Digit-Tech Analytics Workshop

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Analytics workshop on how to turn data into actionable insights.

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  • Customer Behavior Isn't LinearIf analysis has taught us in the online marketing, where a 10 percent visit-to-purchase conversion rate is still considered extraordinary, it's that customers don't behave in a linear fashion. Customers' goals don't always align with our direct online revenue goals. Customers change their minds. They get distracted. They lose interest. They save carts, abandon carts, add items to carts, remove items from carts, and sometimes all the above -- and in no particular order. Sometimes they navigate for products, sometimes they search for products. Sometimes they do both in the same visit. So long as customers are people, customer behavior will be dynamic and at times irrational, random, and unexplainable.So why are we trying to fit the dynamic nature of online customer behavior into a linear model? I've heard this question discussed recently in online retailing circles. It will gain momentum as a better model for analyzing customer behavior for e-commerce organizations. http://www.clickz.com/showPage.html?page=3596566
  • Please insert the actual statistics into the text below the graph and point out that this is based on McKinsey research and best practiceAdmit that NDS is not there to make money and there might not be any direct competitors but point out that the above applies for leads as well And although we might have a limited amount of direct competitors we’re competing for attention with other sectorsThe smoother the overall experience is from TV ad over website content to application process the better we can competeUse the actual care careers numbers to make the connection clear
  • Digit-Tech Analytics Workshop

    1. 1. [Digital Measurement ]<br />Analytics workshop on how to turn data into actionable insights<br />
    2. 2. [ Company history ]<br />Datalicious was founded in 2007<br />Strong Omniture web analytics history<br />One-stop data agency with specialist team<br />Combination of analysts and developers<br />Making data accessible and actionable<br />Driving industry best practice<br />Evangelizing use of data<br />June 2010<br />© Datalicious Pty Ltd<br />2<br />
    3. 3. [ Challenging clients ]<br />June 2010<br />© Datalicious Pty Ltd<br />3<br />
    4. 4. [ Data driven marketing ]<br />June 2010<br />© Datalicious Pty Ltd<br />4<br />Insights<br />Reporting<br />Data mining and modelling<br />Customised dashboards<br />Media attribution models<br />Market and competitor trends<br />Social media monitoring<br />Online surveys and polls<br />Customer profiling<br />Action<br />Applications<br />Data usage and application<br />Marketing automation<br />Aprimo, Traction, Inxmail, etc<br />Targeting and merchandising<br />Internal search optimisation<br />CRM strategy and execution<br />Testing programs<br />Data<br />Platforms<br />Data collection and processing<br />Web analytics solutions<br />Omniture, Google Analytics, etc<br />Tagless online data capture<br />End-to-end data platforms<br />IVR and call center reporting<br />Single customer view<br />
    5. 5. [ Today ]<br />Capturing data<br />Options, limitations, innovations<br />Generating insights<br />Process, metrics, examples<br />Taking action<br />Media, targeting, testing<br />June 2010<br />© Datalicious Pty Ltd<br />5<br />
    6. 6. [ Capturing data ]<br />101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010<br />June 2010<br />© Datalicious Pty Ltd<br />6<br />
    7. 7. [ Digital data is cheap ]<br />June 2010<br />© Datalicious Pty Ltd<br />7<br />Source: Omniture Summit, Matt Belkin, 2007<br />
    8. 8. [ Digital data options ]<br />June 2010<br />© Datalicious Pty Ltd<br />8<br />+Social<br />Source: Accuracy Whitepaper for web analytics, Brian Clifton, 2008<br />
