Using Segmentation to Retain and Attract Different Audiences

WORKBOOK When Good Offers Go Bad Presented jointly by Omniture and Click Z featuring: Bryan Eisenberg; Co-author of Wall Street Journal, Amazon, and New York Times best-selling books “Call To Action,” “Waiting For your Cat to Bark,” and “Always Be Casting.” Sherry Lin; Senior Manager of Web and Business Analytics, Digg.com

When Good Offers Go Bad INTRO You can spend a lot of time trying to appeal to every individual that comes to your site, and never keep up with that impossible task. On the other hand, you can’t treat every visitor the same. They’ll run in droves to your competitors. So, what’s the answer? Segments! In this guide, learn what online marketing expert Bryan Eisenberg has to say about the importance of segments, how to find them and how to keep them organized Marketing is simply and get the most out of them. Then see how Digg took these theories and put saying the right thing them into use. to the right person, EFFECTIVE MARKETING There is a maxim that states that marketing is simply saying the right thing to at the right time. the right person, at the right time. Unfortunately, in online marketing—the very medium where messages can be the most easily controlled—many marketers are saying the wrong thing, to the wrong person at the wrong time. As an example, Bryan Eisenberg cites an example he heard from his brother. His brother is a customer of ProFlowers.com and as such he had filled out a profile allowing them to give him more personal offers. With that in mind, Bryan’s brother received this offer from ProFlowers for a special Christmas offer: The offer was good. The messaging was strong and personalized. The only problem was that Bryan’s brother celebrates Hanukah rather than Christmas. So, for all that the advertisement did right, it missed the mark at a crucial juncture. So, for all that the advertisement did As another example, Bryan presents this example of online marketing from Overstock.com. As a past client of his, Bryan loves Overstock.com and uses them right, it missed the often, but there was one promotion that left him scratching his head. mark at a crucial juncture. 2

When Good Offers Go Bad On one particular visit to their Web site, this is what he was presented: As you can see, there are two instances on the home page of an offer for “free shipping.” Sounds great, right? The catch is that this offer is only good for a first- time customer’s order. Bryan was a regular user of Overstock and certainly not a first-time purchaser, so this offer was immediately useless. The promo continued to show up on the category page: 3

When Good Offers Go Bad …And also on the checkout page: They spent valuable site real estate pushing an offer of no use to a regular user of their site. So, this was an example of the right offer, at the wrong time to the wrong person. They spent valuable site real estate pushing an offer of no use to a regular user of their site. EXECUTIVE MARKETING While in SES Chicago, Bryan heard a presentation from Dan Siroker. Dan was the Director of Analytics in the Obama presidential campaign. Dan discussed some testing they did on the donation site. 4

When Good Offers Go Bad What he wanted to test was how changing the call to action on a donation button on the site would affect behavior. Here are the options he tested: Of these choices, which one do you think got the best response for pulling in donations? Well, the answer is: it depends. It depended on which segment he was looking at. Some segments responded to one option, while others responded to another. Here’s what it looked like: As you can see, those who had not signed up on the site responded with an increase of 15.2% to the option “Donate and get a gift.” For those who had signed up but not donated, the simple call of “Please donate” showed an increase of 27.8%. Lastly, for those who had already donated, the simple request to “Contribute” had the best results with an increase of 18.4%. 5

When Good Offers Go Bad This experiment is a good example of why you don’t want to present the same experience to all who visit your site. Every marketer can find ways to segment their site’s visitors. Here are some of the most basic ways to begin segmenting: All of these different groups must be considered when you’re thinking about what you want to achieve. Think about all of the efforts you use to bring people to your site. There is no way that every single person you target will respond. (That would be nice, right?) But as visitors begin filing to your site, you’ll start to notice some paths that are more commonly traveled than others; you’ll find commonalities and patterns in whole groups of visitors. These paths will be your clues to the different segments that visit your site. 6

