seo

Posted by CraigBradford

If you’re like a lot of people (myself included) it’s very easy to go into an analytics package and focus only on conversion rate. We look at reports like the one below and make short-sighted decisions:

Looking at only the information above, we might decide that “Organic Search” is a bad channel. Making decisions on how successful a channel is based only on conversion rate is short-sighted and will cost you money. Instead, I urge you to think of your channels like a soccer team.

A sensible soccer formation looks something like the image below:

You have one goalkeeper, defenders, midfielders and attackers. You would never think of creating a team of only 11 strikers. But that’s exactly what we do with our channels all the time. We create a team that looks like this:

We have a team of channels that are all being graded on their ability to “score goals”—please don’t make this mistake. I’m okay with the fact that some of my channels have a low “e-commerce” conversion rate; that may not be what they’re designed to do.

Channels aren’t binary

The one thing that I want you to take from this blog post is that channels are not binary. It isn’t that they either drive sales or do nothing; there’s lot’s of value in between if you know what to look for.

In a report “The Customer Journey to Online Purchase” Google showed this to be the case by looking at the relationship that each channel is likely to play in the customer journey. The idea is to show on a very simple scale whether a channel plays an “awareness role” or more of a “decision making” role.This is an interactive piece so please have a look and play around in it. You can segment by industry or by country.

Let’s take the US market as an example:

US – All Industries

It shows that in general, Display and Social are more of awareness channels, while Organic search and Paid search tend to be last interaction/decision making channels. I’m not surprised by that, but if that’s true—if social is best used as a tool for driving awareness of my brand—why would I ever use e-commerce conversion rate as a metric of success? The answer, of course, is that I shouldn’t. Better metrics would perhaps be things like:

• How many new visitors did social bring this month?

• Brand awareness – how many people have heard of my business?

• How many people interacted with my brand in some way?

These are just a couple of examples, but if you want more specifics I recommend you read this post by Hannah Smith on the Distilled Blog: Calculating ROI from Social Media – Problems, Pitfalls & Breaking all the things…

If you dig a little further, it gets more interesting. Let’s look at the health industry in particular:

US – Health

Social is still an awareness channel, but look at display. It’s now playing more of a decision-making role. Email has also moved from an awareness role to a decision-making role.

So what does this mean?

The data above shows that different channels play different roles depending on country and industry, so don’t assume anything. Don’t assume that social will be an awareness channel, don’t assume that email will be a decision making channel, and whatever you do, don’t assume that all channels are designed to only drive sales. Next time you’re accessing your channels, try two things:

1. Assign attributes to channels

As mentioned above, not all channels have the same strengths, but that’s okay as long as they are pulling their weight somewhere else. To see if that’s the case, try assigning them some attributes other than sales. Avinash Kaushik gave an excellent presentation at MozCon 2013 (if you weren’t there, the video can be purchased from Moz), in which he said that channels should solve for performance and relationships. This is shown in the table below (the example is for ModCloth):

As you can see, if we were to only solve for the line with red text (“Orders”) we would ignore all of the other good that some channels are doing. Social, in this example, is terrible at everything except “Be the Buyer.” I encourage you to do the same for your channels; add in all the metrics that are important for relationship-building, not just sales, and take a step back to see what else your channels might be contributing to that isn’t immediately obvious when you simply look at sales.

Create SMART goals

Just about anyone who’s ever read about goal-setting will have seen the theory of creating SMART goals:

I think most people are good at thinking about goals that are specific, attainable, and realistic. We think we’re good at measurable, and we seem to often forget about time-bound. Since the rest could easily be a post on their own, I’ll just focus on time-bound here.

When we look at tables like the one below, If we are going to make bad decisions like declaring channels “good” or “bad” from just one metric, at least remember to consider time.

If we say organic search is a bad channel, what you actually mean is organic is a bad channel at driving sales in the last X days. That’s an important difference, because it has an impact on where the channel is placed on the scale of “awareness” to “decision-making.”

In summary

• Build a team of channels, not just strikers.
• Don’t assume channels work in the same way across all markets.
• Assign attributes to channels (performance- and relationship-based).
• Remember to create time-bound goals.
• Let me know what you think in the comments.

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Posted by EricaMcGillivray

Every year at MozCon, I have the joy of working with our fabulous MozCon speakers. One of the speakers, who we were most excited about for MozCon 2013, was Kyle Rush. Kyle’s name might not be on the tip of your tongue, but he worked on possibly the biggest and best online marketing campaign, Obama for America, as their deputy director of front-end web development. From there, he went to The New Yorker, and he just announced that he’s headed over to Optimizley.

When Kyle told us he wanted to present about the conversion rate optimization and a/b testing the Obama campaign did, there may have been some squeeing from Rand (like the Packers won) and me (like over new Sherlock episodes). Marketing nerds. Because regardless of your politics, Obama’s reelection campaign not only broke fundraising records, but changed the way we think about using big data and CRO.

Kyle rocked that MozCon 2013 stage. He presented a ton of actionable information for attendees, and he was one of our top scoring presentations. When we went to decide which full-length MozCon presentation to share with all of you, for free, Kyle’s was it. Enjoy!

Video Transcription

Kyle: Thank you, Cyrus. It feels great to be in Seattle. I just came from New York City. Is anybody else here from New York? Yeah. You guys all know what I mean when I say it feels great to be in Seattle. You guys know how to do the summer with this 77 degree weather. This dry heat is awesome. We’ve got to figure out how to get that in New York City. Can we get on that?

As Cyrus said, my name is Kyle Rush. I’m currently at ‘The New Yorker.’ Before that I was at the Obama campaign. I worked on a lot of the product and tech aspects of our online fundraising. Obviously, we ran a lot of optimization on that. So, that’s what I’m going to be talking to you guys today about.

Before we get started, I want to give you guys some context on what we jumped into, the situation on day one at the Obama campaign. All the media outlets at the time were reporting that we were expected to raise one billion. They did probably $700 million in 2008. So, we were expected to raise one billion.

Just to put that into perspective for you guys, Amazon’s Q4 profit for last year was only $97 million. So, when you spread that out over a year and a half, which was the life of the campaign, you still only get like half or a little over half what we were expected to raise on the campaign. So, this was a pretty daunting challenge.

