> Marketing Data Strategy <<br />Smart data driven marketing<br />
> Short but sharp history<br /><ul><li>Datalicious was founded late 2007
Strong Omniture web analytics history
Now 360 data agency with specialist team
Combination of analysts and developers
Carefully selected best of breed partners
Driving industry best practice (ADMA)
Turning data into actionable insights
Executing smart data driven campaigns</li></ul>May 2011<br />© Datalicious Pty Ltd<br />2<br />
> Smart data driven marketing<br />May 2011<br />© Datalicious Pty Ltd<br />3<br />Media Attribution & ModelingOptimise ch...
> Wide range of data services<br />May 2011<br />© Datalicious Pty Ltd<br />4<br />Insights<br />Analytics<br />Data minin...
> Clients across all industries<br />May 2011<br />© Datalicious Pty Ltd<br />5<br />
> Data driven marketing<br />What is data driven marketing?<br />Self assessment: Your capabilities <br />Strategies for e...
May 2011<br />© Datalicious Pty Ltd<br />7<br />Clive Humby: Data is the new oil<br />
> Major data categories<br />May 2011<br />© Datalicious Pty Ltd<br />8<br />Campaign dataTV, print, call center, search, ...
>Corporate data journey <br />May 2011<br />© Datalicious Pty Ltd<br />9<br />Stage 1Data<br />Stage 2Insights<br />Stage ...
May 2011<br />© Datalicious Pty Ltd<br />10<br />
May 2011<br />© Datalicious Pty Ltd<br />11<br />Oil and data come at a price<br />
> Google Ngram: Privacy <br />May 2011<br />© Datalicious Pty Ltd<br />12<br />
May 2011<br />© Datalicious Pty Ltd<br />Collecting data for the sake of itor to add valueto customers?<br />13<br />
> Privacy vs. data benefits policy<br /><ul><li>Do not hide behind small print
Use plain English in your privacy policy
Explain exactly what data you are recording
Explain why you are recording the data
Explain the benefits for the consumer
Provide opt-out and feedback options
Make opt-outs a KPI not just opt-ins</li></ul>= Data benefits and privacy policy<br />May 2011<br />© Datalicious Pty Ltd<...
Exercise: Marketing mix<br />May 2011<br />© Datalicious Pty Ltd<br />15<br />
Targeting<br />The right message<br />Via the right channel<br />To the right person<br />At the right time<br />May 2011<...
> Increase revenue by 10-20% <br />May 2011<br />© Datalicious Pty Ltd<br />18<br />
> New consumer decision journey<br />May 2011<br />© Datalicious Pty Ltd<br />19<br />The consumer decision process is cha...
> New consumer decision journey<br />May 2011<br />© Datalicious Pty Ltd<br />20<br />The consumer decision process is cha...
May 2011<br />© Datalicious Pty Ltd<br />21<br />
> Coordination across channels   <br />May 2011<br />© Datalicious Pty Ltd<br />22<br />TV, radio, print, outdoor, search ...
> Combining targeting platforms <br />May 2011<br />© Datalicious Pty Ltd<br />23<br />
November 2010<br />© Datalicious Pty Ltd<br />24<br />
November 2010<br />© Datalicious Pty Ltd<br />25<br />Take a closer look at our cash flow solutions<br />
> Affinity re-targeting in action<br />May 2011<br />© Datalicious Pty Ltd<br />26<br />Different type of visitors respond...
> Ad-sequencing in action<br />May 2011<br />© Datalicious Pty Ltd<br />27<br />Marketing is about telling stories and sto...
> Prospect targeting parameters <br />May 2011<br />© Datalicious Pty Ltd<br />28<br />
November 2010<br />© Datalicious Pty Ltd<br />29<br />
> Sample site visitor composition <br />May 2011<br />© Datalicious Pty Ltd<br />30<br />30% new visitors with no previous...
> Search call to action for offline <br />May 2011<br />© Datalicious Pty Ltd<br />31<br />
May 2011<br />© Datalicious Pty Ltd<br />32<br />
> PURLs boosting DM response rates<br />May 2011<br />© Datalicious Pty Ltd<br />33<br />Text<br />
> Unique phone numbers<br /><ul><li>1 unique phone number
Phone number is considered part of the brand
Media origin of calls cannot be established
Added value of website interaction unknown
2-10 unique phone numbers
Different numbers for different media channels
Exclusive number(s) reserved for website use
Call origin data more granular but not perfect
Difficult to rotate and pause numbers</li></ul>May 2011<br />© Datalicious Pty Ltd<br />34<br />
> Unique phone numbers<br /><ul><li>10+ unique phone numbers
Different numbers for different media channels
Different numbers for different product categories
Different numbers for different conversion steps
Call origin becoming useful to shape call script
Feasible to pause numbers to improve integrity
100+ unique phone numbers
Different numbers for different website visitors
Call origin and time stamp enable individual match
Call conversions matched back to search terms</li></ul>May 2011<br />© Datalicious Pty Ltd<br />35<br />
> Jet Interactive phone call data<br />May 2011<br />© Datalicious Pty Ltd<br />36<br />
> Potential calls to action <br /><ul><li>Unique click-through URLs
Unique vanity domains or URLs
Unique phone numbers
Unique search terms
Unique email addresses
Unique personal URLs (PURLs)
Unique SMS numbers, QR codes
Unique promotional codes, vouchers
Geographic location (Facebook, FourSquare)
Plus regression analysis of cause and effect</li></ul>May 2011<br />© Datalicious Pty Ltd<br />37<br />Calls to action can...
> The consumer data journey <br />May 2011<br />© Datalicious Pty Ltd<br />38<br />To retention messages<br />To transacti...
Campaign response data<br />> Combining data sources<br />May 2011<br />© Datalicious Pty Ltd<br />39<br />Website behavio...
> Transactions plus behaviours<br />May 2011<br />© Datalicious Pty Ltd<br />40<br />CRM Profile<br />Site Behaviour<br />...
> Customer profiling in action <br />May 2011<br />© Datalicious Pty Ltd<br />41<br />Using website and email responses to...
> Online form best practice<br />May 2011<br />© Datalicious Pty Ltd<br />42<br />Maximise data integrity<br />Age vs. yea...
Exercise: Enriching profiles<br />May 2011<br />© Datalicious Pty Ltd<br />43<br />
> Exercise: Enriching profiles<br />May 2011<br />© Datalicious Pty Ltd<br />44<br />CRM Profile<br />Site Behaviour<br />...
Exercise: Customer IDs<br />May 2011<br />© Datalicious Pty Ltd<br />45<br />
>Exercise: Customer IDs<br />May 2011<br />© Datalicious Pty Ltd<br />46<br />To retention messages<br />To transactional ...
Geo-demographic data<br />> Enhancing data sources<br />May 2011<br />© Datalicious Pty Ltd<br />47<br />Customer profile ...
> Geo-demographic segments<br />May 2011<br />© Datalicious Pty Ltd<br />48<br />
May 2011<br />© Datalicious Pty Ltd<br />49<br />
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  • ProsConsumers multi-taskIncreased recollection levelsAbility to track offline channelsConsPaid search competitionDifficult to get natural rankings
  • Transcript of "ADMA Marketing Data Strategy Workshop"

    1. 1. > Marketing Data Strategy <<br />Smart data driven marketing<br />
    2. 2. > Short but sharp history<br /><ul><li>Datalicious was founded late 2007
    3. 3. Strong Omniture web analytics history
    4. 4. Now 360 data agency with specialist team
    5. 5. Combination of analysts and developers
    6. 6. Carefully selected best of breed partners
    7. 7. Driving industry best practice (ADMA)
    8. 8. Turning data into actionable insights
    9. 9. Executing smart data driven campaigns</li></ul>May 2011<br />© Datalicious Pty Ltd<br />2<br />
