Hi Readers! I’ve not been posting lately, which is sad. I’ll try to get back on the horse in 2014
What I have been up to is a fun video interview and podcast with Alex Harris of the Marketing Optimization podcast series. In it, we discuss my framework of the 5 ingredients of a world-class testing hypothesis. Better yet, we do live optimization on landing page designs, showing you how to use the framework on your site pages!
And, if you’re the podcast-listening sort, make sure to subscribe to the Marketing Optimization podcast on iTunes, which features a new podcast with a digital marketing expert every week!
A lot has been written about how to pursue Email Marketing Optimization, often with emphasis on tactics like subject line testing, email creative testing, and landing page optimization for email campaigns.
All great topics, but what I haven’t read about is an overarching framework to use while doing email optimization that will guide you through the process in a strategic way. In my day-to-day world of Conversion Optimization, there are many frameworks that one can follow. For example, the Persuasion Architecture™ developed in the early days at FutureNow, or the LIFT Model™ used by WiderFunnel up in British Columbia.
These frameworks give you guideposts to follow, things to think about, and ways to prioritize work in the field of Conversion Optimization. Maybe some experts have developed similar frameworks for Email Marketing that I don’t know about?
No matter: I’ve got one that I think will work! But I didn’t invent the framework “AIDA,” I’m just going to map it to Email Marketing optimization. Continue reading
In honor of All Hallows’ Eve, I relay this tale of woe and warning about a Multivariate marketing experiment that was doomed, doomed from the start! Read and retain, lest ye tumble into the same pitfalls and traps in your Optimization work. Continue reading
While case studies about conversion rate lift and increases in revenue from testing get a majority of the “press” these days, there is something far less sexy and far more important to be thinking about: The order in which you execute your test ideas.
I know, that’s way more boring than, Learn how company X increased their sales by 4,000% with one simple change!!!!! I don’t blame anyone for wanting to share exciting test results, but what if you burn an hour on an webinar and find out you’ve already made the change they’re talking about? Or, you’ve already tested that change and it didn’t make a difference on your marketing?
That’s why we’re going to talk about something “boring” that is guaranteed to help you get results over a longer time frame. Prioritization – the way you apply resources to Optimization work to get the best ROI. Continue reading
As the testing and Conversion Optimization of websites becomes more widely accepted and practiced, the technologies that enable testing (A/B and Multivariate testing software) are getting better and cheaper. There is good competition in the testing tool market, so it’s a great time to be a company looking to start a formal testing and Optimization program.
With all the choices for testing technology, a common mistake is for companies to simply buy/license a testing tool and assume that they can “handle” the needs of testing and be successful.
Many companies that go down this road fail after a short time due to the difficulties of setting up valid tests, getting measurable results, and coming up with new testing ideas. Even companies that are somewhat successful at taking on testing without any outside help tend to “plateau” after 6-12 months and aren’t able to get sustainably positive test results.
While I can understand a CMO’s desire to reap the touted rewards of Optimization “on the cheap,” this post will explain why you need staffed Optimization expertise to be successful in a formal testing program. Continue reading
I recently had a young Optimizer ask me, “How do you turn analytics data into a hypothesis?” My answer was probably unexpected: “You don’t.” My curt answer was meant to alert this young pup that a single input isn’t enough to form the basis of a good marketing hypothesis.
Today’s post will overview what I believe are the 5 key ingredients of a great marketing hypothesis. Plenty of posts I’ve read have instructed you how to leverage the Scientific Method to write a Conversion Optimization hypothesis. They usually instruct you to make sure it’s provable/disprovable, clearly stated, based on a specific Key Performance Indicator, etc.
This is all good advice, but assuming you know all that, I want to cover the inputs. These inputs, IMO, are the difference between a legitimate hypothesis and a world class hypothesis. Some of these 5 key inputs are probably obvious, but a few may have evaded you. Or, perhaps you thought it was “uncool” to have them as inputs?
I recently read a fascinating paper written by some folks at Microsoft called “Online controlled Experiments at Large Scale.” Skip to the end if you want a link to the paper.
The paper’s topic was how Microsoft has scaled its testing and optimization program on the Bing search engine. It was written with somewhat of an engineering bent, so it wasn’t 100% relevant to my world. The kinds of optimization tests I design and conduct are neither automated nor conducted at such massive scale.
However, the authors laid out 3 “Testing Tenets” that they felt were instrumental to the development (and scaling) of their testing program. These simple rules were fantastic to read and 100% relevant to the world of Marketing Optimization and testing!
I enjoyed them so much that I’m going to summarize them for you, with commentary on why you might want to steal them .
Optimization is difficult. I’m often amazed that good, sound testing ever occurs on websites due to the fast-evolving complexities of digital marketing, web development, and doing business across the digital landscape.
One of the reasons that Optimization is difficult is because it’s extremely cross-discipline by nature. It’s part marketing, part user experience, part design, part analytics, part web development, and part statistics.
Anything that cross-discipline requires a great deal of coordination to make sure all the specialists involved in conducting a test are doing their parts efficiently.
Another challenge of cross-disciplinary digital work is that accountability is sometimes missing, or not strong enough. This is a major reason why a lot of corporate testing programs don’t grow from “skunkworks” into something more accepted and robust—testing efforts become inefficient due to a lack of shared understanding about who is responsible for what and when. And maybe more importantly, who takes command when things aren’t running smoothly? Continue reading
A lunchtime topic came up today regarding Web Analysts and Conversion Optimization specialists. We started debating what each job was all about, what the similarities were, what the differences were, and whether you could be good at both.
Before I dive into my own thoughts and observations on this topic, let me try to answer a crucial question:
Why should I read this post? What’s in it for me?
Fair enough. I respect your time, so IMO you should read this post if:
- You are thinking about a career shift from one discipline to another (e.g. Web Analyst to Conversion Optimization Specialist).
- You are developing Conversion Optimization practices within your organization, and wondering if internal resources can help fill gaps.
- You are recruiting externally for either skill set, and wondering about the overlaps, differences, etc.
- You work with either Web Analysts or Conversion Optimization specialists, and want to understand better “how they tick.”
- You are early in your career, have interest in both, but want to know which discipline to focus on when developing your skills.
We good? Onward! Continue reading
I posted nearly a year ago about how multivariate testing is a flawed method when you use a “recipe” approach. And I haven’t written much about multivariate testing (MVT) on my blog, except to get tactical and talk about how I’d use MVT to experiment with testimonials.
In the spirit of fairness, there are plenty of ways to leverage MVT for business benefit, and plenty of testing scenarios that call for multivariate experiments. One such use case occurred to me when working with a client that was what I call “resource-constrained.” Continue reading