Posts Tagged ‘PPC’

Here are Harrison’s tips on what NOT to do on an PPC campaign – a follow-up post to his tips on how to optimize a PPC campaign.

• Don’t content and search ads in the same campaigns. On search CTR (click through rate) is important, but not on content. On the content network you’re interrupting people, on search ads people are actively looking. The ads must be written differently depending on who you’re targeting.
• Don’t set up campaigns with only one ad group, a ton of unrelated terms, and one generic ad.
• Don’t use Dynamic Keyword Insertion with too much abandon. Be sure your ads still make sense. He also says: “You can dynamically insert the ad, search/content, and a couple other tracking variables in your destination url.”
• Don’t limit your negative keyword lists – come up with a whole list of synonyms and be creative to avoid paying for ads that have nothing to do with what you’re selling. He uses the example of online dating – you think romance – searchers may be thinking science (as in “carbon dating”). Exclude the content network sites that don’t convert.
• Don’t wait until your campaign is perfect before launching. Launch first, then use the data to continually improve.

OrangeSoda runs PPC campaigns for small businesses – we have a very low entry point and serve this part of the market that most companies won’t touch. We also manage PPC campaigns for larger accounts that involve a lot of customization. However, if you want run your own campaigns, be sure to avoid the common mistakes listed above (or if you can’t avoid them, at least learn from them!).

Sometimes businesses or marketers dream of a “secret sauce” to doing SEO or PPC. Most of the time there is no “secret sauce.” There are tools and software, and they give an advantage, but usually it’s knowledge and work that really count. It’s not a cakewalk and it’s best learned when you’re passionate about what you do – (hat’s where we at OrangeSoda comes in).

Shoemoney posted a great article about optimizing your PPC campaigns by 16 year old super affilite Harrison Gevitrtz. He’s an affiliate marketer – so he makes money selling other people’s things for a commission. It also means no results, no paycheck. So I generally trust affiliates.

I call Harrison an affiliate baby – one of those kids who makes more than their parents (Harrison nets 6 figures). I’ve heard stories how parents call up Commission Junction asking why they’re sending their kid a check for thousands of dollars every month. It happens. It’s fun to see the play that Harrison brings to his work.

First, a great quote: “You’ll perhaps be amazed that there are no “secrets”. It’s not because I’m not telling you— rather, it’s a ton of hard work and a little bit of luck. It’s amazing how “lucky” you get when you work hard. Don’t believe the “get rich quick” scams that would have you believe a single piece of magic software or a single technique to find the right keywords is all you really need.”

I’m going to summarize the best points.

KEYWORDS – Quality over Quantity

• Don’t load up your account with a large list of keywords. You’ll get penalized for having low quality keywords in your ad groups.
• DO pick a few high quality terms per ad group. Group them by subject. Make sure they are relevant to the ads that will show for that group.

PPC ACCOUNT MONITORING AND OPTIMIZATION – Use your anayltics program and check bounce rate

• Test your keywords. Run your campaign for a day or two (less if there’s lots of volume) and then look at which terms are driving the most volume. Do this by sorting keywords by click volume – in  descending order, using AdWords Editor.
• Find out what keywords are driving the most clicks and the best quality conversions. Look at your ad groups and see what is performing best. Use that to create variations of the successful campaigns. Try other match types. Increase bids, etc.
• Remove keywords that aren’t getting impressions or clicks. Also, cut ads that aren’t working.
• When testing campaigns, choose the campaign setting to have ads rotate equally– don’t let Google choose. “Your profit is how many clicks you get times how much you net per click– it’s an inverse relationship, unless you are bidding on tail terms or perhaps certain branded traffic.”
• Use your analytics data to get the bounce rate for your landing pages. If it’s over 60% cut it or optimize it.
• Look at your own web site to see what organic terms people are coming in on. Add them to your PPC campaign. Conversely, create pages for your best quality PPC terms on your web site.

He doesn’t use the Google AdWords API or Google Analytics. Here’s what he has to say about that:

“I rarely even use the Google Adwords API– but do in cases where there is enough volume to make it worth putting automated bid management in place. You do get dinged on using the API, for those who don’t know, so AdWords Editor is a more effective prototyping tool. Once you have something stable, then you can consider scaling it to the moon and using the API.”

I’ve heard conflicting feedback from another super affiliate who does use Google Analytics. Also, he is pushing offers for other companies as an affiliate. Thin margins. I’m not savvy to if there is a drawback to using Google AdWords API. This is something to explore – there are probably tradeoffs to each way. If you’re an individual running your own accounts, this may be a luxury.