But, in the end… Oh, I didn’t mean to click to. But, in the end we did $1.1 billion. So, we exceeded expectations. None of us thought we could do it. Obviously, that’s a lot of money. We did $690 million of it online as Cyrus said.

Another thing that I want to talk to you guys about is just an example of one of our online fundraising programs. That was called Quick Donate. This was a way for our users to save their payment information so that they could do one click donations on the Web, and they could also do one click donations in email – which had never been done before. So, we had to do a lot of funky engineering to get that to work.

But, you could also SMS donate which was a first for political campaigns. It was actually a big achievement for us. Because the Federal Election Commission said that political campaigns can not use short codes to fundraise. So, we weren’t allowed to work with AT&T and Verizon to send out short codes and ask people to text those. We had to engineer a way around that. When we launched SMS donations it was the first of its kind.

Quick Donate brought in $115 million over its lifespan. It had 1.5 million users. This was a thrill to work on. But, obviously, this type of program we optimized. We ran a lot of tests. Those are kind of the things I’m here to share with you guys.

You might ask how did we get here. We ran 500 experiments. We always had a test running. It was really, really intense the amount of traffic that we had. We did weeks of user testing. User testing is really simple. It’s just putting a user in front of a computer and observing them.

We used a program called Silverback. I don’t know if any of you guys are familiar with it. But, it records the eyesight camera and the computer screen at the same time. So, you can actually see your user making a donation. We learned a lot from this. We did it on and on and on to the point where we probably did weeks of it.

Sorry, this thing is pretty sensitive.

We also just did general data gathering which I really like to do. Because if you’re not gathering data then you’re kind of flying blind. Just a data point to show you guys how much data gathering we did, we did over 668 million Google Analytics custom events. I’ll be talking about those in a minute. But, that’s a ton. I don’t think that I’ve ever worked at a place that pushed Google Analytics to the point that we did on the campaign. It was pretty intense.

You might ask ‘What did that all get us?’ It got us a 49% increase on our donation page conversion rate. And, it got us a 161% increase in our email signup page. These are two really high level conversion goals for us.

The email signup you might not have known about. We didn’t really talk about it. But, I’ll let you in on a little secret. Email is responsible for just about 90% of our online fundraising. So, gathering emails on our list was super important. We spent a lot of time optimizing email acquisitions.

The three things that I want to talk to you guys about today, and this is really what optimization means to me, is experimentation. I think we’re all mostly familiar with this. This is A/B testing, multi variate testing. The second is observation, and that’s what I was talking about when I was talking about user testing. You want to observe your users using your product. Otherwise, you’re not going to know how they’re using it. Because you’re not a user. Also, just general data gathering, which is super important.

First up is experimentation. Sorry. This thing’s super sensitive. We identified a process when we were on the campaign. I want to share that with you. I’m sure everybody has their own processes. But, this is what really worked for us.

The first step for us in experimentation was to identify our goals. I mean this from both a micro and a macro level.

On the macro level I just talked about some of our goals which was email acquisition and donations. You need money to win a campaign. In our instance we needed emails to get that money.

But, I also encourage you to focus on micro goals. This is like conversion goals when you’re running tests. You should just measure everything. So, micro goals can be like the error rate on a form, like how many errors do you get when somebody mistypes their email address. Is the label clear enough there? You just really want to measure everything.

One thing that really blew me away on the campaign is that we started measuring the conversion rate on the follow-up page. So, when you made a donation and it was successful you got taken to a follow up ask that asked you to save your payment information.

That was Quick Donate. That was the opt in to Quick Donate. That was a very critical conversion goal for us, because we found out early on that Quick Donate users were four times more likely to make a donation in the future. That’s like money right there that we needed to focus on.

We measured that goal even though we weren’t changing that page at all. We were changing the donation page. Then, we found out that some of the variations that we ran actually affected the follow up page. It’s really, really important to measure as many conversion goals as you possibly can when you’re doing your experiments just to get a good sense of what’s going on.

The second step that we would do is develop hypotheses. This is really important. It’s just basically like the scientific process that you guys all learned in grade school. Develop your hypotheses and then test them. This is really helpful in making sure that you’re staying focused.

It’s really easy to fall in this trap when you realize how much you can test. You just start to test everything. You don’t want to make any decisions. You just want to test. It’s like, ‘Oh, what color should the submit button be?’

‘I don’t know, test it.’

Don’t do that. That’s not a good idea.

Create high level hypotheses. One of ours, for example, in the campaign was that less copy does better than more copy for conversions. So, we tested that on our splash page. We tested that on our donate page. We tested that on our email sign up page. We tested it everywhere on the site. We figured out different experiments to test it.

That’s actually number three here is to create experiments. Create many experiments to test your hypotheses. You might want to test the same experiment more than one time. Because you might get different results in the time of the day. There are all kinds of weird things that can happen. Test it multiple times and create several experiments that test your hypothesis.

Oh, wow. The fourth, and I can’t stress this enough, is to prioritize with ROI. I touched on this a little bit earlier. But, as you start building out your experiments… I’ll iterate this with an example from the campaign.

We ran an experiment where on our donate page we had a picture of the President behind a donate form. That was our control. But, then we added an inspirational quote above the President’s head. It said something like ‘Stand with me, work with me, let’s finish what we started.’

When we tested that we got something like a 17% increase in conversions. Because it made the page just a little bit more inspirational and made people really want to finish and stand with the President. That was awesome.

That was just adding copy. That only took us, like, a couple of minutes to get onto a page and actually into production when it won. So, ROI on that is really high.

Our finance team wanted us to implement paying by check, because they had some data that said a lot of people don’t have credit cards. Maybe they have checks that they can pay with. It sounds like a crazy idea to me, but the data that we got from them said that we could expect a 3% increase in the conversion rate.

But, on the technical side that was kind of a big lift. That would take days, if not weeks, to implement. We’re only going to expect a 3% lift. So, when it comes to figuring out what experiments are going to give you the highest ROI, just really dig into the data and make sure that you’re focusing on experiments like the inspirational quote and not things like changing your whole donation system for just a 3% increase in donations.

The fifth one is very easy – test your ideas. Then, lastly, you want to record results. I can’t stress this one enough either. Because on the campaign what happened is we ran so many tests – 500 total – that we couldn’t always remember what the result from one test was.

