SemAngel

Reflections on the X Change Berlin

2012-06-02T10:26:41-07:00

The nature of the X Change Conference is that each is completely different though all share much that is the same. You never hear the same speech or the same presentation, though you may hear the same problems in many different ways. I had almost no idea what to expect in Berlin for our first European X Change. What would Berlin be like? How many people would we get? How well would the format translate when taken away from its native (and notoriously chatty) American soil? What would the attendees be like? How sophisticated would they be? Would the many non-native English speakers as both attendees and Huddle Leaders be a problem? And, most important, would the conversations be interesting?

So many questions and only three short days to answer them.

Let me start by saying how much I enjoyed being in Berlin. I've never been to Berlin (or Germany for that matter) and I suppose my mental images were more of concrete block-buildings in the old GDR than anything else. Of course, I knew that wasn't the Berlin of today but I had no real American model on which to base a guess. In that, at least, I was right. Berlin is quite different than any city in America. Cosmopolitan, growing (construction cranes everywhere you look), stretches of historic and profoundly beautiful buildings and neighborhoods, and, of course, the striking glass skyscrapers (though Berlin is far from a tall city) of the modern city. There are the obligatory Starbucks (better pastries than in the U.S.) and Dunk'n Donuts, along with an eclectic mix of German, Asian, and Italian food all plentifully awash in local beer. It's a city of high-culture (museums, symphony, theatre) and high-tech (a very cool new media gulch by the river including one of the coolest hotels I've ever seen - Matthias tells me they have room service musical instruments to accommodate the many musical groups they draw), with more green and more bikes than you'd probably imagine.

Quick highlights of my sightseeing: the Sand Cats that charmed my daughters (who had to be forcibly dragged away after countless photos), the Wolf pack and the Hippos at the wonderfully walkable Berlin Zoo; the entire open-house day at the Berlin Symphony including a 14 flute ensemble that featured several man-size flutes shaped like a giant number 4 and that finished with a finger-snapping rendition of Henry Mancini's Pink Panther theme; scraping our fingers (but not our heads) on the incredibly low tunnels over the canal as our boat glided underneath to emerge in an ever darkening Berlin sky; the Winged Victory popping up as you suddenly crossed wide lanes; the BBQ boats (great floating inner-tubes with a grill in the center) on the lake behind Matthias' house; and, of course, the winding path of embedded bricks that mark almost all that remains of the Wall.

Of course, I knew the answer to how many people we'd draw before I ever arrived. With a tremendous late burst in registration, we closed the Conference at our maximum capacity of 100 late last week. That was better than I'd ever expected and much better than I'd feared as registrations started very slow - no surprise for our first time in Europe. The upshot was that most Huddles were quite full - with quite a few at or near the limit of twenty that we place on each session. That's a little larger than I prefer, but not unmanageable. And many Huddles were in the very comfortable 13-16 zone. This makes for a diverse but still intimate conversation.

Provided, that is, that people will talk. I had been warned to expect that few people are as talkative as Americans and that Germans, for example, might be a little more reticent. We had people from fourteen or fifteen different countries across Europe, but the largest contingents were from Germany and U.K.

Was it different? It was, a little. I think we probably are a little chattier in the States and it took a little longer for people to get warmed up. I noticed that Day 2 flowed better than Day 1 as people began to know each other (an evening drinking together as we circled Berlin by boat couldn't have hurt) and talk more consistently. But even on the first day, the differences were minor. In every Huddle I attended, a majority of folks participated and often quite extensively.

As for the attendees, I'd say that it was more representative of our first or second X Change than the event as it is today in the U.S. We had more consultants than we typically get in the U.S, and the experience level was more varied. We had more folks from mid-size enterprises - particularly in Germany - and from very small analytic teams. You just don't get the really large enterprise teams that we see at places like Dell or American Express very commonly in Europe. Occasionally, that created situations where Huddles didn't have enough experienced analytics practitioners. That happens in the U.S. too sometimes, but you have to really be pushing the topic envelope in the U.S. before I get worried.

Was language a barrier? Probably a little bit - though I don't think there was a single comment or speaker that I didn't understand perfectly. But there's no doubt that participants less fluent in English were generally less likely to participate heavily. That's something I noticed consistently as the Conference went on and I suppose it's not really a surprise. I think everyone was able to follow the conversations completely - even if they were a bit shy about chiming in.

Which brings me, of course, to the most important questions. Was the conversation interesting - which really boils down to was the Conference good? Because the beer, the boat-rides and the sight-seeing are just extras to what really matters.

It was good. Really enjoyable and deeply interesting. I took away my usual trove of new insights and new things to consider. What the best practitioners in Europe are doing is as good as anywhere in the world and I heard some pretty cool stuff indeed. In posts to come I'm going to discuss some of the insights from my Web to Customer Analytics Huddle, the importance of persona-based segmentation in Virgin's testing program (which is one of the most carefully segmented and thoughtfully constructed I've ever encountered), some clever techniques for managing reporting fatigue that came out of Ross McDonnell's Huddle on measurement foundations, the insights about team-building for Big Data that surfaced in our keynote and that I heard seconded by David Williams from ASOS (despite having to skip his Big Data Huddle - my #1 selection for the whole Conference - to cover a session on Tag Management Systems), thoughts about creating POC and short-data window warehouses for data exploration, reflections on the buy-vs-build decision on Tag Management from Joe Stanhope, discussion of private panels, dynamic QR codes, and Markus Gerlitzki's (Rocket Internet) pretty impressive CRM and Web integrations, and some really brilliant ideas for measurement and Social CRM from Alex Emberey's session. On the other hand, when I find out who bumped me from Tom Bett's Huddle on mobile customer journey integration (which I heard was outstanding), heads will roll! (Just kidding).