He recommends Tim Armstrong’s book on landing page optimization (does he mean Tim Ash??) and promoting related products on your landing pages. And, after a lengthy post, he jokes that he should write a book. I think that’s a great idea – but hire a good editor!

Since this is already long, I’ll summarize what Harrison says NOT to do on your PPC campaign in the next post. Thanks Harrison for sharing your knowledge!

Like SEO, web analytics is not as clearcut as many would like. Unfortunately, there is no standard that all web analytic companies follow. And here’s the even worse news: without a “standard” there can never be reconciliation of web analytic data.

Why not?

Because every program defines a visitor, a bounce, and a click, differently. So when it comes to web analytics this holds true: “The trend is king when analyzing web analytics data.”

There are general guidelines that may help make sure you’re comparing data from two different site tracking information. Here are some important questions to ask.

1. Are both analytics tracking codes implemented correctly on every page of the sites?
2. Are the reporting date ranges the same?
3. Is the same page of the website being reported?
4. Is the bounce rate an isolated metric? Are there also massive differences in the number of visitors to the site, or other statistics?

And the final kicker…

How does the web analytics program define a bounce?

What is the difference in the definition of a bounce for each program? One program might define a bounce as someone leaving after 5 seconds, another 10 seconds, etc. This could result in a big difference. And there are many other variables that can create large discrepancies, in fact, some programs allow the web developer to define their own parameters of a “bounce.” Because of these reasons and the fact that this information is usually propriety, it is not possible to reconcile data from different analytic programs.

If we look at the trend then the differences don’t have to be a problem, but can be complementary. However, those that like to deal with absolutes, this is a hard pill to swallow. It certainly doesn’t make our clients happy and some threaten to cancel unless we can reconcile web stats. It’s not something we’re going to take on but we can guide our clients through to try to make sense of the information.

The bottom line?

SEO and PPC is an art form that are always chasing a moving target.

This post was written by Clint Eagar who previously worked for web analytics company Omniture. I asked him to write it after some complaints about numbers on our tracking not matching the client’s tracking system.

This is a common question – how do you reconcile the differences in web stats. It seems like every analytics program comes up with a different number, which can be frustrating for businesses of all sizes. It’s also a problem with paid search because the numbers you see from your PPC analytics may not match up with the numbers in Google.

OrangeSoda recently hired Clint Eagar who worked for web analytics firm Omniture. I asked him to write a post to try to demystify the discrepancies that are common between different web analytics tools.

I get a lot of questions about why there is a variance between how different web analytics packages report traffic results.

It’s All About Cookies
This has to do with how an analytics vendor uniquely identifies a visitor. Most analytics providers uniquely identify a visitor by a persistent browser cookie. When a visitor comes to a website the analytics code checks to see if the cookie exists. If the cookie does not exist it attempts to place it.

If it cannot place the cookie many analytics providers will ignore the entire visit. A large portion of the discrepancy between analytics providers comes into play when a web site cannot place this cookie. Some vendors will build a unique visitor cookie by combining user-agent and IP address. Some analytics vendors use third party cookies to uniquely identify visitors while others set a first party cookie and some visitors have their browsers configured to not accept third party cookies.

Establish Analytic Metric Definitions
The next thing you need to understand is how each analytics vendor defines a page views, visits and other metrics. One vendor may define a visit as a user session that lasts for at least one minute. Others will count an additional visit if the visitor views a page and then leaves the page idle for more than thirty minutes.

So, for example, say you’re reading a news story at CNN.com and get about half way through the article then you head out to lunch for thirty minutes and then come back to your open browser, finish the article and then click to read a new article. This will count as two visits – not one. Some analytics vendors will count this as only one visit. How does your provider track a visit?

How is a unique visitor defined? Is it a daily unique visitor (a visitor that is unique to the site today)? Is it weekly (a visitor that is unique to the site this week)? Is it monthly, etc? I think you get my point.

Tracking Code Execution
Other obstacles to having perfect harmony between analytics vendors could be loading time of site and the location of the tracking code JavaScript, does it load before page content or after. Did the visitor close the browser or click back button before the JavaScript had time to execute?

Web Analytics Is About Trends
Trend is king when analyzing web analytics data. More important than squabbling over a ten percent difference in how Google Analytics or Omniture reports a visitor you should instead be questioning: How many visits to do I have this week compared to last? How are different referring domains driving conversions over time?

Ultimately the differences between analytics vendors is just noise and you should never (did I say never?) attempt reconciliation.