It’s not as if I’m going out of my way to avoid writing about web analytics process, it’s just that things keep coming up. Or maybe it is that way. I’ll confess to a certain amount of…well perhaps fear is too strong a word…but maybe anxiety would fit the bill - about a post on web analytics process. I’m not really a process guy.
Thankfully, I am able to delay another week thanks to Predictive Analytics World (Feb. 18th and 19th in our lovely San Francisco) – a conference devoted, as you’d expect, to predictive analytics in all its many colors.
The conference is new and I think it sounds pretty interesting. From a web analytics community perspective, it has the misfortune to be scheduled at the same time as the Omniture Summit. And from the macroeconomic perspective it has the misfortune to be kicking off in 2009. But I think it may fill a void in a schedule over-crowded with me-too conferences.
A conference exists to help create a community of interest – be it around a vendor’s product (like the Omniture Summit), a shared expertise (X Change), or a shared field (SES or eMetrics). Most conferences tend to gravitate toward a very broad and low common denominator (since they are mostly done for profit and there are always fewer experts than those who are merely interested) – so they tend to cater less and less to the people who are most important to the community. That’s why I pitched X Change as distinctly focused on the experienced practitioner – I wanted to carve out a distinct niche.
It seems to me that Predictive Analytics World (PAW) has a chance to fill a similar niche for analysts and measurement leaders in a cross-industry space who are focused on using BI technology in the predictive space. There’s a lot of overlap (and learning) in understanding how different industries are using analytics – something I’d like to think about for X Change. And it seems to be me that the conference has a chance to bring a group of people together who can really benefit from each other and actually learn something new.
The point-man for the conference is Eric Siegel, and I did quick interview with him to help promote the conference. It’s pretty good stuff. There’s also a survey they are doing to help gather information for the Conference about the use of Predictive Analytics. You can take the survey here.
Here is the interview with Eric…
I’ll start with the obvious – Why a Conference about Predictive Analytics?
Why is this conference needed? I'll start by defining predictive analytics and why it's needed.
Predictive analytics is business intelligence technology that produces a predictive score for each customer or prospect. Each customer's predictive score informs actions to be taken with that customer, thus automating operational decisions in marketing, web and other business functions. For example, predictive analytics predicts response in order to target direct marketing, product recommendations and web/email content, predicts defection in order to target retention offers, and predicts debtor risk for credit scoring. Business intelligence just doesn't get more actionable than this. For more details on these and other business applications of predictive analytics, see my new article (recently published on BeyeNETWORK): http://www.predictiveanalyticsworld.com/businessapplications.php
Predictive analytics has penetrated across verticals, with wide adoption within some, such as certain financial sectors. It's a proven method, growing in adoption across industries, so its leaders, professionals and newbees need a place to meet up. Predictive analytics managers and practitioners will benefit greatly from this event, which brings them together to share lessons-learned and best practices across industries.
Predictive Analytics World's goal is to strengthen the business impact delivered by predictive analytics deployment, and establish new opportunities with predictive analytics. The conference delivers case studies, expertise and resources to this end. PAW-09 will have 25 sessions across two tracks, so you can witness how predictive analytics is applied at 3M, Acxiom, Affiliated Computer Services, Charles Schwab, Click Forensics, Google, Linden Lab (Second Life), The National Rifle Association, Netflix, Pinnacol Assurance, Reed Elsevier, San Diego Supercomputer Center, Sun, Telenor, Wells Fargo Credit Card Services, Wells Fargo Internet Services Group -- plus special examples from Anheuser-Busch, Disney, Hewlett-Packard, HSBC, IRS, Pfizer, Social Security Administration and WestWind Foundation.
See the full program at http://www.predictiveanalyticsworld.com/agenda_overview.php
It seems to me there is something of gray area between what I’d call classic analytics and reporting (which is mostly what we end up doing) and predictive analytics. When do you really feel like you’ve crossed over from one to the other?
But you can't stop there, because the whole point is to make use of the predictive scores to drive action. Once the scores are deployed, integrated into existing systems or processes to automate operational decisions, then by gosh we're definitely doing predictive analytics.
When I first got involved in analytics and database marketing people were all excited about modeling and segmentation and targeted personal marketing. And while it did work exceptionally well for companies in certain industries, it never seemed to penetrate to many others. Today, I still hear about a lot of the same stuff as cutting edge that we were working on fifteen years ago. Do you have similar experiences – and why do you think analytics – especially advanced analytics has proven challenging for many industries to really embed?
