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One of the greatest advantages of online marketing is the marketers’ ability to quickly adjust and respond to the data they can obtain directly from their interactions with their market.  However, each organization is at a different stage in terms of their online measurement sophistication and each faces barriers to becoming more effective at optimizing their web marketing.

Avinash Kaushik recently posted a good blog entry on Barriers To An Effective Web Measurement Strategy.  In the blog, he recommends some first steps in overcoming the following 11 barriers to an effective online measurement strategy that were cited in Econsultancy’s Online Measurement and Strategy Report.

1.  Lack of budget/resources (45%)
2.  Lack of strategy (31%)
3.  Siloed organization (29%)
4.  Lack of understanding (25%)
5.  Too much data (18%)
6.  Lack of senior management buy-in (18%)
7.  Difficulty reconciling data (17%)
8.  IT blockages (17%)
9.  Lack of trust in analytics (16%)
10. Finding staff (12%)
11. Poor technology (9%)

While I did find Avinash’s insights on each of the barriers valuable, I think the list of barriers is flawed in that it confuses the symptoms with the actual barriers.  Could you imagine, for example, if a baseball manager explained that the reason his team was losing was because he was getting “too much data” from his statistician (point 5 from the barrier list).  If he did, he would not be manager for long.  It’s the manager’s job to determine which stats are important and will make a difference in his game strategy.  While I’m sure there are many executives and analysts who feel that they do have to sift through too much data, the true barrier is the lack of a good strategy that focuses the organization on a few core metrics that get to the heart of what you are trying to accomplish.

Given our experience in helping many organizations with their data driven optimization, I think the 11 point barrier list could be refined down to the following 4 core barriers.

1.  Strategy
It all starts with a good strategy.  It’s necessary for obtaining management buy-in and for ultimately attaining the ROI on any investments made in optimization initiatives.  It is critical that the strategy identify a small set of critical metrics that are meaningful to management and drive any ROI business case.

It’s also important to recognize that the web optimization strategy needs to evolve as the web optimization capabilities of the organization evolve.  The strategy is about pinpointing the most important constraints that you need to overcome and focusing your time and resources on making that happen.  Often this may require small steps first to gain credibility and management buy-in.

2.  Management Buy-in
Not surprisingly, once you obtain management buy-in, many of the symptoms begin to disappear.  Certainly lack of budget/resources and IT blockages begin to dissipate if you have the support of senior management.  While it is likely the most important barrier to overcome, this can often be the most difficult.  It’s also important to recognize that until management is willing to make some level of investment in analytics and optimization, then they have not really bought-in.

This often creates a chicken or the egg situation where the online marketer asks, “How do I credibly demonstrate ROI on the investment prior to making the investment”?   Early on this is where the hard work and innovative thinking must occur to implement examples of how data-driven initiatives can provide the ROI necessary to develop a strong business case.  The good news is that with the use of inexpensive, often free, tools in combination with some good analysis, it is not too difficult to gain credibility by demonstrating substantive ROI.  This is often the key objective of organizations that are relatively early in their web optimization evolution.

3.  Infrastructure for Testing, Analysis, and Change
The infrastructure I am addressing here includes the website or ecommerce management technology as well as the implementation of the analytics tools.  We have come across many situations where online marketers have properly identified what are potentially significant improvements that will really move the needle on their core metrics, but the amount of work involved to test or implement the changes were believed to be too significant to justify the investment.

This can be a daunting challenge in that the investment in the current infrastructure and the staff to support it may have been significant and modifications may be difficult and expensive.  In many cases this requires working actively with someone who is technically proficient enough to implement some relatively small tests across several areas that when viewed together make a strong case for an investment in a new infrastructure or new component to that infrastructure.  In other cases, this is more of an uphill battle and the key becomes just recognizing the constraints and focusing on those areas where improvements can be made.

4.  Skills and Time for Testing, Analysis, and Change
In my opinion this is the most overlooked and most underestimated barrier that must be overcome.   Many organizations that have implemented analytics either largely ignore the analytics reports, don’t have time to analyze them, or generate reports that provide little in terms of insights that stimulate changes that improve the critical metrics and provide a high ROI.  In order for an organization to effectively implement data-driven optimization, they must have time from the personnel who know what data they should be focused on, what tests should be implemented, and what actions should be taken as a result of the analysis.  This, by the way, does not mean that an analyst should be doing all of the analysis.  In fact, quite the opposite, they need to know how to get the appropriate people throughout the organization involved in the analysis (the “Why” behind the “What” happened).   As the benefits of this time become apparent, it becomes easier to build this testing and analysis into normal work processes.

Most organizations also tend to under invest in the time required from the personnel who are necessary to effectively carry out tests.  For example, designing multiple versions of a page for A/B or multivariate testing can pay significant dividends.  Organizations need to plan accordingly for copywriting and design resources in order to make these tests successful.