    10. 10. > Smart data driven marketing<br />May 2011<br />© Datalicious Pty Ltd<br />3<br />Media Attribution & ModelingOptimise channel mix, predict sales<br />Targeted Direct Marketing Increase relevance, reduce churn<br />Testing & OptimisationRemove barriers, drive sales<br />Boost ROAS<br />
    11. 11. > Wide range of data services<br />May 2011<br />© Datalicious Pty Ltd<br />4<br />Insights<br />Analytics<br />Data mining and modelling<br />Customised dashboards<br />Tableau, Spotfire, SPSS, etc<br />Media attribution models<br />Market and competitor trends<br />Social media monitoring<br />Customer profiling<br />Action<br />Campaigns<br />Data usage and application<br />Marketing automation<br />Alterian, SiteCore, 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 />Tag-less online data capture<br />End-to-end data platforms<br />IVR and call center reporting<br />Single customer view<br />
    12. 12. > Clients across all industries<br />May 2011<br />© Datalicious Pty Ltd<br />5<br />
    13. 13. > Data driven marketing<br />What is data driven marketing?<br />Self assessment: Your capabilities <br />Strategies for effective data collection<br />Campaign development and data integrity<br />Effective multi-channel campaign execution<br />Analysis and performance measurement<br />In-sourcing or outsourcing<br />May 2011<br />© Datalicious Pty Ltd<br />6<br />
    14. 14. May 2011<br />© Datalicious Pty Ltd<br />7<br />Clive Humby: Data is the new oil<br />
    15. 15. > Major data categories<br />May 2011<br />© Datalicious Pty Ltd<br />8<br />Campaign dataTV, print, call center, search, web analytics, ad serving, etc<br />Customer data<br />Direct mail, call center, web analytics, emails, surveys, etc<br />Consumer data<br />Geo-demographics, search, social, 3rd party research, etc<br />Competitor data<br />Search, social, ad spend, 3rd party research, news, etc <br />Campaigns<br />Customers<br />Competitors<br />Consumers<br />
    16. 16. >Corporate data journey <br />May 2011<br />© Datalicious Pty Ltd<br />9<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 />
    17. 17. May 2011<br />© Datalicious Pty Ltd<br />10<br />
    18. 18. May 2011<br />© Datalicious Pty Ltd<br />11<br />Oil and data come at a price<br />
    19. 19. > Google Ngram: Privacy <br />May 2011<br />© Datalicious Pty Ltd<br />12<br />
    20. 20. May 2011<br />© Datalicious Pty Ltd<br />Collecting data for the sake of itor to add valueto customers?<br />13<br />
    21. 21. > Privacy vs. data benefits policy<br /><ul><li>Do not hide behind small print
    22. 22. Use plain English in your privacy policy
    23. 23. Explain exactly what data you are recording
    24. 24. Explain why you are recording the data
    25. 25. Explain the benefits for the consumer
    26. 26. Provide opt-out and feedback options
    27. 27. Make opt-outs a KPI not just opt-ins</li></ul>= Data benefits and privacy policy<br />May 2011<br />© Datalicious Pty Ltd<br />14<br />
    28. 28. Exercise: Marketing mix<br />May 2011<br />© Datalicious Pty Ltd<br />15<br />
    29. 29.
    30. 30. Targeting<br />The right message<br />Via the right channel<br />To the right person<br />At the right time<br />May 2011<br />© Datalicious Pty Ltd<br />17<br />
    31. 31. > Increase revenue by 10-20% <br />May 2011<br />© Datalicious Pty Ltd<br />18<br />
    32. 32. > New consumer decision journey<br />May 2011<br />© Datalicious Pty Ltd<br />19<br />The consumer decision process is changing from linearto circular.<br />
    33. 33. > New consumer decision journey<br />May 2011<br />© Datalicious Pty Ltd<br />20<br />The consumer decision process is changing from linear to circular.<br />Online research <br />Change increases the importance of experience during research phase.<br />
    34. 34. May 2011<br />© Datalicious Pty Ltd<br />21<br />
    35. 35. > Coordination across channels <br />May 2011<br />© Datalicious Pty Ltd<br />22<br />TV, radio, print, outdoor, search marketing, display ads, performance networks, affiliates, social media, etc<br />Retail stores, in-store kiosks, call centers, brochures, websites, mobile apps, online chat, social media, etc<br />Outbound calls, direct mail, emails, social media, SMS, mobile apps, etc<br />