It was X Change as I've always known it. Relaxed, intimate, informative, and fun. So many people told me the Conference was as different as we'd advertised and much better than expected that I lost track. I left (on the train to Heidelberg as I write this) knowing many really interesting people and terrific practitioners far better than when I went in and having learned quite a bit about how some of the best measurement in the world is getting done. When all was said and the last Pils drunk, we had that glow that comes from that rarest of times - when something big has lived up to or exceeded your hopes. It was a more than auspicious start to bringing this very special Conference to Europe. So yes, we're already planning year 2. Our usual end-of conference Q&A included a straw poll of top destinations for 2013: Berlin redux, Amsterdam, and Spain (Mallorca or Barcelona) came out on top. I can hardly wait!

Thank you all who participated so very much!

Danke Schoen and Auf Wiedersehen.

Webanalytics Tools Comparison Websites

2012-05-28T12:12:37-07:00

[Guest Post by Semphonic VP Matthias Bettag - Head of our Berlin Office]

There are so many analytics tools available that it's hard for anyone to stay current and informed. Web analytics, Surveys, User Feedback, Social Media, Testing…so many different requirements served by so many different tools each with its own complexities and functionality. There are free tools, open source tools, licensed tools for small sites and companies, and, of course, high-end enterprise-level software.

There are two great resources in Europe which tackle this universe of different tools by comparing them to each other and ranking them according the functionalities and abilities. They are www.AboutAnalytics.com from the Netherlands (English speaking), and www.IdealObserver.com from Germany (German speaking). Btw, if you know another similar website, please let me know.

When using these sites I always wondered why someone would put such an enormous amount of time and workload into such a rapidly changing and emerging market? How to handle this massive workload in any reasonable time? How to keep up with all changes, mergers and new functionalities?

Of course, I appreciate the site’s services, as many of us do – at whatever level of interest and for whichever purpose: they can help explain how one tool’s functionalities differs from another (e.g. to explain why a very basic solution is not a perfect fit for a multinational ecommerce enterprise…), they are a great resource when preparing a technology short-list or Request for Proposal (RFP) process, and absolutely invaluable when you want to see how a particular tool the sales guy was just talking about on the phone is classified by a third party.

I decided to reach out to the site owners of AboutAnalytics and IdealObserver and ask them about their sites. I couldn't resist asking mean questions like “Why do you love excessive work with high risk of immediate obsolescence?” and “What’s your motivation to provoke every vendor to complain on your site (except the one on top of your ranking)?”

It turns out the two sites work in rather a different way and follow a different approach. I think the interview below (with Mieszko Czyzyk, co-founder of AboutAnalytics.com, based in Enschede, Netherlands, and Marcus Nowak-Trytko, based in Düsseldorf, Germany, who runs IdealOberserver.com - formerly web-analytics-tools.com) explains it very well.

Here we go!

Question: What makes your site unique? What does it serve for, and who is/are your target audience/s?

AboutAnalytics: AboutAnalytics is world’s most comprehensive overview of analytics tools. We compare and review analytics software. Our AA Rating™ takes many factors and distills them into one quality score. We focus our advice on analytics end-users: Medium size businesses that don’t have the resources to perform elaborate comparisons. Using our rating end-users can quickly make a short-list of the best analytics software. In doing so they can make better and quicker investment decisions!

IdealObserver: The IdealObserver.com is a site for people who want to know more about a unique Web analytics tool. There are more than 430 criteria and over six categories with screenshots of each tool. The criteria are controlled by me. We have the origins of some of the web analytics companies’ customers. So I have a real user view.
The IdealObserver.com is a neutral platform for companies looking for a web analytics tool. They are looking for information they can trust and not for marketing information.

Q: What is your intention to provide such a tool-comparison, how does this is contributes to your business?

AboutAnalytics: Foremost it is to provide more market transparency in the analytics market.

Second, we are in the process of involving more analytics vendors in the comparison process. End-users can directly requests quotes for analytics tools. Vendors pay for quote requests and market data.

IdealObserver: First of all, it is a platform for neutral information about Web analytics tools. The knowledge of different tools helps us to support our customers. We optimize websites with a method called “user orientated quality management”. We are working for customers who are using different kinds of Web analytic tools.

Q: How long did it take to set this up, and how much time do you have to invest to keep it up-to-date? How do you get notice of new tools and how long does it take to have it analyzed (sic!) for your website?

AboutAnalytics: We build the site in about 6 months, with a part-time team of developers.

Keeping up to date is pretty time intensive. We have 3 part-time content editors. Together they work almost a full-time job to keep content up to date.

IdealObserver: The website was founded by Frank Reese, a web analytics specialist and book author. In 2009 he committed the website “web-analytics-tools.com” to me. At that time Web analytics tools were researched by around 260 criteria. Now by the end of 2011 I analyzed 430 criteria.
Of course it is a lot of work. I need 3 months just for the yearly update, many days for collecting and selecting information from web analytics companies and their tools and talks with companies using web analytic tools for their websites. I can see into different live web analytics accounts from major companies who are active in Germany and around the world.

