Wingify Conversion Optimization Blog
Tips, Tricks, How-tos, Guides, Hacks and Secrets
on Website Conversion Rate Optimization
On this blog and on Visual Website Optimizer’s blog, we get a lot of long tail search visitors. The term long tail is borrowed from power-law like distributions, wherein a small number of elements make up for the most volume while a large number of different elements make up for lesser volume. The latter one is called “long tail” and here is how it looks:
You see I love Split Testing blog is all about (duh) split testing. And I expect search engines to send to the blog people looking for things related to split testing. Of course, a bonus for us, search engines can also send visitors looking for related topics such as SEO, online marketing, web analytics, etc. However, some of the visitors we get from Google were searching for completely different things. Sample some of the following keywords where our blog is apparently ranked highly on Google:
The point of this post isn’t to belittle Google’s job. It is a fantastic search engine and does amazingly job in long term searches. The humorous queries above constitute <2% of total search volume we get.
But, still, it is always good to see such queries in web logs. Makes up for a good laugh. Plus, gives a room for improvement in (now) slow-moving search industry.
For any business, two pieces of information are most important to its survival. One, in order to make decisions, a business needs to know the ground reality of where it stands in the market now. Second, in order to plan forward and determine progress, it needs to know where it stood in the market in the past. These two sources of information individually don’t convey much information. But combined together, they provide actionable insights. Where am I now and where was I is what you need to know if you need to plan for where I want to go.
Making parallels to web analytics, current set of tools (unfortunately) only provide information on what is happening now. Your favorite tool will churn out data on number of visitors, page views, countries, referrers and what not. This exactly tells you how your website is doing today. However, this completely misses out macro trends. Sure, you can see a historical graph of number of visitors and all sorts of other metrics but that is only the first step towards knowing what has changed.
Ideally a web analytics tool should go deep on the segment level and mine signals in the (historical) data and correlate different metrics automatically for you. Here are some of the examples that I expect an analytics tool to mine automatically for me:
Most of what I have written above isn’t super hard. Some of it can be done by having simple heuristics built into the tool. Moreover, data mining and machine learning has progressed a lot and I am surprised web analytics industry has been so slow at adopting the methodologies. Though Google is taking the right steps with their intelligence feature but it still it leaves a lot to be desired: where are correlations, recommendations, trend mining and other interesting stuff? Nuconomy was doing the right stuff but they took far too long, didn’t innovate a lot and end up getting bought by a company for in house analytics.
Web analytics shouldn’t be simply a data collection and reporting tool. It should actually be collection, reporting and mining tool. My tool gives me 100s of metrics to look at which I can’t keep looking at day after day (unless it is my full time job). Instead it should mine all 100s of reports for me, and show me interesting nuggets on what has changed (and possibly what could change). So I ask: where is the innovation in web analytics? All I see around is dumb reports ready to get mind by a human.
What is your perspective on this? Do you think web analytics is ripe for a major change?
Scientific research papers on how to increase sales or conversions are rare. Most of the articles you read on the Internet (admittedly, including a lot of posts on this blog as well) are based on what the writer thinks and what makes logical sense. But scientific research works in a different way. Authors of research papers must produce accurate, reproducible results. And their articles are reviewed by peers before getting published. Hence in most cases you can always trust results of a scientific paper.
So I fished out research papers on the internet which tell you how to increase your revenues online. Here is the list for your reading pleasure:
Usability
Miscellaneous
After compiling this list and reading most of the articles, I realized there is a large disconnect between what happens in research and what is actually applied in the market. Do you agree? Did you even know such kind of research happens at all?
Like everyone else, you want to rank high on Google and you want to extract maximum ROI out of your Adwords PPC campaigns. Your website deals with a particular topic area, say Conversion Optimization (which is the case for this blog). But then the topic is so vast that optimizing (or positioning) website and content on a single broad topic becomes very challenging. A whole gamut of websites deal with Conversion Optimization, so how does this blog have even a minute chance of getting seen on search engines?
The answer is to write website content including keywords and phrases that people search for at prominent places. This is such a no brainer advice that it borders on being completely useless. The real challenge is to know what people search for. You can (and should) bring process to researching what exactly people search and how to rank on it:
Step 1: Go to Google’s Keyword Tool
This tool displays a lot of juicy information on the keywords we enter and other automatically generated related keywords list. Mainly, what we are looking for is:
Enter your main keyword in tool. For example, I enter “conversion rate optimization” as the keyword and get a long list of related keywords. To derive maximum information on these keywords select ‘Show All Columns’ from the drop down (‘Choose columns to display’) towards top right.