By focusing in on and addressing these four key areas, the other issues on the Econsultancy list will likely be addressed in the process.  What do you think of the 11 barriers identified in the Econsultancy study?

There are several reasons why an online marketer wants to know how much traffic a site other than their own is receiving:

• You may want to compare how much traffic a competitors’ site is getting.
• In reviewing the landscape of sites your target customers are visiting, you may want to ballpark the volume of traffic to each in order to get a sense of their relative prominence.
• When reviewing the sources of traffic to your website, you may identify a new source that has had good conversion success and you may want to determine if they have a significant audience and would like to see if that audience is growing. If so, you may want to pursue a more in-depth relationship with that source.
• It may also help to provide focus in trying to establish high quality links to your site for SEO purposes.

There are now several free traffic estimation services (Amit Agarwal did a nice job of outlining these options in his article, Find Out How Much Traffic a Website is Getting). However, one obvious question is how accurate is the data?

In order to help answer that question, we evaluated the quality of these estimation services against the web analytics data collected through Omniture, Google, etc. for a subset of our clients. We thought that the quality of those estimates might vary significantly depending upon how heavy the volume of traffic was to the site being estimated. As such, we grouped the results based on site activity: heavy, moderate, and light. When available, we also evaluated how accurately the services reflected the trend of the site traffic as well as the volume of visits and visitors for the following traffic estimation services: Alexa, Compete, Google Ad Planner, Google Trends, QuantCast, and StatBrain.

The following table shows how the free sources compared to the data collected by our clients’ analytics programs (e.g. Compete’s estimation of traffic for moderate sites was lower than reported by the analytics tools used by those sites).

I should note that this was not a formal study, was based upon a relatively small sample set, and other factors may impact the results (e.g. relative volume of paid search marketing may influence the accuracy of some sites versus others).

A few observations/conclusions:

1. Not surprisingly, the quality of the estimates is considerably better for higher volume websites.
2. At this point, there does not seem to be a reliable source for viewing site trends for lower volume websites and the trends for moderate traffic websites are not much better.
3. The growing volume of incremental demographic information being provided by some of these services is encouraging. Most of the demographic information is fairly rudimentary, but it is definitely more than what has been available in the past.
4. You should definitely review Dataopedia.com. In addition to pulling in data from Alexa, Compete, and QuantCast, this service displays other non-traffic related data such as Google Page Rank and Twitter posts related to the site.
5. Given that none of the free services provided accurate estimates in every scenario, you may be able to use our findings to make adjustments for your specific situation.

Has anyone else conducted a similar comparison? If so, what type of results did you find?

Over the past months, many have proclaimed that the email open rate is obsolete and utterly useless.  The poor open rate has become a persona non grata, and while not as risky as trying to defend the AIG bonus structure, I do think someone needs to stand-up for this email metric.

While I completely agree that clients often focus too much on the open rate, it can be misused, and it isn’t as relevant as it once was because, among other reasons, email clients are more likely today to suppress the image that is used to track an open, I do believe that the open rate still provides value and it is worth following.

Ask any professional football coach what the most important measure of success is and he will tell you that it’s all about wins and losses.  However, he will also acknowledge that when analyzing a team’s performance, you need to go beyond the end result (win/loss) and look at diagnostic metrics like how many yards you gained on offense, how many yards you gave-up on defense, how many fumbles and interceptions you had, how many penalties you incurred, etc.

I believe you take a similar approach with email marketing.  While, if I am an online retailer, I am most concerned about conversion rates and sales, metrics like the open rate provide value.  Obviously, before someone can purchase as a result of your email, they must click on a link, and before they click on a link, they have to open the email.  If you aren’t getting the email to the inbox and the subject line isn’t compelling or engaging, you aren’t going to get a conversion.

I believe that the open rate can still provide insights that will help you improve your email marketing.  If the conversion rate was significantly different between two emails and the open rate for the better converting email was much higher (and assuming the emails were sent within a reasonable time of one another), I might conclude that the subject line, whether it be the way it was written or the offer communicated, was the culprit.  Obviously, I would look at other metrics and analytics but the fact that the open rates were so different would likely impact my conclusions.  Open rates have also been helpful in identifying deliverability issues (when clients didn’t have inbox tracking) and enagement by various segments of a list (e.g. when comparing recent subscribers to ones that have been subscribed for over a year).

So what do you think?  Is it worthwhile to track the open rate or is it ready to go the way of the buggy whip?

In the July issue of Inc. Magazine, there is an interesting article about how one of our clients, Successories, is transforming from a catalog-based company to a web-based company.  Steve, a founding partner of Shay Digital, is quoted in the story:

http://www.inc.com/magazine/20080701/a-direct-mail-pioneer-fights-back.html

Cyber Monday (Monday after Thanksgiving) gets all of the headlines as the most imporant online holiday of the season, but the reality is that in 2006, it was the 12th highest sales day during the holiday season.The following are the busiest online shopping days in 2006 according to ComScore: