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SEMangel
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Last Friday I took part in the DAA’s latest version of Ask Anything where DAA Members can send in questions and the designated responder (me for the day) does his or her best to say something sensible in return. At the end of the day, Jim Sterne sent in a final question on the role of the analytics warehouse and machine learning that I simply couldn’t resist expanding into full essay form. If you’re confused about the role of machine learning in the warehouse or suspicious of the claims of technology vendors touting the benefits of massive correlation to discover... Continue reading
Posted Jun 13, 2015 at SemAngel
I won’t pretend to be an expert on UK politics and even less on UK polling. But in the wake of the disastrous performance of pollsters in the UK predicting the outcome of the general election there, I think it’s worth reflecting on the lessons to be learned. If you’re not familiar with the broad storyline, it goes something like this. In the days leading up to the election, pollsters were reading a toss-up between the incumbent Conservatives and the Labour party with expectations of a divided Parliament and much confusion. It didn’t go down that way, with the Conservatives... Continue reading
Posted May 26, 2015 at SemAngel
[I'm going to be in London the first week of June for the Digital Analytics Hub - running workshops on Segmentation and Data Modeling and participating in the Conference. I took a few minutes to answer some questions from the organizers around my sessions and the Conference in general. Check it out and if you are EU-based, check out the Hub - it's a great event.] Hi Gary, we are looking forward to welcoming you back to the DA Hub. One of your workshops at this year's DA Hub is named "Getting Digital Segmentation Right". The name implies that many... Continue reading
Posted May 21, 2015 at SemAngel
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In my last post, I took a shot at defining what a data science role actually is or might be. My goal wasn’t to try and figure out from the hugely varied, largely confused and often contradictory public discourse a definition based on consensus. Instead, I wanted to layout my own vision for the actual roles required in an organization to do analytics and see if any of them fit the broader, fuzzy data science term reasonably well. Given that approach, I had to define all the roles involved in enterprise analytics efforts (outside of IT and program management type... Continue reading
Posted May 17, 2015 at SemAngel
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In the last couple years the term data scientist has become an accepted part of the broad analytics space. Everywhere I look, I see clients building data science teams and looking to hire that most elusive of breeds - data scientists. While I have been (and remain) highly skeptical of the term itself, I’m not opposed to the broader shift. As absurd as it may be that renaming a job role from statistician to data scientist triples its cost and increases its voice, it seems to me that this new reality is a better place to be – and not... Continue reading
Posted May 5, 2015 at SemAngel
Faceted search is at the heart of the ecommerce site experience. But despite its central role, the complexities of measuring and understanding faceted search behavior have contributed to make it both under-studied and under-optimized. In my last post, I described a basic data model for faceting that was designed to capture non-lossy, detailed facet behavior for analysis. While that data model is a significant improvement over the basic storage of facet data as it’s typically collected, I would expect that any competent analyst could and would design similar structures. In today’s post, however, I’m going to describe aggregation strategies for... Continue reading
Posted Apr 21, 2015 at SemAngel
Faceted search is at the heart of most complex, large-scale eCommerce sites. Not only does it play a huge role on the website, it plays a particularly significant role in those visits that can be influenced with merchandising. There are always a significant number of visits to an eCommerce site that lack any purchase intent. There are, too, a large number of visits where purchase intent is heavily focused on a specific product. Neither of these visit types is easy to influence. But for those visits and visitors who are seriously shopping, faceted search is usually at the core of... Continue reading
Posted Apr 12, 2015 at SemAngel
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If you translate IT analytics professions into their Hollywood counterparts, analysts are the stars and big data architects are the directors. It’s great to be in the leading roles. But you can’t make a movie with just stars and a director. Somebody has to build sets, manage the lighting and roll film. Our IT analytics equivalent is ETL – the difficult but totally essential process of moving data and manipulating it into the highly usable forms specified by the architects and demanded by the analysts. In this extended series on big data, I’ve so far concentrated on the essential role... Continue reading
Posted Mar 30, 2015 at SemAngel
