Using Google Analytics to Increase AdWords ROI With Google’s Justin Cutroni

Are you using Google AdWords and Google Analytics to their full potential? In this interview, Google Analytics Advocate Justin Cutroni discusses how to make the most of Analytics and AdWords integration, from the most basic set up techniques to advanced reporting features that you may not have been aware of.

Key Points

  1. Analytics and AdWords are made to be used together. While AdWords helps advertisers measure ads and their performance, Analytics helps you understand what happens to traffic when it gets to your site.
  2. AdWords/Analytics users should be carefully analyzing on-page factors (bounce rate, pages per visit, conversion rate) in conjunction with off page factors (keyword performance, ad copy, ad groups, etc.) to determine a campaign’s effectiveness.
  3. When configuring goals in Google Analytics that are not ecommerce, it is beneficial to create a value for them and track them as revenue.
  4. Weighted sorts apply an algorithm that compares metrics by their weighted importance. For example, a weighted sort of bounce rate would show you which keywords have a high bounce rate and at the same time are contributing to a large amount of website traffic.
  5. By using the Day Parting feature of Google Analytics, users can decide which times of the week are the lowest/highest converting, and decrease/increase bids for these specific time slots. For example, a Pizza Parlor might convert higher on Friday nights, and thus increase their bid 150% for this particular time.
  6. By using the Matched Search Queries function in conjunction with secondary dimensions, you can compare what someone types into Google to what it matched in your AdWords account.
  7. When you are looking through data in AdWords, you should be thinking: How does my business work? What do I know about my customers? How does my day go? Tailor your campaigns to meet your business needs.
  8. Multi-Channel Funnels allow you to visualize your personal sales cycle. A paid search visitor may not convert on their first visit, but they might convert week later in a return visit.
  9. Within Multi-Channel Funnels there are two very important reports: Time lag and path length. Time lag analyzes the time and date between a visitor’s first entry and the conversion. Path length measures the number of visits between the first entry and the conversion.
  10. The increase in reporting capabilities is also making the Display Network more measurable and effective. By using Multi-Channel Funnels you can carefully pinpoint what value a Display Network ad has in your sales funnel.

Full Interview Transcript

Eric Enge: Could you provide an overview of the “how and the why” of Google Analytics and Google AdWords integration?

Justin Cutroni: I think Analytics and AdWords were made to be used together. AdWords helps advertisers reach an audience and understand ads and their performance, but is missing a lot of data about what happens to your traffic when it actually gets to your site. Analytics steps in and fills that hole.

Analytics helps you understand, at a rather deep level, the behavior of people coming from AdWords. Because Google controls both of these products, you can view reporting and data in Analytics that directly relates back to your choices in AdWords.

The best part about this whole thing is that you are getting data to drive the refinement of your AdWords campaign, in order to improve the performance of your business.

Eric Enge: What are the kinds of things that you need to do to set up AdWords and Analytics so that they work in an optimal fashion?

Justin Cutroni: There are really two key ways to make sure Google Analytics and Google AdWords are working together. The first is within analytics:

You need to make sure you are tracking goals, or have ecommerce tracking enabled.

This allows you to track the transaction, the revenue, and the conversions on your site. If you are not ecommerce, you can use a feature called “goals,” which is analogous to conversion tracking in AdWords. This lets you track form submissions, leads, whitepaper downloads, etc.

Setting Up Goals in Analytics

 

The idea is to make sure that you understand what you are spending and what revenue this spend is generating. A little tip here: when you are configuring goals in Google Analytics that are not ecommerce, you can actually add a value to them. So, for that whitepaper download, try to create a value and put that into Google Analytics, and it will actually track it as revenue.

The second setting that is really important is linking AdWords in your Analytics account. This does two things: First, it automatically identifies traffic coming from AdWords in your Analytics account, so you don’t have to do any manual setup. Second, it pulls in your AdWords data, statistics like impressions, click-throughs, and cost. This allows you to carefully analyze what your spending and what you’re making, and optimize based on those metrics.

Eric Enge: Let’s go back to goal-setting for a moment:

Somebody goes to your white paper download page and they say: “I want to download this white paper.” Presumably, you make them give an email address and once that is done, you have a landing page which might be the trigger that indicates that the goal has been met. You then apply a dollar value to that based on how you value it as a tool towards eventual sales. Is this how it works?

Justin Cutroni: That is absolutely correct. You tell Google Analytics: “Hey, this page on my site is special.“

In the example you gave, you put email conversion as a goal and when someone hits that page, it will count as a conversion. It is a little bit different than AdWords, where you would have to put a special piece of code on your conversion page. You don’t have any special conversion for Google Analytics. It is all about telling Google Analytics: “This URL represents a conversion.”

Eric Enge: Once set up properly, what should people be doing on a day-to-day basis with Analytics and AdWords?

Justin Cutroni: Once everything is setup, you are going to notice in your left hand navigation of Google Analytics that there is a section for Advertising. It contains the AdWords reports.

The campaigns report is the most basic report, but gives you all of the data you need to evaluate performance of AdWords. It is structured just like your AdWords account, so you will see a list of all of your campaigns, with the ability to drill down into ad groups and keywords. It rolls the data up, just like it is in your AdWords account.

What is different now, is that we have metrics that are all about what is happening on your site. This includes traffic, visits, behavior, page views, time on site, and outcomes (goals, conversion rates, and revenue from ecommerce.)

One of the metrics that I really like is bounce rate. A lot of people know about bounce rate, but it is a good thing to reiterate. Bounce rate is when someone comes to your website, they land on a page, and then they leave immediately from that page, without going any deeper into the site. One thing that I am always interested in analyzing with the campaign report is: “which of my campaigns have a really high bounce rate?”

