June 2009

29 Jun 2009 01:40 am

pretty openIt is such a cliché: Don't just present data, tell a story.

Yet it is rarely followed.

We almost always present data.

Actually we don't present data, we send out reports. With data. Lots of it. With 6 size font and some pies and stacked bar graphs thrown in.

Then we are frustrated that no one seems to pat us on the back, sing songs in our glory, give us more money.

We don't truly tell stories because it seems like a lot of work. And it can be. But you'll be surprised at how often it is simply a matter of framing things differently, letting your imagination roam free.

Last month I had to present to a group of executives in New York. One of the key things I wanted to communicate was the power of not doing random advertising but rather using freely available data to target the advertising on sites where relevant audiences exist.

Goals Summary:

1. Show the power of free tools available. [Google's Ad Planner specifically.]

2. Highlight the importance spending money on advertising to relevant audiences.

3. Tell a memorable story.

Below is how I did it. . . . hopefully it will inspire you to look for stories in your data, stories that will hold interest and might even get you some smiles (and you know that a raise is not far behind!).

My first step was to try and tap into current events / pop culture. That calls for some research. I use Google Insights for Search as the best way to get a pulse on what people find interesting.

Specifically what I often do is run this query: Who are the most popular celebrities in New York in the last 30 days?

google insights for search new york celebrities

Turns out it is someone called Kim Kardashian. It also turns out I have no idea who this person is, an unfortunate side effect of not have time to watch television.

Quick Google search and I am caught up on why Ms. Kardashian is "famous". She has some overlap with Paris Hilton in terms of the path to fame.

The key ingredient for any story is to have interesting protagonists. For this story due to their popularity it will be Ms. Hilton and Ms. Kardashian.

The plot: Your business has a need to market something related to Ms. Hilton and Ms. Kardashian, a perfume or a clothing line or a cd/dvd. Amongst other things you'll want to make use of display advertising (banners / widgets etc).

How do you figure out who the right audience is, and where you'll find them? As opposed to of course buying the main banner spot on www.yahoo.com were your ad might be a hit or a miss.

Tools for doing audience segmentation were quite expensive until recently. Google's Ad Planner is free and makes this valuable data democratic. You can segment by demographic (age, education, income, gender etc) and psychographic (Extreme Sports Fan, Film Buffs, Fantasy/Comic Book Readers etc) data.

Perhaps its most cool feature is the marriage between all the above data with Google's search data.

That's where the analysis starts.

Question: What are the websites that are visited by people who have searched for the keywords "paris hilton" and "kim kardashian"?

Here's the answer:

google ad planner analysis paris hilton kim kardashian sm

[Click on the image for a higher resolution version.]

Notice the I have typed the keywords on the bottom left. In the right frame are the sites that are visited by those who searched for those two terms. Some obvious sites, many surprises (good thing, now we know!).

I have a habit of sorting by Comp Index, just to check out concentration of the audience. For example a comp index of 990 means that you are approximately nine time as likely to find the same audience (paris, kim searchers) on wallpaperbase.com.

If you look at the higher resolution version (click on the image) you'll easily find out how many page views are on the target site, what kind of advertising they accept, ad impressions/day and other data you need to create a media plan.

So far so good.

I have always believed that Men are more interested in the kinds of stories and "entertainment" value that Ms. Hilton and Ms. Kardashian generate.

The nice thing is I can validate that hypothesis. I simply open the Gender option in the left panel and choose Male.

paris kim male audience analysis

You are looking at the top part of the segmentation panel. Notice the delta between UV (users) between the overall segment and just the Males.

Turns out I was not totally right. Males make up a bit less than half of the audience.

No worries. They are still a lot bigger than what many people think (and it is wrong to think it is overwhelmingly female).

My next believe, perhaps controversial, is that older males are more interested in Ms. Hilton and Ms. Kardashian than younger males. Now this seems odd because Ms. Hilton and Ms. Kardashian seem to be more cool and hip and more of a young generation cup of tea.

Well we can test my hypothesis, in addition to Gender I can also choose Age. . .

paris kim male young old analysis

This data is still just for people, in this case Males, who searched for the key words paris hilton and kim kardashian.