When Good Offers Go Bad As an example, take social marketing. Your visitors who connect to you from Twitter will be different than the ones who use Digg, and they may all stand apart from the Facebook crowd. So, keep the behaviors of your segments in mind as you try to increase conversion rates. Based on what you know of your visitors today, what are 2-4 segments you could create and start catering to today? IMPROVE CONVERSION RATES If your goal is to improve conversion, you need to have a clear understanding of what that means. Here is one way to think it about it: Conversion rate = The number of people who take the action you want them to take divided by the total number of potential people who could have taken that action. Let’s look at that definition a little more closely. THE NUMBER OF PEOPLE WHO TAKE THE ACTION The first part of the equation talks about the total number of people who “take the action,”; that is, do what you intended for them to do. 7

When Good Offers Go Bad Each one of your marketing buys and marketing actions are geared to attract a certain segment of your audience. Those who type in keyword “A” might act much differently than the group that type in keyword “B.” Some visitors will be in research mode, others will be in buying mode. You may start to see how their actions correlate to their initial interactions with you. Their actions, such as keyword use, may create natural segments. You’ll start to see that you treat the group who searches for “camera phone” differently than the group that searches for “Nokia 5530.” Another way Bryan Eisenberg segments traffic is through the use of psychographics: the use of demographics to obtain marketing data from people’s attitudes, lifestyles, etc. Those who use this approach have traditionally divided people into four personality segments: The four segments come from two contrasting spectrums. One spectrum is made up of those who are emotional vs. those who are logical decision makers. On the other axis is the spectrum of the pace with which people make decisions: quick vs. deliberate. This matrix makes up the four personality categories of: competitive, spontaneous, methodical and humanistic. The usability group, Jakob Nielson, used this approach as they conducted an eye- tracking study on the Web site of the US Census Bureau Web site. After the study, they were able to report back on four distinct patterns of eye tracking found on the site. These four groups match the profiles of the four personality categories. 8

When Good Offers Go Bad Example A shows the eye pattern of the competitive decision making type. They’re looking at the info at the top of the page and along the side column, but they’re not diving deep into the of the content that is on the whole page. Either a page immediately has what they want, or they quickly leave. Example B shows the methodical type. Note how they take the time to look at everything on the page—in detail. The spontaneous type, in example C, is looking at the points of interaction (in this case, the form fields) and the pictures. Lastly, the humanistic type is focused in on the navigation and other humanistic elements. With these different behavioral types in mind, how do you ensure that they’re taking the action that you want them to take? To get to the answer, you need to ask yourself three questions: 1. What actions have you planned for each one of those segments to take specifically? 2. What unique actions do they want to take based on where they are in the purchase cycle? 3. How are you going to measure them? 9

When Good Offers Go Bad The point is, you need to have different metrics for each segment because they are going to behave differently and “success” will be defined different for each group. If you were to divide your visitors into the four psychographic personas, how would you treat each differently than you do today? THOSE WHO COULD HAVE TAKEN ACTION Here’s the second part of the equation mentioned above. It’s important to treat each segment you identify as its own sales funnel. Another way to think of it is from the standpoint that persuasion is a process, not an event. 10

When Good Offers Go Bad Look at your different segments and think about the path they’ll take that gets them to a conversion action that is appropriate for them, and optimizing those experiences along that path. BUYERS BEHAVIOR AND MODELING You don’t just need to look at the psychology of the buyer, but their stage in the buying process. You can do this very effectively with keyword research. You can clue in on the words that are typically used when a buyer is just browsing and researching versus when they know exactly what they want and they’ve come to your site to get it right then. PERSONAS While segmenting might be nice, you may be thinking as you read this that you could theoretically create unique segments into infinity, making the process of managing them impractical, if not impossible. That’s where personas come in. A segment is simply a layer or nuance to the personas that you’ll identify. These personas will become like real people. You’ll know their story, what motivates them, and the best ways to reach out to them. 11