Q: How are you comparing functionalities and features across the different tools to fit into your rating system? E.g. how do you define "segmentation" or "campaigns" so that it can be comparable across the different tools?

AboutAnalytics: We don't. The rating algorithm has different factors within each analytics category. This is not a real problem: it does not make much sense to compare different categories with each other. They only problem is in tools that perform multiple types of analysis (belong in multiple categories). We are working on representing these tools in multiple categories in a better way.

IdealObserver: Segmentation and campaigns are generic terms for a range of single functions. This means that the tools are analyzed under many different aspects. The usability of the functions is also a major factor for their evaluation. These are the main issues for the user’s evaluation of a web analysis tool. The user is not given a score for only one feature. The whole process and the single evaluations are transparent.

Q: Do vendors address their selves to you in order to make suggestions and provide news and updates?

AboutAnalytics: We have good relationships with quite a few smaller to medium size vendors. It is a problem however to get in touch with the biggest guys like Google and Adobe (Omniture).

IdealObserver: We do not publish PR reports, but relevant information that has been written up by journalists, working for my company www.echopress.de and then published. We receive this information directly from the vendors. To most of them we have good connections, to get information from is very hard.

Q: Do you receive regular feedback from people who use your site for a vendor pitch or evaluating a new WA tool?

AboutAnalytics: Yes, our content editors regularly talk to both users and vendors. However, we still need to get more reach with analytics end-users. It still is a young, emerging market. Many end-users choose for Google Analytics by default. Which is a shame, because there are many good quality tools out there.

IdealObserver: Yes, I talk to everybody who is registered on the website or email me questions. Customers use the data to compare analytic Tools. Or they use the data to filter information from Web analytics marketing and sales staff. We offer basic support to our customers and have the role of a neutral observer. Therefore we know their needs and can discuss how to choose the right Web analytics tool. Here we get the input for our next survey. So the features we develop correspond to our customers’ needs.

Q: Do you plan any enhancements for the future?

AboutAnalytics: For now we need to focus on the quality of our content and comparisons. From this more traffic follows, and this in turn makes AboutAnalytics more interesting for analytics vendors and consultants. In the next 2 weeks we will be improving our review system and increasing the visibility of companies that have subscribed.

IdealObserver: We plan to implement an English version of our study. It has been translated and the programming will start in the 2nd quarter of this year. There is enough content to write a “buyers guide” and we have more experience in so many different web analytic tools than any other company. This work will be our goal for this year.

Thank you both very much for your time!

Ich Bin Hier Berlin : Greetings before the X Change Europe

2012-05-25T12:22:38-07:00

We closed registration on X Change Europe today! Full. Sold out. At our limit.

It's hard to believe, but we're at our absolute per Huddle meeting room maximum. With most of the Huddle time slots completely booked (every Huddle at our 20 person limit), we've had to close registration. I didn't expect that, and now I wish I'd booked more Huddles per time slot!

Three weeks ago it seemed like we had plenty of room, but the Conference followed a much later registration curve (much like our first U.S. X Change) than I've come to expect. It's pretty cool. We have more people out for X Change Berlin than that first U.S. X Change and we've pulled people from all over Europe. The U.K. and Germany have contributed most (as we expected), but there's hardly a country in Europe that won't be represented.

And what about Berlin?

It takes awhile to get the feel of a city. Certainly far longer than the six hours I've been here (or maybe even the week I expect to stay). The weather is lovely - a bit cooler and much less humid than Stuttgart, sun everywhere. I had an open-air dinner in Potsdamer Platz; it was "Berlin-Istanbul Day" and the Turkish food stands were out in force. Clearly a cosmopolitan city.

The Scandic Hotel (our venue) has bikes for rent out front (12 Euros a day). It reminded me of the last-day bike ride that Phil Kemelor led at X Change San Diego last year. No beachfront bike paths here. Still, I'm hoping to take one out tomorrow and see the Tiergarten.

So far, Berlin does look rather as I expected. Open, new, vibrant and cool.

On the other hand, Stuttgart, where I spent the last few days doing Think Tank Training, was nothing like the industrial center I envisioned. It had the feel of a lovely country town which just happened to have nothing but Benz's on the road. As always, I enjoyed doing advanced training. It was a bit different in that Jesse Gross and I did many of the classes together. I liked the sharing - it gave me more time to think about what I was saying (which does kind of matter) and my voice didn't get as worn out.

As a kind of parting gift, Matthias and I got a tour of the Mercedes Benz Museum this morning. The building itself is a treat. Striking and beautiful - reminiscent of the Guggenheims (which I've always loved) - but all light and glass. I'm not by nature a car guy, but you'd be seriously wrong not to visit on that basis.

I know...this is all fluff. It's the great drawback of business travel; you have too much time to write. I'll have a real blog over the weekend and there should be plenty to talk about after X Change!

Digital Segmentation

2012-05-20T16:53:06-07:00

It was a crazy end-of-week for me. This coming week Jesse Gross and I are doing Think Tank training (Functional Analytics, Use-Case Analytics, Engagement Analysis and Attribution Analysis - good stuff) for clients in Stuttgart. Then it's off to Berlin and the X Change. But in a fitting last minute frenzy, I had an orgy of talking this Thursday and Friday that left me hoarse and deeply tired of my own voice.