It might have been a odd thing to say but it seems that 45 and older males are a lot more interested in Ms. Hilton and Ms. Kardashian. By almost two to one.


: )

Let's prep for the punch line of this story.

I have identified a audience that is of value to my goal, marketing Ms. Hilton and Ms. Kardashian (or things connected to them).

I want to target the top end of this audience, Males 55 and older, how many of them are there and where can I find them (to ensure my advertising will be relevant for this audience and my ad dollars are spent wisely)?

Here you go. . .

google ad planner older males paris hilton kim kardashian sm

[Please click on the image for a higher resolution version.]

How about now… surprised?

I was.

The top sites listed for this audience (older Males interested in Ms. Hilton and Ms. Kardashian) turns out to be bedrock sites, typically, for Republicans and the Conservative movement! Starting with a Comp Index of 1700 for impactguns.com. Other sites: weeklystandard.com, rushlimbaugh.com, nationalreview.com, worldnetdaily.com, and townhall.com.

Not in my wildest dreams would have I have expected that this audience would be so highly correlated with actual searches done for Ms. Hilton and Ms. Kardashian. It seems odd with the conservative moral values espoused.

Very Important: I am not judging them. To each unto his / her own.

For my marketing campaign one more valuable nugget of insight is in th above data (click above for higher resolution). Turns out they are also very rich. Note the prominent appearance of morningstar.com, pgatour.com, seekingalpha.com and ft.com.

So a bumper crop: right audience, lots of money to spend. That's hot!

Now I have to go execute the campaign and I know where to target my ads, how many impressions/day I can expect and how many people I can hope to target.

Relevant audiences change with seasons, hot trends, shifting preferences. Repeat the analysis to ensure you have the most current data.

End of story.

Closing Thoughts:

    Turns out this was a very effective story to tell, most people in the room were media buyers (especially offline).

    They were impressed with the kind of data we have online, and how easily accessible it was.

    They will never forget how wrong one can be about who the relevant audience might be (it would be impossible to guess the Weekly Standard, Rush Limbaugh audience might have any interest in Ms. Hilton or Ms. Kardashian).

Data Wins.

Ok its your turn now.

When you present data how do you tell your stories? How easy or hard is it? Got a favorite story to share with us?

What did you think of the above story? Methodology or conclusions? What did you link? What did I miss?

I would love to hear from you. Thanks much.

Couple other related posts you might find interesting:

15 Jun 2009 01:43 am

standing out 1A very wise friend, ok Craig, once said this to me: "Paid Search is like playing chess with a Supercomputer."

At that moment I think my reaction was something like "meh!". Of course Craig was right.

Search Engine Marketing (Organic + PPC) continues to be a huge part of any company's acquisition strategy on the web. Like other online channels it is targeted, it is effective and it is accountable. Perhaps its most unique asset being the ability to hyper-target relevant customer intent.

It would be fair to say that Paid Search it has also gotten very complex (Search Long Tail anyone?).

Your campaigns and ads are impacted by the many shiny buttons and pretty dials provided by search engines, complex algorithms that determine if your ad shows up (or not), and a bunch of cool things that search engines are doing (like Universal Search).

Given that context measuring impressions and clicks and click thru rates (CTR) and cost per click (CPC) and conversions are now merely price of entry, in fact you focus on those in the first couple days and then very quickly have to elevate your game.

Yet with our tools like Omniture or WebTrends or Google Analytics etc that is kind of all we end up focusing on as Analytics Professionals. Partly because of the limitations of the data available in the tools, partly because most Web Analysts don't have the required deep understanding of what Paid Search is all about.

In this post I wanted to share five cool, "non-normal", analyses that you can do to get a much better understanding of your Paid Search performance. The reports are all inspired from analytical principles I have advocated for quite some time on this blog.

All the analyses been created using the ClickEquations PPC Platform's ability to do impressive deep analysis with its ClickEquations Analyst tool. [Disclosure: I am on the ClickEquations board of advisers.]