Then, you can start to drill down and look at the ad groups and identify which ones have a really high bounce rate. This will tell me which ad groups and keywords are driving traffic to my website but not doing anything else. So, if I am putting people on product pages or putting people on product category pages, my expectation is that they are going to move deeper into the site. If they are not, something is not working. There is some type of disconnect between the ad that they are seeing and them landing on the site.

I like the bounce rate in this report because I can look at it at different levels: campaign, ad group or keywords. Very often, if you just look at the campaign level, you could be missing some outlines that are getting obscured by averages. Having the ability to drill down is really important. To me, that is one of the most basic things that I think everyone should do be doing: understanding if the campaign is successful or not, and using that in conjunction with the Bounce Rate to see if there a problem between the stickiness of your landing page and the ad that you are showing people for certain keywords.

Eric Enge: I think the key advantage is the ability to slice at multiple levels. The ability look at keywords, ad groups, or campaigns…

Justin Cutroni: Absolutely. You don’t want to be too far “up” and you don’t want to be too far “in the weeds”. That’s why I like ad groups as a nice middle road. It is not too high, and it is not too low.

Another really useful tool in this report is something that gets a little bit advanced. You can click on the heading of different columns and you can sort based on that column. So, if you click and you sort by bounce rate, normally everything that has a hundred percent bounce rate will show up at the beginning of the table.

However, that is not very useful, because you will see one visit from an ad group or from a campaign or from a keyword, that has a one hundred percent bounce rate, which is not very actionable. But at the top of that table, there is a sorting option called the weighted sort.

Weighted Sort in Google Analytics

 

Weighted sort applies an algorithm to the data and sorts based on the traffic volume and the bounce rate. So, you may have a campaign or ad group that gets seven hundred visits and has a bounce rate of 73%. The algorithm can detect, based on the volume of traffic and the bounce rate, this is something that you should address. I think that’s a really neat tool doesn’t get as much attention as it should.

Eric Enge: It does sound like a neat tool because, without the tool, you would have to go through on your own and figure out: “Am I getting enough data here?” Now you can click on a button and have it just happen.

Justin Cutroni: We are really blessed at Google to have some pretty smart people. You can walk in and say: “What if we could magically show people what they should be looking at first and paying attention to first?”

Then someone will say: “Sure, I can make that this afternoon for you.”

I should mention that the weighted sort will work on any column that is a percentage. You can switch the view to look at your different goal conversion rates, and you can also switch it to ecommerce data to look at the transaction rate.

I like switching those columns because I can get conversion rates or ecommerce transaction rates. I can do the same type of analysis for the ecommerce transaction and apply a weighted sort. This allows me to easily see where the really good campaigns or keywords are and investigate these a little bit more to promote them.

Eric Enge: Right, because oddly enough, it is not just about clicks, it is about conversions at the end of the day.

Justin Cutroni: Right, a lot of times what will happen is you will be looking at these reports and see that campaigns are driving traffic but no conversions or outcomes.

As we go deeper in the conversation, I will discuss some other tools that will help you dig into those campaigns a little bit deeper. Just because something is not driving a lot of conversions directly doesn’t mean that you should turn it off. We have a great feature called Multi-Channel Funnels, which we will get into it in a few minutes. It will take your analysis to the next level and help you understand if certain visitors that you may think aren’t driving conversions, actually are.

Eric Enge: So, in our world of paid search marketing, when we first grew up, it was just viewed purely as a direct response market place. Get someone to click on something, some percentage of those people buy something, do the evaluation and now you know whether it is a profitable keyword. It is obviously a bit more complicated than that today.

Justin Cutroni: Yeah, the behavior of people is changing radically because of the devices we have, how we split our time between different devices and how we search. We are trying to give advertisers as much data as possible to make good decisions.

Eric Enge: I know we do want to get into some deeper topics, but are there some other things that you want to fill in at the introductory level before we take it to the next stage?

Justin Cutroni: Yes, let’s play on this theme of data in Analytics to help you understand the choices you have in AdWords.

I think that, looking at the campaigns in ad groups is good, but let’s talk about a feature in AdWords called day parting. Anyone that has been running ads knows that you can run ads at different parts of the day. This is one of my favorite things to do because we have so much data in Analytics about people’s behavior and the ability to segment that based on time on your site. We can use that information to fine tune your AdWords campaign.

In the same section of Google Analytics (Advertising > AdWords) there is a day parts report:

Day parts report in Google Analytics

 

This report shows you the AdWords data by the day of the week or the time of the day. You can see your traffic based on Mondays, Tuesdays, Wednesdays, etc. or even by the hour of the day. This is really important, because there is a feature in AdWords where you can change your bidding based on the day of the week or the hour of the day.

Now you can understand the cyclical nature of your website traffic and optimize accordingly.

So, most of the websites that I am seeing, you see traffic on Mondays, it peaks during the week and then on the weekends it usually starts to slow down. However, that’s going to be different for every business.

If you have a lot of traffic and a really high conversion rate at some point during the day for campaigns, you might want to increase your bids some percentage higher than a hundred percent (140% or 130%) because that’s a really good time of the day for your business.

Likewise, if you see traffic drop off and conversion rates drop off on the weekend, you might want to throttle back, maybe 50% or 60%, save some money during those times because when the audience isn’t there, you are not converting. This a really good feature that you can start to leverage immediately.

I will say that so much of AdWords is in making incremental changes. You may not want to double your spend on a certain part of the day, but rather just start to creep it up a little. You may not want to completely turn it off on the weekends, just throttle it back a little. It is all about the incremental changes based on the information you get.

