Are your visitors telling you if you’re getting hotter or colder?
By Billy | November 13, 2008
In elementary school, I played the game Hot or Cold in class. The rules of the game are simple:
- One child is picked as the “searcher” and leaves the room
- The class collectively chooses an object in the room, like a marker or eraser, for the searcher to find
- Once the object is selected, the searcher returns to the room and has to find the mystery object as quickly as possible
To help the searcher out, the other kids in the room scream hot, if the searcher gets closer to the object, or cold, if they get farther.
To make the game more challenging, the searcher might be limited to only one clue, just hot or just cold. Kids that were told both hot and cold found the objects fairly quickly, but if they were only allowed one type of feedback, it took them much longer.
For the same reasons that it is hard to find the object in the game without being told where it is closer and farther from, in testing, if you don’t design your tests with two distinct variations, you might go wandering for a long time trying to find what exactly your customer wants.
My metaphor fails in one way though. In the game, the searcher does find the object eventually, even with just one type of hint. However, If you don’t design tests correctly though, you may never find a page that resonates strongly with the audience. You might test dozens of testimonials and find the most successful testimonial, but if you never test it against no testimonial or a review, you may be missing out on even bigger gains.
Let your audience tell you hot and cold by designing your tests intelligently and they’ll help you find the optimal page faster than ever.
Photo credit: Night Owl City CC
Topics: Uncategorized | No Comments »
Have me look over your landing page at ad:tech
By Billy | October 28, 2008
I will be at ad:tech New York on November 3-4 manning the Widemile Booth #922. If you have any questions on optimization, landing pages or anything else, stop by and we can chat.
Also, I will be giving some mini-clinics on optimization best practices, how creative influences optimization and perhaps a case study or two based around those topics. The last half of those clinics, I’d like to take a look at some live pages and review them.
But to be more effective, I’d like those live pages to be from volunteers. If you have a page you’d like me to look at, send me a URL and a good time for you and I’ll try to make sure you get included in a clinic around that time.
Find me at ad:tech booth #922
If you catch me when I’m free, I also can take a look at your page and give you some of my thoughts on how to improve and test it. Send me your URL’s beforehand for best results though.
Hope to see some of you there!
Topics: Uncategorized | No Comments »
Gamble with your conversions to raise them
By Billy | August 19, 2008
You and your competitor’s all have the same landing pages. You have a hero shot of the product, a big call to action button and short, punchy copy. Or maybe you’re already ahead of your competitors and have run a few tests on your page, picking up more conversions on the way. In either situation, you’ll eventually hit a wall and struggle to get additional lift. So how do you continue to improve?
Go for broke. Try something you’ve never tried before. It might end up being a total failure, but it also might give you the lift you want.
The gamble you make with optimization can end in 2 ways:
- You lose X amount of conversions over the week or two that the test is running
- You gain X amount of conversions for the effective lifetime of the page
The possible upside dwarfs the downside by a large margin and, either way, you learn something new and can optimize the next test more successfully based on what you learned.
Luckily, with skill and experience, the risks of testing are minimized, however beating a strong page is never easy or guaranteed. But when you do find something new that works or see that your current page still is a champ, you can rest assured that you’re doing all you can to drive conversions.
Topics: Methodology, Testing Concerns, Testing Techniques, Why Test? | 1 Comment »
SES San Jose: Landing Page Optimization Roundtable
By Billy | August 14, 2008
If you’re going to SES San Jose and want to really learn about optimization, check out the Landing Page Utopia: Expert Roundtable. My boss and Director of Optimization, Frans Keylard, will be on the panel. Everything I know was taught to me by Frans, so if you’re serious about talking to an optimization expert here’s your chance. He has a wealth of testing experience and is a fun guy in general.
In addition, Jonathan Mendez will be on the same panel. If you don’t know him, he used to run OTTO Digital, a former division of Offermatica. He is on top of the optimization game as well. It should be a great panel!
Topics: Industry News | No Comments »
An Essential Primer on Full and Fractional Factorial Test Design
By Billy | July 24, 2008
What are full and fractional factorial test designs? How do they relate to optimization and what about interactions?
Once you get down and dirty with testing, these questions matter. Whether selecting an optimization platform or trying to thoroughly understand the tests you are building, grasping these concepts will put you in greater control and allow you to design and analyze your tests more effectively.
As simply as possible, I hope to educate you and other marketers about full and fractional factorial test designs and why fractional factorial is the best choice for multivariate testing of online campaigns.
Note: “Partial factorial” and “fractional factorial” are the same. Also, if you don’t have a thorough understanding of experiments and interactions, please read those first.
The tests used in optimization are from the design of experiments field. (From Wikipedia: “Design of experiments is the design of all information-gathering exercises where variation is present, whether under the full control of the experimenter or not.”) The two types of tests I will focus on are fractional factorial and full factorial.
