Google Insights for Search – A Primer (Part 1)

If you’re looking for insight into the mind of the average internet searcher, (or, in this case, the aggregated minds) you have probably already stumbled across Google’s aptly named Insights for Search (which is of course, BETA!). While far from a comprehensive solution, it’s price tag results in a tool that can yield some very cost effective insights.

Unfortunately (and somewhat intentionally), Google has made Insights for Search a bit of a black box, with the data stripped of any meaningful scale aside from relative to what’s being compared. That’s not to say that you can’t draw some meaningful conclusions, so long as you have a thorough understanding of how the tool works. This post is the first in a series aimed at giving you such an understanding. Nowhere else have I seen this much detail on Insights for Search in one location; I put this guide together by piecing information from a variety of sources.

Last, if you find something you disagree with, or know is outright false, I’d love to hear about it in the comments.

So here we go!

Part 1 – What is Google Insights for Search Anyway?

The Digital Tea Party

A little over a month ago, Republican Scott Brown pulled off one of the biggest political upsets in recent history, overcoming a 30+ point deficit to win the vacated seat of Ted Kennedy in a special election in a heavily Democratic state. One month prior to that, virtually no one had heard of him.

Much has been written about what happened in that month, and at some level it’s safe to say that Brown’s campaign embracing the digital space above and beyond the traditional political campaign played a major role in his success. But what is up for debate is whether or not his tactics should have other campaigns rushing to imitate. After all, there’s only so many hours in the day, and so many days in the week.

If every election had similar conditions to the one between Scott Brown & Martha Coakley, the answer would be pretty straightforward: candidates should be investing heavily in social media, leveraging rapid, cost-effective platforms for interacting with broad bases of support.

But the Scott Brown election was special, and while other elections might share some similarities, the following conditions combined into the perfect storm for Scott Brown’s digital revolution:

Dirty Traffic

Have you taken a peak at your traffic today? Is it up? Yes? Good.

Or is it?

What did you look at to determine if your traffic was up? Hits? Assuming even a mild sense of internet sophistication, hopefully not. (If you did, quickly acclimate yourself to How Idiots Track Success, and then grab a cup of coffee with good old Ted).

Maybe you looked at visitors? Unique page views possibly? Time on site? Bounce Rate? Pages per visit? These metrics are getting warmer, but still not quite there…

Think Like a Hardware Store – Capture Customers During Discovery

Here’s something to think about over lunch: What are your customers thinking when they visit your website?

I’m not referring to their opinions on your color pallet or whether or not they like drop down vs. static menus. Think bigger picture. When someone steps into your website, what mindset are they in? Do they know what they’re looking for? Are they ready to purchase as soon as possible? Have they even heard of your company before?

You might be thinking that the average visitor is in ready-to-purchase mode when they hit your site, and that could actually be reality. But I would like to pose that you consider changing the average mindset of your visitor in the name of increased revenue (and profits, of course!). Travel upstream in a customer’s journey to their purchase and drive them to your site during their discovery/exploratory phase. Why? More after the jump…

Is Your Branded Search ROI Fact or Fiction?

AdAge Digital has an interesting article on the effectiveness (or supposed lack of effectiveness) of paid search for online retailers.

Less than 10% of online retailers’ web traffic, on average, comes from search engines…

…the majority of retailers’ web traffic (61%, on average) comes from people going directly to a retail site — consumers typing, say, Amazon.com into a browser address bar.

…many people use search for product research, which influences their behavior down the line. He illustrated an example: You search for a red cashmere sweater, looking for who has the best deal. You see J. Crew has it for $119 and Neiman Marcus for $329. You don’t buy it then but later head over to jcrew.com and make the purchase.

So what’s the answer? Are consumers really steering away from non-branded paid search because retailers like Amazon have such massive brand presence? Is branded search ROI significantly higher than general search terms? Should you adjust your marketing investment away from general search terms, or away from paid search completely? In short, no.

Tracking Yahoo Search Marketing & Microsoft adCenter in Google Analytics

Search engine marketing can be an effective tool in your digital marketing tool box, so long as you can completely understand how your spend is affecting your business goals. If you can’t, you may be throwing hundreds of dollars a day away on visitors who aren’t converting, and as a result, drastically lowering your ROI.

If you’re using Google Analytics, your paid search efforts will not automatically show up correctly in your traffic stats. Google Adwords is the easiest to fix by simply clicking a check box in your AdWords account settings to link to your Google Analytics account. Yahoo Search Marketing and Microsoft adCenter are a bit more complicated. Both offer placement in search results and on their respective content networks. In Google Analytics, search results placements will be recorded incorrectly as organic traffic. This is a lose-lose – you gain no insight into the actions of pay-per-click visits and muddle your understanding of your organic search performance. Similarly, content network placements will show up incorrectly as referring sites. Not quite as detrimental, but equally useless in determining cost effectiveness. The good news is, with a little bit of work, these problems can be overcome.

Step by step guide and a before and after example after the jump…