Eric Enge: Right, so you might do something like jack your bids 20% during a hot time and take them down 20% in a slow time. Big enough so you are going to get a measurable result and find out if it was good for you, but not so big that it goes off the deep end if something is wrong. At the end of the day, even though I know we are going to talk about some very sophisticated tools, you do have to rely on your ability to test and see what works.

Justin Cutroni: Yes, I think what you just said is so important.

You still need to be getting some data to understand: Is it moving in the direction that you expect it to? If there was a magic bullet, you could push a button in Analytics to make a million dollars today. But there is not, and it is all about making these small incremental changes and reacting over time.

Eric Enge: The other part of that is making sure the change is large enough that you will be able to measure the result without having to wait several months to see it. You want to get statistically significant data reasonably quickly, just not necessarily crazy quickly.

Justin Cutroni: Exactly.

Eric Enge: So you discussed day parting and hour parting. Are there people that find that there are volume drops after the work day?

I have been involved in internet marketing long enough to know that most people do their online shopping when they are supposed to be doing their jobs. So you might actually have campaigns where after 7 at night, you begin to tweak the bids back and maybe early in the morning they are kind of normal and maybe in the afternoon they are tracked up a little bit. Whatever it is that you see from looking at the data, but that’s another thing that you can do in AdWords too, isn’t that right?

Justin Cutroni: Absolutely, and I think you bring up another good point.

What I hope people take away from this is that when you are looking at this data, the first thing that should be in your mind is how does my business work? What do I know about my customers? How does my day go? Imagine that if you are a small business and you have to run deliveries between 12 pm and 3 pm. Maybe you can’t handle any leads during that time for whatever reason. You might just turn AdWords off because you know that any leads that are coming in during that time will not get handled and you can’t deal with them. It really is about understanding the flow of what you do and how your business runs and then reflecting that in AdWords.

That’s why I think the Analytics data is really such a critical piece. It is data about your specific business.

Eric Enge: Any sense as to what kind of scope of impact people are seeing? Have you seen advertisers get dramatic impact from day and hour parting?

Justin Cutroni: We know you are going to see an increase in business, you are going to increase conversions, and you are going to save money. You are not going to use money when you don’t need to. It doesn’t matter how big your company is or what you do, using the day parting will help everybody.

Eric Enge: Let’s talk a little bit about match types.

Match types in Google Analytics

 

Justin Cutroni: Match types are another part of the integration between Analytics and AdWords. The match type has been used for a long time and is going to continue to change and improve.

Broad match campaigns give you a way to reach a really large audience without getting into too many details. However, you want to fine tune that over time and identify specific keywords that are really important and target those with exact matches or use phrase match to fine tune your account and get a better return.

Within Analytics we have a report for the matched search query.

Matched Search Queries

 

I really like this report because I can look at what someone types into Google and what it matched in my AdWords account and identify any differences.

If you navigate to the matched search queries report in the Advertising > AdWords section, at the top of the table, you will be able to change the view to match type and see what happened for the traffic that came from broad matches, phrase matches or exact matches.

Matched Type feature in Google Analytics

 

I like to click on broad match and drill down into all of the broad match keywords that I have in my AdWords’ account. This is where I like to use another feature that I don’t think is really leveraged enough: the secondary dimension.

Secondary dimension in Google Analytics

 

I can add a secondary dimension of keyword: now I have broad match terms in one column and keywords in the second column. Someone might have searched for “Easter chocolate” and that might have matched on “Easter” or “Easter gifts” or something else.

Here is another way that I can look for ways to improve. So if I see that in broad match “Easter candy,“ someone typed in “Easter chocolate”, and I am getting a really good return on “Easter chocolate”, I might promote that and go in with an exact match to improve my performance. I can start to graduate things out of broad match and into exact match to fine-tune my account.

Eric Enge: That’s one of the things that a lot of advertisers don’t realize. Just because that broad match keyword picks up a particular phrase, (“Easter chocolate” I think was the phrase you used as an example, when the broad match term was “Easter candy,”) it is still worth taking those terms and bidding on them in exact match mode.

Justin Cutroni: Absolutely. This is another great place where you can switch over and look at the ecommerce or goal conversion data and sort by your conversion rates. Now you’re starting to use some really heavy features in AdWords.

We could even get into a feature called advanced segments and drill into even more segmentation. I know you are a huge fan of segmentation, I am too.

Eric Enge: Yeah.

Justin Cutroni: Well, we could even start to segment by geographic location. For example, just focus on the New York or Chicago area. Now I have match type, keyword, and geographic location. The whole idea here is that we can go back into AdWords and say: For this geographic location I want to fine tune my keywords in this specific way and then tweak your settings. We are giving you data that reflects all of those different levers in AdWords so that you can keep fine tuning and making incremental changes.

Eric Enge: Right. Then, of course, the thing you want to do is focus on the keywords that have the biggest impact, because that is where you get the best returns on these kinds of effort and analysis.

Justin Cutroni: That’s the great thing about that weighted sort feature. It is going to tap those things that are going to have a high impact.

Eric Enge: Anything more you want to add to match types or should we try another one?

Justin Cutroni: Let’s talk about the Multi-Channel Funnel:

Multi-Channel funnel in Google Analytics

 

Multi-Channel Funnel, a section we have in Google Analytics, is all about helping you to understand the multi-touch behavior and journey that customers have on their way to conversion.

People might take multiple visits to convert and that might be multiple clicks in AdWords. In Multi-Channel Funnels, we are providing a whole bunch of information about the length, time and touch points of your sales cycle. You will notice the assisted conversions report in the Conversions, Multi-Channel Funnel reports. This report is not only going to show you the conversion and the revenue, but it is going to divide them into two groups.