    9. 9. [ On-site analytics tools ]<br />June 2010<br />© Datalicious Pty Ltd<br />9<br />Google: ”forrester wave web analytics pdf” or http://bit.ly/aTLAKT<br />Source: Forrester Wave Web Analytics, 2009<br />
    10. 10. [ What platform to use ]<br />June 2010<br />© Datalicious Pty Ltd<br />10<br />Stage 1: Data<br />Stage 2: Insights<br />Stage 3: Action<br />Data is fully owned in-house, advanced predictive modelling and trigger based marketing, i.e. what will happen and making it happen!<br />Sophistication<br />Data is being brought in-house, shift towards insights generation and data mining, i.e. why did it happen?<br />Third parties control most data, ad hoc reporting only, i.e. what happened?<br />Time, Control<br />
    11. 11. [ Governance and data integrity ]<br />June 2010<br />© Datalicious Pty Ltd<br />11<br />Source: Omniture Summit, Matt Belkin, 2007<br />
    12. 12. © Datalicious Pty Ltd<br />[ Free off-site analytics tools ]<br />http://www.google.com/trends <br />http://www.google.com/sktool<br />http://www.google.com/insights/search<br />http://www.google.com/webmasters<br />http://www.google.com/adplanner<br />http://www.google.com/videotargeting<br />http://www.keywordspy.com<br />http://www.compete.com<br />http://www.alexa.com<br />http://wiki.kenburbary.com<br />June 2010<br />12<br />
    13. 13. [ Search at all stages ]<br />June 2010<br />© Datalicious Pty Ltd<br />13<br />In Australia Google has a market share of almost 90% of all searches, making it a very large and reliable data sample<br />Source: Inside the Mind of the Searcher, Enquiro 2004<br />
    14. 14. [ Search call to action for offline ]<br />June 2010<br />© Datalicious Pty Ltd<br />14<br />
    15. 15. [ Client side tracking process ]<br />June 2010<br />© Datalicious Pty Ltd<br />15<br />What if: Someone deletes their cookies? Or uses a device that does not support JavaScript? Or uses two computers (work vs. home)? Or two people use the same computer?<br />Source: Google Analytics, Justin Cutroni, 2007<br />
    16. 16. [ Tag-less data capture ]<br />June 2010<br />© Datalicious Pty Ltd<br />16<br />Google: “atomic labs” <br />www.atomiclabs.com<br />
    17. 17. The study examined data from two of the UK’s busiest ecommerce websites, ASDAand William Hill. <br />Given that more than half of all page impressions on these sites are from logged-in users, they provided a robust sample to compare IP-based and cookie-based analysis against.<br />The results were staggering, for example an IP-based approach overestimated visitors by up to 7.6 times whilst a cookie-based approach overestimated visitors by up to 2.3 times.<br />Google: ”red eye cookie report pdf” or http://bit.ly/cszp2o<br />[ Overestimation of unique visitors ]<br />June 2010<br />© Datalicious Pty Ltd<br />17<br />Source: White Paper, RedEye, 2007<br />
    18. 18. [ Maximise identification points ]<br />June 2010<br />© Datalicious Pty Ltd<br />18<br />Campaign response<br />Email subscription<br />Online purchase<br />Repeat purchase<br />Confirmation email<br />Email newsletter<br />Website login<br />Online bill payment<br />
    19. 19. June 2010<br />© Datalicious Pty Ltd<br />19<br />DataliciousSuperCookie<br />Persistent Flash cookie that cannot be deleted<br />
    20. 20. [ Mobile page headers ]<br />June 2010<br />© Datalicious Pty Ltd<br />20<br />MSISDN = Mobile Number<br />Source: Mobile Tracking, Omniture, 2008<br />
    21. 21. [ Single-sign on ]<br />June 2010<br />© Datalicious Pty Ltd<br />21<br />Facebook Connect gives your company the following data and more with just one click!<br />ID, first name, last name, middle name, picture, affiliations, last profile update, time zone, religion, political interests, interests, sex, birthday, attracted to which sex, why they want to meet someone, home town, relationship status, current location, activities, music interests, tv show interests, education history, work history, family and email <br />Need anything else?<br />
