We just announced a new partnership with Webtrends, one of the leading web analytics companies.   This is an exciting announcement that will make it really easy for Webtrends customers to get Quantivo behavioral analytics in addition to all the great reports and analysis they already get from Webtrends.   One quick note: yes, we support both Webtrends Analytics and Marketing Warehouse.

We have been hard at work with Webtrends for a while and they have been a fabulous group of people to deal with.  We are planning a webinar in the next couple of weeks to go through the benefits of the announcement.  Stay tuned.

Finally, we are offering Webtrends customers a no risk trial so they can experience Quantivo’s analytics on data from their live site, with no upfront costs. For more information, visit http://www.quantivo.com/solutions/quantivo-for-webtrends.php

The charts and tables that you work with, are they analysis or reports?  I will submit to you that if they are automated, they are just reports.   And we all know what they look like: page views, click-throughs, conversions, purchases etc by day/week/month/location… Definitively required for running your business but useless for looking forward and telling you what to do.

By contrast, analysis is about finding the golden nuggets inside the data that you have.  And because that gold is never twice in the same place, it takes some intelligence each time to uncover patterns and trends that can be acted upon.  Does that mean that it has to be difficult and time consuming? Today it indeed requires a mixture of programming and statistical skills.  But that is a reflection on the tools and technologies available, not the problem at hand.

Check out our analytics gallery for a selection of examples of powerful analysis that can be developed in minutes with the right solution.

If you are into Web Analytics, check out the analyst commentary on how Quantivo makes it possible to conduct “second generation” behavior analytics on large scale web data.

Hung LeHong, research vice president at Gartner, is hitting the nail on the head when he says “To analyze behavior, over time, of a repeat customer is something that SiteCatalyst can’t do very easily. There are some things that Quantivo can do that SiteCatalyst cannot, [and] there are some areas of overlap but Quantivo just does [those] significantly faster.”

Indeed, what Omniture customers are telling us - and by the way we are not singling out Omniture, they just happen to be the first Web analytics vendor we support - is that analyzing web behavior over time and multiple visits is incredibly hard.  The reason is that your analytics engine needs to uncover patterns across many separate interactions, something that is hard to do with a traditional relational or column based database.

So how do we do it?  The secret sauce is our “affinity database” technology, specifically designed for this purpose.  More info is on our web site but the beauty of the Software-as-a-Service delivery is that instead of going through a long evaluation and justification, you can try it out on your actual web data with zero (0) investment.

Lately, we’ve been using several great examples of how online trends develop quickly and then diminish just as fast, requiring e-commerce retailers and website operators to have the tools to both identify and act upon those trends in minutes, not weeks.  You can watch our CEO, Brian Kelly, talk about some of these trends in this short video.

One of the examples that Brian covers is the J. Crew / Michelle Obama story, where the First Lady wore a J. Crew outfit on The Tonight Show with Jay Leno, and then sales exploded.  It’s a great example of how a trend can come out of nowhere, and how companies need to quickly react.  And, it’s such a good example that it was covered by US News, Time, The NY Daily News, and The Huffington Post, among others.

But, a recent post in Slate, titled “There Is No Michelle Effect,” asserts that J. Crew did not benefit at all from the Michelle Obama connection, and that JP Morgan listed the “Michelle Obama Bounce” as one of the big myths of the year, right up there with the Easter Bunny!  They go on to note that J. Crew’s CEO even mentioned Mrs. Obama in a November earnings call, saying that she had no effect on same store sales.

First, I should mention that November was waaaay before Mrs. Obama’s Jay Leno appearance, and even several months prior to the Obama children wearing J. Crew at the inauguration.  But, let’s not lose focus.  The focus should be on J. Crew’s ability to quickly understand, exploit, or debunk any perceived trend.

Was there a bounce and they missed it?  Did they have the behavioral analytics in place to see the effect in the days after the Jay Leno appearance?  Or, did they quickly jump on their online and POS data and see that there really was not a material jump in sales?

The point is that companies need the ability to quickly identify potential trends, then either quickly convert them into more traffic, more dollars, and more profits, or quickly determine that there is no monetizable trend and move on.

In either case, companies can no longer afford to wait weeks or even days for their analysis.  In today’s world, you need analytics that can give you answers, actionable patterns, and decisions in minutes.

I am excited about our just announced support for Omniture SiteCatalyst.  In the last few weeks, we have been working with several Omniture customers and heard a general need to get a handle on what visitors are doing on a given site, above the standard operational reports delivered by Omniture (see this and this post as examples).

We have made it a no brainer to get Omniture server-call transaction level data into Quantivo where it becomes possible to do interactive segmentation and find behavioral patterns at scale.  If you are an Omniture SiteCatalyst user, check us out.  We are offering a no-risk trial where we (Quantivo) do all the heavy lifting and deliver concrete, actionable (forward looking) insights on your web site.  As several customers have told us, “there is no downside.  Why wouldn’t it do this?”.  Exactly!

We’re trying to encourage everyone interested in eMetrics to add the official hashtag (#emetrics) to all of their event-related tweets.  This will be a great way for both attendees and those unable to attend to share in the knowledge and networking!

As a teaser, here’s a live (or fairly live…) feed of all the #emetrics tweets happening in the world right now:

If you’re at the event, stop by our booth and register to win an Amazon Kindle!  If you’re not at the event, we hope to still see you in the Twitterverse!

