. This meant abandoning the ‘FREE’ messaging (white papers, webinars, etc.) in favor of more direct selling language to attract more immediate and more qualified buyers. That said, the gorilla wasn’t being offered superfluous bananas — if they clicked and engaged, we were pretty sure they were our people.
So I had two basic conversion paths. Each experience was about seven total pages and featured 1-3 conversion points (lead capture forms for requesting an ROI calculator, requesting a platform demo or requesting contact). That’s about fourteen pages of web content for each message (A|B test). Multiply that times forty messages and you’ve got around 560 web pages. Hefty.
A screenshot showing one of the 76 landing experiences in flowchart view can be seen at right.
532 Landing Pages in 3-1/2 Days
Obviously I used LiveBall to roll out my 532 pages (using the aforementioned Flash objects) to minimize my pain. I localized each experience by matching its copy and imagery to the ad group. It took me about three and a half days to create and launch what ended up being 76 landing experiences. I did it all myself (because I am a control freak).
Our plan is to iterate challenger landing experiences as soon as winners emerge (with confidence) in each message/ad group. For some ad groups this will happen within a few days, others may take a few weeks. I’ll blog about performance and iteration as we extend the campaigns.
I’ve fielded some questions regarding testing, tracking and managing all this stuff, so I thought I’d post a screenshot of a performance view in one source of traffic (one of the 40 messages). What you’re seeing is the performance of an A/B test of two landing experiences behind keyword ads for ‘landing pages’ (the most generic and low-level of our SEM terms). You can see the overall conversion funnel (top left), the segmentation profile (pie chart, top-right) and the head-to-head landing experience performance on curves showing 80% and 95% statistical confidence. Click for a larger version.