    22. 22. [ Research online, shop offline ]<br />June 2010<br />© Datalicious Pty Ltd<br />22<br />Google: ”digital future report 2009 pdf” or http://bit.ly/ZkLvr<br />Source: 2008 Digital Future Report, Surveying The Digital Future, Year Seven, USC Annenberg School<br />
    23. 23. [ Offline sales driven by online ]<br />June 2010<br />© Datalicious Pty Ltd<br />23<br />Tying offline conversions back to online campaign and research behavior using standard cookie technology by triggering virtual online order confirmation pages for offline sales using email receipts.<br />Credit Check Fulfilment<br />Phone Orders<br />Website.com Research<br />Virtual OrderConfirmation<br />@<br />Retail Orders<br />Credit Check Fulfilment<br />Website.com Research<br />Virtual OrderConfirmation<br />@<br />Advertising Campaign<br />Website.com Research<br />Online Orders<br />Credit Check Fulfilment<br />Online Order Confirmation<br />Virtual OrderConfirmation<br />@<br />Cookie<br />Cookie<br />Cookie<br />
    24. 24. [ Summary: Capturing data ]<br />Plenty of data sources and platforms<br />Especially search is great free data source<br />Maintaining data integrity takes effort<br />Cookie technology has its limitations<br />New tag-less technologies emerging<br />Maximise identification points<br />Offline can be tied to online<br />June 2010<br />© Datalicious Pty Ltd<br />24<br />
    25. 25. [ Generating insights ]<br />101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010<br />June 2010<br />© Datalicious Pty Ltd<br />25<br />
    26. 26. [ Corporate data journey ]<br />June 2010<br />© Datalicious Pty Ltd<br />26<br />Stage 1Data<br />Stage 2Insights<br />Stage 3Action<br />Data is fully owned in-house, advanced predictive modelling and trigger based marketing, i.e. what will happen and making it happen!<br />Sophistication<br />Data is being brought in-house, shift towards insights generation and data mining, i.e. why did it happen?<br />Third parties control most data, ad hoc reporting only, i.e. what happened?<br />Time, Control<br />
    27. 27. [ The ideal analyst ]<br />Business minded<br />Setting realistic improvement goals<br />Technically savvy<br />Bridging gap between business and IT<br />Strong sales skills<br />Raising awareness for the value of data<br />Seniority and experience<br />Needs to be taken serious across organisation<br />Position within hierarchy<br />Able to analyse without loyalty conflict <br />June 2010<br />© Datalicious Pty Ltd<br />27<br />
    28. 28. [ Process is key to success ]<br />June 2010<br />© Datalicious Pty Ltd<br />28<br />Source: Omniture Summit, Matt Belkin, 2007<br />
    29. 29. Website, call center and retail data<br />Quantitative and qualitative research data<br />[ Defining metrics frameworks ]<br />June 2010<br />© Datalicious Pty Ltd<br />29<br />Media and search data<br />Social media data<br />Social media<br />
    30. 30. [ Key metrics by website type ]<br />June 2010<br />© Datalicious Pty Ltd<br />30<br />Source: Omniture Summit, Matt Belkin, 2007<br />
    31. 31. [ Conversion funnel 1.0 ]<br />June 2010<br />Campaign responses<br />Conversion funnel<br />Product page, add to shopping cart, view shopping cart, cart checkout, payment details, shipping information, order confirmation, etc<br />Conversion event<br />© Datalicious Pty Ltd<br />31<br />
    32. 32. [ Conversion funnel 2.0 ]<br />June 2010<br />Campaign responses (inbound spokes)<br />Offline campaigns, banner ads, email marketing, referrals, organic search, paid search, internal promotions, etc<br />Landing page (hub)<br />Success events (outbound spokes)<br />Bounce rate, add to cart, cart checkout, confirmed order, call back request, registration, product comparison, product review, forward to friend, etc<br />© Datalicious Pty Ltd<br />32<br />
    33. 33. [ Additional success metrics ]<br />June 2010<br />© Datalicious Pty Ltd<br />33<br />Click Through<br />$<br />Click Through<br />Add To Cart<br />$<br />Cart Checkout<br />?<br />Click Through<br />Bounce Rate<br />$<br />Pages Per Visit<br />Video Views<br />Click Through<br />Call back requests<br />Store Searches<br />?<br />$<br />
