Well, we’re getting there. We’ve previously proved visitors clicking on a paid listing are of higher quality than “free search” visitors for the same search term, and now we see there is also significant variability in quality of visitor by the term itself, according to the last chart. Look at Customer Loyalty (CL). Much shorter visits, and lower download and newsletter subscribe percentages, but much higher bookmarking percentages. What could this mean, why the difference?
The stats above are a combination of all visitors for the same terms from both Google AdWords and GoTo, so it seems logical the next “Drill Down” would be to look at each source individually, and that is just what I have done. For clarity, instead of creating two charts and having you bust your eyeballs trying to compare them, I have created a ratio between the Google and GoTo numbers.
If you were to read down the Relationship Marketing (RM) column, this chart says:
“For the paid search term Relationship Marketing, the Average Visit Length for visitors from Google is 65% that of GoTo, the percent one page visits is 110% that of GoTo, the percent Downloading is 48% that of GoTo,” and so on. A number over 100% means Google is higher than GoTo, under 100% means Google is lower than GoTo.
One thing is perfectly clear from this chart – Google dramatically under-performs GoTo for the paid search term Relationship Marketing, and outperforms GoTo on the paid search term Customer Loyalty, across the board, in every category (note a lower number on % 1 Page Visits is better).
Things are less clear-cut for the term Customer Retention, although I’d have to give it to GoTo because Bookmarking and Subscribing to the newsletter are highly correlated to future purchase of a book.
Where does this leave us? Overall, it appears you can not attribute “quality” as defined here to either a search term or a search engine; there is a combined contribution which creates dramatic visitor quality differences. This is a perfect example of the mistake people make when using “averages” or looking at the “average customer” – rarely does the average customer represent the true underlying behavior of the actual customers.
Tactically, it means I should budget paid search expenses by term by engine, and in the case above, shift most if not all the budget for Relationship Marketing to GoTo, and most if not all the budget for Customer Loyalty to Google. Customer Retention might need a little more work to resolve, but instead of running the budget 50 / 50 as initially set up, it would make sense to maybe run 70% on GoTo, and 30% on Google, from what I see here. Hey, it doesn’t always come out black and white, you know?
As far as why this occurs, it’s fun to speculate, but a marketing behaviorist cares more that it does happen – it’s a fact, Jack – and takes action based on this fact. There’s plenty of time to wonder about it later, after the spending has been reallocated and the highest ROI possible is being realized.
A “gun to the head” guess? It’s the content at the other end of the click making the difference. The content on the Customer Loyalty page appeals more to a Google user, and the content on the Relationship Marketing page appeals more to a GoTo user.
Why? I haven’t got a clue. Check them out for yourself:
Customer Loyalty
(favored by the Google user):
Relationship Marketing
(favored by the GoTo user):
Let me know what you think. If the responses seem to be trending one way or the other, I’ll present the arguments in the next newsletter. Meanwhile, the idea of content making the difference (a 3rd variable in addition to term and engine?) is kind of interesting – maybe there’s a way to test the idea.
One thing was perfectly clear from this chart – Google dramatically under-performs GoTo for the paid search term Relationship Marketing, and outperforms GoTo on the paid search term Customer Loyalty, across the board, in every category (note a lower number on % 1 Page Visits is better).
Things are less clear-cut for the term Customer Retention, although I’d have to give it to GoTo because Bookmarking and Subscribing to the newsletter are highly correlated to future purchase of a book. This analysis brings up an interesting question, though. What is the effect of the content searchers land on when clicking on a search item? Could the variances above be at least partially explained by a good or poor match of the content with the expectations of the searcher? How large could this effect be, a double or a triple in response?
That’s what I tried to find out, by sending all these searchers to the same page – my home page, which covered all three subjects in a generic sense, and had prominent links to the same pages searchers were sent to previously – Custom Landing pages written to match the search term used. Note: The current Home Page is different than the one used when this test was run. The Home Page used in the test was similar to this page with links to the Custom landing pages displayed prominently at the top of the page.