    36. 36. > Combining targeting platforms <br />May 2011<br />© Datalicious Pty Ltd<br />23<br />
    37. 37. November 2010<br />© Datalicious Pty Ltd<br />24<br />
    38. 38. November 2010<br />© Datalicious Pty Ltd<br />25<br />Take a closer look at our cash flow solutions<br />
    39. 39. > Affinity re-targeting in action<br />May 2011<br />© Datalicious Pty Ltd<br />26<br />Different type of visitors respond to different ads. By using category affinity targeting, response rates are lifted significantly across products.<br />Google: “vodafone omniture case study”or http://bit.ly/de70b7<br />
    40. 40. > Ad-sequencing in action<br />May 2011<br />© Datalicious Pty Ltd<br />27<br />Marketing is about telling stories and stories are not static but evolve over time<br />Ad-sequencing can help to evolve stories over time the more users engage with ads<br />
    41. 41. > Prospect targeting parameters <br />May 2011<br />© Datalicious Pty Ltd<br />28<br />
    42. 42. November 2010<br />© Datalicious Pty Ltd<br />29<br />
    43. 43. > Sample site visitor composition <br />May 2011<br />© Datalicious Pty Ltd<br />30<br />30% new visitors with no previous website history aside from campaign or referrer data of which maybe 50% is useful<br />30% repeat visitors with referral data and some website history allowing 50% to be segmented by content affinity<br />10% serious prospects with limited profile data<br />30% existing customers with extensive profile including transactional history of which maybe 50% can actually be identified as individuals <br />
    44. 44. > Search call to action for offline <br />May 2011<br />© Datalicious Pty Ltd<br />31<br />
    45. 45. May 2011<br />© Datalicious Pty Ltd<br />32<br />
    46. 46. > PURLs boosting DM response rates<br />May 2011<br />© Datalicious Pty Ltd<br />33<br />Text<br />
    47. 47. > Unique phone numbers<br /><ul><li>1 unique phone number
    48. 48. Phone number is considered part of the brand
    49. 49. Media origin of calls cannot be established
    50. 50. Added value of website interaction unknown
    51. 51. 2-10 unique phone numbers
    52. 52. Different numbers for different media channels
    53. 53. Exclusive number(s) reserved for website use
    54. 54. Call origin data more granular but not perfect
    55. 55. Difficult to rotate and pause numbers</li></ul>May 2011<br />© Datalicious Pty Ltd<br />34<br />
    56. 56. > Unique phone numbers<br /><ul><li>10+ unique phone numbers
    57. 57. Different numbers for different media channels
    58. 58. Different numbers for different product categories
    59. 59. Different numbers for different conversion steps
    60. 60. Call origin becoming useful to shape call script
    61. 61. Feasible to pause numbers to improve integrity
    62. 62. 100+ unique phone numbers
    63. 63. Different numbers for different website visitors
    64. 64. Call origin and time stamp enable individual match
    65. 65. Call conversions matched back to search terms</li></ul>May 2011<br />© Datalicious Pty Ltd<br />35<br />
    66. 66. > Jet Interactive phone call data<br />May 2011<br />© Datalicious Pty Ltd<br />36<br />
    67. 67. > Potential calls to action <br /><ul><li>Unique click-through URLs
    68. 68. Unique vanity domains or URLs
    69. 69. Unique phone numbers
    70. 70. Unique search terms
    71. 71. Unique email addresses
    72. 72. Unique personal URLs (PURLs)
    73. 73. Unique SMS numbers, QR codes
    74. 74. Unique promotional codes, vouchers
    75. 75. Geographic location (Facebook, FourSquare)
    76. 76. Plus regression analysis of cause and effect</li></ul>May 2011<br />© Datalicious Pty Ltd<br />37<br />Calls to action can help shape the customer experience not just evaluate responses<br />
    77. 77. > The consumer data journey <br />May 2011<br />© Datalicious Pty Ltd<br />38<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 />
