"Being creative with data" 25th November - KXEN presentation
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"Being creative with data" 25th November - KXEN presentation

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Alan Furness from KXEN at the IPA's "Being creative with data" workshop and seminar on Wednesday 25th November.

Alan Furness from KXEN at the IPA's "Being creative with data" workshop and seminar on Wednesday 25th November.

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  • Over time your business environment and strategic goals will change. Markets change. Competitors add new features and services, the economy expands or shrinks, new technologies and products come to market. Those changes in the market drive the need for changes in your strategy. And at the same time, customers change their behavior in response to changes in the marketplace. All of these changes drive the need for analytics that help you understand and predict customer behavior. However, at the end of the day the Marketing Director is not looking for more models, but more insight at the speed of (his/her) business, in order to make better decisions.
  • Let’s take a look at what happens when you employ traditional data mining technologies: The business user starts out with a business question: “As the luxury car dealer you want to know who of your mailing list is likely to earn over a certain income e.g. $50,000” Now you have to get hold of an analyst from your statistical department to help you with your project You explain your problem to the analyst who starts by working on the data that you have for him; s/he will look for outliers, identify missing values, try to reduce the number of attributes that you want to use… The first step is to reduce the number of variables from perhaps 800 (that are available in your data Warehouse) to about 20 – 30 that a traditional modeling tool can handle The next step is to prepare the data for modeling – this is where the expert spends 60% to 90% of the time: Data Mining tools can only handle numbers, so all text information has to be converted to numeric values, Outliers have to be discarded, missing values have to be replaced and much more Then the analyst is ready to build a great model and it actually explains your data very well But when you try to run this model on new data, the results are bad – so the analyst goes back and tweaks the model. An then s/he tries it again on new data and that way, after several iterations, a compromise is found between fit and robustness Now the analyst has to interpret the resulting several pounds of paper that running the model has produced so that you understand what happened 3 weeks for this process is considered to be aggressive - the average cost per model is somewhere between $20,000 – $100,000, which accounts for the time of the analyst and the systems and software tools KXEN proposes to shrink this process to hours or minutes at a cost of less than $500 per model, which can quickly converge to 0 as customers build high numbers of models
  • Analytics is not rocket science anymore! And we do not have to be rocket scientists! Tools are available that enable business analysts close to the business people to begin delivering insight into the meaning of the organisation’s data Finally no insight has any value unless it can be actioned profitably. To optimise that value there is a another stakeholder in the mix – the agencies, the creatives who can take that insight from the analysts and quickly turn it into an appropriate and compelling action. The circle needs to be closed.

"Being creative with data" 25th November - KXEN presentation "Being creative with data" 25th November - KXEN presentation Presentation Transcript

