Tuesday, March 18, 2008

Interesting SEO article from seochat.com

I came across an interesting article about SEO optimization for new websites. This article can be found here.

Some key takeaways from the article include:

  • Start with keyword research and then build your content around your keywords.
  • Make sure the title, description, and meta tags for each page are relevant to that page.
  • Don't publish a site with "under construction" pages and little content.
  • If you are going to use a blog to generate content, make sure you have a good writer who can post frequently and that these posts will help contribute to the goals of the website.
  • Get Google's help. Google offers Google Webmaster Tools.
  • Create a XML site map.
  • Use web analytics!
  • Use external blogs and social bookmarking sites to link to your site.

Friday, March 7, 2008

Omniture Summit | March 6| Discover Exploration Strategies - Know your Visitor's Story

The last breakout session I attended was based around Omniture's Discover. This product is amazing and Tim Lott, Discover product manager and Laura MacTaggard, best practices consultant, both from Omniture, did an excellent job in presenting on this tool. Aaron Wixom, internet marketing analytics manager, Dex Media and Paula Tellez, web analyst, ProFlowers also presented interesting case studies of using Discover.

The presentation began with the simple question "Why use discover?"
The answer was three-fold:
  1. It is the perfect companion to SiteCatalyst
  2. It allows you to hunt for the needle in the haystack
  3. It allows for more concise analysis through segmentation and drilldown
Tim explained that in marketing assumptions have to be made. However, the more assumptions you make, the more of a gamble you are making. Discover helps reduce the number of assumptions that you have to make by providing precise targeting of your visitors that expands beyond the capabilities found in SiteCatalyst.

For example, in SiteCatalyst you can do a fallout analysis with up too eight checkpoints. With Discover there is no limit to the number of checkpoints you may use. In addition, Discover allows you to use multiple pages as a single checkpoint (this is good for a site where customers might go through different processes in a checkout process depending on if they are a registered member or a new customer). In addition, Discover allows you to segment the data before you run it through the fallout analysis.

In addition, Discover has a tool called Site Analysis. This tool is a 3D representation of your website. It can show different metrics at the same time as well as provide a page flow analysis all in one graph. This appears to be a very powerful tool and you would have to see it in action to realize its potential. In fact, if you get the chance to ever take a look at Discover I suggest you view the Site Analysis tool.

At this point in the presentation Aaron Wixom presented a case study on DexKnows.com. Aaron explained that Dexknows.com uses Discover for quick and highly detailed analysis. They were able to use the site to identify a marketing channel that was performing well below the other channels and as a result of this they were able to direct funding away from that channel and towards the other channels.

Dexknows.com was able to find relationships between data that cannot be found in SiteCatalyst. This is possible because Discover uses the same raw data that is used by Omniture's Data Warehouse. The major difference between Discover and Data Warehouse is that the information for Discover can be obtained much more quickly and segmentation can be done on the fly.

After this case study Laura continued the presentation by demonstrating how Discover can be used to improve paid search campaigns through search analysis. She demonstrated that you can use Discover to create additional metrics that cannot typically be created in SiteCatalyst like page views per visit. You can even dive in deeper into analysis and look at things like time spent on site by keyword. This analysis can then be even more specific by viewing the paths that visitors are taking based on their payed keyword and how long those visitors spent on each page.

As you can see, Discover allows for some very advanced targeting and segmentation.

The presentation concluded with a case study by Paula Tellez from ProFlower. Paula explained how they used discover to analyze two potential campaigns for the Valentines day sales. The data was leaning towards using one of the campaigns on the main page. When presenting this data to the executives, one of the executives asked if the data was accurate because it was tracking all data going to these two campaigns, not just visitors coming through the homepage. Tellez was able to create a segmentation in the meeting and the results were exactly the opposite of the initial findings. This lead the executive team to select the other campaign and use it for the Valentines day period.

In conclusion, I found this presentation to be very interesting. Discover is THE tool too use if you really want to segment your visitors and improve their experience on your site.