    78. 78. Campaign response data<br />> Combining data sources<br />May 2011<br />© Datalicious Pty Ltd<br />39<br />Website behavioural data<br />+<br />The whole is greater than the sum of its parts<br />Customer profile data<br />
    79. 79. > Transactions plus behaviours<br />May 2011<br />© Datalicious Pty Ltd<br />40<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 />
    80. 80. > Customer profiling in action <br />May 2011<br />© Datalicious Pty Ltd<br />41<br />Using website and email responses to learn a little bite more about subscribers at every <br />touch point to keep<br /> refining profiles<br />and messages.<br />
    81. 81. > Online form best practice<br />May 2011<br />© Datalicious Pty Ltd<br />42<br />Maximise data integrity<br />Age vs. year of birth<br />Free text vs. options<br />Use auto-complete <br />wherever possible<br />
    82. 82. Exercise: Enriching profiles<br />May 2011<br />© Datalicious Pty Ltd<br />43<br />
    83. 83. > Exercise: Enriching profiles<br />May 2011<br />© Datalicious Pty Ltd<br />44<br />CRM Profile<br />Site Behaviour<br />+<br />?<br />?<br />
    84. 84. Exercise: Customer IDs<br />May 2011<br />© Datalicious Pty Ltd<br />45<br />
    85. 85. >Exercise: Customer IDs<br />May 2011<br />© Datalicious Pty Ltd<br />46<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 />
    86. 86. Geo-demographic data<br />> Enhancing data sources<br />May 2011<br />© Datalicious Pty Ltd<br />47<br />Customer profile data<br />+<br />The whole is greater than the sum of its parts<br />3rd party data<br />
    87. 87. > Geo-demographic segments<br />May 2011<br />© Datalicious Pty Ltd<br />48<br />
    88. 88. May 2011<br />© Datalicious Pty Ltd<br />49<br />
    89. 89. May 2011<br />© Datalicious Pty Ltd<br />50<br />Event sponsor presentation<br />
    90. 90. transcape<br />data solutions<br />
    91. 91. Magazine Subscribers<br />Mail Order Catalog Buyers<br />E-commerce customers<br />
    92. 92. transcape<br />Buyer File <br />1<br />Buyer File <br />2<br />Buyer File <br />7<br />Buyer File <br />3<br />Buyer File <br />6<br />Buyer File <br />4<br />Buyer File <br />5<br />"IMP have been working with Alliance Data ever since they launched and have using their Australian & NZ datawith great success across a range of products"<br />Victoria Coleman<br />Media Manager<br />International Masters Publishers<br />
    93. 93. transcape<br />Selectable by:<br />Recency<br />Money<br />Frequency<br />
    94. 94. transcape<br />Gender<br />Age<br />Income<br />Selectable by:<br />Female<br />Male<br />
    95. 95. RFM Segmentation (house file)<br />0-6 mo.<br />7-12 mo.<br />13-24 mo.<br />25-36 mo.<br />37mo.+<br /><$10<br />0.10%<br />1.20%<br />0.30%<br />0.50%<br />0.70%<br />$10-$24<br />1.50%<br />0.90%<br />0.70%<br />0.40%<br />0.20%<br />$25-$49<br />1.80%<br />1.20%<br />1.00%<br />0.50%<br />0.30%<br />$50-$99<br />2.00%<br />1.70%<br />1.20%<br />0.80%<br />0.40%<br />2.50%<br />2.10%<br />1.50%<br />1.10%<br />0.50%<br />$100-$249<br />$250+<br />3.00%+<br />2.20%<br />2.00%<br />1.40%<br />0.70%<br />450,000 Buyers<br />50,000 Buyers<br />
    96. 96. Last bought from YOU<br />25-36 mo., $25-$49<br />Response Rate = 0.50%<br />transcape<br />35,000 matches<br />50,000 Buyers<br />1 .4 million names<br />
    97. 97. 0.50%<br />0.90%<br />Response Rate =<br />Last bought from you<br />25-36 mo., $25-$49<br />50,000<br />35,000<br />20,000<br />Universe =<br />Have also bought elsewhere<br />1x<br />2x<br />3x<br />1+<br />Frequency =<br />Recency<br />Value<br />0-12 mo.<br />25+ mo.<br />12-24 mo.<br />0.30%<br /><$25<br />0.10%<br />0.50%<br />$25-49<br />0.70%<br />0.50%<br />0.30%<br />0.70%<br />0.90%<br />$50-$99<br />0.50%<br />$100+<br />0.90%<br />1.10%<br />0.70%<br />Further optimise your house file segments<br />
    98. 98. Transactional Data<br />Demographic Data<br />Geographic Data<br />
    99. 99.