After you click on show all columns, you will see an image like the one above. You can note we have multiple data points here:
Let’s download all this information in MS Excel format to crunch some numbers. Click on Download all keywords (.csv for excel) towards the center right.
Step 2: Delete irrelevant keywords
Open the freshly downloaded list of keywords and pour through it. You will notice that it may have many irrelevant keywords. In my case, I found a lot of keywords related to currency conversion. Delete all such keywords. Aim to have a short list of keywords which closely relate to your area of operation.
Step 3: See competition on Google for remaining keywords
In the list we have a field called advertiser competition. But that related to PPC campaigns on AdWords. For organic, natural search results (from SEO perspective) we want to know the competition on Google search. Ideally, it will be easy to rank on the keywords which have low competition.
A good proxy of competition on Google is the number of search results. So fire up Google.com and take each keyword, enter it into the search engine (you can try including the keyword inside double quotes to get finer results but searchers seldom use double quotes so best to enter keyword as it is) and note the number of search results. For example, the keyword “optimizing conversion” (without quotes) gets us 1,650,000 results while “improving conversion rates” gets us 3,930,000 results. This tells us that there is more competition for the latter keyword than the former. Make a new column in excel and for each keyword add number of search results into it. It may be bit tiring to repeat it for 30-40 odd keywords but trust me, it will be worth it.
Step 4: Do the magic!
This is the step where we define our new metrics for each keyword (using the existing columns in the excel):
Idea is that those keywords are most attractive for SEO which get most searches on Google but have least competition.
This ranks keywords on bringing most traffic through AdWords CPC campaigns.
This ranks keywords in your area which will be most pocket friendly.
This ranks keywords in your area which will be most pocket friendly and which bring in most traffic.
So, you simply add these four new columns and do simple calculations in Excel to get values for these four new metrics. (Tip: only do the calculation for the first keyword, drag the results down to all the rows to get values for all keywords automatically).
Step 5: Sort the columns to get most important keywords
Now all you have to do is sort the columns for Organic Attractiveness and PPC Attractiveness to know which keywords are best for SEO and PPC Campaigns respectively. In my case, for SEO (Organic Attractiveness) I get following keywords at the top:
Click here to download the excel file.
I marked some keywords in green to indicate the keywords which I think will turn out to be most useful. Red keyword (“conversion rate”) is too broad to be useful. And I left topmost keyword (“conversion tracking”) uncolored because Wingify doesn’t only concentrate in this to justify maximum effort into optimizing the website for it.
In the end I get keywords “landing page optimization”, “conversion rate optimization” and “conversion optimization” which will yield maximum benefit from SEO perspective. If I choose to advertise on Google through Adwords, all I have to do is to sort the column PPC Attractiveness (Volume or Budget or Overall) to get list of keywords on which I will be bidding first.
Let me know if you find this strategy useful by leaving a comment below.
All right, let’s admit it: increasing conversion rate on a website is still a voodoo science for many. With new technologies and terminology being thrown around (on Twitter, blogs, etc.) every other day, it doesn’t get any easier for people just starting to understand conversion optimization. In this post, I will try to briefly talk about all technologies and methodologies being used today for extracting more juice out of existing traffic:
Apart from these categories, numerous other tools in search analytics, PPC analytics, affiliate management, etc. are available but the above ones are the most useful ones. Even amongst the above, I will argue web analytics and split testing tools should be an absolute must for anybody serious about improving his/her website conversions.
Leave a comment here if you think you have additional toolssuggestions for conversion rate optimization which I missed here.
Sick of tearing your hair for doing a simple A/B test? Do you seek help of highly paid consultants simply for testing whether a red button would increase conversions? Do you continuously churn ideas for improving your website but your developers are sick and tired of your regular code changes to the site? Do the terms page tagging, HTML and Javascript give you nightmares?
Despair no more, Ta-da! Introducing Visual Website Optimizer – a hassle-free A/B, split and multivariate testing tool that you can use with your eyes closed. Okay, a bit of exaggeration there but honestly VWO makes split testing super fun and dead simple. Some of the VWO features which promise to make your life much, much easier:
We won’t do self-praise here (even though we would love to), so here is what one of the initial beta testers has to say:
“[Visual Website Optimizer] does it so disruptively, embarrassingly better than Google does, that it puts a smile on my face” – Patrick McKenzie
Of course, he is referring to a Google optimizer product you probably know about. Ask me privately on email if you don’t
Now for some Good News.