First there is last interaction conversion and last interaction value. This is similar to the current last click model. You will see the campaign or ad group and how it performed at the last click. You can choose which goal you want to analyze in this report.

You will also see something new, called “assisted conversion” or “assisted conversion value.”

What that helps you understand is: “where does this campaign or keyword appear in the visitors journey prior to conversion?” This is the report you look at after you are looking at your basic campaigns report. Now I can go and look for all of those campaigns and ad groups that didn’t generate any revenue and see if they did help drive traffic before conversion. All of a sudden, you don’t just kill something that is not getting you any revenue, because it may eventually assist in a conversion.

Eric Enge: What kind of channels are included in this data?

Justin Cutroni: In the Multi-Channel Funnels, if you are just using the report in regular mode, it’s going to automatically group your traffic into channels: social, display, cost-per-click, organic traffic, direct traffic, etc. It will (based on referral information) auto-detect where people are coming from. You can configure that if you want to change the grouping. Or you can view the data based on campaign, adgroup, etc.

Eric Enge: I presume this uses cookie-based tracking, is that how that works?

Justin Cutroni: We do use some cookies in Goggle Analytics. When you land on the site, we know where you came from and we store that in a cookie, but we also have the ability on our back-end to connect the dots and say: “Eric did this sequence of visits over the last month.”

It’s all completely anonymous data because we don’t believe in tracking the individual. We track you as part of a group or segment.

Eric Enge: Are you tying it to my being logged in?

Justin Cutroni: No, it actually has nothing to do with you being logged into anything. Let’s use an example of an online chocolate store.

Let’s say I am looking for a Mother’s Day gift. Maybe I do a search for a chocolate and go to a particular website. Google Analytics will record that visit, it will record that I clicked on AdWords and that I am not ready to buy today.

Next week I may do another search because I really want to fine tune and I don’t just want chocolate, I want the salted caramel chocolate. The same website I visited last week may come up again and I may click on another AdWords ad.

Analytics now knows I visited once on Monday from an AdWords’ ad and didn’t convert, but visited a week later from an AdWords’ ad and did convert. It doesn’t have anything to do with me logging into that vendors site or anything, it is just the fact that the cookie identified me as the same person.

Eric Enge: This is incredibly important stuff. Attribution is a big deal because it varies by business. For some businesses, multiple touches before sale is the norm not the exception

Justin Cutroni: A really great place to start is that Multi-Channel Funnels section. In it there are two really simple reports. One is called time lag and one called path length.

Time lag is the time between someone’s first visit and when they do a conversion. Path length is the number of visits between your first visit and when you convert.

Time Lag and Path Length in Google Analytics

 

Using those two reports, you can understand if you even need to worry about multi-touch. What I have seen a lot is that multi-touch is happening, but it is the time that is different. For a smaller type purchase, maybe sneakers or a book, you might have a couple of visits within a day. With a more expensive type of purchase, you might have a few visits scattered over a week or two weeks. Those two simple reports will tell you if even really kind of need to worry about this whole multi-touch thing. I think most people do need to look at it, but for a lot of people it’s not going to be straddled over a long period of time. It is going to be compressed into a shorter period of time.

Eric Enge: Is there a way to associate a value with the different touches? How does that work?

Justin Cutroni: You can actually segment these reports with a feature called conversion segments. When you are looking at a path, whether it is in that Assisted Conversions report or a path length report , you can create a segment and separate data based on your high-value conversions versus your low-value conversions. You can’t actually apply a value to each specific visit in the past; it’s all based off of the goal or the transaction that happens at the end of the conversion path.

Eric Enge: That sounds like a fun area where you can get a lot of headaches, but a lot of value too.

Justin Cutroni: Yes, and I will just point out that another part of AdWords that I think is really getting very awesome: the Display Network.

Eric Enge: I was going to ask you about that.

Justin Cutroni: I remember, even four years or five years ago, when everyone suggested turning off the Display Network, but the cool thing is, again, we are giving you information about the Display Network and how it is working in Analytics.

Whether you are using automatic placement or managed placement, we have data about both of those in Google Analytics. There is a placements report in the AdWords section that will tell you not only the placement type (like managed or automatic) but allow you to see the placement domain.

So, if you know you are running automatic placements, you can drill in there and evaluate how well they are working. If you have some automatic placements that’s underperforming, you can go in and remove that. If you have an automatic placement that is doing really well, you might move that into a managed placement. The idea is that, in Analytics, you are going to be able to see the placement domain and the actual ad format and location on that site so that you can then go back into AdWords and tweak your ads to run in those spots.

We have really detailed information so you can get the most out of the display network. You can even take it back to what we were talking about multi-channel. I can go through Multi-Channel Funnels again and I can use it to look at the placement domain. If I am not getting the revenue from Display Network, let me jump over to Multi-Channel Funnels and understand what are they doing in terms of Assisted Conversions. This elevates the usefulness of the Display Network..

Eric Enge: I think something that is still at the forefront of what people should do is have your Display Network set up in a different campaign The use of keywords is entirely different from how it is used in a regular AdWords campaign.

Justin Cutroni: I couldn’t agree more.

Justin Cutroni:, Also, there are a lot of settings you can customize for your display advertising campaigns. You have many levers that you can pull, so segmenting display advertising into their own campaign is a good way to focus on that type of advertising.

Eric Enge: When you look at these view-throughs, you have to step back and say: “okay well what was that worth to me.” I think it’s a really good idea for people to go through the discipline of deciding what the value of a view-through type of conversion is to them so that they can actually decide how they want to invest in this piece of their campaign.