Thursday was one of the weirdest office days ever, as Fox News was out at Semphonic taping a documentary. Not only was our office a shambles (though like The Cat in the Hat they put everything perfectly back in place before they left), but the filming was endlessly tiring and distracting. I spent almost two hours in talking-head mode and another 30-40 minutes running a demo, not to mention shots walking up and down our offices, shots at the whiteboard, and shots at the drinking fountain (just joking)...It was exciting but exhausting. Which left me in no shape for a Friday in which I had scheduled two webinars with iJento including a 5AM start-time for an EU-convenient session. Brutal. If you missed both sessions, you should be able to check it out on our site (and iJento's) this week. Both Barry Parshall and I agreed that the afternoon session was the better of the two (imagine that) so that's the one you'll hear. It's actually pretty darn good. Barry was great, my voice didn't fail and I think you'll enjoy the content.

Anyway, it was a huge relief to go to the Symphony on Friday night. Not so much for the music* but because I didn't have to say a word for more than 2 hours!

I've covered much of my content from the webinars previously, but one piece that I haven't much covered and promised to address is the alternative techniques for building a digital segmentation. For the past year, I've been blogging and talking repeatedly about our Two-Tiered Segmentation techniques and how fundamental they've become to Semphonic's digital analytics practice. The segmentation techniques drive everything from implementation design to reporting to use-case analysis to data models in the warehouse.

The basic concept is pretty simple. Proper segmentation in the digital world requires traditional visitor based segmentation (the who) paired with a visit-based segmentation (the why or what). This creates a two-tiered segmentation within which live interesting metrics and KPIs, testing opportunities, and good data warehousing aggregations.

I think that most analysts who've had a chance to reflect on the basic concepts will almost certainly agree that this approach makes far more sense than a focus on sitewide KPIs and metrics and is a promising direction for modeling digital behavior in the CDW.

On the other hand, there's often a healthy skepticism about the challenges of building a Visit-based segmentation. How successfully can one really infer intent when it comes to web visits? That is the trick of course. I've talked and written extensively about some of the methods to do this.

What I haven't covered in great depth is three quite different approaches to actually implementing visit-based segmentations.

The first method of creating visit-based segmentations is to create a set of hierarchical filter-based rules. This is the approach we take when we're building a visit-based segmentation with Omniture, Coremetrics, or Google Analytics. In Discover, for example, you have a rich segmentation builder that allows the analyst to construct a complex segmentation based on visitor, visit and even page-based criteria. With both Exclude and Include Logic, it's perfectly possible to create quite complex systems of hierarchical rules. That's important, because we generally craft visit-based segmentations to be mutually exclusive.

This works and, in fact, it's by far the most common method we've used to create two-tier segmentations. For Use-Case analytics and Management Reporting, it's ideal.

There are some limitations inherent in this method. First, if you're building segmentations in the Web analytics tool, you're often terribly limited in the amount and nature of the offline customer data you have. One of the most frequent questions I get asked (and it came up again this last Friday) is whether an online segmentation should include offline data. To which I, like any analyst, pretty much answer "the more the merrier." It's a rare analyst who will turn down additional data for a segmentation. For many enterprises, offline data is absolutely critical.

Even where you're working exclusively in an online world, however, filter-based rule segmentation has some limitations. Unlike clustering techniques common in traditional segmentations, rule-based segments have a very hard time capturing more ambiguous groupings - especially around quantities of behavior. If you did X amount of behavior A and Y amount of behavior B, which other customers are you most like? Rule-based segmentation doesn't answer that type of question well.

The limitations in rule-based construction can also be challenging. Rule-based systems don't handle any type of weighting or scoring. It's usually impossible to create rules of the sort "visitors who did X more than Y" without specifying particular values of X and Y - something that you generally don't want to do.

That isn't the only limitation in filter-based rule construction. You often can't access critical visit-segmentation variables around which action a visitor did first or how long it is since they did something. When you're trying to understand visit intent, it's often essential to know whether a visitor did an internal search right away or after viewing fifteen pages, or whether they'd visited the Website and started an order earlier in the day. Sequence often makes a huge difference when it comes to understanding visit intent. Any time-based or sequence based behavior is surprisingly hard to capture with filter-based systems.

So is there an alternative?

There is, but it's harder, more expensive and more complex (well - that's what you'd expect). By importing Web analytics data into a statistical analytics package, you can take advantage of a much richer set of variable manipulation, rule construction, and analytic methods all in an environment that joins offline and online data.

Traditional clustering techniques can be used to construct visit-based segmentations that group visits along dozens or even hundreds of variables and take full account of both the frequency and intensity of behavior.

Using clustering techniques to create visit-based segmentations will almost certainly yield a superior visit segmentation to one constructed by even a very clever analyst in a rule-based filtering system.

On the other hand, there are some significant drawbacks to this method from an operational standpoint.

First, it's a lot harder. You have to export, format, join and analyze the data. Worse, most Web sites spin off volumes that make it pretty much impossible to analyze the entire web population. Sampling isn't an issue if all you're looking for is a marketing model that will help you understand how visitors use your Website. But that's rarely the only (or even primary) goal of a visit segmentation. If you want to generate reports, create tests, build data warehousing or CRM aggregations, or do any form of targeting, you need a method for attaching segment codes to every visit. That means your building a model that then needs to be translated back into some form of rules so that you can actually apply to each visit/visitor. You don't want to constantly export data, analyze it in SAS, and the re-import the segmentation codes.