I’ve got 50 free invites for this blog’s readers. Use the invite code “wingify-blog” (without quotes) while signing up for a free account here: http://visualwebsiteoptimizer.com Use it or share it, but do it fast as they won’t last long.
Also, you shouldn’t miss watching a quick (4 minute) video below which shows just how simple it really is to start increasing your conversion rates using Visual Website Optimizer:
Let me know your feedback on the new tool! Did you like it? Bugs, comments or praises – all sorts of feedback is welcome. Leave a comment here or email me at paras@wingify.com
Just a quick post. We are too glad to be shortlisted for most innovative company in the domain of web analytics and optimization. You can see the whole shortlist here.
There are number of metrics that startups and websites obsess on. Some of the most overanalyzed yet non-useful metrics are number of visitors or pageviews on a website. The reason startups get obsessive about them is that these metrics are easy to use and are no brainer. Just slap some code on the website and you are ready to get insights on your startup’s progress, supposedly.
In fact, there are three metrics that a startup (or for that matter, any website or online business) should single mindedly obsess on accurately measuring and hence optimizing for:
The three strategies of: a) getting new customers, b) retaining existing ones and c) up-selling and cross selling new offerings are not new. Management gurus have been discussing them for ages. Even then startups and websites get drowned in a flood of metrics and forget that they are there to make money. They should better be optimizing how to make more money. And only way to optimize that is to focus on the right metrics. Do you agree?
Let’s face the truth; Alexa is not the best source of traffic data out there on the Internet. Plus, it does not have statistics on conversion rates. But, hey, Alexa is free and we are going to use it to benchmark (approximately) the conversion rates for your competition. Here is how to do it two simple steps:
Step 1. Establish industry norms using your actual conversion rate data
Suppose you are SEOMoz (I am using this website as an example and have no real data for them) and you sell paid tools for SEO. Let’s suppose your current conversion rate is a conservative 4% (again, hypothetical data) and you want to estimate how your competitor SEO Book is doing.
You and your competitors (since it is the same industry after all) follow a similar trend when it comes to relationship between conversion rates and other site metrics such as bounce rate, time on site, and page views per user. In this step, we try to calculate values for parameters which relate conversion rate to all these metrics. Using your actual conversion rate data and the stats that Alexa shows about your website, calculate X, Y and Z as the following:
The reason we don’t use your actual bounce rate, time spent and page views data is because you don’t have that data for your competitors. You only know what Alexa says about your website and what Alexa says about your competitors. So it is better to work on the Alexa data that is freely available and uses the same methodology all across.
As an example of SEOMoz, Alexa tells the bounce rate, time spent on site and page views / user is 50.7%, 219.7 seconds and 3.2 respectively. Using this data, we get the values of X, Y and Z as:
Step 2. Use the parameters to estimate competitor’s conversion rate
Now we have obtained the parameters which relate your actual conversion rate to the data that Alexa shows about your website. Next step is to simply use those parameters on your competitor’s data (as shown by Alexa) to get estimates of their conversion rate.
Competitor Conversion Rate:
Finally, to get an idea of what their real conversion rate, we simply average the estimates.
Competitor Conversion Rate = (Estimate 1 + Estimate 2 + Estimate 3) / 3
Continuing the SEOMoz example, if we were to estimate the conversion rates for SEOBook, we calculate 3 estimates of conversion rate (based on the data shown by Alexa for SEOBook):
As you can observe, the estimates are quite close. Hence, we can be pretty confident that the actual conversion rate is close to the average of these three estimates, which is:
Estimated conversion rate = 2.77%
Of course, the above estimated value is only valid if the real conversion rate for SEOMoz that I assumed (4%) is true, which may or may not be the case as I don’t have access to their real web analytic data.
Summary
Simply plug in your conversion rates in the above methodology and you should have pretty good estimate on how you are doing as compared to your competitors. You can also try to triangulate your estimates by using other data sources (apart from Alexa) such as Compete.com or Quantcast.
Do let me know if you find this approach helpful. As always, feedback and comments appreciated. Want a tool to automate all this analysis for you?
PS: The way I define Bounce Rate and Conversion Rate, they are not related. But the way Alexa defines, the two metrics are definitely related.
Lately, I have got quite a few requests for how effective call to action buttons are created in Photoshop. Though having persuasive text as call to action is important, button shape, size, color and style can also make a tremendous difference in conversion rates. So, here goes the list of free resources on creating buttons that convert and examples to get you started:
Photoshop Resources
Ideas for Buttons
This list is an ever expanding list, so feel free to suggest more (free) resources for call to action buttons. Leave a comment and I will add it in the list.
