Over the coming weeks, the media industry experts in Adobe Consulting will share a series of analysis quick wins for media publishers, using Adobe Discover 3. For a limited time, Adobe SiteCatalyst 15 clients can inquire with their account team and ask to take part in a free trial of Adobe Discover. We’ve made it easier than ever to try Discover, and we’re showing some great Discover analysis opportunities specific to the retail industry. For more information and to request Discover trial access, contact your account manager or account executive.
Even though I’m an analyst and a marketer because I’m in the Tech industry, my friends and family consider me a “computer guy” and direct computer questions to me. The way I approach answering these questions is going to vary depending on their skill livel and knowledge.
Scenario 1: If my wife were to ask me how to use our new computer, she would probably be refering to the new windows 8 operating system and how to find her music or saved files. She has good computer knowledge so I would talk to her as a peer and could quickly give her a few tips, show her some new features, and she whould be on her way.
Scenario 2: When my 5-year-old asked me that question, she really just wanted to know how to find the games. I could just show her where the game section is and within a few minutes she’ll be playing games I never knew we had.
Scenario 3: When my mother-in-law asked me how to use the computer I had to take a completely different approach. I knew she really just wanted to know about this ”Facebook Thingamajig”. This was an involved conversation where we talked about the on button, how to use a mouse, browsers, and finally ended with me helping her create an account and navigate Facebook.
The point is that each of these people wanted different things, and I need to customize my explanations based on their needs and experience.
Too often I see my clients making the mistake of analyzing and optimizing site behavior at the aggregate level rather then putting their traffic into meaningful user segments. Just like with my family, your customers have unique wants and should be treated diffrently. There is great value in segmenting and targeting your site traffic.
I recently helped a client group their users by visitor frequency per month, such as Infrequent Users, Moderate Users, Frequent Users, and Power Users. By following this approach, you will find a wealth of knowledge about user behavior in these different groups. Often you’ll find completely different results when looking at the internal search terms, marketing channels, articles, and content types viewed by your Power Users compared to an aggregate analysis. This type of analysis is especially useful when it comes to using Test & Target to customize your site experience for your visitors. Why optimize for a generic site experience when you can group your visitors into various engagement levels and customize the user experience accordingly?
For the purpose of this blog post, I’ll be focusing on Monthly Visits/Unique Visitor. However, you could just as easily perform this segmentation using Page Views, Time on Site, Video Views, or other metrics.
This type of analysis needs to be done in Discover because there are time-based segmentation options. You can also use it in conjuction with the new visitor participation metrics (see my last post ) to perform some powerful analysis.
Prior to setting up any segments, you will need to implement an eVar for visit number that expires each month. On each visit to the site, this eVar is populated with whatever visit number you are on for that month. This is typically done with a plug-in (ask your friendly SiteCatalyst Implementation Consultant about this).
After implementing this eVar, we are ready to use Discover to segment based on various engagement levels (1visit, 2-3 visits, 4-6 visits, 7 or more visits…).
For `this example, let’s say one of your segments was a visitor that comes to the site 2-3 times a month. The first step is to segment based on date. In Discover, the segmentation wizard has dimensions for various date groupings (hour, day, week, month, quarter, and year). You’ll need to define a visitor segment where a visit happened during a specific month.
After segmenting for the month you’re analyzing, you will need to define which visit number your visitor reached. To do this, you’ll need to inculde visitors where visits during the month (stored in your custom eVar) was greater than or equal to 2 and exclude visitors where visits during the month were greater than or equal to 4 (see completed segment below).
Once you’ve created segments for each of your engagement levels, you are ready to apply them to any report. This is a great way of comparing the browsing behavior of your Frequent Users compared to that of your Infrequent Users. You can then make decisions on how you can get your Infrequent Users to come back more often and how to improve the experience for your most valuable customers. If you have any questions or thoughts on this Discover tip, feel free to comment below or reach out to your Adobe Consultant. Good luck with all of your segmentation.