In some cases, you'll find that you can actually translate cluster-based segments back into rules in rule/filter based system and still have a pretty decent approximation of the segmentation. When that happens, it's very convenient and it means you can re-create your statistical models in a system like Discover. Not surprisingly, however, it doesn't always happen. The more you push the data and the more sophisticated your rules, the less chance there is that you'll be able to build a decent approximation of them in a Web analytics tool.

Which brings me to the third method of instantiating a visit-based segmentation - ETL rules. At Semphonic, we've built a pretty sophisticated system for processing Web analytics data feeds and incorporating our segmentation concepts directly into the process. Initially, we create the segmentation (which can be rule or cluster based) and then we instantiate the segmentation rules into the ETL. Because we have full programmatic control of the process, ANYTHING we need to instantiate a cluster or rule-based model is available to us. This means that the segmentation is incorporated directly into the data stream as it's processed and pushed into warehouse tables.

As I spotlighted in the iJento webinar, we can do exactly the same things with the iJento system. They've built a flexible data model and an ETL system that gives us almost full access to the records and logic. What that means is that Semphonic's segmentation schemes can be directly incorporated into an iJento-based warehouse on a near real-time basis. That's pretty cool.

Digital segmentation on the Two-Tiered model isn't pie-in-the-sky stuff. It isn't "advanced" stuff you can postpone while you get along with the never-ending business of tagging, building reports and serving ad hoc requests. It's the bedrock of a good web analtyics program - driving everything from useful reporting to testing to targeting. As the systems and options to deliver worthwhile segmentation continue to grow and expand, the competitive necessity for moving beyond a traditional web analytics program keep growing.

Whether it's driving a rule-based segmentation in Omniture Discover, creating Hadoop based ETL, or creating an analytics warehouse in a system like iJento, the choices and systems for delivering segmentation in digital analysis have never been better or the need to do so more pressing!

I'll check-in next week from Berlin and I'm also intending to post a guest contribution from our own Matthias Bettag on several Websites that provide comparative information on analytics tools.

Wir sehen uns in Berlin!

*Though it was a beautiful Symphony program - classic MTT - with a sure-fire crowd-pleaser to anchor the program (Beethoven's Pastoral), a far less known but pristinely beautiful piece in the classic tradition (Mahler's Blumine) and a challenging modern piece by (a German composer - how appropriate!) Schnittke (Violin Concerto #4) that I and probably most of the audience had never heard before. I particularly enjoyed the placement of a violinist in the side terrace above us for Schnittke's piece. A kind of Fiddler on the Roof! Amidst dissonance, the ominous chimes and the orchestral clock ticking there lived a furious violin battle and some lovely little harmonies as well as a surprisingly complete ending. And you would have to be almost immune to the solace and joys of music not to smile with pleasure at the opening lines of the Pastoral - the musical equivalent of a girl skipping across a golden field. I could speak for a hundred years and never say anything a tenth so beautiful.

The Warehouse Technology Stack : How much is too much?

2012-05-13T11:54:27-07:00

If you're interested in digital segmentation and analytics warehousing, you might want to check out the webinar I have this coming week in conjunction with iJento and CheapFlights. We're going to start the webinar with CheapFlights and a case-study of how they are using an analytics warehousing for targeting. Then I'm going to cover our digital segmentation (2-Tier) models and how they support this type of work. If you're a regular reader (or webinar listener), this may not break a lot of new ground for you; EXCEPT for a section on three strategies for building Visit-based segmentations. I plan to blog on that next week, but why not get a head start by listening in! Finally, Barry Parshall of iJento is going to talk about their solution (a robust, SQL-Server based analytics warehouse) and the Semphonic/iJento partnership. So even if you know (most) of what I'm going to say, I think the first and last parts will be valuable. We're doing versions for EU and US convenient times - so check it out even if you're EU-based.

iJento is one of the newer Semphonic partnerships and they fit right into our broader strategy of bringing customer analytics and digital segmentation to digital measurement world across a variety of technology platforms. U.K. based iJento provides a full-service (SaaS or on-premise) technology stack for analytics warehousing based on Microsoft's SQL-Server platform. Full-service means they bring ETL, integration (including Celebrus), optional hosting, and UI software to the table - as well as all the benefits and technology of being on one of the two most popular traditional relational database solutions on the planet.

I know...that isn't nearly as sexy as Hadoop. But that's part of what I want to talk about, because while Hadoop is cutting-edge cool, it's far from the right solution for every enterprise seeking to build an analytics mart. I'm not knocking Hadoop. We have about a dozen clients running Hadoop clusters and we even run our own cluster in the cloud (largely for knocking around).

If you have really large big data analysis problems, Hadoop may be the only plausible technology stack to consider. But when I say really large big data problems, I mean it. I'm not talking a couple hundred million rows of analytics data. That's not Hadoop country. If you migrate to Hadoop when you don't have to, you'll pay a real price. Sure Hadoop is free, but it's still a very rough-and-ready technology stack. You won't get anything like the tools, the polish and robust ecosystem that come with Oracle, SQL-Server or established enterprise platforms like Netezza or Teradata. That means you're going to spend LOTS more in custom consulting and development getting to (or at least somewhere near) the same level of capability. Hadoop isn't meant (at least so far) to provide many of the functions of a traditional data warehouse. It's a great ETL platform. It's a great exploration platform for teams sophisticated enough to use programmatic approaches to data analysis. It's great for provisional data analysis. It's not a customer data warehouse and it's not ideal for many traditional enterprise analytics requirements even around digital. Maybe someday it will be, but for now, with Hadoop, you're still on the bleeding edge of a pretty immature technology.