If we didn’t have this awesome Google doc that we built out that recorded the time, the hypothesis, the result, a screen shot of the control and the variation and the results, and a link to the results, an optimized link, if we didn’t have all of that we really couldn’t have functioned. Because you just can’t remember the results of 500 tests.

You can also disseminate that information when you have it in a Google doc. Just make sure that you’re recording your results.

Now, I just want to talk about four areas where you can experiment. I’ve ordered these by ROI. Copy is, in my experience, by far the highest ROI that you can experiment with. It’s very simple, because you don’t have to change any code or anything. Changing copy only takes a minute or two, and the results that you can get can be really awesome.

Here is the Quick Donate opt in page that I was talking about before. This is the page where if you make a successful donation we ask you to save your payment information for next time.

We did a variation of the header. This one says ‘Save your payment information for next time.’ Very simple, right. Then, our variation changed the copy and it said,’Now, save your payment information.’ It only changed a few words around. It’s not a huge change. Obviously, it only took us like a minute to get this test into production.

By making the copy more direct and directing the user into what we wanted them to do we got a 21% increase on conversions. Again, this is very little development effort, but a huge result in conversions, or conversion lift I should say. Here you can see if you missed it before what the control and the variation was.

After copy, the next highest ROI area of experimentation that I would say is imagery. Because it’s very easy to switch images out, almost the same as copy. It takes a little bit longer, though.

Here’s an example of what we did on the campaign with imagery. This is our splash page for the ‘Dinner with Barack’ contest which is a super cool contest. You could actually win dinner with Barack. They would fly you out to Washington, DC. You’d sit down with Barack and have dinner. Sometimes Michelle would be there. Actual people won this contest. After you submit you would get entered into that.

Here we have a picture of the President. We figured out early on that big smiling pictures of the President worked because people love him. We had a hypothesis that people would be more likely to submit this if they could picture themselves in that scenario. You can’t really see the people that he’s talking to. It doesn’t really seem like a real contest. It’s like, ‘Could I really have dinner with Barack Obama?’

So, we came up with a variation that gave the user a view of a little bit more of the situation. Those are two actual people on the right that won this contest. They flew them out, and they had dinner with Barack and Michelle.

The results of this putting a more situational image in there gave us a 19% lift in the conversion rate. Again, this does not take a lot of time to implement. It’s just a very easy test. We got a huge lift on it.

Here are the two different images so that you can see them again.

Another area that I want to talk about is performance. This is going to be a little bit techie for technical. But, you guys are all probably very familiar with how page load affects conversion rate. We were, too. Early on in the campaign we knew that Amazon had published a statistic, and it’s a crazy statistic, that even 100 milliseconds of additional latency on page load could drop the conversion rate by one percent. So, that’s like huge.

We’re obsessed with performance. We want to make our pages as fast as possible. Here is a look at the architecture diagram for the platform that we started with. It’s very simple. It’s very basic. It was built by a company called Blue State Digital which was one of our vendors. I actually came from there before I started at the campaign.

It worked really well for us in the beginning, because it was built out of the box. As the first engineer there I didn’t have time to build a new platform. This was already out there and working.

The user makes requests to a load balancer, and that splits requests to two clusters. If you’re asking for the page it would send you to the web cluster. If you actually hit submit on the form it would send you to the payment cluster.

Very simple, but there were a lot of problems with this in terms of performance. We, on average, saw five second page load time which is horrendous when you’re processing $690 million worth of donations. You want something more like below two seconds, or how about zero seconds. Can we get the page to just load automatically?

It didn’t have a CDN. I don’t know how many of you people here are familiar with CDN. That’s content delivery network. If I’m in LA and I request a page, in that architecture diagram the servers were in Boston. So, the data has to go all the way from Boston to LA. If you put it on a CDN… We used Akamai. There’s an Edge server in LA, so it gets it to you much quicker.

There wasn’t any caching in this environment. There were a lot of things that we needed to change. We basically started from scratch and built a new platform. We asked Blue State to turn their hosted platform into an API that we could hit on the client side.

Here’s what that looked like. I’m going to run through it really quickly. We put our static assets, which is our JavaScript files, our images, our CSS and such, on an Amazon AWS S3 bucket which is a super simple data store. It’s awesome.

Then, we put the Akamai CDN in front of that. So, we have really fast access to those. Then, we generated our HTML, the actual pages for these, with a static site generator called Jekyll which is built in Ruby. It’s super simple to work with. It’s great for front end engineers. They don’t have to worry about server side templates and all of that stuff.

Then, we hosted all those HTML files on AWS S3 just like our static assets, and we put Akamai in front of that. The cool part is the two donation processors. Like I said before, Blue State built a donation API for us to post to, and then they had load balancing on their end. They had two nodes behind their endpoint.

We put ours on EC2, and we put them in two different regions. We put one payment processor in California, or it may have been Oregon. But, it was on the west coast. We put another payment processor in Virginia on the east coast.

So, if you had an IP address that was in the western side of the United States you’d be sent to the west coast payment processor, and the same for the east. If the west coast went down for some reason… There was actually a hurricane in Virginia and actually caused EC2 servers to go down during the campaign. All that traffic just got sent to the west coast. It was great. It was very redundant.

Once we got this system in place there was never a down time for accepting donations. We were accepting donations 100% of the time.

The new platform, the biggest metric I think is that it had an 80% faster time to paint. That means how fast the user puts something on the screen, not page load. The browser can start rendering the page, and the page load metric can still be going on because maybe it’s loading some JavaScript or something that’s not critical for page load. I like to focus on time to paint. We got 80% faster here.

To show you what that is, what that looks like, I use WebPagetest – which you guys should all use if you’re not using it now. It’s super easy to get data like this. The top film strip shows you that that’s the fast platform. In one second we have a painted screen. That’s a screen that the user can start filling out a donation. That’s super fast. The only thing that’s not loaded is the graphic assets. Those load by two seconds.

You can see our old platform doesn’t even have anything on the screen by four seconds. That’s awful.

We did a lot to increase the performance here. We had a 63% reduction in page weight. We just threw out all that legacy code and wrote our own. We went from something like 720 kilobytes to, like, 120 kilobytes. Then we had a 52% reduction in HTTP requests which is one of the most common things that contribute to page latency.

