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
A quick announcement today that a new book on Conversion Optimization is now available on Amazon! It has, possibly, the longest title ever: You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing. Why am I pumped about the release of this book? Three main reasons:
1) The author, Chris Goward of WiderFunnel, is a smart guy who’s run a lot of tests and developed a solid framework for Optimization.
2) I played a small part in the creation the book as his Technical Editor. I got to read the book as it was written, chapter by chapter, to help optimize the experience you’ll have reading it.
3) Any book with a foreword written by Avinash Kaushik is a book worth reading!
Read more and/or place your order today »
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 »
I’ve written a fair amount over the years about using the 3 stages of the decision-making process as a framework for doing analysis and Optimization. At each stage of the process, the prospect’s mindset and needs are different. Therefore, your tactics for persuasion, testing, and Optimization should be different.
Today I’m going to focus on “Middle” and “Late Stage” prospects, and on one crucial tactic for converting prospects at these stages of their conversion journey. The tactic is more often used in B2B (and especially SaaS) marketing, but I believe it can be applied effectively in B2C scenarios as well.
I call the tactic for this post the “Rebuttal” Approach. It’s a borrowed legal phrase which is also used in politics; especially in debates. A rebuttal is an expected opportunity to counter-argue known points that your opponent has made. In political debates, an opponent is often given, say, 30 seconds to make a rebuttal argument against a specific point just made.
In Optimization, the Rebuttal Approach is your chance as a marketer to make a counterargument against your competition in order to convert Middle and Late Stage prospects. This is a crucial tactic because prospects tend to engage in a lot of comparison research or shopping before they make a decision. A prospect on your site in Middle and Late stages is almost always conducting some sort of comparison between you and your competitors. Continue reading
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