The chart below shows the conversion metrics of visitors for my three primary search terms – Relationship Marketing, Customer Retention, and Customer Loyalty – when they are all sent to the Home Page (far left column) and when they are sent to a Custom Page designed to reflect the search term they were using (far right column). Also provided for comparison are the same metrics generated by All Search visitors and All Google search visitors:
If you were to read down the Home Page column, this chart says: “When visitors searched the terms Relationship Marketing, Customer Retention, and Customer Loyalty on Google and GoTo and clicked through to the Home Page, they stayed an average of 3.35 minutes, 39.9% viewed just this page then left, 3.19% downloaded a book sample, 3.72% bookmarked the site, and 3.19% subscribed to the Drilling Down newsletter (which you are reading now).
But check out what happens when they land on a page designed for the topic they were searching. Shorter visit (bad), higher abandonment (bad), higher download, bookmark, and subscribe (very good, since these stats directly correlate to future purchase of my book).
What does this mean? Can we reconcile the “bad” and the “good” in terms of the behavioral marketing approach?
Well, sure. Two possibilities come to mind:
1. When I dump highly targeted visitors on the generic home page, they stay longer and view more pages *looking for what they came to find*, but a higher percentage then leave without engaging in the desired behavior. When I take the exact same traffic and dump it to Custom Landing Pages, they stay for a shorter length of time and view fewer pages, but they download, bookmark, and subscribe at a much higher rate, because they found exactly what they were looking for.
2. It’s also likely the targeting of the Custom Landing page itself is causing shorter visits / higher abandonment. In other words, a visitor types in “Customer Loyalty,” a pretty generic concept, and lands on a page with a specific view on the search term. It’s more likely this specific content differs from what was desired by the visitor *relative* to the Home Page, which by nature is meant to have a generic appeal. The generic approach gets the longer visit and deeper site penetration relative to the specific approach, but also ends up driving away the specific visitors I am looking for (those who might want to buy a book on measuring and tracking loyalty metrics) at a higher rate.
This kind of effect is seen quite frequently in direct marketing efforts; the more targeted you get on the front end, the lower the “initial response” but the higher the “final conversion” to the desired outcome you are looking for. The results may seem intuitive to you (give them what they want and they respond at a higher rate) but you don’t know for sure until you measure the effect. To maximize the ultimate conversion of the whole site, you have to find the “perfect balance” between the initial response and final conversion to the desired behavior.
Did you notice how the stats get better and better as you read from the left to the right of the chart? Scroll up and look at it again. Weird, huh? Almost mystical in consistency. I get better performance from natural search traffic than I get from driving highly targeted (and paid for) traffic to the generic Home Page. And “natural” Google traffic is even better than “All Search” engine traffic. What does this mean?
That’s right, you guessed it. I’m going to have to go down another layer and find out what the heck is going on.
Do the different engines really deliver traffic all that different in quality? Google is a bit of a strange bird, because it is currently a media favorite and never got into the “portal” business. What about all the other search engines?
Here’s what the “action behavior” (behavior leading to book purchase) stats look like on the rest of them, in order of the percent of traffic they deliver to my site:
Hmmm. Sure are different, aren’t they? There’s frequently a difference of double or triple in the same metric across the engines. But traffic also matters. FAST delivers great overall stats but hardly any traffic, so I should probably look into what is going on there.
And I will. Fortunately, you will be spared the results, as this is the promised end of the series on analyzing web logs. What did we learn? Keywords, landing pages, paid search links, and the search engine itself all have a tremendous impact on the quality of your visitor traffic. Not just “an impact,” but a huge impact. All traffic is not created equal, and if you are not doing this kind of analysis for your site, you are undoubtedly wasting resources chasing what you think is working, as opposed to what you know is working. My advice – let the behavior of the visitor tell the tale.
Make sure to download and try the free visitor metrics calculator, it works with just about any traffic analyzer and contains 22 more metrics like the ones above. Not all of them will apply to your web site, but you will probably find many of them do apply to your site. If you really want to get serious about this area, check out the book on creating / using visitor metrics.
Visitor metrics are all about getting customers. Once you’ve mastered visitor metrics, some of you might be interested in making more money from and keeping customers; that is what my other book, Drilling Down, is all about – the metrics you need to create and track High ROI customer marketing programs.
Jim Novo has nearly 20 years of experience using customer data to increase profits. He is co-author of The Guide to Web Analytics and author of Drilling Down:Turning Customer Data into Profits with a Spreadsheet. If you want more visitors to take action on your web site, try using the free conversion metrics calculator, downloadable here. If you need to sell more to customers while reducing marketing expenses, get the first nine chapters of the Drilling Down book free at http://www.drillingdownbook.com.