What did we get with an 80% faster time to paint? An increase in conversions by 14%. To measure that, we made a page on the fast platform that was identical to the slow platform. Then, we A/B tested them with Optimizely. 14% is not as big as the numbers I was talking about before, but this was in the beginning when we first launched this platform. This was the A/B test to put it into production.

When you calculate the $250 million that this platform brought in over its lifetime that’s $32 million dollars. I’ll take that. The money raised on the campaign was tight. Just by making that 80% faster we got $32 million. Obviously, this takes a lot more engineering, time, and effort, which is why it’s less ROI than the copy and the imagery. But, this is huge. This is $32 million dollars that we got just by making that faster.

The second area of optimization that I want to talk about is… Sorry. This is experimentation and user experience, which also takes a little bit more time.

The screen that you’re looking at right now is a donate page that is already super optimized. This was later on in the campaign. We had run hundreds of tests on this page, and it was performing brilliantly. We ran a lot more experiments on it to try and increase the conversion rate, and we kept failing. We couldn’t get the conversion rate up. So, we got really frustrated and we couldn’t figure out what to do.

We decided to try something big. What we did is on the variation we chunked the donation experience into four parts. Because if you look at this slide right here you see all 16 fields. It looks very intimidating to fill out. It looks like it’s going to take you forever. But, if you look at this one all you have to do is select an amount. That’s a much lower barrier for entry on engagement here. Then, you just go through that and it guides you through very nicely.

We tested this one. I like to call this the gradual incline instead of steep slope. We got a 5% conversion lift. Obviously, that’s not as big as the numbers before. But, like I said, we had already picked all that low hanging fruit. So, 5% at that point was major, because we went a month or two where we couldn’t get the conversion rate up at all.

That was a pretty big win for us. Like I said, it was on an already optimized page. You can see the two forms here. One is obviously much simpler to fill out, or it looks like it is.

Here are some best practices I want to share with you guys. The first is start simple. You don’t have to make this complicated. My motto in any engineering scenario at all is start simple and test up. You don’t have to make a really fancy user experience. You don’t have to make it all Ajaxy when you launch.

Just get something out there and get it into production, because done is better than perfect. Then, since you’re in production so much earlier you can start experimenting. Each feature that you roll out you’ll know what affect that has on the conversion rate because you can test it.

The second is always have a test running. If you have traffic coming to your site, which you probably do right now, and you’re not running a test that’s just wasted potential right there. Because you’re not learning from the people that are going to your site. Always have a test running.

The third is don’t be afraid to fail. I can’t stress this one enough. I can’t actually remember the numbers, but I want to say something like only 20% of our experiments on the campaign actually raised the conversion rate. A lot of them were a statistical tie where it resulted in nothing. Some of them even decreased the conversion rate. Those are pretty damaging psychologically, but you can’t let that get you down.

I want to show you an example of this. Ignore the amount buttons. This is a bad screen shot. I don’t know how this came about. But, everything was the same except for a little check box down there that says ‘Save my payment information on the variation’.

Somebody had the idea to instead of ask the follow up screen to save your payment information we wanted to put it on the donate page. Because they thought maybe that would increase the conversion rate on saving people’s payment information. Well, this slide is a little out of order.

That actually reduced our conversion rate by 44%. Right when we saw that we stopped the experiment immediately and just moved on. That’s the whole thing about testing. It’s not permanent. You can just move on. You might not even have thought that that would result in that. I’ll go back to this side. If you aren’t failing then you aren’t testing enough, because you’re not going to have 100% success in your tests. It’s just not possible.

The second area of optimization I want to talk about quick is data gathering. You really can not gather enough data. That’s really my motto.

We on the campaign just gathered any kind of data that we could think of – error rates on forms, when people focused in the forms, and how long it took people to submit the form. And, how long it took for our Ajax response when the user hit submit to get a response from the server so that we could tell the back end engineers how long it’s taking. Because we want it to be faster, obviously. Anything we could think of we measured it.

Again, here’s this number. We did over 668 million Google Analytics custom events. Here’s an example of one. This is an interactive infographic that we put out to showcase our 1 million donors. It was pretty early on in the campaign. It has a lot of little pieces of interactive content there where you can scroll to see names, what are the most popular names people donated under, and where people are from.

One part of that is this little piece right here which you can just scroll through and see the most popular names. We put Google Analytics custom events on the left arrow on the right arrow, and we found that 82% of the clicks were to the right arrow. So, that left arrow was unnecessary, and it’s just cluttering the UI and gives the user more options. You obviously want to be guiding the user through what you’re presenting to them.

We used that learning to optimize our UI’s further down the road, and we just didn’t put left arrows on anything, because it doesn’t really make sense. This is the Google Analytics custom event to track that data. It’s super simple and it’s arbitrary. The category is one million infographic. The label is name slides. Super simple.

The last area that I want to talk about is user testing. This is actually a really cool example, because it solved a problem that I don’t think that we were going to be able to solve without user testing.

This is the last step in the donation process. This is where we’re asking for your employer and occupation. This is required of us by the Federal Election Commission. So, there’s no choice. We had to gather this information.

Well, when we put the error tracking on our donate form we found out that the two most common errors behind people entering their credit card information was employer and occupation. We were like,’Wow, that’s really weird. How can that be such a hard question?’

We went through and looked at the data people were submitting. It was like, ‘None of your business’, ‘F you’. People just aren’t comfortable, right. So, that was that. There’s nothing we can do to make people more comfortable, really.

So, we just left it at that until we started doing user testing. We took a lot of the volunteers that came into headquarters. There was a ton of them. There were students, there were retired people, and all kinds of age ranges.

We sat them down on the computer on Silverback, and we asked them to make a donation. Sorry, I’m cheating a little bit. We found out that the students and the retired people did not know what to put in there. Because they’re not employed.

Again, this is us thinking as us as the users. We work for the campaign. ‘I know where I work. I work for Obama for America.’ That’s a very simple question for me.

But, to a retired person it’s like, ‘What do I put in there?’ So, they don’t put anything, and then they hit submit and that triggers the error. That’s why the error rate was going up so high on these forms.

Once we got that feedback from user testing and observing our users use our product we put a little tiny – and I don’t know if you guys can see it but it’s just a little tiny line that says ‘If you are retired please enter “retired” in both fields’. Little tiny bit of copy. It did not take us a long time to put that in there.