Here is an example I will use to explain these concepts. Below is a test matrix outlining a test for a landing page with 5 factors with 2 levels each. Don’t let the vocabulary scare you away, this means that there are 5 parts of the page being tested and 2 variations of each.
Recipe Matrix: 5 factors = 5 parts (hero shot, headline, etc.) and 2 levels = 2 variations
These factors and their respective levels make up the possible combinations for a landing page. The combinations displayed are called experiments.
Let’s calculate the total number of experiments possible (even if you know how to do this already, this is important to understanding the distinction between fractional and full factorial.) There are 2 levels for each factor, so you can have 2×2x2×2x2 (2 to the 5th power) = 32 possible experiments. This means there are exactly 32 combinations of hero shots, headlines, sub headlines, button text and main copy from our matrix outlined above. Note that if we add another factor, it becomes 2 to the 6th power or 64 possible experiments. Additionally, if you add 2 more levels to any of the existing 5 factors, it will increase from 32 to 4×2x2×2x2 = 64 experiments also.
In testing, each experiment must get a minimum amount of measurable conversions, known as the sample size per experiment. This ensures that there is enough data for a solid statistical analysis. Therefore the more experiments you have, the more conversions you need. You can think of conversion data as time also, since the longer you leave your web page up, the more data you get.
Now we’re ready to go back to the difference between the two test designs. Full factorial testing requires that every possible experiment combination is shown, so our 5-factor test would need to display all 32 experiments. This means that if there is a sample size of 100 conversions, 3,200 conversions will be required. Fractional factorial works differently, it displays a much smaller number of experiments, about 8 in this case, so it would need about 800 conversions.
Since full factorial gathers additional data, it reveals all possible interactions, but as seen by the numbers above, there is a trade-off. More data equals more information but more data also equals a longer test duration. The minimum data requirements for full factorial are very high since you are showing every experiment.
Even if you are using full factorial to get the same amount of information as a fractional factorial test, it will take more time since you need more data to see statistically relevant differences between the many experiments.
You might be wondering how fractional factorial can be accurate if interactions are possible?
Random interactions of high relevance are very rare, especially when looking for interactions of more than 2 factors. You really need to design tests where you look for meaningful interactions that are based on true business requirements rather than hoping for a random and low influence interaction between a red button, a hero shot and a headline.
Whatever the interaction is, you need to be able to understand your audience and infer why there was an interaction in the first place, only then are you ready to start designing for interactions.
Tests should not be filled with random levels, they should be carefully designed for success by focusing on testable hypotheses around the audience. Could a 1 pixel drop shade on a button interacting with the copyright statement ever be truly significant, and not a victim of random error? Is it worth sacrificing thousands of conversions to learn a lesson that won’t result in any relevant increase of real world conversions?
There are interactions that might make sense and those that should be avoided from being measured because of the amount of testing time it adds.
This brings me to fractional factorial. It is possible for fractional factorial tests to detect interactions. How so? Using our example of a 5-factor test, fractional factorial can include everything from only main-effects all the way to 4-factor interaction effects. Full factorial’s only difference is that it is the full extension and includes the 5-factor interaction effects.
Fractional factorial is not a one-trick pony, it is a continuum ranging from testing for no interactions (only main effects) to one factor less than full factorial. It is exactly what the name fractional implies; even one less is a “fraction” of full factorial. It gives you the power to make trade-offs between testing only main effects to testing for interactions based on intelligent test design.
Once you decide to test for all possible interactions, you are committing to a full-factorial test and incur the associated traffic requirements. I’d love to see a test design that is designed for full interactions and still makes sense! Not having the ability to reduce the number of interactions is a huge detriment rather than a benefit of solutions limited to full-factorial testing.
Radically shorter test times allow for many more smart marketing ideas to be tested and adapted based on what you learn from each test run. You, the marketer have the ability to analyze your results and tweak follow-on tests to capitalize on what you learn. This common-sense approach is what hypothesis-based testing is all about and is very powerful. Focus on testing smart ideas to increase your conversion rate – that’s what matters most.
The graph below illustrates how much information is gained and the amount of testing needed, based on the number of interactions tested.
In my experience, the red area shows how valuable the data is based on which effects are being tested, while the blue area shows the amount of data (or time) needed to gather the data to confirm those effects. The x-axis goes from left to right, from main effects to full factorial (5-factor effects).
At Widemile, we believe it is more effective to perform quick, successive tests detecting only main-effects rather than randomly hoping for interactions. While interactions might give you small or even large gains, it likely will never not trump the gains from additional testing, nor the time and money lost looking for random interactions. The additional time required for full factorial tests is large and not many marketers want to wait more than a month for a test to complete.
Fractional factorial is preferred by a few camps, including Widemile, Omniture’s Test&Target (formerly Offermatica) and Interwoven’s Optimost. Full factorial is used in Google’s free Website Optimizer and some tools offered by smaller providers.