Here's how I see the market for big data analytics in terms of capability and size:

In other words, there are LOTS of organizations that have big data needs that are still serviceable with solutions like SQL-Server and Oracle. Maybe you don't consider those applications big data. Fair enough. I'll say it differently. There are LOTS of organizations that have digital analytics warehousing needs that are still serviceable with solutions like SQL-Server and Oracle. And when you push systems like Netezza or Aster into the mix, a very heavy majority of enterprises can meet their digital analytics needs. Most organizations simply don't have "Google" like problems with big data.

I realize this may run counter to a fair number of people's actual experience. If your enterprise has loaded digital data into Oracle or SQL-Server, you may well have had hands-on experience that suggests these technologies aren't up to the job - even with data volumes far short of the billions. We see some remarkably slow and poorly designed analytics warehouses. That's one of the reasons that solutions like Netezza are deservedly popular; they eliminate much of the need for clever design to generate good performance.

In the traditional relational database world, however, good design is a necessity. You can get terrible analytics performance on a relational system with a fairly small number of rows! It's also an enabler. A well designed relational model and architecture can make it possible to effectively support digital analytics within the traditional technology stack. Will it be as screamingly fast as Hadoop? No, but it will provide far better tools, far more options when it comes to resourcing and support, and far more integration opportunities. It will also be quite a bit cheaper when it comes to TCO (Total Cost of Ownership) and the time to value will be significantly less.

This need for good design is an undeniable risk point. One of the nicer aspects of the iJento solution is that you remove much of that risk. iJento provides the fundamental model and design architecture and, in the SaaS model, your costs in getting a system up and running so that you can measure the real-world performance are quite moderate.

How does the work that Semphonic does with data models and segmentation fit into our partnerships with companies like iJento and Infobright? Our partners provide the technology stack and, in iJento's case, the integration services and basic architecture and model. They'll take care of some of the more challenging details of the low-level data model (things like partitioning and indexing) and the ETL on multiple data sources. They also provide upstream UI tools in addition to the rich SQL-Server stack.

Our work on digital segmentation builds an additional layer on top of these systems. It makes the data more understandable and accessible and makes aggregations much more consistently useful. In next week's post, I plan to talk about three strategies for integrating our segmentation work into your enterprise with solutions like iJento and Infobright but also up and down the full set of possible technology stacks.

The work we've done in building a digital data model is meant to serve every level of this market: from SQL-Server to Hadoop. It works at the highest levels and the lowest. Understanding how to make sense of your data isn't platform specific.

It is, however, an integral part of a really good traditional relational model and it helps those relational systems scale to larger volumes by reducing the need to constantly hit the detail level data. Systems like Hadoop and Netezza are built to do precisely that on a routine basis. That doesn't mean that you don't need a digital segmentation to use the data well - even on Hadoop. It does mean that a digital segmentation won't yield performance benefits in the Hadoop world - it will simply drive better data usage. In the traditional relational technology stack, keeping the vast majority of queries out of the detail level is critically important.

SQL-Server based solutions aren't for every organization. I wouldn't recommend iJento to Turner Broadcasting, Walmart or Expedia. It's not the right fit. But if you're one of the many mid and even very large enterprises whose digital data volumes aren't in the billions, there are better choices than Hadoop for your analytics warehousing needs and iJento may well be one of those.

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Tealeaf, IBM and Warehouse Technology Stack

2012-05-06T12:23:36-07:00

Acquisitions are, by far, the most significant milestones in a technology landscape. Sure, new technologies and brand new vendors can be transformative. Hadoop is having a profound impact on the high-end data analytics warehousing ecosystem. Radian6 was transformative in social media measurement. In an industry like ours, however, acquisitions tend to rule. Think about the acquisition of Urchin by Google; Sane by Unica, IBM of Unica (and Coremetrics, Netezza, etc.), WebSideStory of Visual Sciences, Omniture of that combined company, and Adobe of Omniture (and Offermatica, TouchClarity, Efficient Frontier, etc.). We've seen a continuous ascent up the food chain as small analytics vendors were acquired or grew into mid-size companies who were then acquired by behemoths. Analytics is now a cornerstone of the growth strategy of the world's largest enterprise technology companies.

All of which is just a prelude to thinking about the IBM acquisition of Tealeaf this past week. Tealeaf isn't just the leader of the Customer Experience Management (CEM) space, they are almost it's de facto owner. For true enterprise CEM analytics, Tealeaf is pretty much the only game in town.

Tealeaf, as a company, is a natural fit for IBM. Not only is IBM building up a comprehensive suite of digital measurement and analytics tools (a suite that's strikingly different in shape than Adobe's), they play heavily in areas where Tealeaf is dominant: call-center and customer operations. A great many of Tealeaf's core clientele aren't really analytics clients; they are customer operations and call center clients who use Tealeaf primarily for web-related customer support problems. Unlike most analytics vendors (such as Adobe), this class of enterprise problem is meat-and-potatoes to IBM.

So IBM has a natural path to value in terms of Tealeaf's core business. That's always a good thing when it comes to acquisitions. But I'm more interested in whether or not IBM has a deeper interest in Tealeaf and how Tealeaf might be a part of the broader IBM digital suite.