    34. 34. June 2010<br />© Datalicious Pty Ltd<br />Exercise: Metrics framework<br />34<br />
    35. 35. [ Exercise: Metrics framework ]<br />June 2010<br />© Datalicious Pty Ltd<br />35<br />
    36. 36. [ Exercise: Metrics framework ]<br />June 2010<br />© Datalicious Pty Ltd<br />36<br />
    37. 37. Customer data<br />[ Combining data sets ]<br />June 2010<br />© Datalicious Pty Ltd<br />37<br />Web analytics data<br />+<br />The whole is greater than the sum of its parts<br />3rd party data<br />
    38. 38. [ Behaviours vs. transactions ]<br />June 2010<br />© Datalicious Pty Ltd<br />38<br />CRM Profile<br />Site Behaviour<br />one-off collection of demographical data age, gender, address, etc<br />customer lifecycle metrics and key datesprofitability, expiration, etc<br />predictive models based on data miningpropensity to buy, churn, etc<br />historical data from previous transactionsaverage order value, points, etc<br />tracking of purchase funnel stagebrowsing, checkout, etc<br />tracking of content preferencesproducts, brands, features, etc<br />tracking of external campaign responses<br />search terms, referrers, etc<br />tracking of internal promotion responses<br />emails, internal search, etc<br />+<br />Updated OCCASIONALLY<br />Updated continuously<br />
    39. 39. [ Store searches vs. actual locations ]<br />June 2010<br />© Datalicious Pty Ltd<br />39<br />
    40. 40. [ Enriching customer profiles ]<br />June 2010<br />© Datalicious Pty Ltd<br />40<br />All you need is an address<br />Source: Hitwise, 2006<br />
    41. 41. [Hitwise Mosaic segment swing ]<br />australia.com vs. newzealand.com<br />australia.com vs. bulafiji.com <br />June 2010<br />© Datalicious Pty Ltd<br />41<br />Source: Hitwise, 2006<br />
    42. 42. [Hitwise Mosaic segment swing ]<br />australia.com vs. newzealand.com<br />australia.com vs. newzealand.com<br />June 2010<br />© Datalicious Pty Ltd<br />42<br />Source: Hitwise, 2006<br />
    43. 43. [ Single source of truth ]<br />June 2010<br />© Datalicious Pty Ltd<br />43<br />Insights<br />Reporting<br />
    44. 44. [ De-duplication across channels ]<br />June 2010<br />© Datalicious Pty Ltd<br />44<br />Paid Search<br />$<br />Bid Mgmt<br />Central AnalyticsPlatform<br />Banner Ads<br />Ad Server<br />$<br />$<br />Email Blast<br />Email Platform<br />$<br />$<br />Organic Search<br />Google Analytics<br />$<br />$<br />
    45. 45. June 2010<br />© Datalicious Pty Ltd<br />Thinking outside the box<br />45<br />
    46. 46. [ Search and brand strength ]<br />June 2010<br />© Datalicious Pty Ltd<br />46<br />
    47. 47. [ Search and the product lifecycle ]<br />June 2010<br />© Datalicious Pty Ltd<br />47<br />Nokia N-Series<br />www.google.com/trends<br />Apple iPhone<br />
    48. 48. [ Search and media planning ]<br />June 2010<br />© Datalicious Pty Ltd<br />48<br />www.google.com/adplanner<br />
    49. 49. June 2010<br />© Datalicious Pty Ltd<br />49<br />
    50. 50. June 2010<br />© Datalicious Pty Ltd<br />50<br />
    51. 51. June 2010<br />© Datalicious Pty Ltd<br />51<br />Fiat 500: Online influencing offline<br />Google: “slideshare fiat 500 case study” or http://bit.ly/lh7bx<br />
    52. 52. [ Search driving offline creative ]<br />June 2010<br />© Datalicious Pty Ltd<br />52<br />
    53. 53. June 2010<br />© Datalicious Pty Ltd<br />53<br />
    54. 54. June 2010<br />© Datalicious Pty Ltd<br />54<br />Sentiment analysis: People vs. machine<br />Google: “people vs machines debate” or http://bit.ly/8VbtB<br />
    55. 55. [ Social metrics and tools ]<br />June 2010<br />© Datalicious Pty Ltd<br />55<br />Google: ”slidesharealtimeter report” or http://bit.ly/c8uYXT<br />Source: Social Marketing Analytics, Altimeter, 2010<br />
    56. 56. June 2010<br />© Datalicious Pty Ltd<br />Exercise: Statistical significance<br />56<br />
