Web Metrics | Search Marketing
Site Strategy

"In a nutshell, Jason created our marketing analytics capability. He was able to figure out what data we collect, where it is, what was missing, and hook it all up so we canget meaningful, actionable data. Our marketing efforts have improved leads and conversions in some cases by an order of magnitude. He knows his stuff."
Chris Foleen, Marketing Project Coordinator, TransCore, Inc.


Friday, July 23, 2010

Test Results: First vs. Last Touch Keywords with Google Analytics

The idea of what the value of topical search is in a situation where branded phrases clearly dominate the conversion metrics is not a new one.  This is a big motivator for multi-touch tracking.  I wrote about SEOMOZ's article on multi-touch keyword tracking previously, and this got me thinking through how you would actually implement first and last touch tracking in the current Google Analytics platform.  So, I made some changes to the tracking script and pushed it live. 

The results of my first and last touch keyword attribution test were not as robust as I'd hoped.  The usable data set was much smaller in the end than I was looking for. After filtering out all the things you can't use, you find this type of analysis really applies only to a small group.  Mostly this is becuase I was primarily interested in the cases where the first touch keywords as different than the last touch keyword.  The ones that were the same were not as interesting to me.  that being said, seeing the difference in volume was eye-opening.

A custom Google Analytics tracker was created and placed on a website for 30 days.

The test was to see:

1. How often visitors returned to the website on a different keyword.
2. How often topic initial keywords led to brand keywords on repeat visits
3. How first vs. last keywords differed in general.

During that time, 860 visits were tagged from google search with a custom variable that captured the first visit's keyword. 57 visits were scrubbed for weirdness.

459 visits were recorded as 100% new and were filtered out.

After filtering 100% new visits and funky data, the working data set was 344 visits.

264 visits were tagged as having identical first and last touch values.

80 visits showed different first and last touch keywords. (23%)

Of these, 61 showed a branded first touch keyword and 19 showed a non-branded keyword.

Branded First Touch Keywords
19 out of 26 distinct first touch keywords were some kind of branded keyword with many mispellings. Of these, the second touch keyword was set by google analytics as "not set" in 16 cases. In 100% of the remaining cases, the second touch keywords was a branded phrase of some sort, usually very related to the first touch phrase.

Stacked bar showing the volume of visits relative to each other.
The visits that were most relevant to this test turned out to be a very small percentage of the total.

Non-branded First Touch Keywords
In the remaining cases, "not set" as the last touch keyword became more common (12 out of 19). In the remaining 7 cases, a little more than half (4) had a branded last touch keyword.

Summary and Next Steps
Overall, when thinking about how topical phrases and brand phrases interact with each other, you're really talking about a strick minority of the overall visits to a website. This perspective raises the question of how much this type of analysis really worth at the end of the day. But if you are really interested in web traffic behaviour like I am, you do it anyway because:

1. Finding out that people are most likely to keep finding you in the ways they have already found you is interesting and helpful. They are unlikely to change the way they think and find you.

2. Understanding that if you do want to change the way they think and find you, the path of least resistance is moving from topic to brand, not from brand to topic. No one who used a branded phrase returned on a topical phrase, but the other way did show some movement. This can be important for how you position a product in marketing because, in my mind, this represents more of a bottom up approach, rather than a top down approach.

Next steps are really to get a bigger data set. Reliable conclusions are hard to claim when looking at such a small group. Also, I want to factoring in conversion rates to determine traffic value would add more context. So, more testing is on the way!

Thursday, July 08, 2010

Brand Marketing, Web Analytics, Social Measurement, and the Future

So often the topic of branding and marketing is coming up for me that I almost can't believe it.  It seems like this is the thing everyone is trying to understand right now. I think it all started with social media and people trying to get their arms around what the value of it is.  If there are 28 million tweets flying across the internet every day, that must represent some kind of value, right?  The answer was assumed to be YES, and analysts when to work trying to find it.  

But the answer has been elusive because it is a different answer than what people expected. Tweets can skyrocket.  Visits from Facebook and Twitter and jump.  Sales can stay flat.  Sometimes there is a direct correlation with sales, but a lot of time there isn't.  I don't think this is what many people expected.  I know it is not what I expected.

But no one stopped there.  If social doesn't drive sales, and we believe that it has values, then we just have to keep looking for what that value is.  

The Social Media Situation
Jim Stern's book on Social Media Metrics is wonderful at working through this.  For all us bean counters, he gives exhaustive lists of metrics that can be used to measure social media.  But, to be honest, there are so many metrics it is almost like a sarcastic joke saying "You can apply almost any metric to this".  There is just no guarantee the numbers will be what you want to see. 

But there is a way to make more sense out of it.  In talking through measuring outcomes, Sterne mentions that social can be used to see "storm clouds on the horizon" (p.115).  In this way, tracking social sentiment is like weather forecasting.  Although everyone knows how unreliable weather forecasting is, it is still useful as an early indicator of where things may be going in the (near) future.  This is important because when that future becomes the present and you need to engage in actual revenue generating activities, your results may be better or worse than expected. If you can get some advanced warning of performance, then you can plan accordingly.  This, of course, is very useful if there is negative sentiment to be overcome. New messaging can be created in the next campaign and hopefully the tide can be turned and that campaign will do better than expected.  Sterne goes on at length about this in his book, several times.

How Branding Fits In
Branding seems to fall strongly in line with this approach.  Brian Lesser wrote an interesting article on branding measurement and expectations that perplexed me at first.  He writes:
A variety of branding campaign goals can be measured, including how a campaign reaches an audience beyond the advertiser's core customers, how it lifts brand awareness and recognition, and how it drives traffic to the website...
More importantly, the click-through and conversion metrics that are central to measuring direct response campaigns are almost irrelevant for most branding campaigns
I have to say it was a bit perplexing to me, because you can't pay the bills with good intentions.  At the end of the day, revenue and profit keep the lights on.  Avinash Kaushik recognizes this in "A clear line of sight to net income."   Stern devotes more than one chapter to it.

If you own an apple orchard, it is great to know how the summer weather is going to help or hurt you, but at the end of the day, no matter what, you need to sell apples. 

This last part seems to be not only left out of so many of the conversations on branding and social media, it is almost violently ejected from the conversation.  This seems like a huge mistake to me.  

Business intelligence needs a business to support. It cannot be an end unto itself.  But the conversations are seeming so polarized to me, especially lately.  

Why does Lesser disconnect brand from conversions?  I'm not sure, but my guess is that he intends it to be seen only as a part of a bigger picture, and not be mistaken for a complete approach unto itself.

When I think about where to go with this and how to use it in a cohesive way, it seems that there are a couple takeaways:
  1. Don't ever forget that revenue is the goal.  Conversion metrics matter.  You gotta sell apples.
  2. People will not buy your product if they do not like your company (usually).
  3. Understanding what people think of your brand is like weather forecasting and there are new tools coming on the market almost everyday that can help you read the horizon.
  4. AFTER you have an idea of what is on the horizon--what the marketplace thinks of you--use branding to build on strengths and address weaknesses.  Continually do this--monitor and message--as long as you need to and/or can afford to.  Measurement is critical.
This stepped approach seems to make a lot of sense.  

Measuring sentiment leads to brand messaging (and social outreach) which helps fertilize the ground for response marketing that drives sales.

When used in this way, brand and social activities fit nicely into the revenue generation process.