Semphonic is a relatively new (just since the beginning of this year) Tealeaf partner, but I've long believed that Tealeaf was one of the most under-utilized tools in the digital analytics space. Many of our clients have Tealeaf tucked away in their call-center operations area and get little or no use from it analytically. It's a shame, though there are some reasons why Tealeaf often get siloed.

What's unique about Tealeaf is also what makes it challenging. Tealeaf is a sniffer - collecting data from the HTTP stream as it passes to and from the user to the client servers. Unlike some other sniffers, however, Tealeaf doesn't really weed, filter, and structure the data as it passes through. Tealeaf saves pretty much all of it. This makes Tealeaf expensive, but it also drives significant value. From a customer service standpoint, saving everything is like never having to say you're sorry. You don't know what data is going to be significant, so you pretty much have to save everything.

Analytically, of course, that's not always true. You CAN make pretty shrewd guesses about what's going to be significant. That's what tag requirements and design are all about. But as I discussed in last week's Webinar with Tealium on Tag Management Systems, that process of building requirements is non-trivial and error-prone.

So there's real virtue in a "save-everything" kind of approach. It's the same virtue I lauded in Celebrus. What's more, while the Tealeaf approach is technology expensive, it's people cheap. You don't need two or three web analytics consultants full-time onsite building tagging requirements when Tealeaf is your data collection mechanism. It's also zero impact: no page weight, no page changes, no site risk.

And here's another consideration. Systems like Tealeaf support a fundamentally different type of interface into the data than traditional Web analytics systems (or BI or Statistical tools for that matter). When you're collecting HTTP data streams (which are inherently unstructured), search becomes the primary query language. Users of traditional systems tend to be skeptical of search as a primary interface into the data (I know I am), but take a look at a system like Splunk and you can see that there is real power in the approach.

So I'm wondering if IBM isn't seeing Tealeaf as the potential data infrastructure piece for their entire digital suite. To make that happen, they'd have to provide tools for building structured views of the Tealeaf data (something Tealeaf already does). A fair number of tools in the suite wouldn't work otherwise. It's not that difficult a task to extend Tealeaf's existing capabilities, however, and once accomplished, IBM would have a unified data collection piece that completely bypassed the whole world of tagging and tag management. Yes, there are some drawbacks to this. Tagging handles client-side tracking of interactions that simply aren't capturable server side. Still, with a Tealeaf-based infrastructure, IBM would be able to support a wide range of analytics, call center and operational needs without any pre-planning or tagging. They would be able to source multiple tools all from a single real-time and exhaustive collection piece. They would be able to support both structured and un-structured access to the data. That might be pretty compelling.

It wouldn't be a solution for everyone, but for IBM's core enterprise-class clients, you can see that it might have real advantages as a comprehensive real-time analytics and warehousing infrastructure.

Which, as it happens, is a topic I've been thinking quite a bit about lately. Here at Semphonic we've been doing an ever increasing amount of work around the analytics warehouse and a real-time technology stack is one of the issues we keeping running into. I plan to talk more about some of the tools (most of which are a bit obscure) that potentially fit inside that technology stack in upcoming posts.

[Notes: Last year at X Change, we did the first Non-Profit Challenge. A day of deep-dive analytics by X Change participants into the analytics problems of two large non-profits. We recently published the results of that work in the Non-Profit Guide to Using Analytics Whitepaper. Not only can you download that whitepaper - a truly collaborative effort - if you're a non-profit, I strongly encourage you to tune into this week's webinar with Emily Fisher of Oceana, Linda Shum of United Way, and our own Phil Kemelor as they discuss the work, the whitepaper, and the use of digital measurement in the non-profit space.

And speaking of the data warehousing technology stack, I'm doing a webinar the following week with one our partners, iJento, with more on customer journey tracking. We've partnered with iJento because they provide a robust traditional (SQL-Server) database platform that can leverage our Two-Tiered segmentation data model (and collection mechanisms like Celebrus). iJento probably isn't the right solution for the 1% with extreme digital data volumes. But for companies with large but manageable digital data volumes, they provide a much less risky technology stack (and both SaaS and on-premise models) that can deliver deep access to customer digital data on top of a robust platform with a lots of support, great software, and tremendous flexibility.

Finally, I'll be leaving soon for Germany (I have some client engagements there prior to X Change). If you're EU-based and would like to setup meetings in Stuttgart, Berlin, Paris or London, drop me a line. I'd love to chat!].

Tom Betts of the Financial Times on Big Data Hype, Data Democratization, and Integrated Mobile Tracking : More from the X Change Berlin

2012-05-02T16:45:28-07:00

I first met Tom a couple years back at X Change when he was a participant, and after just one Huddle together I knew I'd love to him back as a Huddle Leader. He led Huddles last year in San Diego and is pulling double duty this year in Berlin and Los Angeles. He's built up a really cool practice at the Financial Times and every-time I talk with him I learn something. His work in mobile has been fascinating, the FT's technology platform strategy has been unusual and innovative, and while I'm not always a huge fan of data visualization if Tom says it's working, I'm interested. Check out his take on Big Data as well. I think he just about sums up the state of the industry perfectly!

Could you briefly describe your role at the FT?