Omniture Summit | March 5 | A/B, Multivariate Testing wtih Omniture Test & Target

The second breakout session I attended was presented by Lily Chiu, Consultant, Omniture and Josh Friedman from Dell presented a case study.

Lily began by identifying one of the major problems for online marketers. This problem is that marketers have a whole bunch of different ideas that they would like to try, but the deployment of these ideas are controlled by IT. This leads to idea's not being deployed quickly enough. The solution to this problem is to use a product like Omniture Test & Target to quickly deploy and test these marketing ideas.

Test & Targeting allows you to A/B and Multivariate Testing to test multiple site layouts at the same time. This testing can help answer common problems such as:

"I know my cart page results in the most drop off but I don't know what will improve it..." and "I know my high-frequency visitors should have the best conversion rate but..."

A/B testing is where different sites are compared against each other to see how well they convert. Multivariate testing takes A/B testing to the next level by testing multiple portions of a site at the same time. With Omniture Test & Target, you can have different customers directed to different site layouts and then after a given period of time you can view the KPIs for the different layouts and see which is performing the best.

When first starting with this type of testing, Lily had 3 suggestions:
  1. Start out with something simple. It should be something that is both technically easy to implement and politically easy to get approved.
  2. Know your goal. You should know what you are trying to improve. For example, are you looking to increase conversion rate? or do you want to increase the time spent on the page?
  3. Define your question. Make sure you know exactly what it is that you are trying to answer by doing the testing.
Lily then explained that the two most important aspects of a testing platform are:

  1. Speed - The ability to test and learn from those tests quickly
  2. Control - Being able to make the changes without needing to go through IT
A good testing platform, such as Omniture's Test & Target allows for both speed and control.

Next Lily presented some best practices for multivariate testing:

  1. Consider your traffic
  2. Define your goals and success metrics
  3. Think different when designing alternatives (if all of your alternatives are too similar, then there probably won't be statistically significant results from your testing)
The presentation then continued with Josh Friedman giving a case study of Dell and how they used multivariate testing to optimize the layout for their product pages. It was interesting to see that while the pages looked somewhat similar, statistically some page layouts performed better than others. Dell was able to use this data to make the best possible layout for their pages.

In conclusion, I enjoyed this presentation as it was an excellent introduction into A/B testing and Multivariate testing. Any site that is serious about optimization would benefit greatly from Omniture's Test & Target software.

Omniture Summit | March 5 | Think Big: Using Analytics to Win in Today's Economy presented by Matt Belkin

Over the past few days I have had an opportunity to attend four of the breakout sessions for the 2008 Omniture Summit. It was a great opportunity and I learned quite a bit more about Web Analytics.

The first breakout session that I attended was presented by Matt Belkin, VP of Consulting, Omniture. Matt's presentation was titled: Think Big: Using Analytics to Win in Today's Economy. The key theme of this presentation was to Maximize success with the tools you've got.

Matt started off by giving an example of Dell back in 1991. At the time the US was going through a recession and most companies had cut back on advertising. Dell however, increased its advertising and as a result became one of the top computer manufactures in the world. Matt showed that a recent study indicated that during a recession companies that cut spending on average see a .8% decrease in profitability while companies that increase spending see a 4.3% increase in profitability.

The statistics above shows that it is important to continue to invest in advertising even during a recession, but Matt emphasized that this spending needs to be justified and that analytics is what helps justify this spending. Matt advised that when advertising "Don't get distracted by all of the different mediums. Don't reach out without accountability."

I feel that this is a major part of the reasoning behind analytics. With analytics, a company can see what type of advertising is doing well and what is not. The company can then take action based on this data. Companies that optimize their advertising based on analytics will have much better return on advertising than companies that just invest in what they think will be the best.

Matt continued his presentation by talking about some of the tools available from Omniture to help with analytics. He talked about SearchCenter and how you can setup bid rules to automate bidding on keywords. This type of setup would be great for a company that has thousands of different paid keywords.

Matt also suggested to look at what your customer uses as internal search words to identify potential external keywords. After doing this Matt suggested optimizing landing pages so that you increase your conversion rate without having to spend more in paid advertising.

