Thu 13 Mar 2008
If you are too social for words, you might consider this nifty widget from People Search Engine Wink.com. What’s cool is that if you take a few minutes to consolidate your identities, you can use this widget and it links to all of your profiles from a single location.
Thu 20 Dec 2007
We all recognize a bad neighborhood when we are walking or driving. Trash and broken glass lay scattered on dirty, cracked concrete. Billboards adorn the buildings on every corner, presiding over liquor store & payday lender. Pan handlers, can collectors, scam artists, drug dealers and prostitutes lurk by the bus stops and most of us lock our doors while we try to find a safer neighborhood. Urban blight inevitable leads to plummeting property values and anyone who can afford to do so quickly flees in search of a better neighborhood.
Websites and virtual communities suffer from the digital equivalent. Spam, Sock Puppets, Bot Attack, Slogs and Advertorial mix with aggressive affiliate programs, ads for debt consolidation, pay day lenders, porn, casino’s and pharmaceuticals without a prescription – everything you encounter online that makes the web feel like a bad neighborhood have been given a name along with an interesting new site that wants to create a discussion about how to combat it- Virtual Blight .
Like it’s real world counterpart, blight left unchecked it will chase away the inhabitants of a community and destroy the value of the site and the brand.
Sun 1 Jul 2007
Happy Bat Mitzvah day to Hana Jael.
Fri 10 Nov 2006
Boogy Bon Bon writes about how “a flaw in MSN’s new anti-spam algorithm that will remove just about any website” out of their index, as well as how to combat this attack, at least until MSN fixes its algorithm.”
Thu 19 Oct 2006
Rand Fishkin posted the best analysis to date of web stats versus online tools to determine a site’s traffic: Website Analytics vs. Competitive Intelligence Metrics, A survey of 25 blogs in the search space comparing external metrics to visitor tracking data.
Despite varying collection methods and numerous flaws in the data that makes it impossilbe to use this information in a quantitative model, this is a must read for anyone who wants to highlight the limitations of these third party marketing intelligence systems. Here is the summary from the SEOMOZ paper:
“This project’s primary objective is to determine the relative levels of accuracy for external metrics (from sites like Technorati, Alexa, Compete, etc.) in comparison to actual visitor traffic data provided by analytics programs. 25 unique sites, all in the search & website marketing niche, generously contributed data to this project. Through the statistics provided, we can also get a closer look at how the blog ecosphere in the search marketing space receives and sends traffic.”
Mon 9 Oct 2006
You can always prove your point by defining what to measure. Jakob Nielsen is a renowned pundit, the leading evangelist for measuring results of user interface design and one of the most experienced and influential voices in design. His October 9th Alertbox shows how even the best pundits can fall into the trap of drawing conclusions using measurements from incompatible systems.
Nielsen’s intent is laudable. He contends that the vast majority of users are consumers of content instead of creators and is urging site operators to make participation easier.
User participation often more or less follows a 90-9-1 rule:
* 90% of users are lurkers (i.e., read or observe, but don’t contribute).
* 9% of users contribute from time to time, but other priorities dominate their time.
* 1% of users participate a lot and account for most contributions: it can seem as if they don’t have lives because they often post just minutes after whatever event they’re commenting on occurs.
Nielsen goes afoul when he talks about blogs, “There are about 1.1 billion Internet users, yet only 55 million users (5%) have weblogs according to Technorati. Worse, there are only 1.6 million postings per day; because some people post multiple times per day, only 0.1% of users post daily.”
“There are about 1.1 billion Internet users, yet only 55 million users (5%) have weblogs according to Technorati. This analysis has three fundamental flaws.
1. Nielsen takes the broadest measurement of internet users and the narrowest definition of a blog, posts using one of the popular blog publishing platforms such as WordPress that happen to report postings to Technorati. The total number of internet users is not the same as the number of blog readers. To assume that even half of that 1.1 billion “users” would recognize a blog as being a blog defies credibility so it makes no sense to count them when measuring participation. Does someone who has never been to a site count as a lurker or passive participant?
2. Comparing measurements of different values from two different systems is unreliable. It is perfectly reasonable to compare the measurement of the same value from two different measurement systems to compare the measurement approach. You can’t do analysis with measurements tfrom two different system without normalizing the data.