When Good Offers Go Bad Once you understand your personas, you can start optimizing your business much more effectively. Take one of your segments you’re aware of today. Give it a name, a gender, and write a short bio: DON’T SLICE & DICE YOUR OPTIMIZATION Bryan is a big fan of multivariate and A/B testing. Unfortunately what he sees many marketers do is what he calls “slice & dice” optimization, where they take a landing page and cut it up into lots of little pieces and change things around almost randomly trying to figure out what works better. Bryan gives the example of Overstock.com, a past client of his. They had a Web page that had an unusually high abandonment—to the tune of almost 91.8%. It was their movie page. 12

When Good Offers Go Bad What they typically did is slice and dice the page into many segments, come up with variations for each one, and then mix and match until they got better results. Unfortunately, that takes a lot of resources to create the extra content, and doesn’t offer enough traffic to visit the variations in order to provide significance. What Bryan got them doing was using their segment personas to do a lot of the work for them. For instance: » Spontaneous seek top sellers & new releases » Humanistics care about reviews » Methodicals find by genre » Competitives search by actor, title, etc. With that knowledge, they could create experiences that were more intuitive to the various segments. The page was redesigned, but it had one problem: The graphic at the top of the page read “Kid Titles for Learning” next to the search bar made the competitive personas think that search bar was only for searching kids’ titles. Bryan suggested they change that to communicate that all titles can be searched for there, like this: 13

When Good Offers Go Bad Now, with a graphic that had clearer communication for the competitive types, there was an immediate 5% lift in sales from that page. With a graphic SEGMENTS CONTINUED that had clearer Here are some questions to ask to gain insights into your segments: » Who buys our product? communication » Who does not buy it? » What need or function does it serve? for the competitive » What need is our product satisfying for our targeted groups? » What price are they paying? types, there was an » When is the product purchased? » Where is it purchased? immediate 5% lift in » Why is it purchased? sales from that page. Once you start gathering this information, you will know a lot more about the different segments that are looking for your product or service, and you’ll begin to market to them saying the right thing, to the right person at the right time. 14

When Good Offers Go Bad SUCCESS STORY: DIGG Sherry Lin has seen some amazing successes at Digg using segmentation. Here Digg applies an are some of her experiences, as well as the programs that have been launched by advanced algorithm Digg to take advantage of segmentation. to determine what First off, as an introduction to Digg, it is a place online for people to discover and share content from anywhere on the Web. will be popular and Digg has no editors. Content made popular by community vote. Digg applies an it always links to the advanced algorithm to determine what will be popular and it always links to the original source. original source. Here is a sample of a Digg page: 15

When Good Offers Go Bad Viewers can click on the Digg icon on the left. Content with the most positive votes is moved to the home page. Key Digg stats: » 40 Million Monthly unique visitors (MUV) » 5 Million Registered Users » 5.6 Million Diggs per month » 20,000 Stories submitted daily Digg’s Business Goals » Page views through increased engagement (monthly repeat visits, PV per visit) Who are these users » Contribution—number of “contributors” and rate of contribution » Quality Content —Exit Links clicks per Visit, Submitter Diversity, Promotion Rate and how should Digg retain and Digg has seen explosive growth in MUV in the past years, but PVs are not growing as quickly as MUVs. engage them? Identify addressable user segments and get to know them. Who are these users and how should Digg retain and engage them? The answer was to identify addressable user segments and get to know them. Here is how Digg did this: They started by looking very broadly and deeply at their data with the use of Omniture SiteCatalyst, the analytics solution. That data was supplemented with other Digg data » Internal data on registered users » Third-party data (comScore) » Focus groups & quantitative surveys 16

When Good Offers Go Bad With all these sources of data, they were able to get answers to questions such as: » Where are our visitors coming from? » From search engines or organically? » If they’re coming through search, are they coming from branded keywords or other keywords? » Are the users coming through the home page or linked directly to posted content? » Are the visitors unique, or are they regular visitors? » If they are return visitors, how frequently do they visit? » Of those who visit regularly, how many of them contribute content? » Are there some visitors who submit content only, but do not view or consume content otherwise? Once they had a pulse on this data and they were able to start identifying segments, they had to decide what the right amount of segments was for them to articulate. They came to the conclusion that there were four that made the most sense serving going forward: » Contributors—Logged-in users » Frequent Lurkers—Those who’ve visited more than three times » Newbies—Have visited less than three times; the referrer is “None” or “Other Web sites” » Searchers—Visited less than three times; referrer Search Engines. Many of these visitors did not even realize they were on Digg, or what Digg is 17