Adding that field hint in reduced the error rate by 63%. That’s just crazy. Like I said, we would not have known to test that beforehand if we weren’t doing user testing and watching our users.

I blog about all of this stuff a lot on my personal website. It’s kylerush.net. I go into a lot more in depth on the technical side and a lot more experiments if you want to check that out.

That’s all I have for you guys. Thank you.

Cyrus Shepard (emcee): Let’s step over here under the light…

Kyle: …You want this?

Cyrus: Awesome work, man.

Kyle: Thank you.

Cyrus: I assume you’re using the enterprise version of Google Analytics.

Kyle: Is there an enterprise version?

Cyrus: Yeah, yeah.

Kyle: I know that we had a direct line over there where we were like ‘Hey our stuff’s not loading, can you please do something?’ They were, like, ‘Refresh it because there was too much data…’

Cyrus: Yes, yes…

Kyle: …It was a lot going on.

Cyrus: One question I did want to ask. For your testing platform, did you build that yourself, or did you use an off the shelf version?

Kyle: No, we used Optimizely.

Cyrus: You used Optimizely.

Kyle: Yeah, which is awesome…

Cyrus: …And, you’d recommend it?

Kyle: If you guys aren’t using that, use Optimizely. It’s amazing.

Cyrus: Yes, question?

Amanda: Is this on? There we go. Hi, my name’s Amanda Stevens. I’m from marketing agency in Winnipeg, Canada. Fantastic presentation. My question for you is you talked a little bit about the design elements and the UX changes you made to the website to add that lift. I’m just wondering if you can expand on some other design elements that you incorporated to increase conversions.

Kyle: Yeah, sure. I don’t want to be too harsh on design, but in my experience what we tested on design, embellishments and stuff, is just kind of a waste of time. It’s fine if the designers want to put that in there. That’s great.

But, like I said, when you’re testing, like, button colors, and rounded corner versus square corner, do not waste your time with that. That’s not going to do anything. It’s just going to sink. It’s a time sink.

Really, when it comes to design, our brand was all about imagery and photos. That’s where we got the real big increases in design changes is imagery. Other than that, I wouldn’t say that we found anything as far as design goes that had a real impact on the conversion rate.

Amanda: Cool. Thank you.

Kyle: Yeah.

Cyrus: Yes.

Alan: Hi, I’m Alan. I’m with Three Ventures Technology and Agency. I actually watched Dan speak at an analytics conference in San Francisco. One of the things that I think I actually would like to ask you about is why Optimizely and not Google Analytics content experiments with the multi arm banded approach, and basically minimizing the time increasing a certain conversion rate at 95% probability. So, I mean the amount of time basically that it would take for an A/B test to finish at those rates.

Kyle: Yeah, sure. I can talk about this forever, but I’m going to make it really brief. If you’re an engineer there’s really no other option for you. Because Optimizely makes your life so, so easy.

All it is is running JavaScript on top of your page. When you can do that you just add CSS classes to the page and it changes the design. It’s so easy.

We actually were tasked with finding other A/B testing platforms that were either cheaper or I don’t know what the situation was. We evaluated a lot. I don’t want to dump on other platforms, because every one has its use. But, for us on the campaign Optimizely was by far the best.

One of the problems with Google Analytics is the data’s not live. Optimizely gives you a live reporting on the results. So, you can see right away if your experiment is dragging your conversion rate through the dirt and you can stop the experiment.

It also gives you a lot of customization. You can do really advanced targeting. You can target people based on a cookie. You can target people based on their region. It has, like, a JavaScript expression.

There’s nothing that we couldn’t do in Optimizely. Any idea that we came up with we could do in Optimizely. We tried it in other platforms. There were a lot of limitations. From an engineering perspective that’s why Optimizely is great. That’s mainly why we chose to go with it.

Alan: Cool, awesome. Thank you.

Kyle: Yeah.

Cyrus: And, I think we have time for one more. We’ll go over here.

Q: Okay, so I work in fundraising. Most of the time the relationships that we’re dealing with in terms of how long a person is going to donate is five or ten years, longer if we’re talking about direct mail. So, it seems like a lot of what you were looking at is immediate return. I don’t know if you had an LTV where you were saying we got a 60% increase in conversions, but it affected the LTV or even just the length of the relationship by X. Did you look at things like that?

Kyle: Yeah, we did. I would say it’s very difficult to measure something like that, because it’s not like an exact, like the user’s on the page clicking something. But, if you think about it, we’ve been raising money, not me personally but the campaign, since 2007. So, there is a long term donation cycle there.

The campaign is actually still raising money now. They have an organization called Organizing for Action that exists to support the President’s legislative agenda. They’re still raising money.

I would say that in a political campaign where it’s so crazy and there’s a deadline that is election day, which usually people do not have to deal with, it’s more about the short term. But, they are still doing long term stuff. We just didn’t have to worry about that as much because it was November 7, that’s the day.

Q: Okay, thank you.

Cyrus: Kyle, thank you so much for coming to Seattle.

---

Want more? Kyle’s coming back for MozCon 2014, and you can buy your MozCon 2014 ticket today and save $400.

Can’t wait? Get a front-row experience for all 37 sessions, plus their slide decks, with the 2013 MozCon Video Bundle. Moz Analytics Subscribers, you get $100 discount. $399 regular price – $100 subscriber discount = $299 for the entire video bundle!

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Posted by lenawest

Visual assets like memes and truly informative infographics have always been (and will continue to be) effective ways of driving traffic and generating conversations. In today’s Whiteboard Friday, Lena West walks us through some of the more effective examples, proving that it isn’t difficult to create visual assets that get people talking.

For reference, here’s a still of this week’s whiteboard:

Video Transcription

Video transcription by Speechpad.com

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Posted by Yoast

Editor’s note: This post was co-authored by Joost de Valk and his brother Thijs de Valk.

At Yoast, we’ve recently written about how we’ve drastically changed our checkout page. This process and our findings gave us the idea to do a best practice of sorts on checkout pages. As it is, a lot of checkout pages are far from optimal, and this short film from Google Analytics is rather harsh but lays it out quite well:

There are some elements to a checkout page that, in general, really help your conversion rate. Ignore these findings at your own peril. I’ll be looking at the following factors, all of which have a serious impact on your conversion rate: Focus, Assurance, Clarity, Time, and Social proof.