[Note, at this time View Through conversions are not part of Google Analytics or Multi-channel funnels.]

Justin Cutroni: That’s a great point. One thing I love about the Assisted Conversions report and Multi-Channel Funnels, is that we are trying to help you with that. Now you can say: this placement on Marthastuart.com didn’t generate direct revenue, but it assisted in $35,000. Now I have a good way to go and determine what I should be spending.

Eric Enge: Anything else you wanted to add for us today, Justin?

Justin Cutroni: To be honest, at some level, we are still just scratching the surface because with Analytics we can do so many other things. I would just encourage everyone to really take advantage of all the features in Google Analytics because they can really help you fine-tune AdWords.

Eric Enge: Thanks for taking the time to talk to us today.

Justin Cutroni: Thank you, this was really fun. I appreciate it.

The New Bing Interface With Stefan Weitz

The new Bing interface is aimed at bringing you clean and decisive search results while helping you interact with your friends and network for a holistic search experience. In this interview, Stefan Weitz from Bing talks about the functionality of the new Bing, how it came about, and plans for its future.

Key Points

  1. The web has gone through a kind of seismic shift. Whereas before, it was all based primarily on text and links, there is now the ability to remodel the world in digital.
  2. In ethnographic studies, 68% of people told Bing that they were trying to actually do something with search, rather than just find information.
  3. During the studies, Bing also found that many people take information from the web and bring it to friends and family offline to help in decision-making.
  4. Sidebar is Bing’s social product, and attempts to take the offline action of engaging people in decision-making, and actually bring that into the online sphere.
  5. Sidebar not only brings people you know into search in a more natural way, it is actually able to show you people that you don’t even know that might be able to help you with your query.
  6. The goal is to make offline more visible online, and actually make that more efficient and effective in helping you do stuff.
  7. A majority of the people Bing studied said that search has gotten too complicated, and that they expect search to be able to organize and make sense of the information more effectively.
  8. Snapshot will take a lot of the tasks out of finding information on the web by actually organizing and summarizing information directly on the search result page.
  9. Bing’s entity engine has about three hundred and ten million objects in it right now, ranging from wine bottles to celebrities and artists.
  10. Bing prefers partnering with 3rd party services rather than trying to build or acquire them.
  11. Bing is currently working with Facebook, Twitter, Quora, LinkedIn, Foursquare, and Google+ in an attempt to make the most inclusive area for social activity on the web.

Full Interview Transcript

Eric Enge: Can you give me an overview of the new Bing announcement?

Stefan Weitz: As we have talked about before, the web has gone through a seismic shift. Where it used to be based primarily on text and links, it now more closely models the world in digital format. 5 billion social networking things are happening each day. The geospatial stuff clearly is a huge area because we now have gone past just buildings and streets and have moved into literally modeling all the stuff that we can touch, see, feel, and interact with into some digital format.

There are also a million plus applications across all the platforms, and these intelligently help you do something by understanding what it is you are talking about in the real world and linking that to a service or application which can help you do that. That is really where search has to go because search is really predicated on the structure of the web. That is the background for this big release. It is trying to create an experience that allows us to actually model or reflect that new reality of the web and reflect how people get things done in real life.

snapshot, which is what we call the center pane, is really catering to the fact that 68% of the people told us that they were trying to actually do something with search, not just find out information, which is a big shift from even a few years ago. And then, as far as sidebar is concerned, which is what we call the social section on the right rail of the page, that really came from watching how people were using social data to make decisions and to do things. We did lots of offline studies and went into people’s homes to see how they were doing things.


New Bing sidebar


I remember sitting there one day and seeing this woman who spent hours and hours searching and printing out web pages about hotels and other travel options, and binding them in a three-ring binder and taking them to her husband to help her decide where they would go on vacation that year. At first I thought she was a complete outlier. Then we started looking at how other folks were using search. They did not all print out and bind the results, but some put the information in an email, or bookmarked pages, or copied information into notepad. What emerged was this notion of using search to do research and get information, but ultimately they were not able to take an action until they were able to validate it with a human.

And, that’s where the sidebar came in. Sidebar says: How can we take the offline action of engaging people in decision-making and actually bring that into the online sphere? I was talking about it a few weeks ago and we were going back and forth on how to talk about this. I said, I equate this to the transformation that occurred when you look at US Mail versus email.

US Mail is a very solid, reliable, offline process, that has always been somewhat inefficient. Email came along and added an efficiency to the entire process.

We think of sidebar the same way. Sidebar not only brings people into search in a more natural way, it enables us to actually show you people that you don’t even know who might be able to help you with your query. That’s the big problem, is that I may know that you were a part of the Phoenix BIOS Team but Joe may not. Now, Joe does a search for Phoenix BIOS and suddenly sees in sidebar that Eric Enge was one of the guys that was a part of that.

Well, he would have never known to ask you that question because he doesn’t know you well enough

The point is that it can expose you to information about your network that you may not have known. For example, I lived in Australia for three years. I built model rockets when I was a kid. These are the things you didn’t know.

Because of the proliferation of social data that people are putting online and tagging, suddenly the system is going to actually make those connections, where before that was impossible. It is the notion of bringing the offline online and actually making that more efficient and more effective in helping you do stuff.

Eric Enge: Estes Rockets by chance?

Stefan Weitz: Indeed, Estes Rockets with Double D engines I liked to use the big huge ones.

Eric Enge: Yeah of course, that’s what I did too. So anyway, that’s a great example.

Stefan Weitz: That’s the theory behind what you are seeing here in this new Bing experience. That pane now is really focused on presenting what search knows in a very clean interface so there is not a lot of distraction.

