Jul
Yea, not much else to say here. Hopefully the industry doesnt make another pointless scene of this one.
Jun
Xobni, an Outlook email analytics & more plugin, just integrated [very sparse] LinkedIn data. No matter if Xobni is a bad startup name or not, it shows a lot of promise. I’ve used Xobni on and off ever since it was profiled on TC and was at first impressed. After some use however, I’ve noticed that aside from the email analytics function, I’ve already been using most of the features in Outlook itself. So after the initial novelty wore off, I eventually stopped using it.
Now, Xobni (”inbox” spelled backwards) has announced LinkedIn integration. It’s a great idea but flawed in implementation. You see, I already have a LinkedIn plugin for Outlook that I use pretty heavily. Xobni partnered up with LinkedIn to implement a small snippet of contact data (just position & company). All that partnership did is further clutter and already cluttered Xobni toolbar. If I wanted to see LinkedIn data on a contact, all I have to do is hover over the LinkedIn “info” button in Outlook.
Xobni’s core features is really where the bread & butter is and that is what they should focus on, especially after backing down from a $20M offer from Microsoft. Their email analytics data is actually pretty useful and their search is just a bit better than Outlook’s. I’d like to see them expand on that functionality as well as offer their plugin for more email providers other than Outlook.
PS. For those that are having trouble viewing LinkedIn data in their Xobni toolbar, you have to activate it first by going to Xobni > Options in your Outlook menu.
Jun
There’s been a lot of chatter about Google’s new Ad Planner so I decided to sign up just to see what all the craziness was about. After about 12 hours, this email came in from Google:
Thanks for your interest in Google Ad Planner. We’re happy to announce that you’ve been accepted into our beta testing program.
To get started, visit www.google.com/adplanner and sign in with your Google Account username and password.
If you need immediate assistance with Google Ad Planner, please visit our Help Center at http://www.google.com/support/adplanner/. We also welcome your suggestions and feedback at http://www.google.com/support/adplanner/bin/request.py.
Welcome to Google Ad Planner!
Sincerely,
The Google Ad Planner Team
Great, time to play.
When you first login to Google Ad Planner, you are presented with two options: Create a new media plan or Begin research. Let’s start with Begin research.
The first screen you will see after clicking on Begin research is a listing of all the sites that Google has data on (presumably from the Google Toolbar). Towards the top of the left sidebar, you are presented with 3 key metrics that refresh based on your selection of demographic filters below. Combining all of the sites selected by default, Google supposedly has 100% country reach which equals 240M unique visitors and 180B page views.
What is likely the bread and butter of Google Ad Planner, the demographics filters allow you to drill down by filtering sites by gender, age, education, and household income. Google Ad Planner also allows a user to specify demographics based on a specified site. For example, selecting techcrunch.com, Ad Planner will display demographically similar sites such as crunchbase, techmeme, ycombinator, and scobleizer. You can also enter more than one site to search against if you need to drill down further.
Once you have narrowed down your demographic filters by using one of the two methods I have outlined above, you can now sift through the results on the right hand side. Selecting multiple updates a metric aggregator towards the top of the Ad Planner page with total site statistics and selects them for inclusion in a media plan. The metrics that are presented are Category (Computers & Electronics for example), Comp Index (Score showing how concentrated your audience is on a site relative to users in your defined country), Unique Visitors, Country Reach (Estimated percent of total internet users within your defined country), Page Views, and Google Content specific metrics including Ad Formats and Impressions per Day. It’s important to note that not all the sites in Ad Planner are part of the Google Content Network.
Google Ad Planner also has the handy option of drilling down even further per site by clicking on a little graph icon next to the site name (reminiscent of Quantcast site metrics) for insight into its demographics and traffic data/patterns which looks to be like a perfect integration of Google Site Trends (btw, why does the Google Site Trends page default to Wikipedia stats?) released just last week. Unfortunately, as of right now, it looks like Quantcast does present more data than Ad Planner does – Ad Planner only displays data that I have covered in this post.
That’s about it for the research module (let me know if I left anything out here). Now let’s move on to actually creating media plans.
Another important note is that Google Ad Planner doesn’t yet seem to be integrating with your Adwords accounts for one-click plan implementation for your content campaign. The only thing that the Media Plan option provides is an exportable (CSV or MediaVisor CSV) and an overview of all your selected sites.
So that’s basically it. Out of the box, this tool isn’t incredibly useful but the functionality is definitely there for future improvements. I look forward to seeing what the Google Ad Planner team has in store for us.
May
People today go to the web to research their options and to get answers to their questions. They want clear, accurate information and they want it quickly. This means that your website has only seconds to grab the attention of a potential client. How can you make sure that you’re getting the most out of your online presence?