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Focus

A page needs focus for people to understand what it is you want. On the checkout page this is doubly true; if your focus isn’t on the process of checking out, people will get confused. And confused people don’t convert.

An easy way to add focus to your checkout page is to implement calls to action. Calls to action are somewhat of a science, and people have performed a lot of tests to find the call to action that will work on any website. However, we believe it all depends on context.

Call to action

You should always use a color for your call to action (CTA) that stands out in your design. Usually we recommend people use a color they haven’t already used in their design (or at least that page). Next, bigger is better. The bigger you make your CTA, the more attention it will draw to itself, thus the more focus it will render.

Obviously the size of your button needs to stay workable. Also think about the shape of your CTA. We like to use calls to action that are shaped like an arrow, because they give people a sense of direction. The shape of your CTA alone will give people a sense of forward movement, which is associated with all things positive:

Lastly, the copy on your CTA is of importance as well. In general, be short and concise. People don’t like reading buttons, they just want to know where it leads.

Clutter

Especially on your checkout page, you need to remove as much clutter as possible. By clutter we mean “mess” on your website that distracts from the main goal. Any element on a page that’s not aimed toward that page’s main goal is clutter, and too much clutter makes your page lose focus altogether.

Clutter that is “outbound” (takes your visitor to another page) is especially bad. Make sure that the most important thing on the page is your checkout process. This can mean removing breadcrumbs, products you’re cross-selling and sometimes even a “continue shopping” button.

---

Assurance

Assurance is something people crave. People have to feel safe on your website and its pages, because if they don’t, they simply won’t spend their money there. So be sure to give them the safest feeling possible.

Safety signs

One of the most important things is to assure people your website is ok using safety signs—signs that mean the page/site you’re currently viewing is free from malware and is “hacker proof.” People want a visible affirmation that the page they’re viewing is safe, especially if that page is the checkout page. They want assurance that their money will be safe. So don’t just expect people to understand your website is safe; show it.

Payment methods

People want to know as soon as possible if you’re offering the payment method they want to use. So it’s best to show the credit card logos of the companies you support. If you support PayPal, include that as well, obviously. To avoid clutter, we’ve done this on our checkout page:

This way, it actually adds clarity to the payment options, assures people we have their kind of payment method, and reduces clutter by not showing it somewhere else.

Unexpected costs

As in the video, people do not like to be surprised at the counter. That’s why unexpected costs are the #1 reason people abandon their shopping carts. To prevent this, you need to assure people that there won’t be any unexpected costs. This can be as simple as adding a line like “there will be no additional costs” next to the total of the visitor’s shopping cart.

---

Clarity

Clarity and conversion are often mentioned in the same sentence. If your copy and your pages aren’t clear, they just won’t convert as much as they could. So be sure to make your checkout page process as clear as possible.

Progress bar

A progress bar gives people insight in how far along the process of checking out they are, and also adds the positive effect of gamification. This gamification effect means people will want to get to the next step as fast as possible. On our own checkout page we’ve decided to have people always step in on the second step. The first step is choosing a product:

The reason we do this, is because the visitor has already taken the hardest and biggest step in your process: he chose a product he wants to buy! So validate that step and make them feel good about it. This way the visitor has already done part of the process without any effort.

Product images

It has to be very clear that the product people have added to their shopping cart is actually the product they want. Showing pictures of your product is by far the easiest way to do this. An added bonus is that (decent) pictures actually increase your conversion rate.

Inline validation

Another form of clarity is inline validation. This makes it very clear for users whether they’ve correctly filled in the field or not:

This kind of immediate feedback is very clear and actually makes people more likely to complete the entire form. And in fact, creating inline validation for your form fields isn’t hard at all, as we explained in a post on the technical aspects of implementing inline validation recently.

---

Time

Time plays an important role in your conversion rate. You literally just have seconds for your page to load and convince your visitor that they should stay on that page.

Site speed

In order to convince your visitors within that few-second window, your site needs to be fast enough. Having a website that’s too slow, can literally cost you money. This is especially important if you have a (large) user base on mobile devices.

Cookie expire time

You can actually have your website “remember” what people added to their shopping cart. This information is stored in cookies, and you can determine how long this information will be stored. Only 50% of your shopping cart visitors will buy within an hour. After that, it takes people a lot longer to make a decision.

If you want 80% of your shopping cart visitors to buy what they added to the cart, you’d have to save those items for 7 days. Doing this will make sure people can leave your website, come back later and simply pick up where they left off. This makes it a lot easier for people and removes the risk of having people go through the choice and thought process of picking one of your products twice.

---

Social proof

Social proof is a powerful way to persuade people. There’s nothing more useful for influencing people than other people telling them your product is awesome. Social proof works because people will get more confidence in a product if they, for instance, read good reviews from other people. The manufacturer of a product is always going to say their product is fantastic. Having other people talk about it, simply makes it more objective, and thus more trustworthy.

However, you have to take care, because social proof can also seriously backfire. You have to make sure you’re using positive social proof. Positive social proof means providing people with things they can gain from using your product, instead of what they’re risking not to gain (negative social proof). Telling people what they’re risking, or worse, how many other people are risking it, can have the exact opposite effect of what you’re trying to achieve. People will only find more reason not to use your product.

Testimonials

Testimonials are stories or pieces of text from actual users about your product. If positive, these can have great impact on people. Always be sure to use as much information of the person giving the testimonial as possible. Adding pictures has been found to increase trust, even if the picture didn’t make any sense at all. However, a picture of a face always draws more attention:

This actually has a drawback, because people looking right at you will keep your attention. If at all possible, it’s best to have the eyes of the person in the picture pointed to an important element on your page, such as your call-to-action.

Lately we’ve been reading a lot about ‘mini stories’. These are basically testimonials, but written like short stories. When written right, mini stories are supposed to have a kind of seductive effect on people.

Numbers

Telling people how many went before them in buying your products persuades people to also buy your products, especially if it’s a high number. This is due to multiple things, among which peer pressure is probably the most important. It’s basically trust based on numbers. Peer pressure means people are afraid to “stay behind” if a lot of other people have already done something. When using this tactic, be sure to use the exact number of people who’ve bought something or signed up, and to not round anything up. It turns out that for your visitors exact numbers are more believable.