Testing for all interactions sacrifices a lot of time. With the speed that audiences, marketing campaigns and seasons can change, it is important to get the most testing done in the least amount of time without sacrificing the quality of the data. Fractional factorial allows you to do just that, making it the wisest choice for multivariate testing.
Topics: Methodology, Terminology, Testing Techniques | 4 Comments »
How to do efficient optimization
By Billy | July 2, 2008
A beginner’s mistake is to test every idea with every test. This is the most obvious way of being efficient. If I can test 50 things in a week, why not?
In my experience, efficiency has more to do with careful test design and doing things right the first time, than trying to test everything and rushing the process. By testing a few big ideas quickly and then designing the next test based on those results, you can do a set of small tests and get answers fast without having to risk your page to many bad ideas.
Every test should have specific questions its trying to answer. Not just “What’s the best performing page?” but questions that lead to that. A car salesman doesn’t blindly try every tactic in the book get you to buy a car, a real salesman probes you with a few questions and changes their technique accordingly.
That’s how you should design your tests.
Here’s an example test plan that works for most clients:
- Step 1 (Split Test) - Find an optimal template/design: What template and/or design effectively gets visitors to stick, click and convert? At this stage, you aren’t testing messaging yet, you’re merely re-skinning and moving elements around to find a good design. Some techniques to use are simplifying the page by de-emphasizing unimportant content (shrink company logo, move ads to the bottom of the page) and emphasizing core content (moving 3rd party validation near the call to action) and adding more whitespace to the page to enhance readability. These are in addition to a well done creative design. This test usually has the greatest impact, however it all depends on your current page and the audience. (Read more on template testing)
- Step 2 (Multivariate Test) - Find the biggest converting segment: This test focuses on finding the correct messaging by appealing to different segments that you know and hypothesize visit your page. If your product was Google Apps, you might test appealing to business users and freelancers. Or if you are selling a cell phone, you might test features against benefits.
- Step 3 (Multivariate Test) - Find the perfect way to communicate to the segment: Step 2 points you in the right direction, but this step helps you find the exact place you should be with your page. Use what you learned (freelance messaging won) and try variations on that winning theme to really grab your audience and give them what they want. Also, step 2 may have revealed 2 or more segments that are worth targeting. If you can segment them out, run multiple tests that are customized for each segment, and you’ll raise conversions even higher.
The alternative is to test 50 ideas of which many of the ideas overlap. Why test any ideas that are remotely similar until you know that they work in general? If I go to a dealership wanting a sports car and the dealer offers me 5 colors of minivans, I’m still not going to buy a minivan. Show me 4 types of cars, let me pick the one I like and then we might talk about color.
Let your visitors lead you!
This really is a simple process, but it drives results. Be methodical to be efficient. By course correcting in each test, you get closer and closer to what you need and don’t spend a lot of time testing losing elements. Follow a test plan like this and you’ll get results and learn a lot about your core converting visitors.
Topics: Landing Page Optimization, Methodology, Testing Techniques | 1 Comment »
Updates coming…
By Billy | June 6, 2008
I was on vacation and have been swamped in catching up with client work, but I promise I’ll finish my article on fractional factorial test design soon! It’s a very long article and I want to make sure I get it right.
Hope some of you got to see the Widemile booth at SMX Advanced in Seattle (I didn’t since I was on vacation unfortunately.) I heard good things about the panel Widemile’s CEO, Robert Bergquist, was on and that Jonathan Mendez was kind enough to recommend my blog as a resource, so thanks goes out to him.
Thanks for sticking with me!
Topics: Site News | No Comments »
Interactions
By Billy | May 23, 2008
I’ve written an extended definition for interactions in preparation for a long post about full and fractional factorial. Understanding interactions is a critical part to understanding full and fractional factorial also. I look forward to clearing up some misconceptions about fractional factorial test design. Hopefully I’ll have the post done next week.
Topics: Site News, Terminology | No Comments »
Optimization Glossary
By Billy | May 15, 2008
Someone at the office has put together a great glossary, so I modified it slightly and have posted the glossary as its own page (it has a tab dedicated to it above now.) It is in a usable but not optimal form right now, so I’ll be updating it every now and then. I have also decided to add expanded definitions, in the form of separate pages dedicated to a single word. The first word to be done was “experiment.” Please check it out and let me know what you think.
In the past, I have stepped away from using technical language and jargon but, with this glossary, I will begin using the language I use at the office. My hope is to acclimate others and help them understand the terminology used by myself and others at Widemile and around the industry.
Topics: Site News, Terminology | No Comments »
Billy’s Twitter
By Billy | May 2, 2008
If any of you use Twitter, I’ve opened an account, Billysblog. I’ll be posting interesting links related to optimization, marketing and Widemile, as well as any thoughts I have about online marketing. I’ve included a feed on the left nav bar of this blog too.
Topics: Site News | No Comments »