Most people were saying the social stuff was too distracting. Around 72% of the people we talked to actually said that search has gotten too complicated. 84% of the people actually said that they expect search to be able to organize and make sense of this information more effectively.

So, that’s what led to what you see now. The results are much cleaner than they used to be, there is more spacing, we have a nice gutter on the left hand side, and it is far easier to scan the interface.

People are saying: “You have all this data, you understand all these services, you understand this new web of social data and applications and objects, do something with that.”

What snapshot is going to let us do, is actually know that Hotel Max is a hotel and offer a bunch of data about that hotel, including where it is at, reviews, photos and even the ability to go ahead and check rates on that particular place right here.

snapshot allows us to take a lot of the doing tasks and actually organize and summarize those things in a way that helps you interact directly on the page.

snapshot also tries to address the second big complaint we heard which was: there is too much data, you should do a better job of organizing this data.

Another good example I think actually is something like this for restaurants:

If I search for “San Francisco Italian”, it is a fairly ambiguous query, but it is not too bad. Bing will detect that it is likely a restaurant type query and add filters at the top that allow you to filter through your web results.


New Bing San Francisco Italian Search Results


Also, as I scroll down, I can actually see the Italian restaurants. I get reviews, a map, hours, street view, and I can see the inside using a service called <a href=” http://www.everyscape.com/ “>EveryScape</a>. I can also book a reservation online through Open Table.

We partner with 3rd party services instead of trying to build or acquire them. There are probably something like a million apps out there today.

I talk to probably two dozen start-ups every week that are doing different cool things on the web. To think that we are ever going to be able to actually beat them, or out-execute them (when they are talking about 12 guys with half a million angel funding building some really interesting apps), it is just not likely.

We are trying to make snapshot the place where we integrate other people’s services and drive them traffic has tremendous value both to developers, but also of course to the users who can now actually do something with these algorithm results versus just clicking on and hope that it gets to a decent page.

Here is another good example using the search query “BMW 5 series”.


New Bing BMW Search Results


snapshot pulls in the official BMW website and data from other sites. We know about the BMW 5 series, the type of car, reviews, price, etc. We can go look at our entity engine and have compete information about the product.

What we have done here is literally take a bunch of data from across the web and re-associate it back with the entity from which it came. That’s a fundamental difference. Another example is Coldplay:


New Bing Coldplay Search Results


In the right rail, snapshot pops up and I get all their events.

We know Coldplay is a band, we know bands have events, we know events have times and places and we can again stitch all those things together in real time to augment the algorithm. Snapshot is only going to become more powerful over time as we do more and more of this integration.

The entity engine that we have currently has about three hundred and ten million objects in it right now. That being said, there are probably a hundred times that many entities in the actual planet, so we are aggressively building on it as fast as we can.

Eric Enge: What percentage of queries do you think you are addressing at this point?

Stefan Weitz: We are talking low numbers. You are not going to get a ton of the things here because they are scoped pretty much to restaurants, hotels, movies and events, people, and cars. They are all pretty high frequency queries and you will see it, but you won’t see it for every query yet.

Eric Enge: What about sidebar?

Stefan Weitz:

What sidebar is doing is allowing you to more effectively bring offline behavior online. I can enter a query on Coldplay and have a section in the right rail called “friends who might know.”

In this case we are looking at just Facebook friends and we are analyzing their public profiles, likes, shares, where they have lived, and photos. We are trying to see if any of these things give a hint, that potentially one of these people has information about your query.

The idea here is that I can literally now engage friends in conversations. I can go ahead and click on a friend and ask “hey, do you know when Coldplay’s new album is coming out?”

Eric Enge: You can pick who to ask which is nice.

Stefan Weitz: Yes. What is cool here is that that it will go out to Facebook, onto my wall, and all my friends will see it in their news feed, and the friends that I ask will receive the question as a message. As they answer my question, if I hover over in the activity feed, I will see their answers.

The other piece in sidebar is called “people who know.” In many queries, you may end up with no friends that know anything about what it is you are querying on. We want to invoke the wider web and we want to actually utilize data and social data from across the wider web to get you information on your query.

We can actually find Coldplay’s official Google Plus profile and put it there. Now you don’t have to know this person obviously, but it enables us to actually look across a number of different social data sources and attempt to find expertise and influence for those topics. In this case we think the Coldplay Google Plus page is the best page for that.

Eric Enge: Now presumably I won’t be able to message them directly because we are not yet connected, right?

Stefan Weitz: You can’t message them directly, no.

Eric Enge: Right.That makes sense of course because otherwise you would be flooding all these people with all kinds of communications and that would be ugly.

Stefan Weitz: Exactly, here is a cool example that really highlights the power of combining those two:

For San Francisco Italian restaurants, I may not have any friends who have any opinions about them. But, look what has happened.


New Bing Social Results


Bing has literally gone out and found people who have blogs and Twitter accounts that we think are influential about San Francisco Bay Area Italian restaurants. I can also literally scroll down and see people’s reviews on Italian restaurants in San Francisco.

Suddenly, I go from a lot of pages and links to nouns, to one where Bing is able to find a small blogger in San Francisco called FoodNut who happens to have data about San Francisco Italian restaurant entities. It is a fundamental shift in search.

Eric Enge: What are the social networks you support?

Stefan Weitz: We are currently working with Facebook, Twitter, Quora, LinkedIn, Foursquare, Google+ and Blogger. Our goal is to make this right rail, the right sidebar, the most inclusive area for social activity on the web. Four Square check-ins may actually be more interesting for me when I am looking for good seafood in Boston There is a bunch of cool stuff that we are going to enable in that right sidebar as we incorporate more of the social data in.