    57. 57. June 2010<br />© Datalicious Pty Ltd<br />57<br />How many survey responses do you need if you have 10,000 customers?<br />How many email opens do you need to test 2 subject linesif your subscriber base is 50,000?<br />How many orders do you need to test 6 banner executions if you serve 1,000,000 banners<br />
    58. 58. June 2010<br />© Datalicious Pty Ltd<br />58<br />How many survey responses do you need if you have 10,000 customers?<br />369 for each question or 369 complete responses<br />How many email opens do you need to test 2 subject linesif your subscriber base is 50,000?<br />381 per subject line or 381 x 2 = 762 email opens<br />How many orders do you need to test 6 banner executions if you serve 1,000,000 banners?<br />383 sales per banner execution or 383 x 6 = 2,298 sales<br />
    59. 59. [ Summary: Generating insights ]<br />Right resources and processes are key<br />Define a flexible metrics framework<br />Maintain framework to enable comparison<br />Combine data sets for hidden insights <br />Establish a single (data) source of truth<br />Think outside the box and across channels<br />Data does not equal significance<br />June 2010<br />© Datalicious Pty Ltd<br />59<br />
    60. 60. [ Taking action ]<br />101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010<br />June 2010<br />© Datalicious Pty Ltd<br />60<br />
    61. 61. [ How to drive ROI ]<br />Increasing revenue<br />Increasing overall amount of sales <br />Increasing the average revenue per sale<br />Reducing costs<br />Increasing media effectiveness<br />Increasing website conversion rates<br />Increasing online self-service usage<br />Improving customer experience<br />Reducing steps necessary to complete a task<br />Perceived value or quality of the final solution<br />June 2010<br />© Datalicious Pty Ltd<br />61<br />
    62. 62. [ How to drive ROI ]<br />June 2010<br />© Datalicious Pty Ltd<br />62<br />Media or how to optimise the channel mix<br />Targeting or how to increasing relevance<br />Testing or how to maximise conversion<br />
    63. 63. [ Success attribution models ]<br />Banner Ad<br />Paid Search<br />OrganicSearch$100<br />Success<br />$100<br />Last channel gets all credit<br />Banner Ad$100<br />Email Blast<br />Success$100<br />First channel gets all credit<br />Paid Search<br />Paid Search$100<br />Banner Ad$100<br />Affiliate Referral$100<br />Success$100<br />All channels get equal credit<br />Print Ad$33<br />Social Media$33<br />Paid Search$33<br />Success$100<br />All channels get partial credit<br />June 2010<br />63<br />© Datalicious Pty Ltd<br />
    64. 64. [ First vs. last click attribution ]<br />June 2010<br />© Datalicious Pty Ltd<br />64<br />Chart shows percentage of channel touch points that lead to a conversion.<br />Paid/Organic Search<br />Neither first nor last-click measurementwould provide true picture <br />Emails/Shopping Engines<br />
    65. 65. [ Path to purchase ]<br />Banner Click<br />SEM Generic<br />PartnerSite<br />Direct Visit<br />$<br />Banner View<br />June 2010<br />65<br />© Datalicious Pty Ltd<br />SEO Generic<br />$<br />TVAd<br />SEOBranded<br />Banner Click<br />$<br />Print Ad<br />Social Media<br />Email Update<br />Direct Visit<br />$<br />
    66. 66. [ Forrester media attribution ]<br />June 2010<br />© Datalicious Pty Ltd<br />66<br />Google: ”forrester attribution framework pdf” or http://bit.ly/dnbnzY<br />Source: Forrester, 2009<br />
    67. 67. [ Customer data journey ]<br />June 2010<br />© Datalicious Pty Ltd<br />67<br />To retention messages<br />To transactional data<br />From suspect to<br />To customer<br />prospect<br />Time<br />Time<br />From behavioural data<br />From awareness messages<br />
    68. 68. June 2010<br />© Datalicious Pty Ltd<br />68<br />
    69. 69. June 2010<br />© Datalicious Pty Ltd<br />69<br />
    70. 70. [ Matching segments are key ]<br />June 2010<br />© Datalicious Pty Ltd<br />70<br />On and off-site targeting platforms should use identical triggers to sort visitors into segments<br />