At Quantivo, we don’t like to toot our own horn.  Um, well, OK, who are we kidding?  Yes, we LOVE to toot our own horn!  Quantivo has had some great news hits in the past few days, and we wanted to pass them along to everyone.

• Red Herring 100 - Yay!  We’ve been selected as a finalist for the RH100, which will be announced at a Red Herring event in San Diego on May 11-13.  We’re keeping our fingers crossed!
• TMCnet Article - This week, TMC published a great article on Quantivo, detailing the latest advancement to our customer behavior analytics product.  Click here to read it.
• BtoB Magazine - BtoB, the magazine for marketing strategists, also covered our latest product release with this great article.

We’re so happy, we can barely stand it…and, it’s only Wednesday!  Thanks to the whole Quantivo team for continually increasing our level of success and traction as we revolutionize the analytics world!

I was just forwarded a fantastic white paper that dives deep into the details of developing an analytics-driven retail sales forecasting model. The paper was written by Wipro, and goes into very granular detail on the retail sales forecasting analytics process, the areas to analyze, the time periods, and myriad other variables that should be factored into the sales forecasting model.

The paper quickly gets into the value locked within customer behavior data, building on the typical POS analysis and adding store details, customer lifetime transactions, credit history, weather, etc.  This is an area in which Quantivo excels, and our product can quickly unearth the valuable patterns within this potentially large set of customer data.

While their paper does get mathmatical at some points, it’s a very worthwhile read and only serves to highlight the value of having an analytics tool like Quantivo that can quickly join various data sets and then quickly surface the valuable and actionable customer patterns within the data.

You can download their white paper here (registration required).  You may also be interested in a related white paper that we’ve written, downloable here, that focuses on using SaaS analytics for just this type of analysis.

Let us know what you think of both papers.

In the web analytics world, the past 3-4 months of behavior data is like a lifetime for a web visitor, and marketing managers are craving more insights faster, such as:

• Understanding key behavior differences between first time and repeat visitors (getting customers vs. retaining customers)
• Identifying niche segments of high-frequency repeat visitors (above 5-10 visits per month) who view content (across visits or in the same visit), spend more time on key pages, and get routed from top referrer sites
• Analyzing geo-based behavioral/affinity differences to better optimize ad placements across international web properties

Such rich analysis on a near real-time basis helps highlight early trends or changes in visitor behavior and allows companies to course-correct or exploit as appropriate.  To meet this need for deep visitor insights, web analytics tools must meet two fundamental requirements:

1. Analysis over any combination of, or even all, attributes that are present in the data set (allowing the thoughts forming real-time in a business manager’s head to decide these attributes vs. some limited, generic pre-built models)
2. Highly interactive analysis ability (over millions of rows of clickstream data) everyday vs. canned reports and pre-defined drilldown paths(i.e. limitations)

Most web analytics tools simply cannot answer #1 above as they first have to pre-aggregate (see this article) their clickstream data to provide for the operational and canned “business-oriented” daily reports - in the process,  losing valuable information that is critical to unearth segment-specific behavior.  Analyzing ground-up in various ways, with or without specific visitor segments in mind, is critical to spotting recent trends in visitor behavior and then allowing companies to target them with quick changes to ad or content placements.

Quantivo web analytics does not need to even think about pre-aggregating clickstream data, given its unique ability to quickly pick up just the required information from clickstream data based on the segments and data subsets featured in the query definition. Quantivo can also easily process more complex segmentation queries through its multi-pass query capabilities, processing that typical BI and web analytics tools need deep customization and extensions to perform.

Quantivo’s easy ability to do interactive ad hoc train-of-thought analysis based on what’s seen in the data meets #2 mentioned above, thus giving decision makers what they need to make a difference vs. what they want normally (which many analysts unfortunately spend a long time accessing in typical tools). The time it takes to get to such information in typical tools forces the decision makers to avoid asking the far more difficult questions - timely answers to which could make a real difference to profitability and market share in real “business time.”

(Here’s another related article.)

I just got back from the Webtrend’s Engage event in Las Vegas this week.  While I did not have the opportunity to stay for the entire event, I gained a lot of value from the event and my time talking with other attendees.  Being in sales, I was looking through a totally different lens than most of the web, IT, and analysts there, so I was able to see an entirely different set of value within online data that can really help increase a sales team’s success.

The overall theme of the event was around the openness of data.  My experience is that, over the last several years, web analytics has been its own silo of information, used only to optimize a company’s website.  The rest of the organization has had little access to that information, which prevents marketing, sales, support, and others from this valuable insight into customer’s behavior.  Webtrends is making an effort to open up that information to others in the organization and expose this value across the company.  I think that this is a great move that will surely increase customer satisfaction, as well as profits and transactions.  Before you make a call into one of your customers or prospects, wouldn’t you like to know how they recently used your website?

I also thought that they had some strong presentations by customers, partners, and internal folks.  I was especially impressed with how Polaris (recreational vehicle manufacturer) is using Webtrends merged with their CRM system to help drive business at their dealerships.  We are doing something similar with Cisco Webex, and it is good to know that others have related business issues.

I also wanted to thank the Webtrends team for being such gracious hosts.  While I did not get to meet Alex Yoder, I hope to sometime in the future.

All in all, it was a great experience!