May
Offline sales are a crucial element to many online business including transaction (ecommerce) based and lead generation. While web analytics solutions like Omniture, Coremetrics, and Google Analytics can provide in-depth analysis of online sales cycles, they cannot track sales that occur offline out of the box. Online retailers and other business models have struggled with the offline metrics for a long time, typically just estimated offline contribution to their online marketing efforts.
I’ve recently invited a account executive from Omniture to present their offering to myself and my team. While I am pretty familiar with their web analytics platform, there was one added feature that really peaked my interest. Omniture has came up with such a simple solution to track offline sales: reference numbers! It’s quite simple how it works. A reference number is attached to each page view that tracks these key metrics (and many others):
Once a potential client/customer calls in on the 1-800 number, they provide the reference number to the sales person. The sales person then inputs the number into whatever CRM solution they are using. That reference number is now retained through the entire sales process all the way to the very end.
Simple huh? So simple that the feature can be easily developed in-house with the help of a smart developer! All you need to do is assign unique identification numbers. Tracking unique keywords is easy: just append a key to your destination URLs within your campaign. The URL should look something like this:
http://www.yoursite.com/?kwid=12345678
The first 4 numbers (1234) within the ID can differentiate the search engines while the rest of the keys differentiate keyword and match type. Once a user lands on your site, the entire key (12345678) is visibly populated right under the phone number. If they use the 1-800 to call in for more information or to complete a sale, the sales representative asks them for the reference ID and inputs it into the CRM solution. Presto!
May
So a crazy thing happened to me the other day. I had invited my buddy Gary Caponegro to come in and do a demo for Omniture SiteCatalyst (a web analytics platform). I had 4 people attend: a marketing writer, 2 web designers, and a front-end developer. I thought that it would be great for them to hear someone else speak about web analytics other than me. Keep in mind that all 4 people know very little about online marketing and even less about web analytics.
I have used SiteCatalyst before so the presentation wasn’t as beneficial for me as I hoped as it would be for them. As I sat there during the presentation, I started gazing around the room at their expressions. Each and every one of them were intently paying attention at the slides and demo. This is a group of individuals that are highly skilled at their craft and are sitting in a presentation that barely has any content specifically geared towards them or their daily tasks.
Or so I thought. It suddenly dawned on me that web analytics (regardless of which product you use) are in fact as beneficial to them as it is to me as an analyst! In fact, web analytics plays a huge role in their daily activities; it validates their efforts! Web analytics measures every single piece of creative, every block of copy, and every line of code that they create. They had no idea that their work can be tracked with that infinite amount of detail and accountability.
I later met with the attendees and asked them what they thought about the presentation. The response was unanimous: they loved it and thought that it was very beneficial. The marketing writer in particular actually thanked me for dragging her away from her pile of work. She was truly interested in what Gary was presenting. Her words sparked the motivation for this post.
Web analysts love to tout their analytics tools and how they are able to track every cent of their online marketing budget. For this reason, the adoption of these tools typically occurs within the online marketing department while the rest of the web design/development departments stay out of the way and just take the lead from the analysts. It’s time to clue them in; it’s time to make them feel like their daily tasks are no longer just part of the grind; every change they make affects the bottom line.
Feb
So with all the hoopla surrounding Microsoft’s press release touting their “Engagement Mapping” beta, I thought I might delve a bit into analytics.
Microsoft’s big claim is that they will now allow advertisers to attribute an entire click-stream to a single goal (conversion, lead, etc.). So let’s take an example to illustrate this point:
You’re a online lead farm for education and you have purchased various CPM banner ads from BlueLithium (first mistake there). You would now like to determine which ads are really converting for you and which ones you can trash.
You fire up Coremetrics or Omniture and take a look at your tracking code reports for those banners. Judging by conversion numbers over a 30 day period, it looks like 7 out of your 10 banners have converted and 3 of the 7 are actually positive ROI. What do you do? You end up trashing the 3 banners that have not converted at all and optimizing the banners that have converted but are in negative ROI territory.
The issue with the above methodology is that users typically have their analytics solution setup to only track conversions to the last source (cookie). There is quite a simple solution and it doesn’t require letting Redmond run your analytics. Both Coremetrics and Omniture allow you to switch to weighted click attribution while still allowing you to track conversion on last click! As far as I know, neither analytics solution even requires you to change any code.
Still, I value what Microsoft is doing here. If they can bring this critical issue to the foreground and force other analytics providers to explicitly support multiple click attribution, it may open the doors to a new kind of website performance analysis. Now let’s hope that Microsoft doesn’t leverage Engagement Mapping to convince advertisers to spend more advertising dollars by saying “But look, all of these other ads received clicks too!”
