Filed under: Research, Search | Tags: Blog Action Day 2008, Google Insights for Search, World Poverty
Well today is Blog Action Day 2008 so I decided to participate.
I started with Google Insights for Search and entered the word “Poverty”.
Here is what i found interesting. The top 10 regional search interest for the term “Poverty” were actually those places in the world that are faced with the most extreme levels of poverty and not those countries who have clean running water, housing and appropriate levels of medical care. You can see from the volume of searches from these countries that these people are screaming out for help. Its up to us (the lucky ones) to get behind this cause and support them.
Top 10 locations of people searching on the term “Poverty” were:
Filed under: Data, Visualisation | Tags: Advertising, Data, Visualisations, World
Here is an example of an advertisment using wordle.net
Will we see more ads in the future targeting consumers with real world data?
Pretty interesting concept if you asked me…
Filed under: A/B Testing, Behavioural Targeting, Multivariate Testing, Optimisation, Segmentation, Web Analytics | Tags: Omniture, Optimisation, Test&Target
Optimisation is a fuzzy word. It’s been used to describe everything from decreasing page load time to improving user experience.
1) Testing - the process of testing alternatives on your site to see what converts best. Testing is most often implemented as simultaneously delivering alternative content to your visitors in a randomised fashion.
2) Targeting – the process of displaying relevant content to a particular segment or individual based on implicit and explicit variables such as gender, search terms, and intent. Targeting is most often implemented as delivering content to your visitors in a rules-based fashion. For some companies with enough site traffic, targeting can be delivered to the individual in an automated fashion.
Testing and Targeting: 1+1=3
Both efforts rely on the ability to deliver content dynamically on your site. Both are designed to increase key success metrics on your site. However, they are often separated as two completely different initiatives within a marketing organisation. While people seem to be interested in the idea of combining them, they are usually already siloed as different projects with different teams, budgets and timelines by the time we have the discussion.
Let’s first talk about testing by itself. It’s a great way to figure out what version your visitors prefer. If you’re just throwing new designs up on your site today on a wish and a prayer, testing is definitely a must. But then think about who your visitors are. Are they all people who are coming for the first time? Are they all visiting during work hours? Do they all enter on the same page looking for the same thing?
If your answer is no to any of these questions, then you have to ask yourself if it makes sense to assume that they all prefer the same winner in any given test. The easiest way to figure this out is to segment your reporting. That doesn’t change anything about how the test is designed or implemented, but it can give you additional learnings in the reporting and analysis.
What if you found out that the reason a particular version won was because it resonated deeply with your new visitors coming organically to your site? And balancing out that great lift was actually a negative result with other smaller segments such as direct mail and branded queries coming from paid search? This type of data is incredibly valuable for any organisation trying to get deeper insights into what their visitors are looking for and responding to. What makes it invaluable is to then take action on those learnings by delivering that targeted, winning experience to your organic, first-time visitors and then simultaneously beginning a new test on the rest of the traffic.
eHarmony ran a test with Omniture to understand whether adding tabbed navigation to a landing page would be more effective in getting users to convert. The hypothesis was that providing more information about the service directly on the landing page would be a positive change. Here are the different versions.
What they found was that the test actually performed worse for overall traffic, and that people preferred the simplified page without the AJAX navigation. Once they dug into their segments though, they found a more complex and interesting story. They had set up geo-segments to track how people from different countries behaved, and it turned out that visitors from Canada significantly preferred the navigation. This learning would never have been found without segmentation, and worse, the tabbed navigation would have probably been thrown out based on the overall negative lift.
What is Targeting Without Testing?
What is targeting without testing though? Isn’t it the same as just putting your hypothesis out onto the site and hoping your hunch aligns with your visitors? For example, let’s say you own a retail clothing site, and you want to target visitors who look at accessories and then return to the home page. You may wonder which accessories to now reinforce upon their return, but what if you should instead be asking yourself whether accessories is the right category to show? What if you should be featuring women’s clothing instead because there is a high correlation between the two or the potential for higher margin profit? Or what if showing 2 featured products instead of 6 would make all the difference? Do you know which price range you should be staying between? All of these questions are great opportunities to combine testing and targeting into a single initiative focused on creating conversion and revenue on your site.
BabyCenter ran a test with Omniture’s Test&Target module to understand the impact of increasing relevancy on one of their most highly-trafficked keywords: “baby names.” Below is the control version, along with the alternatives tested against it. What’s interesting to note here is that all of the alternatives have some element of targeting in them. Recipe B offers some relevant text, Recipe C adds some category links, Recipe D provides top 5 names of 2005 for both girls and boys, and Recipe E builds on Recipe B with a few more bullets of information. Can you guess which one won?
If you guessed Recipe D, then you are in sync with most of the marketers who see this case study. However, the answer is Recipe B, the alternative that provides the simplest reinforcement of just a headline and a couple lines of copy. Here’s the test data:
You can see that Recipe B provided 65.32% lift against control with very high statistical confidence. In fact, nearly every alternative performed better than the control except for Recipe D, the version that people most often pick as the winner. It makes sense that we naturally gravitate to Recipe D because it provides us with the most relevant information given that we are searching on the term, “baby names.” However, since we are measuring the success of the landing page based on those who sign up for the magazine, we have to balance driving both relevancy and engagement. Without testing this targeting effort though, we would have no idea whether we picked the right mix.
If you are in the process of testing today, I’d strongly advocate setting up segments so you can begin to see which ones behave differently. Targeting is a natural extension of testing, but don’t forget to go back and test your hunches as well, whether they apply to one segment or all of your traffic. Taking action on your data is the best way to do more with less, a strategy we will all have to follow more closely through the immediate future.