• One or more experts in-house or deeply engaged
• A business case for predictive analytics deployment, such as one of the business applications I listed above (i.e., a way a predictive model can and will be used, rather than just being a nifty model that may not provide business value); management buy-in for the integration and deployment of predictive scores
• Sufficient data to train a predictive model for the prediction goal at hand
• General understanding and buy-in of a predictive analytics initiative by stakeholders across business functions
• Implementation of organizational process best practices. For analytics, this means CRISP-DM (Cross-Industry Standard Process for Data Mining -- www.crisp-dm.org) or equivalent. An iterative process that ensures comprehension, feedback and buy-in is attained across a group of relevant managers at key phases of a predictive analytics project
• When initial deployment success is achieved, sufficient executive buy-in to facilitate long-term maintenance that keeps the deployment alive and effective
Some of these are elusive; if one goes astray, adoption or longevity is not attained.
The good news is that in fact these ingredients usually do exist for mid-tier to large companies – and often for smaller companies, if they have data pertaining to enough customers or prospects. And, with these ingredients place, predictive analytics delivers high returns – significantly higher than analytics that are not predictive in nature. An IDC study showed that predictive analytics initiatives show an average ROI of 145%, in comparison to 89% for non-predictive analytics ("Predictive Analytics and ROI: Lessons from IDC's Financial Impact Study," September, 2003).
What makes the difference is a certain level of global understanding, a great deal of widespread buy-in, key executive buy-in (and perhaps a bit of executive understanding :), and adoption of best practice business processes (on top of killer core analytical methods). This is where Predictive Analytics World comes in. This stuff, the basic analytics concepts and business benefits of predictive analytics, needs to be made more widely accessible. There’s no better way for non-experts to learn what predictive analytics does and how it works - and to become convinced of its effectiveness - than named case studies, which is why PAW’s program is built primary of such success stories, across verticals. See the full program, at http://www.predictiveanalyticsworld.com/agenda_overview.php
I guess this is a related question, but do you sometimes find yourself surprised at the low-level of analytic sophistication in even very big organizations with very large marketing budgets?
More objectively, we can look to survey results to tell us concretely how far along and sophisticated organizations are in their adoption of analytics, such as:
• The Predictive Analytics World survey on applications of predictive analytics. This survey is in process, and we'd like the reader's help - take a few minutes, answer a handful of questions, and help us keep you informed: https://www.surveymonkey.com/s.aspx?sm=8dHx_2bFz7yxw3FPKlbi3OVg_3d_3d . To make sure you don't miss the survey results, sign up for PAW event updates, at http://www.predictiveanalyticsworld.com/notifications.php
• The Rexer Analytics 2008 Data Miner Survey report, covering the most popular software tools, which verticals have embraced modeling and more. Available for immediate download at http://www.predictiveanalyticsworld.com/survey-signup.php
• Davenport and Harris' results in their book, "Competing on Analytics"
• The Web Analytics Benchmarking Study: http://www.benchmark-analytics.com/d/?q=Web+Analytics+Benchmarking+Study+-+Aug+2008
I noticed that your top keynoters were all Ph.D.’s so it’s no wonder I’m not speaking! I couldn’t handle that much schooling. But I wondered what is the target audience for the conference? How knowledgeable and experienced do you expect/hope/plan for attendees to be?
The conference program is designed to speak the language of marketing and business professionals using or planning to use predictive analytics to solve business challenges. Since the best way to catalyze commercial deployment is to show the people it really works outside "the lab", PAW's program is packed primarily with named case studies of commercial deployment. And for the hands-on practitioner or analytical expert focused on commercial deployment who wishes to speak this same language, it's an equally valuable event.
So regarding the higher academic degrees, I would venture to claim that myself and the other two keynoters are delivering great, actionable talks despite our Ph.D.'s, and based mostly on our experiences outside the ivory towers :) . PAW’s program of speakers has been optimized for commercial viability, not academic credentials.
If you'd like our informative event updates, sign up at http://www.predictiveanalyticsworld.com/notifications.php
For an overview of predictive analytics, and additional reading and resources, see the Predictive Analytics Guide http://www.predictiveanalyticsworld.com/predictive_analytics.php
Hey I might tease Eric about it, but if I had a Ph.D., I'd never say "in spite of my Ph.D". I don't buy into the idea that you can know too much about your subject and it seems to me that people often discount academic learnings only because they aren't doing anything as remotely interesting or rigorous. This seems like a great opportunity for people to actually get ahead of the curve a little bit and hear about some of the most interesting applications of analytics out there.
If you’re interested in attending the Conference, check out their web site. I believe I can also get you a 15% discount – so if you’d like to get a promotion code for that just drop me a line.
And damn it - there's even some process stuff in Eric's answers. I swear that by next week I will at least begin my process post!
Talk to you then.
Notes from the non-Ph.D. department :) ....
Have you seen the wildly fun book Collective Intelligence?
Posted by: Greg Moore | January 19, 2009 at 01:22 PM