    71. 71. [ Off-site targeting platforms ]<br />Ad servers<br />Google/DoubleClick<br />Eyeblaster<br />Faciliate<br />Atlas<br />Etc<br />Ad Networks<br />Google<br />Yahoo<br />ValueClick<br />Adconian<br />Etc<br />June 2010<br />© Datalicious Pty Ltd<br />71<br />http://en.wikipedia.org/wiki/Contextual_advertising, http://hubpages.com/hub/101-Google-Adsense-Alternatives, http://en.wikipedia.org/wiki/Central_ad_server, http://www.adoperationsonline.com/2008/05/23/list-of-ad-servers/, <br />http://lists.econsultant.com/top-10-advertising-networks.html, http://www.clickz.com/3633599, http://en.wikipedia.org/wiki/behavioural_targeting<br />
    72. 72. [ On-site targeting platforms ]<br />Test&Target (Omniture, Offermatica, TouchClarity)<br />Memetrics (Accenture)<br />Optimost (Autonomy)<br />Kefta (Acxiom)<br />AudienceScience<br />Maxymiser<br />Amadesa<br />Certona<br />SiteSpect<br />BTBuckets (free)<br />Google/DoubleClick Ad Server (free)<br />June 2010<br />© Datalicious Pty Ltd<br />72<br />
    73. 73. [ Prospect targeting parameters ]<br />June 2010<br />© Datalicious Pty Ltd<br />73<br />
    74. 74. [ Vodafone affinity targeting ]<br />June 2010<br />© Datalicious Pty Ltd<br />74<br />Different type of visitors respond to different ads. By using category affinity targeting, response rates are lifted significantly across products.<br />
    75. 75. [ Affinity targeting ]<br />Function of behavioural targeting<br />Grouping of visitors into major segments<br />Based on content and conversion behaviour<br />Ease of use vs. reduced targeting ability<br />Most common affinities used<br />Brand affinity<br />Image preference<br />Price sensitivity<br />Product affinity<br />Content affinity<br />June 2010<br />© Datalicious Pty Ltd<br />75<br />
    76. 76. [ Coordinate the experience ]<br />June 2010<br />© Datalicious Pty Ltd<br />76<br />By coordinating the consumer’s end-to-end experience, companies could enjoy revenue increases of 10-20%.<br />Google: “get more value from digital marketing” or http://bit.ly/cAtSUN<br />Source: McKinsey Quarterly, 2010<br />
    77. 77. AvinashKaushik: “The principle of garbage in, garbage out applies here. […] what makes a behaviour targeting platform tick, and produce results, is not its intelligence, it is your ability to actually feed it the right content which it can then target […]. You feed your BT system crap and it will quickly and efficiently target crap to your customers. Faster then you could ever have yourself.”<br />[ Quality content is key ]<br />June 2010<br />© Datalicious Pty Ltd<br />77<br />
    78. 78. June 2010<br />© Datalicious Pty Ltd<br />Exercise: Targeting matrix<br />78<br />
    79. 79. [ Exercise: Targeting matrix ]<br />June 2010<br />© Datalicious Pty Ltd<br />79<br />
    80. 80. [ Exercise: Targeting matrix ]<br />June 2010<br />© Datalicious Pty Ltd<br />80<br />
    81. 81. Google: “change one word double conversion” or http://bit.ly/bpyqFp<br />[ClickTale testing case study ]<br />June 2010<br />© Datalicious Pty Ltd<br />81<br />
    82. 82. [ Testing platforms ]<br />Test&Target (Omniture, Offermatica, TouchClarity)<br />Memetrics (Accenture)<br />Optimost (Autonomy)<br />Kefta (Acxiom)<br />Maxymiser<br />Amadesa<br />SiteSpect<br />ClickTale (cheap)<br />Unbounce (cheap)<br />Google Website Optimiser (free)<br />June 2010<br />© Datalicious Pty Ltd<br />82<br />
    83. 83. [ Summary ]<br />There is no magic formula for ROI<br />Focus on the entire conversion funnel<br />Media attribution is hard but necessary<br />Neither first nor last click method works<br />Create a coordinated targeted experience<br />Content is always king no matter what<br />Test, learn and refine continuously<br />June 2010<br />© Datalicious Pty Ltd<br />83<br />
    84. 84. June 2010<br />© Datalicious Pty Ltd<br />84<br />Contact mecbartens@datalicious.com<br />Learn moreblog.datalicious.com<br />Follow ustwitter.com/datalicious<br />

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