When Good Offers Go Bad TACTICS LAUNCHED TO ADDRESS DIGG’S SEGMENTS The first was a strategy aimed at keeping the Searchers on the site. It was the creation of “capsules.” The first was a strategy aimed at keeping the Searchers on the site. It was the creation of “capsules.” As you can see by the sections circled in red, these capsules are places where content is aggregated that relates directly for the search keyword the searcher used. The primary capsule is the “Related Keywords” found near the top of the page. Another capsule, found in the bottom right corner, is dynamically populated by articles of a related topic to the initial search. Also, there is another section, “What is Digg?” that helps searchers know where they are and how Digg can serve their needs going forward. The drawback to the capsules is that it pushed the comments down toward the bottom of the fold, discouraging people from adding comments. To address this, if a visitor was a regular contributor, the capsules are removed pushing the comments higher above the fold. Additionally, instead of “What is Digg?” is replaced with the top stories in the contributor’s search keyword. 18

When Good Offers Go Bad Additionally, there were ways to target content a contributor would likely want to see. First off, a green badge is placed to the left of a story that a contributor’s friends have commented on. 19

When Good Offers Go Bad In the lower right-hand side, these are recommendations based on an algorithm that calculates what the contributor will want to read based on users with similar interests. 20

When Good Offers Go Bad Last of all, Digg came up with strategies, targeted to the different segments, to remind them to come back: » For contributors: emailed alerts (Reply to your Comment, Story You Dugg Became Popular, Friends’ Activity Digest, etc.) » For lurkers: Digg Twitter feeds—their most popular feed has 1.2MM followers » For less-frequent visitors: Best of Digg Digest—subscribe with just your email (no registration required) All of these support the various Digg visitors in the right way, bringing them back to up Digg’s traffic. 21

When Good Offers Go Bad WRAP UP In summary, this is what Digg learned from its segmentation efforts: » As Digg grows, their audience becomes more diverse…so segmentation and customization allows them to stay relevant to all » Iteration is key—they are rethinking their definition of user segments » Iteration is key, part II—not all of their features have been successful » Web stats alone only get you so far—talk to your users! *** If you would like to learn more about segmentation using the Omniture Online Marketing Suite, contact your Omniture Account Manager or call (866) 923-7309. For internationally-located businesses, visit Omniture.com for the office information nearest you. 22

When Good Offers Go Bad NOTES _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ 23

When Good Offers Go Bad NOTES _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ _______________________________________________________________________________________________________________________________________ 24

WEB: omniture.com EMAIL: info@omniture.com A MERICAS UK FR ANCE GERM ANY NORDICS & BENELUX + 1.877.722.7088 TEL +44 (0)20 7380 4400 TEL +33 (0) 1 70 37 53 56 TEL +49 (0) 899 0405 408 TEL + 45 (0) 36 98 89 50 TEL + 1.801.722.7001 FAX +44 (0)20 7380 4401 FAX +33 (0) 1 77 72 56 38 FAX +49 (0) 899 5464 252 FAX + 45 (0) 36 98 89 51 FAX JAPAN AUSTR ALIA SWEDEN KOREA HONG KONG + 81.03.6418.6600 TEL + 612 8211 2707 TEL + 46 (0) 8 601 30 91 TEL + 82.2.2008.3228 TEL + 852 2168 0873 TEL © Copyright 1996-2010. Adobe Systems Incorporated. All rights reserved. Omniture® is a registered trademark of Adobe Systems Incorporated in the United States, Japan, and the European Community.

Using Segmentation to Retain and Attract Different Audiences

by SherryYLin

Accessibility

Categories

Upload Details

Usage Rights

2 Embeds 9

Statistics

Using Segmentation to Retain and Attract Different Audiences Document Transcript

http://www.linkedin.com	7
http://www.lmodules.com	2