  • Using Predictive Analytics Presented by: Alan Furness November 25 th 2009
  • Agenda
    • KXEN – Company Background
    • The Impact of a Changing Environment
    • Getting the First Mover Advantage
    • Examples
    KXEN, Inc Company Confidential
  • Agenda
    • KXEN – Company Background
    • The Impact of a Changing Environment
    • Getting the First Mover Advantage
    • Examples
    KXEN, Inc Company Confidential
  • Your Environment and Goal Change over Time KXEN, Inc Company Confidential Requires More Focused Models Requires More Current Data Requires Frequent Updates Markets Are Different Customers Are Different Products/Channels are Different Your Strategies Change Customer Situations Change The Environment Changes
  • Combining data in models
    • CRM
    • EPOS and shopping data
    • eCommerce
    • Web analytics
      • Behavioural
      • sequencing
    • Unstructured (text)
      • Attitudinal
    • Social Networks Analysis
      • Churn and fraud
    KXEN, Inc Company Confidential
  • Too much data…..? KXEN, Inc Company Confidential Have you got lots of data? Are you getting Value from it? Analytics is about Insight
  • Do More…Modeling Automation is Key! KXEN, Inc Company Confidential 3 Weeks Next Generation 3 Hours Build Model Understand Apply
    • Variable selection
    • Data preparation
      • Variable encoding
      • Missing value handling
      • Outlier handling
      • Binning and banding
    • Model Fitting
    • Model Testing
    • Model Reporting
    • Model Deployment
    KXEN Automates Legacy Data Mining Select Variables Under- stand Apply Prepare Data Build Model Test Model
  • Agenda
    • KXEN – Company Background
    • The Impact of a Changing Environment
    • Getting the First Mover Advantage
    • Examples
    KXEN, Inc Company Confidential
  • Goals:
    • Understand each customer’s unique needs
      • Customise offers
      • Personalise sites
      • Serve up the right offer
    • While tracking the impact of the offers
    KXEN, Inc Company Confidential Grow Customer Relationships Improve Marketing Efficiency
  • Behavioral-Based Insight KXEN, Inc Company Confidential Thousands of Audience Segments Thousands of Potential Advertising Placements Ingest Large Volumes of Self-expressed User Data Deliver Real-time Recommendations and Predictions Model Dynamic Continuous Fast cycle Next Best Offer Next Best Activity Marketing Mix Retain Cross-sell Attribution Acquire Next Best Product
  • For Each Customer… Determine
    • The Right
      • Product
      • Channel
      • Creative
      • Offer
      • Timing
    KXEN, Inc Company Confidential Product Timing Channel Offer Creative Customer Next Best Offer
  • How Analytics Can Help you be a First Mover
    • Provide the right content
    • On the right media
    • At the right time
    • To sell the right product
    • To the right prospects
    • While being able to
      • attribute the cost and value
      • understand the net value
    KXEN, Inc Company Confidential Grow Customer Relationships Improve Marketing Efficiency
  • Agenda
    • KXEN – Company Background
    • The Impact of a Changing Environment
    • Getting the First Mover Advantage
    • Examples
    KXEN, Inc Company Confidential
  • Example : Ad Attribution for Financial Services Provider
    • Spends $48MM /year with DoubleClick
    • Data volumes are large
      • 500m users (cookies) per month
      • 12b impressions per month
      • 450 distinct page placements
      • 300 distinct creatives
    • Users see the ad many times before they convert, what are the key drivers of conversion?
    KXEN, Inc Company Confidential Solution Solution Solution Situation
    • Data Preparation on the Amazon Cloud – 6 days
    • Model Building with KXEN took 90 seconds
      • 130k rows
      • 100 columns
      • High accuracy and robustness
    • Key drivers and business insight identified
  • Example : Ad Attribution for Financial Services Provider (cont.) KXEN, Inc Company Confidential Solution Key Drivers Variable % % of impressions from the site they visit most often 21% number of creatives seen 19% internet domain 13% site page they see most often 11% city 8% number of days with impressions 7% DMA 6% site they see most often 5% number of operating systems 5% number of domains 4% Top Referring Site Freq 1 - Crossed Frequency Fool.com, KxOther, Seeking Alpha 1.32% 4.51% CNNMoney, TheStreet.com 3.44% 2.29% Bloomberg.com, Silicon Alley Media , Vibrant Media Inc, Wall Street Journal Online, Yahoo 39.76% 1.24% InvestingChannel, MSN 36.57% 0.75% AOL.com, Turn, Inc., United 18.92% 0.53%
  • Example : Conversion for an Ad Network
    • Ad Network collects customer shopping behavior from a number of retailers
    • which customers would be good prospects for which offers
    • Revenue is based on the number of click-throughs obtained – accurate targeting means more $$
    • Need to develop and refresh acquisition and cross-sell models for each retailer, monthly
    KXEN, Inc Company Confidential Solution Solution Solution Situation
    • Built infrastructure for the data collection and preparation
    • Automate the model refresh and model validation
    • Analyst only reviews model results, rather than manually train each model
  • Example: Online Conversion KXEN, Inc Company Confidential
    • Situation
    • Due to limited service representatives, an interactive chat company needed to predict which on-line visitors are more likely to have a “positive outcome” if engaged in a live chat session.
    Situation
    • Process
    • Using click-stream behavior to build a random test model
    • Models are built and embedded on the website that predict the probability of a positive reaction.
    • Visitors are scored every 10 seconds
    • The highest scoring visitors are approached
    Process
    • Solution
    • Increase conversion rates
    • Enhanced customer experience
    • Optimised service center resources
    Solution
  • Example : Royal Shakespeare Company
    • Reach broader diverse audiences
    • Encourage core of loyal customers to visit more
    KXEN, Inc Company Confidential Solution Situation Josh Kirby c1993 Results
    • Stratford ticket sales up 61%
    • Regulars up 80%
    • New London market identified
    • Donations up 67%
    • Membership increased by 40%
    • London DM strategy – 45 minutes
    Solution
    • Segmentation models
  • At the end of the day…..
    • Modelling and Analytics only provide insight….
    KXEN, Inc Company Confidential
    • The insight has to be actionable
    • And usually the action is a marketing one
    The Far Side
  • Thank You