Authority

Telling people what other important people or businesses have used your product or service is a great way of persuading people. Especially if you use the kind of people and businesses you know your visitors will like. This is all because of the Halo Effect, which means people’s impression of you can be influenced by their overall impression of you. So if you make that overall impression more positive by naming those great names working with you, they’ll think more highly of you.

Up to you

Your checkout page needs every much bit of thought as the rest of your website. In fact, if you manage to convert more people here, this will be the closest thing to direct money you’ll ever find in Conversion Rate Optimization. So what do you think? Let us know!

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Posted by Brian_Harnish

This post was originally in YouMoz, and was promoted to the main blog because it provides great value and interest to our community. The author’s views are entirely his or her own and may not reflect the views of Moz, Inc.

For any SEO who collects email leads from web forms, the dreaded part of their existence tends to be the end of the month, when it comes to reporting conversion results to clients—verifying, re-verifying, downloading, and exporting them to generate the all-important month-end reports. It can take hours and can be very tedious, but the information gleaned from this process is well worth it. There are, however, ways to optimize your workflow to the point that it almost feels like cheating your way through the process.

By using standalone programs or macros (mini scripts within a program), a project that would normally take hours turns into minutes, and I want to take this opportunity to teach you how to do this on your own. I will use a standalone program and a macro that I found through my research to demonstrate the process so you can get a better idea of what is involved.

How to scrape leads from your Gmail (or almost any other email client)

There are a wide variety of ways to scrape leads from Gmail. You can spend the money to get a program like UBot that will help you automate the task without much effort. You can get a program like iMacros, and spend the time learning how to build proper macros that will scrape from your email box. You can spend the time to learn how to program scripts using Grease Monkey, or you can program your own stand-alone scripts. Whatever you do, you will want a solution that is as quick and easy as possible and helps to automate the task without adding much effort. I found a program on Black Hat World that is made to work on Windows, so you Mac users will need to install Windows to use it. You can download the program here.

While I am aware of the hesitation involved in downloading anything from black-hat websites, my own tests of this tool have worked out well. There are comments and reviews about this tool around the web, and it seems to work well for many users. My own research has not found an instance of this tool doing anything nefarious behind the scenes, and I would not hesitate to use it in my own email scraping.

How it works

This program works by accessing the Gmail account that is added to it and exporting the To:, From:, Body:, and Date: fields from each email. Here is how to use it:

1. Select the email settings you wish to use to download your emails. You can select To:, From:, Subject, and Date. The “Body” export is disabled; according to the tool’s creator it would end up scraping all of the HTML.
   
   
2. Enter your username. This is your full email address (username@domainname.com).
3. Enter your password.
4. Enter the server and port number you wish to use. By default, it’s set to pop.gmail.com and port # 995.
5. Select whether or not you wish to use a secure connection. This will allow the program to access Gmail whether or not a secure connection is available. If your email does not actually require a secure connection, be sure to uncheck the box.
6. Once these settings are selected, it will save a file in the email extractor folder with a name that looks like this: 10-1-2013-1-00 AM_Username@gmail.com.

This program is quite useful for those who either do not have or just don’t use Microsoft Outlook. If you have Outlook but are not comfortable with downloading and using this program, you can set Gmail to send your messages to Outlook, and then set up Outlook macros to to export all messages to Excel (covered later in this article).

Be sure you don’t violate your host’s terms of service

This program can also work for other email hosts. Try it! Be sure to put in your applicable login details, and you should be able to scrape your emails without any trouble. However, be sure that you are actually allowed to scrape email from your host. Not all hosts will allow you to do so. Before using egregious scraping on your email account, just double check your terms of service (ToS) so that you don’t accidentally get yourself banned from your email service. Why would an email service not allow scraping? Well, it can cause bandwidth issues if you have hundreds upon hundreds of thousands of emails to export. If this becomes an issue, you may raise an eyebrow or two at your email provider. So, be sure that you really want to do this if you want to place such a large load of use on the email services. The author of this article is not responsible for things that may happen if you do not follow specific terms of service regulations. For your reference, here are the terms of service from several common providers:

Gmail ToS: Gmail does not have any terms that specifically prohibit scraping emails. While Gmail does state you may not access it using a method other than the interface, this is a very gray area that does not provide examples. If someone is collecting lead information for a valid reason like monthly reporting for their own use, there shouldn’t be an issue. If, however, someone is using access via another method in order to take down the Gmail service, then I would imagine this is where the Terms of Service here comes into play. And this is why I mentioned the large bandwidth usage that downloading thousands of emails can cause to a server, for example. Be sure you really want to proceed before doing so and make sure you won’t be somehow banned from your email service as a result. We are not responsible for egregious misuse of a service with intentions to cause interference of the service through significant bandwidth use.

MSN ToS: Does not have any terms that ban exporting emails using any of these methods to export emails. (Be sure to read your own ToS).

Yahoo! ToS: Does not seem to have any terms that prohibit exporting emails. (Be sure to read your own TOS).

Hostgator email limits: While ToS doesn’t specifically seem to limit scraping or exporting of emails, there are policies and limits in place. According to Hostgator’s mail policy and limits page, “Each connecting IP is limited to 30 POP checks per hour.” Possible interference issues with Hostgator services and this software can occur if you are using the software 100s of times per hour, for example. However, because it uses at least one pop check in order to download your emails, you shouldn’t have too many issues unless you continue multiple downloads of emails from your account per hour. In which case, you will “likely get a password error indicating that the login is incorrect.” Such an issue corrects itself within an hour and the email checking will automatically unlock.

Also according to their mail policy and limits page, their VPS plan and Dedicated do not have the same restrictions as their shared accounts do, so you will probably have more success with high-volume scraping on your own private servers.

A fair warning, however: I haven’t specifically tested this with Hostgator, so be sure to use caution when exporting too many times.

Importing your scraped file into Excel

Once you have scraped your email and it saves it as a text file, it shows up all garbled. What we want to do now is import it into Excel so it displays all of the tab-delimited items as columns, so that we don’t have to manually copy and paste every single one. To do this, let’s open up our file in Excel by clicking on File > Import.

It will ask you: What type of file do you want to import? By default it has selected the CSV format but let’s select the text file format since our program saved this to a text file.