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More Thoughts on Analyzing the User Journey I saw an article this past week in the local rag touting a bold new initiative in social media to localize advertising by country. In the featured case study, a company had targeted different messages by gender and country. Imagine, personalization at the 50% of the country population level! Wow. That's kind of like walking around at a conference, shaking people's hand and saying, "Hello girl" or " Hello boy". This is 2015, right? I didn’t fall asleep last night and wake up in 1995? Are we really bragging about digital (digital!) media... Continue reading
Posted Mar 22, 2015 at SemAngel
The single biggest reason why enterprises build a big data digital analytics warehouse? To do attribution or customer journey optimization. Since attribution is just an extension of customer journey with a marketing lens put on top, it follows that modeling customer journey is a critical part of building a successful digital big data warehouse. Here is an approach to creating simple, compact and very powerful representations of the customer journey for the omni-channel enterprise. Continue reading
Posted Mar 8, 2015 at SemAngel
Building a data model for real-time personalization is one of the most interesting challenges around. In this post, I layout the basic architecture and approach for a real-time digital data model and show how it can deliver incredible performance at massive scale with in-memory approaches and clever use of data structures. That's essential to delivering web personalization that combines the essential ingredients of effective personalization decisioning - knowing who the customer is, where they are in their journey, and what they are doing right now. Continue reading
Posted Mar 1, 2015 at SemAngel
In my last post on building a digital data model for the analytics warehouse, I described the concept of statistical ETL and argued for its critical importance in creating a robust and easily used visit-level data model. That post drew an interesting comment from a friend of mine arguing not with the concept of statistical ETL, but against the idea of a visit-level aggregation. Here’s the comment (from John Stansbury): Gary, As usual, great blog. It just seems that we've got to get past the notion of visits and sessions. Those entities only exist for the convenience of measurement tools--consumers... Continue reading
Posted Feb 22, 2015 at SemAngel
Guest Post by Kelly Wortham I’ve been involved in several conversations lately regarding the pros and cons of MVT vs A/B for isolating and understanding results of optimization testing. The conversations go something like this: “A/B gets you an answer so much faster with easier to interpret and explain results!” “MVT is the only way to understand each element’s interaction with the other elements!” “MVT can create nonsense combinations that simply waste traffic and unnecessarily lengthen test time while also risking customer experience! At least with A/B you can be confident you’re avoiding that!” “If you’re not running MVT, you... Continue reading
Posted Feb 15, 2015 at SemAngel
I began this series with a short essay on the meaning of big data and why digital data is paradigmatic of big data. In digital, the unit of meaning lies above the level of the individual records we collect and cannot be represented as a simple aggregation of those records. A page view, taken in isolation, is largely without meaning, and no simple count, sum or average of page views will capture the meaning inherent in the behavioral stream. This lack of meaning at the detail level is a huge challenge. In my last post, I described a re-formulation of... Continue reading
Posted Feb 8, 2015 at SemAngel
Not too long ago I enjoyed a fascinating conversation over lunch with Loren Hadley on our team here at EY around some work he's been doing analyzing Web performance in China. This seemed highly germane to many of our clients, so I asked Loren if he'd be willing to redo the conversation in written form. I wrote up the questions, Loren provided the insight... You’ve been working on some analytics projects that are China focused and part of that has been comparing China to other regions and countries – not just the U.S…what’s your sense of how different China is?... Continue reading
Posted Feb 1, 2015 at SemAngel
Where should you start when modeling digital data for the big data analytics warehouse? A good place to begin is by re-thinking the way the event-level data is stored. Yes, you'll want to keep this data at the lowest level of detail. In fact, you'll actually want to unpack some of the data to make for a more consistent and queryable data stream. In this post, I'll catalog some of the deficiencies in the shape of the data in a digital analytics feed (such as Adobe's) and show how it can be transformed into something that is much easier to understand and that makes many, many queries much easier to write. Continue reading
Posted Jan 24, 2015 at SemAngel
A Quick Introduction to Big Data Does the term big data get at something real or is it just a handy catch-phrase for helping IT departments get more budget and IT vendors sell new kinds of boxes? It’s not an easy question to answer, largely because most of the people buying and selling big data have largely missed the real point of it. Most of those buyers and sellers have tended to describe “big data” in terms of things like volume, variety and velocity. We have more, they say, and this somehow changes the problem. It doesn’t. People have struggled... Continue reading