Here's how I think of CQ Analyst: Take one part data from all search engines, one part unique custom metrics, one part custom database front end integrated into excel and the resulting ménage à trois combines to produce incredibly powerful insights.

Here are five that we'll cover here:

#1: Identify Keyword "Arbitrage" Opportunities.

#2: Rock Your World, Focus on "What's Changed".

#3: Analyze Visual Impression Share, Compute Lost Revenue.

#4: Embrace the ROI Distribution Report [Identify: Lovers, Friends, Losers].

#5: Zero in on the Actual User Search Query (and Match Type).

Let's go rock it!

#1: Identify Keyword "Arbitrage" Opportunities.

Most web analytics tools dutifully report on search engine data, which ones sending how many visits and what not. They also have a report for keywords. And surely by now you know that you can drill down from the search engine report to look at keywords for that search engine.

Now here is the reality : The ranking of search engines by traffic to your site is fairly well settled. Has been for a long time. It does not change month over month, or changes very little.

What does exist in your data is a different how one keyword performs across search engines! Thanks to the difference in algorithms for both organic and paid search in each engine.

Lookie here, my ClickTracks report….

clicktracks keywords by search engine report

See what I mean? The heatmap shows you how even my humble blog is optimized for different keywords in different engines. This allows me to look for "arbitrage" opportunities (focus on selective keywords for each search engine).

You can do this exactly same thing for your paid search keywords with ClickEquations Analyst, i.e. look at side-by-side performance rankings by clicks or conversions.

clickequations analyst keyword clicks by search engine

In this example, we see that the keyword dog boots is generating huge traffic on Google (1,309 clicks) but almost nothing on MSN or Yahoo. Why? Are we not buying this delightful keyword on those engines? Is our bid too low or our ad copy ineffective?

Questions you want to answer quickly before your once a year annual huge sale is over and you are left with tons of extra dog boots (heaven forbid!).

Sorting by clicks-per-keyword in another engine, Yahoo in this case, we see that our top traffic terms there are ones where Google is under-performing.

keyword clicks for yahoo clickequations

More opportunity!

Let's bring this puppy home, switch to conversions for the same keywords across different search engines. . . .

click equations conversions by search engine report

It is pretty clear now where immediate opportunities exist (in case you did not notice, the frowny faces : ) and where you are doing ok.

In our case the keyword that is our second highest performer in terms of bringing home the bacon (conversions!) is doing great on Google but is we are getting eggs on AdCenter (or is it Bing now?) and YSM.

It highlights a possible Sales / Revenue opportunity and gives you marching orders to investigate. Remember you already know that this is working on Google, why not on the other engines?

#2: Rock Your World, Focus on "What's Changed".

While we obsess about our brand terms and our top ten key phrases the reality is that the long tail of search means that our organic and search campaigns focus on tens of thousands or hundreds of thousands of keywords.

One effective strategy to deal with this purely data problem is to focus on what's changed.

No more data pukes. Just looking at things that need attention.

[imagine whip being cracked, politely]
You must do this to stand a decent chance of making ROI on your Search Campaigns.
[/imagine whip being cracked, politely]

The focus of your What's Changed reports is to show campaigns, ad groups, keywords that are gaining more impressions, getting more clicks, producing more revenue (or not!) compared to a prior relevant time period.

Here's the report:

whats changed google paid search campaigns

[Click on the image for a higher resolution version.]

Here's your schedule: Wake up. Take shower. Review major "rises" and "drops" in Gross Profit. Press buttons. Take action. Get coffee. Drive to work to receive praise for a job well done!

Notice the focus is not on Clicks or Visits (not that there's anything wrong with that), its on money baby!

Here's one more very useful example, focusing on Avg CPC's, as you figure out what dials to move. . .

average cost per click changes clickequations 1

Every line in these reports begs a simple question: Why?

What is causing that ad-group's revenue to soar 498% above what it did last month?

How come that keyword is down 74% in the number of impressions yesterday vs the day before?

Why did the cost per click for doghouse pets boulder suddenly shift that much?

The biggest problem with paid search, or web, analytics is that you don't have starting points. These reports, and metrics, give you that. You can then go investigate the hot leads. Perhaps your competitors have sprung into action. Maybe your quality score has taken a dive. Who knows, the boys in the warehouse may have run out of stock.