Now, click the file that you want to open and click on “Get Data.” The text import wizard will pop up showing you settings to choose from. Select the “Delimited” option unless it is already checked by default. Then click on Next.

In this step you can set the delimiters that your data contains. Remember when we selected the semicolon back while importing our file? Select the semicolon option here. Then, let’s click on next.

Here, we can set up our columns and set the data format. For our purposes, however, let’s just go with the default options.

Now, it will ask you where you want to put the data. You have a choice of Existing Sheet (which starts at =$A$1), new sheet, and pivot table. For the purposes of this article, let’s just go with the default and click on OK.

Here, you see we have perfectly aligned columns and data without much work. Now you can move forward with formatting these columns and data in whatever orientations or pivot tables you like.

How to download leads from Outlook to Excel

For those who use Outlook, depending on your version, it can be cumbersome to get the data out of the program and can take longer than in just about every other program. Thankfully, Outlook features macros which can be used to export all of your data in the span of just a few seconds!

Step 1: Find or create the macro script you want to use

There are a ton of options and configurations available for this task. For our purposes, we will use modified versions of the scripts located here.

Before we get started, we will need to get the basic code from the very first code snippet, shown below. This code only exports the Subject, Received Time, and Sender of the email message. Our goal is to modify this script so that our new code will extract the entire body of the message and output it to the spreadsheet as well. Don’t worry! I am going over each line of code that we modify in this tutorial! This way, you will understand exactly what we are doing and why.

Sub ExportMessagesToExcel()
  Dim olkMsg As Object, _
     excApp As Object, _
     excWkb As Object, _
     excWks As Object, _
     intRow As Integer, _
     intVersion As Integer, _
     strFilename As String
  strFilename = InputBox("Enter a filename (including path) to save the exported messages to.", "Export Messages to Excel")
  If strFilename <> "" Then
     intVersion = GetOutlookVersion()
     Set excApp = CreateObject("Excel.Application")
     Set excWkb = excApp.Workbooks.Add()<br>  Set excWks = excWkb.ActiveSheet
     'Write Excel Column Headers
     With excWks
        .Cells(1, 1) = "Subject"
        .Cells(1, 2) = "Received"
        .Cells(1, 3) = "Sender"
  End With
  intRow = 2
  'Write messages to spreadsheet
  For Each olkMsg In Application.ActiveExplorer.CurrentFolder.Items
     'Only export messages, not receipts or appointment requests, etc.
     If olkMsg.Class = olMail Then
        'Add a row for each field in the message you want to export
        excWks.Cells(intRow, 1) = olkMsg.Subject
        excWks.Cells(intRow, 2) = olkMsg.ReceivedTime
        excWks.Cells(intRow, 3) = GetSMTPAddress(olkMsg, intVersion)
        intRow = intRow + 1
     End If
  Next
     Set olkMsg = Nothing
     excWkb.SaveAs strFilename
     excWkb.Close
  End If
  Set excWks = Nothing
  Set excWkb = Nothing
  Set excApp = Nothing
  MsgBox "Process complete.  A total of " & intRow - 2 & " messages were exported.", vbInformation + vbOKOnly, "Export messages to Excel"
End Sub
Private Function GetSMTPAddress(Item As Outlook.MailItem, intOutlookVersion As Integer) As String
  Dim olkSnd As Outlook.AddressEntry, olkEnt As Object
  On Error Resume Next
  Select Case intOutlookVersion
     Case Is < 14
        If Item.SenderEmailType = "EX" Then
           GetSMTPAddress = SMTP2007(Item)
        Else
           GetSMTPAddress = Item.SenderEmailAddress
        End If
     Case Else
        Set olkSnd = Item.Sender
        If olkSnd.AddressEntryUserType = olExchangeUserAddressEntry Then
           Set olkEnt = olkSnd.GetExchangeUser
           GetSMTPAddress = olkEnt.PrimarySmtpAddress
        Else
           GetSMTPAddress = Item.SenderEmailAddress
        End If
  End Select
  On Error GoTo 0
  Set olkPrp = Nothing
  Set olkSnd = Nothing
  Set olkEnt = Nothing
End Function

In order to get started, fire up your version of Outlook. I’m using a relatively old dinosaur version (Outlook 2003), but the steps can easily be found online for all versions. Most Windows versions should allow you to use Alt+11 to open the Visual Basic code editor, which we are going to fire up next. To do this, follow these steps:

Step 1: Click on Tools.
Step 2: Click on Macro.
Step 3: Click on Visual Basic Editor.

Next, we are going to copy and paste our code here into the editor window. Now, I used the revision 1 script and modified the original version to extract text from the body by coding the following lines. One after line 19, and one after line 29:

.Cells(1, 4) = “Message” <– This line tells the macro program to add another column to the first row that is labeled “Message”. This will add a new column that displays the text extracted from the email. This one was added after line 19.

.excWks.Cells(intRow, 4) = olkMsg.Body <– This line tells the macro program to extract the message text from the Body of the email. This way, we have an extremely easy and fast method of verifying all of our important conversion emails that we are going to be using in our reporting.

Now that we have our script ready, let’s go to the Visual Basic macro editor.

In the project window underneath the project, right-click within the window, click on insert, and then click on module. This will bring up a VbaProject.OTM file that you can add your code into, as shown in the following screenshot:

Once you have made your desired modifications (or if you desire to use the original script and copied and pasted it, just click on the floppy disk in the upper left hand corner and save the file. Or you can use Ctrl+S to save it. Then, close the Visual Basic editor.

Next, we’re going to run our newly modified macro! First, make sure the folder that you want is selected and all the leads you want to export to an excel spreadsheet are in that folder. Then, let’s click on Tools > Macro > Macros.

Next, you will see a Macros window pop up. We need to click on the macro we want to run, and then click on run.

True to the nature of the script, you will be prompted with a dialog box that asks you what you want to name your file. Let’s call it “ExcelExportTest”. It will save it into your My Documents folder. Fire up Excel, and open your brand new spreadsheet. Here is the final version of our example, complete with all extracted elements of that folder:

Wrap-up

By using these methods, it is possible to greatly reduce the time that you spend on manually verifying and copying/pasting leads from your email box. It will be completely automated! Once you get the hang of using these methods, most of your time will be spent in the formatting phase that comes next. So, it will be necessary to spend this time adding some proper formatting that will help make your reports beautiful and impactful.

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