Another example is Windows 8. I can see people who know about Windows 8. Here I get Paul, I get Mary Joe and their Twitter accounts.


New Bing Windows 8 Results


I am seeing their actual tweets about Windows 8 and a set of reviews.

Eric Enge: Right.

Stefan Weitz: It is focused on understanding the real world that we live in and helping to do things in that. It is focus on connecting people to those queries and letting you engage with those people in a way that helps you do things and it builds your network.

Eric Enge: Very cool. I imagine you have done some live user testing with this?

Stefan Weitz: Thousands of tests were run on the left hand side on the new page (from fonts to color to spacing to caption lengths.)

For snapshot, we have done a lot of testing. I don’t think we have any real great data on that except for the fact that people appreciate being able to take action from that. I think the challenge we are going to have, frankly, is to get people to understand what to do with all of the features

On sidebar, we do a lot of work to understand what is the most interesting set of data to bring in there.

The right rail is going to take a bit of a user shift because they aren’t used to seeing that in search today. They are used to the way we used to have it, the way Google currently has it. Here it is about having the ability to do the same thing and get things there as well.

Eric Enge: So, did you end up getting a richer data set from Facebook in order to implement this?

Stefan Weitz: No, it’s what our agreement currently covers. It is public Likes, it is public profile data. What we have to do with Facebook is make sure that our Service Level Agreements are good so when somebody does post something or take something down, updates come very quickly.

If you “unlike” something in the old days, and didn’t catch it for five minutes, it wasn’t the end of the world. Here, if someone shares something they didn’t mean to share, being able to make sure that is deleted quickly is important.

It is important to also remember that this right rail, the sidebar, really is open. You can’t author into it today, but the whole point is that we are going to be including all these additional social networks and all the additional social signals.

Eric Enge: Was Facebook involved in any way in the development of this or consulted with it?

Stefan Weitz: Yeah, they definitely were consulted. We showed them the early mock ups, along with other partners that we had that were involved, there were no surprises, let us put it that way. I know the folks who work at Facebook are pretty excited to see it roll out.

Eric Enge: Are you actually in touch with Google Plus development team or…?

Stefan Weitz: We are actually just crawling that. They don’t offer an API anyway so it wouldn’t be really easy.

Eric Enge: Do you have access to the LinkedIn data through the API as well?

Stefan Weitz: I don’t think we have even gotten down to how we are going to be using that honestly. I don’t know.

Eric Enge: For the other services, do you do it by crawl?

Stefan Weitz: It is just going to depend on what we want to do with the data and how fast it needs to be done. Crawling is not going to be very effective on check-ins, for example, for Four Square. With Quora, it is not necessarily critical real time data, so it might be effective to crawl

Eric Enge: So when do you think this will be generally available?

Stefan Weitz: Well today, if you go to Bing.com/new you can opt in and get it today. Then, at the beginning of June-ish timeframe (I am not sure we have actually locked on that date) it should be available more generally.

Eric Enge: Right. Well, that’s very cool. The experiment with the social stuff is particularly interesting I am going to be really interested to see how this plays out for you in the market. Thanks Stefan!

Stefan Weitz: Thank you Eric!

Personalization In Google Search Results With Bruce Clay

Today’s post is focused on a hot topic in search: Personalization. Personalization is Google’s attempt to personalize search results based on a variety of individual factors, including web history, social connections, and much more.

In the following video, Eric interviews Bruce Clay of Bruce Clay, Inc. gives his thoughts on Google and personalization:

Key Points

  1. Web history has existed for 5 years, and Google uses this information to tailor search results to individuals.
  2. Google is trying to overcome ambiguity. When you search for a term like “hammer,” what do you mean?
  3. Two people might be searching for the same word and get different results, depending on their location and web search history.
  4. While personalization may lead to less false positive results (and therefore lower total site traffic), it also leads to more highly targeted visitors to your website. This can actually increase conversion rates as a percentage of search traffic in some cases.
  5. In some cases, personal history may give Google incorrect signals, and actually increase the amount of false positives.
  6. Ranking is no longer the best way to track SEO efforts, as ranking will vary from person to person.
  7. In the past, SEO professional’s were optimizing around one word, whereas in the future, they will have to optimize for communities.

Full Interview Transcript

Eric Enge, CEO, Founder, Stone Temple Consulting: Hi, I’m Eric Enge with Stone Temple Consulting. We are an internet marking optimization firm that does SEO, paid search, social media, and a variety of other things for fun.

I’m here today with Bruce Clay. We are going to take on an interesting topic, which is that of personalization. But, Bruce, why don’t you introduce yourself for us?

Bruce Clay, President, Founder, Bruce Clay, Inc.: Thank you. Bruce Clay Inc. We’ve been in business since January of 1996. We focus on internet marketing optimization. That is: SEO, PPC, analytics, social conversion, and information architecture.

We sponsor a lot of conferences that many people probably have gone to. I am sure at one point or another they’ve had a drink ticket with my name on it. So, that’s an important networking activity we support.

Eric Enge: You know how to make friends.

Bruce Clay: I do. Certainly, sponsoring drinks is one sure-fire way of doing it. It’s the ultimate social media platform at a conference.

Eric Enge: Right!

Bruce Clay: So, we do that. We have offices internationally and we’re (centrally) located in Southern California.

Eric Enge: Awesome! So, today we wanted to talk, like I said, about personalization a bit.

Boy, there are a lot of dimensions to that. But we’re going to try to hit the high points here, I guess, and maybe you could give me your sense of what personalization involves at Google today and where you think it might go.

