Author Chris Goward defines personalization and segmentation, and shows why average conversion rates aren't as important as conversion rate differences by segment.
- After being invited to speak at hundreds of industry conferences and corporate events over the years, I've come to see patterns of the types of challenges business leaders are facing. I've answered hundreds of questions from attendees. And you know what the most common question is? What's the best button color? (laughs) Now, in this course, we're definitely not going to answer that question. Here's a hint though. It's irrelevant. There are much more important and powerful questions to ask in your conversion optimization program. In this course on personalization, I will answer the second most popular question I hear.
And that is what's the average conversion rate in my industry? Now, in reality, this is an irrelevant question too. Or, at best, it reveals an underlying insecurity in marketers. What the question really says is should I be trying to improve my conversion rate? How bad are we doing really? Or when should we stop trying to improve? When you think about it, average conversion rates are meaningless too. Think about your own business. You'll have different conversion rates for visitors on different pages throughout your website or from different traffic sources, different email lists, different tiers within your database scoring algorithms, and all the other ways of identifying different visitor segments too.
So, what's much more interesting is to ask yourself why your conversion rates are different for all the different segments? There's much more to learn from the peaks and valleys than from trying to generalize for averages. And the next obvious question to ask yourself is how can I enhance and build on those differences? If one segment of your visitors responds better to a marketing message than another, are there better, more customized messages that would work for each of them? And, if that's true and you split your marketing message into two segments, let's call them Segment A and Segment B and that improves your results, then why stop there? Should you split them into more customized segments? Maybe A, B, and C or all the way to Z? Or should you continue until you have a single customized experience for each person who interacts with your company? Now, what we're talking about is the Marketing Customization Spectrum.
At one end, we have mass marketing, where everyone sees the same message. This is, arguably, the place for general awareness, brand building, and positioning. At the other end of the spectrum is one-to-one messaging, where each visitor to your marketing touchpoints gets their own individualized message. That's the dream of one-to-one personalization that direct marketers have been dreaming of ever since David Ogilvy made his most famous statement. He said, "I know half of my marketing investment is wasted. I just don't know which half." Now that technology makes it technically possible, we need a strategy and a process to implement it effectively.
See, in between these two extremes, is some variation of segmentation. Now, different people will call this tactic by different names. You can call it segmentation, personalization recommendations, ABM, or something else. In this course, when I talk about personalization, I'll be referring to any point along this customization spectrum.
Chris Goward has helped lead conversion optimization and personalization strategies for companies like IBM, Google, and HP. Join him in this course to learn the principles of marketing personalization, and strategies to put personalization to work in your campaigns. Chris reviews the different personalization platforms, and explains how to integrate them into your existing toolset. He helps you sort through data and find new opportunities, and prioritize your projects using the PIE framework.
- Why is personalization important?
- When to use personalization
- Integrating personalization platforms
- Personalizing existing targets
- Finding new opportunities
- Using personalization data
- Validating with A/B testing for growth and insights