3. The biggest problem is the definition of “blog”? Blogging is a term that embraces much more than the enabling technology. It isn’t about posting your opinion in Word Press; it is about adding your thoughts, opinions and analysis into the public discussion. Nielsen’s AlertBox, for example, is an opt-in electronic newsletter that is also posted to his site. The content he writes is widely discussed in blogs and gets its share of links from the blogosphere. The only reason AlertBox is not a “blog” is that the technology he uses to publish. It shouldn’t surprise anyone that mixing a broad definition of users and a limited definition of participants produces lopsided results.
Worse, there are only 1.6 million postings per day; because some people post multiple times per day, only 0.1% of users post daily.” Nielsen disappoints again on this point in three ways.
4. Nielsen defines daily participation as the threshold for determining whether someone is a regular contributor to the discussion. His definition stipulates that quantity of posts is the only thing worth analysis. Take Alertbox as an example again. Since 1995, Nielsen has published his column roughly twice a week or about 260 times over 11 years. By his definition of participation, one of the most widely read column on User Interface and Design, written by one of the leading experts on the topic, counts as an occasional contributor.
5. He ignores comments as a form of participation in the blogosphere. Most blogs have at least a few comments and many have hundreds or even thousands. It is hard to justify not including these as participation.
6. The last issue is how he crunches the numbers. Technorati’s measurements are “ancient” as judged by the historical rate of change. Still, if we accept 55 million blogs and 1.6 million posts/day, 2.9% of bloggers post EVERY DAY. If we use a more reasonable threshold like posting once a week or even once a month, participation in the blogosphere may be as high as 10 or 15%.
The final issue in this 90-9-1 analysis is that users are in multiple communities. A user who is a devoted participant in the Amazon community for example, one who has read thousands of books and posted reviews for each, can hardly be expected to be a daily blogger as well, but do you count him as a lurker?
You can prove almost any point with statistics and measurements tailored to your definition. If you want data for reliable decision making, you need to be more thoughtful in your approach.
Tue 3 Oct 2006
Dave Morgan made a great point about the impact of online marketing on traditional brand advertisers, “These days, all marketers want measurable results related to sales objectives from their advertising and marketing expenditures, particularly online.”
ROI metrics and the sense of accountability they provide are addictive. Decision making is reduced to how much you are willing to spend for every dollar or customer you get back. It appears to take the risk out of marketing investments. Dave is absolutely correct…as far as he takes it.
Marketers who believe they can accurately quantify the impact of their online advertising, whether SEM or Brand, do so at there own risk. Every analytic system I have ever used is flawed; The assumptions and methodologies inherent in each approach creates measurement error. Managing campaigns on a strict ROI basis demands that you have at least two analytic systems and a detailed understanding of how each works and what they actually measure.
Determining ROI for search marketing requires you to understand user behavior. One very common issue to watch out for is how you treat keyword search and a brand search. Marketers will frequently separate ROI for their brand terms from keyword search. If a customer converts after searching for “red widgets,” that ROI is credited to keyword search for the term red widgets. If a customer converts after searching for “brandxxx widgets,” the ROI is credited to a brand search.
The problem is that customers may visit your site during the interest phase, the research phase and the purchase phase. Most analytic systems are not configured to track multiple visits through CPC and/or SEO channels, so the return doesn’t appear to make the investment.
I just finished a three month contract for a startup. Despite deploying sophisticated, redundant analytic systems (Google Analytics and ClickShift’s Statistical Bid Management, only 60% of the orders in the first three months were tracked and many were reported as direct navigation or searches for the brand.
You might expect this for a mature brand with a large repeat customer base, but it defies logic for a startup that was still only using CPC for marketing. Since we had a small data set, I was able to research the orders individually and attribute the source and term for each record in the customer table.
You wouldn’t want to try to repeat that method with 10,000 orders, but the result was a 160% increase in the reported ROI for the CPC campaign. Individually or combined, the analytics systems didn’t produce accurate enough data for decision making.
The only way to really understand ROI from each channel and search term is to find ways to induce customers to login as quickly as possible, while the referral data is as fresh and accurate as possible. Incorporate that referral/source data directly into the Customer table and import all sales information into internal systems to produce the ROI measurement.
If you do not have an initial source associated with a customer record, make it a goal in every customer interaction (survey, customer service call, etc.) to obtain that information. This allows you to accurately attribute revenue to the marketing investment and track every additional touch point that generates a visit regardless of source, medium or computer. With that kind of data on hand, you have a baseline to begin to understand the value of each advertising channel. Then your ROI based decisions can be good ones.