I lead a global team of analysts at the Financial Times to understand, explain and optimise user behaviour on FT.com for a diverse range of stakeholders. Like our peers in media, we support the entire gamut of teams working on our online business - from marketing through editorial, advertising, product development and IT. Arguably our 'web analytics' group is due a rebrand, since we cover all digital platforms for the FT.

Can you tell us a little about the technology the FT is using to measure digital channels? And how is that evolving?

We standardised on web analytics technology from iJento around 4 years ago and use this to capture consumption data across all of our digital channels. Their technology suits us well since the notion of customer level analytics has always been at the heart of their solution, and multichannel comes natively too. Our solution from them is backed by a Microsoft SQL Server database which provides us with complete click-level data for each of our existing or prospective customers.

We've evolved our desktop web analytics database to include data from all platforms of consumption (spanning desktop, mobile web and apps, as well as ePaper), linked up for complete visibility of our customers' interactions. We've been combining this data with other customer data (CRM, content metadata etc.) for quite some time in order to shape our marketing and personalise our offering. In order to do this, we use a variety of tools, including SAS and R for analysis, combined with a customer 'data hub' which connects this data to other tools to make it actionable.

What are the key analytical challenges faced by the FT?

Meeting the demand for information within our business continues to be a challenge. The success of our analytics programme over the last few years has been infectious and has increased demand for analytics exponentially. We've been investing quite a bit of energy in improving how we best disseminate information (hence my huddle on democratising data), but we don't profess to have cracked it yet!

Another challenge that we face - which is common for so many - is the apparently constant redefinition of our digital propositions. While we used to just have FT.com, now we face an array of platforms and mobile-optimised offerings to understand, model and analyse. We're fortunate to have standardised on an HTML5 core (the basis of our Web App - app.ft.com) which makes developing analytics across devices easier, but we still need to manage constant change across these platforms.

Your first huddle topic is “Mobile in the Mix - Integrating Multichannel Data for 360 Degree Visibility”. What led you to pick that topic?

Mobile is a huge growth area for us and the rapid pace of innovation has meant that we have relied heavily on data to help guide our product strategy. Early on in the development of these channels we realised that if we wanted to understand the value and role of emerging platforms we needed to be able to answer some fundamental questions that we couldn't with a siloed 'platform view' of the world. For example, do new platforms increase consumption overall, or do they simply displace our audience and their existing reading from one platform to another? Are they a source of new business or just re-engaging existing customers?

Being able to answer these kinds of questions has been critical in allowing us to make investment and product development decisions around mobile. I'm hopeful that we can discuss both tactical and strategic solutions to providing mobile insights, how others are integrating this data as well as how it is used in practice. This is an exciting topic and one that I hope will be relevant regardless of your maturity in this area.

Your second huddle topic is “Democratising Data - Replacing Static Reports with Bespoke Visualisation Tools”. What will this huddle cover?

Recently we have been looking at how we better surface information to business users, and ended up building a range of bespoke web-based tools for business users to access behavioural data. This was largely because off-the-shelf packages either didn't do exactly what we wanted or were too costly. By designing these as bespoke and interactive data visualisations we've seen a step change in adoption, and I think have made a number of key areas more data driven as a result. I was staggered by the interest that these generated within our organisation and I'm looking forward to find out how others are using visualisation or building data tools to improve access to their data.

Web analysts are often accused of failing to convey the commercial value of their data to senior management. What role does data visualisation play in rectifying that problem (if at all)?

One key difference that data visualisation plays is in making the information digestible by a much wider audience. This means that key messages can be conveyed by business people, without necessarily needing the support of analysts. In my experience, it not only vastly increases the utility of your data but can also lead to a step change in the kinds of questions you get asked to answer (not 'what happened?' but 'why?' and 'what can we do about it?').

What are you hoping to achieve through your huddles?

Both areas I've selected have been priority areas of development for us and no doubt are for many others. We've invested a lot of energy in working on them, but there is plenty more we can learn. I'm hoping to share some of my experiences to kick-start the conversation, but fascinated to hear what others have been doing in these areas. From experiences with off-the-shelf tools and technology to open-source to home-brewed technologies built in house.. what is working best, and why?

Of the other Huddles at X Change which are of particular interest to you?

Big data is flavour du jour across the data analytics community and I'm keen to see how it plays out for digital measurement. I think you can get pretty far with traditional database architectures and data analysis tools, but it's clear that reducing latency in crunching data can have a measurable impact on the bottom line. The explosion of big data seems to be treading a fine line somewhere between game-changing and hype and I'm looking forward to discussing how these new technologies are really making a difference (away from the omnipresent vendors!).

You have participated in X Change 2011. What were your biggest takeaways? Why should web analysts and optimisation professionals attend X Change 2012?

X Change is a unique event where you get to meet and engage in conversation with some of the best practitioners in our field. It is a must-attend in my annual calendar now simply because it so accurately allows me to take the pulse of the industry and keep abreast with where things are heading next. 2012 will be my 3rd year attending X Change - during the last two years I saw the maturity of conversation go up a gear, so I'm excited to see what's on the horizon for 2012.

As I hope this short series has made clear, X Change delivers something when it comes to Conferences - a chance to sit down and talk deeply with some of the very best practictioners in the industry. These are frank, honest, no BS discussions with real back-and-forth. Even in these short Q/As, I think you get a good sense of what X Change is like and how much each practictioner brings to the table.

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Thinking ahead to X Change U.S. in September? (Tom will be there too) Click here to register since the U.S. Conference always sells out early!