The nice thing about the ClickEquations Analyst is that you can easily use the delta feature to set the am out of change between two time periods for any paid search metric.

You can create customized Top X modules of what's changed and literally you have a living breathing dashboard that highlights the most important, and it never gets auto deleted by the HiPPO's!

#3: Analyze Visual Impression Share, Compute Lost Revenue.

Did you read my post about Google's Search Based Keyword Tool ?

One of the really cool things that SbKT offers is Ad/Search Share (8th picture in that post). It tells you how often your ad shows up when someone searches using a specific search query (for both paid and organic).

It is very useful in understanding what share of shelf you have (think shampoos in walmart). It is surprising that only the most hard core PPC folks seem to focus on this metric.

You can also get Impression share for your own keywords portfolio from the Adwords Campaign reports. You want to know how many people who are searching for a keyword that you are bidding on are not seeing your text ads (no see = no click = no honey!).

The CQ Analyst helps you visualize the impression share metric very efficiently, even your HiPPO will understand the story!

The impression share, Exact, report showing "share of voice" for queries matching your keywords. . . .

adwords impression share report clickequations sm 1

[Click on the image for a higher resolution version.]

Orange = Yea! Green = Ouch!

Need more motivation to work harder to improve your impression share? Here you go, missed clicks and revenue. . .

adwords lost revenue impression share clickequations sm

[Click on the image for a higher resolution version.]

Orange: Cause (ouch!). Green: Effect (ouch! ouch!).

The ClickEquations Analyst report is showing above the lost revenue in green, and the orange line shows why that is lost revenue (lost impressions).

It takes the average revenue per click from the impressions you are getting from your campaigns (so the real conversion data from your site) and extrapolating it out to show how much revenue the lost impressions represent.

In the above real customer example the lost impressions alone (without doing anything else) represents revenue growth opportunity of 30%.

Remember this is using your actual current clicks from ads when you do show up (impressions) and your actual current conversions.

Winning those missing impressions would require either a budget increase, or more likely some significant improvement in bids or quality score – but knowing that potential exists offers a clearer view of specific expansion opportunity than paid searcher usually see.

This is a superior understanding of the opportunity then what you'll get out of standard web analytics reports. Superior because you are truly bringing deep AdWords data together with your site's outcomes data.

#4: Embrace the ROI Distribution Report [Identify: Lovers, Friends, Losers].

If you are a Analysis Ninja prepare yourself for a minor orgasm. This is so cool.

Remember the 80/20 rule?

80% of ROI comes from 20% of your Campaigns. Replace ROI with revenue, profit, your favorite metric.

Step One: Specify your ROI goal and your minimum acceptable ROI.

Step Two: Run Report. :)

The report tells you how many of your campaigns, adgroups and keywords fall into three performance bands: Great (exceeds expectations), Good (meets expectations), Poor (sucks!). Or: Lovers, Friends, Losers.

clickequations search roi distribution report sm

[Click on the image for a higher resolution version.]

You'll see the raw numbers, the cost vs revenue breakdowns, and the comparative percentage contributions.

great good poor performing adgroups

So what's happening here?

8% of the AdGroups are responsible for 54% of the revenue (!). Checkout the Avg ROI contrast.

Or more visual. . .

great good poor spend to revenue comparisons

Its not even 80/20, more like 90/10!

It's a ruthless way to determine which elements are hurting you, and which are actually helping.

This type of analysis allows you to take a very close / critical look at exactly how many of your keywords are really profitable, and which ones are sucking wind.

It should lead to a complete reevaluation of your keyword selections, match type settings, bid choices, ad copy, and campaign organization. Or in other words, the baby and the bath water.

This analysis is super cool because you end up with a prioritized to-do list of campaigns or keywords that require your full attention.

#5: Zero in on the Actual User Search Query (and Match Type).

While the entire business of Paid Search revolves around keywords, often there is not enough attention being paid to the role Match Types play in determining which search queries (the words the search engine user actually types) trigger your paid search ad.