Matt continued by talking about some of the other avenues for advertising such as online videos, social media, blogs, widgets and even mobile marketing (like the iPhone ). One cool feature that is in the new SiteCatalyst 14 is that you can track what domains your video is played on.

Lastly, Matt pointed out that while there are many different marketing channels, it is all one big experience in the eyes of the customer. He showed the audience a current project called the engage-o-meter. This meter used data from a customized SiteCatalyst implementation that tracked all of the media channels a unique user went through before making a purchase. This then allowed the contribution of a success event to be spread across all of those channels rather than just being attributed to the channel that finally made the sale. I was really impressed with this meter because of all of the insight that could be obtained from it. This meter would really allow a company to see how they are viewed through their customers eyes

Wednesday, March 5, 2008

The Winter 2008 OWAC

Its only been a few days since the Omniture Web Analytics Competition ended and I am already suffering from SiteCatalyst withdrawals. The competition this semester was great and I think I learned more this time around then last time.

This semester my team started by defining the key business requirements (KBR). Once we had these KBRs we defined key performance indicators (KPI) to measure them. Our primary KPIs were Conversion % (Orders to visits), Average Order Size (AOS), Average Order Value (AOV), and Yield (revenue per visit). We then compared and validated these KPIs to the metrics Revenue, Visits, and Orders.

Our next step was to take these KPIs and use them to compare all of the marketing channels. This simple analysis became the backbone of our presentation. Just by looking at the marketing channels report we could immediately see areas for improvement and where we should look for additional analysis. For example, we could see that Paid search's conversion rate was well below the site average. By knowing this we were able to focus in on why this happening and we found that the process of going from search term to landing page was misaligned.

Once we had the main marketing channels, we decided to focus on three of the channels for the initial presentation. We focused on shopping search, paid search, and email. We selected these channels because we felt that they had the most actionable analysis. We also wanted to conclude our presentation with a bit of checkout analysis since this affects all of the major marketing channels.

We added a few more KPIs and metrics when analyzing the paid search channel. First we replaced the currently used KPI Return on Advertising Spending (ROAS) with two custom metrics Gain/Loss per Click (GLPC) and Margin. We decided to use these new metrics because we felt that they better represented how much money was gained or lost by each paid search campaign. So for paid search GLPC and margin became our KPIs and we compared these KPIs to several other metrics such as cost per click (CPC), average position, and clickthrough rate.

As we conducted further analysis on these marketing channels we set goals for improvement for each channel. For example, with shopping search we wanted to raise the average order size from its current value to the site average. This allowed us to calculate a potential uplift and helped focus our recommendations to obtain the goal. We found this method to be quite useful and it resulted in very focused recommendations to improve the weaknesses of each channel.

Our initial presentation went great. We practiced it quite a bit and cut it down to 7 minutes (our initial practicing showed it to be about 11-14 minutes long so we had to cut out quite a bit). Our efforts payed off and we made it to the finals!

For the finals we began by bringing back much of the material that we had to cut out in the first round. We also added some analysis of the ODAT marketing channel (One deal at a time). Lastly, we ended our presentation with a analysis of the main page layout.

We had to take a bit of a different approach for the page layout section since the data for this was not in our initial marketing channels report. We began by looking at the layout using clickmap and next page flow reports. From these reports we determined that the majority of customers would be finding product either by using the internal search or the category pages. At this point we used SiteCatalyst to analyze the two methods and found that search was converting better than the category pages. We analyzed this further and discovered that search got customers to product pages much more quickly than category pages typically did. At this point we made recommendations to optimize the category pages so that customers could get to the product pages in only a few clicks. We then calculated a potential uplift that would occur if the category pages were able to convert at the same rate as the search pages. This worked well and ended up being an excellent conclusion for our presentation.

The hours of work payed off in the end as our team, "Three Performance Vindicators" took first place in the competition!

I enjoyed the competition and I enjoyed working with my teammates Chris Haleua, and David Woolsey. They both presented excellent insights on numerous occasions and I'm confident that our presentation worked so well because of the many refinements provided by our "discussions." In addition, Chris has some mad PowerPoint skills!