Personalized Search Results Option

Bruce Clay: Personalization is a little bit like the blind man and the elephant. No matter what part of the elephant you touch, it looks like a different kind of an animal. Unless you see the whole thing, you don’t know it’s an elephant. I think personalization fits into that.

I think, in the beginning, Google had; well, if you remember back, Google had 10 blue links, one algorithm, one-size-fits-all, no matter where you were in the world you got the same 10 results.

For about five years, they’ve been attempting to auto-localize. They’ve been attempting to look at your web history and web history has existed for about five years.

I think the impact on search results has been growing over time, but I have slides in my training course where we talk about web history from five years ago. I have samples of those slides.

What I think has been going on is Google has been fighting the battle against something called ambiguity. Ambiguity is where somebody puts in a word and Google doesn’t know what you meant.

What I really like is my example for a search for “hammer.” Now, we all know what a hammer is. But if you search for hammer in Google, the number one result is a vitamin. The number two result is the Armand Hammer art museum at UCLA. And the number three result is a bowling ball known as “The Hammer.” Number four is Wikipedia, number five is MC Hammer. Nowhere in there are you really dealing with striking instruments.

Personalized Search Results For Hammer

But, they didn’t know what you meant by “hammer.” Now, we can keep going. Guns have hammers. Pianos have hammers. I mean, there’s a lot of different things going on. So, Google has attempted to give you nutrition and art and sports. The best hammer in each of them, because they’re the popular categories.

Well, that ambiguity becomes a problem for Google. So, where web history is played, and this personalization, is they’ve started to look at where are you and what have you previously searched for? So, if I search for equipment and tools and pliers and screwdrivers and then hammer, they’re gonna know what kind of hammer I’m likely looking for.

Eric Enge: Right.

Bruce Clay: Personalization, then, has migrated us from the 10 blue links one-size-fits-all to something that is individualized. It is what I want, based on what I searched for in front of it. And that personalization is changing the top 10 results for each individual, even if they search for the same word.

Now, the good news is, if somebody actually does go to my site for hammer, it’s going to be a more targeted visitor. The bad news is, I’m not going to get as many false positives, if you will; people that will find my site my site when they didn’t really want the tool.

Eric Enge: Right. A little less serendipity.

Bruce Clay: Yeah. So, my traffic is going to drop, but my conversion, perhaps, won’t. And my conversion as a percentage may actually improve.

So, I think Google is using personalization as a way to address “how do I better target the search results by eliminating ambiguity?” And I think that’s really part of the battle.

Eric Enge: Right. Well, that makes a lot of sense.

On January 10th, actually, we got the Search Plus Your World update from Google, which introduced a new level of personalization to search results, didn’t it?

Example of Search Plus Your World

Bruce Clay: Yes. I refer to it as Search Rocks Your World. There were so many things that changed that people saw dips in traffic. A lot of ecommerce sites saw the traffic drop without actually seeing a conversion change, which is what I had alluded to. But they immediately freaked out because of the traffic drop. Now, I think that that’s a natural kind of a thing.

But I’ll tell you where the problem comes in, is that nobody knows how to get rid of web history. That means that I’m getting even more false positives. If I search for baby gifts because one of my employees had a baby, and then I search, because I’m going to a conference in Las Vegas, if I search for Las Vegas hotels the last thing I want is Las Vegas hotels catering to babies. Trust me. That’s not what I’m after.

So, you know, it could backfire on me finding results, and we’ve heard many people; many people indicate that the Google results are not any better; that they’re actually worse.

I think that one of the reasons they’re worse is that they’re using mixed queries. They’re searching for this gift and then that destination and then this travel means, and the signals are actually creating false positives. And I think that makes it a little bit harder.

The other thing you have to understand is, you know, when Google does all this, the intent is to improve. They don’t always get to improve.

Eric Enge: Right. It’s not as simple as you might think it is. Just because we can take one scenario and design an algorithm for that, we need to remember it’s being designed for, really, literally billions of scenarios.

Ambiguity in Search Terms

Bruce Clay: Yeah. How do you anticipate what somebody would have searched for before they searched for your keyword?

Eric Enge: Right. And I think when I interviewed Google’s Jack Menzel last, one of the things that he commented on is that is exactly one of the reasons why they don’t reach that far back into the web history and they keep it fairly localized just to try to minimize some of the fallout from that kind of problem.

Bruce Clay: But it also impacts the ability to use, for instance, in SEO, a lot of people using ranking as a determining factor of how well am I doing.

And unless you have an apples and apples and apples way of determining ranking, it turns out that you can say “I’m in position five” and everybody else sees you in position 20. They don’t even see you at all. So, it does mess up the SEO methodology a little bit.

Eric Enge: Yes, it does.

Any other thoughts that we should add on personalization before we finalize?

Bruce Clay: Well, I think that personalization is being comingled with other things. I think we’re gonna see it actually change the way pay-per-click works as a part of that algorithm.

You know, Google makes money on pay-per-click. They obviously want that to work.

We know that localization is occurring in the Google Places realm. Places was occasional, then it’s 30 percent, and now I expect it, within a year and a half, two years, to be 70 percent of all queries that have places on them.

Auto-localization is happening. I think that SEO becomes harder. I think that we as search engine optimization professionals have got to understand and wrap our head around the persona of the actual target.

We try to anticipate the keywords that they’re going to use and then content has to be changed. So many people for so long have written content around one keyword, not around a community. And I think that that change is going to impact how the whole world optimizes for traffic. And I expect it to be a very exciting period.

Eric Enge: Well, that’s awesome. That’s a big thought to leave this off on, but actually a really good one for people to think about.

Thanks for taking the time to be with us today, Bruce.

Bruce Clay: Thank you.