We sadly make far too many decisions based on keywords we bid on.

In our campaigns we use Broad, Phrase and Exact match types to ensure we are showing up for relevant user searches. Hence most of our campaigns include key words which use all or some of these Match Types.

One of the simplest report you can create using the ClickEquations analytics platform helps you analyze the impact of these different match types on performance. . . search query by key word by match type. . . .

paid search user query by match type analysis

Column 1 is what was typed into the search engine. Column 2 is the keyword that was in your paid search campaign. Column 3 was the Match Type used.

And here is a report that will really solidify the Match Type concept in your mind: The match type report is for the keyword wellness cat food and the actual user search query. . . .

match type keyword user search query clickequations

Impressed at the creativity of users who search?

The analysis you should do right away is to understand the performance of individual match types with the user search query for a clump of specific keywords you have bid on.

This analysis will instantly spark ideas for:

1. Match Type promotions (keywords and search queries that you are now buying in Phrase or Broad Match but could and should be in Exact Match)

2. Search queries that are matching your Broad Match keywords but should themselves by Phrase Match keywords

3. (of course) A list of negative keywords that you should add to efficiently stop buying unqualified traffic

If you pause and think about it for a moment this search query report is perhaps the ultimate keyword research tool you could get your hands on. And it is free! Use it!!

The Analysis Ninjas amongst you won't stop there.

No sirree, bob!

You will want to understand performance of various Match Types across your entire account! You'll take three steps up and try to understand the forest view first.

A typical expectation would be that Exact Match keywords, which are very precise targets carefully chosen, will perform better than Precise and certainly Broad Match.

So is it?

The first report in ClickEquations Reporting gives you the top level analysis of your Match Type distributions.

It answers fundamental questions such as: What is the result of all your hard work in finding and promoting keywords to Exact Match? What about your plan to conquer the earth and moon and pluto to increase the % of revenue you get through Broad Match?

Here you go. . . . Happy Fathers Day. . . .

match type analysis google keywords revenue sm

[Click on the image for a higher resolution version.]

In one nice view (come on you can't argue with a pie and a bar chart on the same page!) the information you need at a glance to understand performance, all the way down to Revenue / KW.

Let's drill down on that to look at it more clearly. . . .

revenue per keyword by match type clickequations

Revenue Per Keyword from Exact Match is much higher than Broad and much much higher than Phrase. That validates our hypothesis and it provides nice support for all the effort we have put into creating highly targeted Exact Match keywords

Do even more of that, while you shift to leveraging Phrase and Broad more strategically.

My favorite view is perhaps to look at the bang for the buck of keywords based on match type. Outcomes sweetie, outcomes!!

The complete picture, Cost -> Revenue -> Gross Profit -> Net Profit by each match type. . . .

revenue and profit per keyword by match type clickequations


For this specific client it turns out that every dollar spent on Broad Match is yielding a much lower return when compared to Phrase or Exact Match types.

Immediate work needs to be done on negative keyword expansions to further optimize spend.

Each company is unique, your picture might look like this. . . .

sem revenue profit bymatch type analysis clickequations

By focusing on Cost in addition to the four layers of Outcomes (revenue, gross profit, net profit) you are able to see a multi dimensional picture.

Digging deeper, as in the first part of recommendation #5, will help you then make changes to your match types and campaigns to optimally utilize the opportunity in front of you.


Five sweet recommendations you can follow tomorrow, or today!

Paid Search has changed dramatically over the last few years. Yet we tend to report and analyze like we did during the days when hotmail was cool (!).

The stories we have shared today show that taking a different approach to the data already available gives you super awesome insights that lead to immediate cost savings / revenue improvements.

And it is not that hard is it? You need a bid management software like ClickEquations with built in advanced analytical capabilities, you need some awareness of AdWords / YSM / AdCenter and you are on your way.

Ok now your turn.

What do you think overall of this approach? Have you done any of the above five types of analyses? Got any other favorites that you would care to share? What do you use to do your Paid Search Campaigns analysis? Any tips or horror stories you want to share?

I would love to hear from you. Thanks.

Couple other related posts you might find interesting:

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