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
On December 6 of last year, I presented a session at the BestPractices conference in Seattle, WA. BestPractices is a conference and webinar series presented by Analytics Pros and focused on, you guessed it, “best practices” around digital analytics and optimization.
The session was titled “Building a Successful Optimization Program” and the slides have been posted for public consumption.
I will be presenting a follow up webinar, “Testing & Optimization: A Deeper Look” on Wednesday, January 16th at 10am PST. Seats are still available, so feel free to put your name on the list here »
We all know that Optimization and testing efforts should be “data driven.” Quantitative and qualitative data should lead you to the problems that testing attempts to solve for your prospects.
But how, exactly, should quantitative web analytics data be used to power your Optimization efforts? How does analysis differ when you’re looking for insights and testing opportunities? Great questions, if I do say so myself 😉
I’m going to answer both in this post as I lay out a basic framework for how to “do” web analytics in the context of Optimization. I compare web data analysis to looking with different “lenses” at the same set of data depending on the context. For example, if I’m doing analysis on “site performance,” I would take a different view of the data than if I were doing “campaign analysis” or “content performance analysis.”
It’s the same for Optimization. You look at the same data as always, but you look through a different, contextual “lens” to suit your needs. Continue reading
Last month, the venerable Bryan Eisenberg wrote on his blog about Content Marketing Personas. The article was a good reminder for us that there are a lot personas out there in the marketing world, and many of them are sub-par if not dangerous.
I especially liked his suggestion that readers explore his “conversion trinity” on paid ads and landing pages using existing personas to see if they were up to the task of helping optimize a landing page experience. He has promised us more columns about “getting personas right” in the future, so I recommend you keep an eye out for those.
Coincident with me reading Bryan’s post, I was doing an on-site consulting engagement with a new client. They were looking to redesign a microsite with the goal of boosting lead conversion rate. I was relatively unfamiliar with their marketing efforts, so I asked if they had marketing personas. They answered, “Yes,” and I was delivered an 8Mb PDF with a professional layout, high-quality stock images, and content that was backed by legitimate research.
I deleted it minutes later.
Why did I delete these personas, choosing to “start from scratch” instead of leverage a document that had obviously taken many hours to produce?!? I won’t answer that specifically about this client’s personas, but it’s my segue into my 3 warning signs that your personas may be toxic. If the personas you’re using to do Optimization (or any Marketing) show any of these traits, you may be shooting yourself in the foot. Continue reading
For years, I’ve been searching for better and better ways to explain what it is that I do as a Conversion Optimization specialist, and to encapsulate the value I bring to marketing organizations.
I’ve heard that you should be able to explain your job to your grandparents. Anyone who works in new media, web, or technology knows how challenging this can be!
For those in the web industry, I could easily argue that Conversion Optimization is a sub-skill of User Experience (UX) design. I’m constantly experimenting with, and trying to improve, the experiences that users have on websites so that they’ll be more likely to buy, become a lead, etc.
But, that last paragraph is useless when you’re explaining Optimization to your grandparents, or even to marketing executives that have lived most of their lives in the years “B.I.” (Before Internet).
So, in this post, I’m proposing a new metaphor that I’ll be testing in the near future with grandparents, clients, and maybe even strangers at dinner parties!