Content Referened from the Omniture Blog. http://blogs.omniture.com/
Filed under: Web Analytics | Tags: Fallout Report, Next Page Flow, Omniture, Pathing, SiteCatalyst, Web Analytics
For most Omniture SiteCatalyst customers, Pathing Analysis is something with which they are pretty familiar. After all, one of the primary reasons to use a web analytics package is to be able to see how site visitors are traversing the pages of your site.
What is Pathing?
Traditional Pathing Analysis consists of viewing flow reports which show you how often site visitors go from Page A to Page B or Page C on your site. By simply having Omniture SiteCatalyst code on your site pages, you will be able to see several different pathing reports right out of the box. Pathing is commonly used to analyse key website process flows in hopes of identifying opportunities for improvement. For example, you may notice that an unusually high number of site visits show pathing exits after viewing the “Shopping Cart” page. After you have several months worth of data, you should be able to baseline your standard pathing exit rates and then make changes to key pages and see if these changes have a positive or negative effect.
There are eighteen pathing reports available in SiteCatalyst. Here are the most common:
Next Page Flow
This report allows you to see two levels of pathing from the selected page so you can visually see where visitors are going from the selected page. The thickness of the bars is representative of the percentages.
The fallout report allows you to add several pages to a canvas and see how often visitors viewing the first page in the canvas viewed the second page and how often those viewing the second page viewed the third, etc… It is important to understand that the visitors do not need to have viewed the pages in the exact order indicated on the canvas, but rather, need to have viewed them in the specified order to be included in the fallout report. While you can only add a finite number of pages to a fallout report in SiteCatalyst, you can add many more to the canvas if you use Omniture Discover.
The pathfinder report allows you to add pages to a canvas, but also provides the ability to add wild cards and choose whether you would like to include entries and/or exits in your analysis. This pathing tool is commonly used for understanding all of the different ways visitors can get from Page A to Page Z on your site.
Important Things to Know About Pathing
The following are some important things to know about Pathing:
- Pathing can be enabled on any Traffic Variable, not just Page Name. The most common uses of Pathing are Page Name and Site Sections (s.channel), but there are many creative uses for Pathing beyond this. For example, if you want to have an easy way to see the order that site visitors view your products, you can pass the product name or ID# to a Traffic Variable on each product page and then enable pathing to see which products are viewed concurrently.
- Pathing reports only consider that a path has changed when a new value is passed to the Traffic Variable. This is important, because, if you accidentally use the same page name for two different pages, you will not be able to see instances where visitors went from one page to the other.
- Pathing reports do not span multiple visits.
- In SiteCatalyst, you cannot combine several pages into a bucket and view pathing to/from the bucket of pages, but you can do this in Omniture Discover.
- Pathing reports are not available in Omniture DataWarehouse or the ExcelClient.
- You cannot view pathing on a Classification of a Traffic Variable (sProp) in SiteCatalyst (though you can in Discover). Therefore, you should take this into account when determining whether to capture data values directly into a variable or a Classification.
- Pathing reports cannot span across multiple SiteCatalyst report suites so if you want to see pathing for different sites, you need to have a common tag on pages of both sites (known as multi-suite tagging).
In this installment of our real-world example, let’s say that one of Greco Inc.’s subsidiaries is a Finance related media site and its goal is to increase Page Views so it can increase paid advertising revenue. As part of its SiteCatalyst implementation, Greco Inc. captures the ticker symbols visitors search upon in a Traffic Variable. It turns out that people are willing to pay top dollar for Paid Display Ads served up on the ”Apple” ticker symbol (AAPL) results page. Unfortunately, many of the other ticker symbol search results pages don’t command such a premium. Therefore, Greco Inc. would like to find a way to identify more “Apples” on its site so it can increase overall advertising revenues. To do this, they decide to enable pathing on the Traffic Variable containing the ticker symbols being searched upon. This allows them to see which ticker symbols are being searched directly before and after (shown below) ”AAPL.”
Armed with this information, Greco Inc. can make a case to its clients that it can provide an almost identical audience as those searching for “Apple” at commensurate price. From a usage standpoint, the best part is that the Ticker Symbol Traffic Variable does not contain all of the site pages, which makes it much easier to follow and provides only the data that is needed.
Content Referened from the Omniture Blog. http://blogs.omniture.com/
Filed under: Marketing Automation, Optimisation, Segmentation, Technology, Web Analytics | Tags: Add new tag, Dynamic Segmentation, Forrester Research, Unica, Unica Interactive Marketing
Unica has announced today the availability of its latest solution, aimed at preparing marketers for the increasingly popular multichannel battleground.
Unica Interactive Marketing is a channel-neutral solution that can be integrated with any inbound touch point, whether it’s the Web site, contact center, or a kiosk, explains Elana Anderson, former Forrester Research analyst and now vice president of product strategy and design at Unica.
By creating and managing a “memory” of ongoing interactions, marketers will be able to capitalize on the ever-important dialogue with the customer.
Anderson highlights three new enhancements associated with this launch:
- scalability: for high-volume Web sites and contact centers;
- advanced analytics and self-learning algorithms: supports known customers as well as anonymous visitors (whereas competitors, Anderson says, often only tackle one or the other); and
- dynamic segmentation: continually captures information provided by customer actions, building a memory of the interaction while continually rethinking and refining its response messages accordingly
- customer awareness from historical and current perspectives;
- centralised decision-making through interactions and dialogues;
- cross-channel execution that supports customer interactions through any channel (including those that switch channels during the decision-making process); and
- marketing organisation tools and technology to enable collaboration and foster transparency.