Posted Jan 19, 2015 at SemAngel
Here at EY, we spent a good chunk of time last year helping client’s build out digital capabilities in the analytics warehouse. In some cases, that meant building traditional data stores and traditional data models in Oracle and SQL-Server. But for the most part, it meant building analytics capabilities on top of Hadoop systems; that’s been bracing, difficult, sometimes frustrating, and always interesting. I remain convinced that the future of analytics lies in working at a very detailed level of the data (though I think there’s much to be debated about exactly which level of detail is right). I also... Continue reading
Posted Jan 11, 2015 at SemAngel
I just did a quick count of my posts from 2014 and it came to (surprise!)….52. So I (or I plus analytics club members Kelly and Jim) averaged exactly 1 post a week. Of course, that’s assuming I don’t finish this post till after the New Year. Most years past I’ve tried to write a year-end summary that called out the posts I really liked – the ones I think worth seeking out. I know it’s expecting a lot to read all or even most of these posts during the year. Who has the time? But this year I’ve decided... Continue reading
Posted Jan 2, 2015 at SemAngel
My daughters have recently begun to stage weekend “film festivals” where they will run four, five or even six movies over the course of two or three days. It began with a Best-of-Pixar marathon that included Toy Story, Finding Nemo, Monster Inc., Incredibles, Ratatouille, and Up. "Success" lead to a Miyazaki festival (Kiki, Cat Returns, Castle in the Sky, Totoro, Howl) and, last weekend, a best of Dreamworks that included Monster v. Aliens, Shrek, Madagascar and Kung Fu Panda. Perhaps that’s thinner gruel, but I love Kung Fu Panda and my topic today brought to mind Kung Fu Panda’s “Secret... Continue reading
Posted Dec 17, 2014 at SemAngel
Thursday morning I spent an hour talking “live” with Jim Sterne as part of a new DAA program called “Thought Leader Conversations”. It was cool. The conversations are a more relaxed, unfocused, genuinely enjoyable (at least for the participants) kind of public experience than I’m used to. It’s really nothing more than an extended conversation / QA – but Jim is a master at this kind of thing and non-panel Q&A is something that I’ve always liked better than speaking. We talked about everything from my early history in credit card (and why I think that data was much easier... Continue reading
Posted Dec 7, 2014 at SemAngel
There are four areas from our Voice of Customer (VoC) discussion at X Change that I'm highlighting. In the first post, I wrote about a way to explore task accomplishment in more depth. In the second I outlined a method for using VoC to understand customer journeys. For the third, I described how VoC can be a super-efficient way to test creative strategies before investing in an expensive A/B or MVT test. Here, I discuss why it might make sense for digital analytics folks to spend a little more time measuring product not just website and marketing. The overwhelming majority... Continue reading
Posted Nov 22, 2014 at SemAngel
There are four areas from our Voice of Customer (VoC) discussion at X Change that I'm highlighting. In the first post, I wrote about a way to explore task accomplishment in more depth. In the second I outlined a method for using VoC to understand customer journeys. Here's the third, showing how VoC can be a super-efficient way to test creative strategies before investing in an expensive A/B or MVT test. One of the really interesting discussions in the VoC Huddle that illustrates how flexible online surveys can be revolved around the use of online intercept surveys to test creative... Continue reading
Posted Nov 21, 2014 at SemAngel
There are four areas from our Voice of Customer (VoC) discussion at X Change that I'm highlighting. In the first post, I wrote about a way to explore task accomplishment in more depth. Here's the second - outlining a method for using VoC to understand customer journeys. I really should devote a full post (or even a series) to the techniques we’ve been deploying around VoC to measure a broader spectrum of the customer journey. Here, I’m just going to try and sketch out a capsule summary of the overall approach we discussed at X Change. When we ask someone... Continue reading
Posted Nov 18, 2014 at SemAngel
No area of analytics is as underserved in the enterprise as Voice of Customer (VoC). Despite plenty of lip-service to caring about what the customer thinks, VoC data tends to under-collected, under-processed, and under-distributed. It’s a shame, because VoC is powerful, easy to deploy, inexpensive and easy to understand. Yes, it’s true that most enterprises these days do collect basic information around satisfaction – especially NPS. But as I’ve written before, NPS is no more than scoreboard. It’s a reasonably interesting metric in terms of brand perception, but its information content is very low and largely non-digital. You can get... Continue reading
Posted Nov 15, 2014 at SemAngel