    100. 100. transcape<br />data solutions<br />Thank you!<br />
    101. 101. Exercise: Targeting matrix<br />May 2011<br />© Datalicious Pty Ltd<br />62<br />
    102. 102. > Exercise: Targeting matrix<br />May 2011<br />© Datalicious Pty Ltd<br />63<br />
    103. 103. > Exercise: Targeting matrix<br />May 2011<br />© Datalicious Pty Ltd<br />64<br />
    104. 104. May 2011<br />© Datalicious Pty Ltd<br />65<br />
    105. 105. May 2011<br />© Datalicious Pty Ltd<br />66<br />
    106. 106. May 2011<br />© Datalicious Pty Ltd<br />67<br />
    107. 107. May 2011<br />© Datalicious Pty Ltd<br />68<br />
    108. 108. Exercise: Marketing automation<br />May 2011<br />© Datalicious Pty Ltd<br />69<br />
    109. 109. May 2011<br />© Datalicious Pty Ltd<br />70<br />
    110. 110. > Quality content is key<br />Avinash Kaushik: “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 />May 2011<br />© Datalicious Pty Ltd<br />71<br />
    111. 111. Plan to fail …<br />May 2011<br />© Datalicious Pty Ltd<br />72<br />
    112. 112. > Develop a testing matrix<br />May 2011<br />© Datalicious Pty Ltd<br />73<br />
    113. 113. > Develop a testing matrix<br />May 2011<br />© Datalicious Pty Ltd<br />74<br />
    114. 114. > AIDA and AIDAS formulas <br />May 2011<br />© Datalicious Pty Ltd<br />75<br />Old media<br />New media<br />Social media<br />
    115. 115. > Simplified AIDAS funnel <br />May 2011<br />© Datalicious Pty Ltd<br />76<br />
    116. 116. > Marketing is about people <br />May 2011<br />© Datalicious Pty Ltd<br />77<br />40%<br />10%<br />1%<br />
    117. 117. > Additional funnel breakdowns <br />May 2011<br />© Datalicious Pty Ltd<br />78<br />Brand vs. direct response campaign<br />40%<br />10%<br />1%<br />New prospects vs. existing customers<br />
    118. 118. May 2011<br />© Datalicious Pty Ltd<br />79<br />New vs. returning visitors<br />
    119. 119. May 2011<br />© Datalicious Pty Ltd<br />80<br />AU/NZ vs. rest of world<br />
    120. 120. > Potential funnel breakdowns <br /><ul><li>Brand vs. direct response campaign
    121. 121. New prospects vs. existing customers
    122. 122. Baseline vs. incremental conversions
    123. 123. Competitive activity, i.e. none, a lot, etc
    124. 124. Segments, i.e. age, location, influence, etc
    125. 125. Channels, i.e. search, display, social, etc
    126. 126. Campaigns, i.e. this/last week, month, year, etc
    127. 127. Products and brands, i.e. iphone, htc, etc
    128. 128. Offers, i.e. free minutes, free handset, etc
    129. 129. Devices, i.e. home, office, mobile, tablet, etc</li></ul>May 2011<br />© Datalicious Pty Ltd<br />81<br />
    130. 130. > Developing a metrics framework <br />May 2011<br />© Datalicious Pty Ltd<br />82<br />
    131. 131. > Developing a metrics framework <br />May 2011<br />© Datalicious Pty Ltd<br />83<br />
    132. 132. > Establishing a baseline<br />May 2011<br />© Datalicious Pty Ltd<br />84<br />Switch all advertising off for a period of time (unlikely) or establish a smaller control group that is representative of the entire population (i.e. search term, geography, etc) and switch off selected channels one at a time to minimise impact on overall conversions.<br />
    133. 133. > Importance of calendar events <br />May 2011<br />© Datalicious Pty Ltd<br />85<br />Traffic spikes or other data anomalies without context are very hard to interpret and can render data useless<br />
    134. 134. >Out-sourcing or in-sourcing?<br />May 2011<br />© Datalicious Pty Ltd<br />86<br />Year 1Platforms<br />Year 2Training<br />Year 3Support<br />Reduce vendor reliance to absolute minimum but consider the value of support agreements for both maintenance as well as updates on market innovations and new features.<br />Degree of in-house control and sophistication<br />Start taking control of technology and data, shift vendor focus to enhancements and the provision of training <br />for internal resources<br />Engage third parties with more experience to get started and to implement technology<br />Time, Control<br />
    135. 135. May 2011<br />© Datalicious Pty Ltd<br />87<br />Contact mecbartens@datalicious.com<br />Learn moreblog.datalicious.com<br />Follow metwitter.com/datalicious<br />
    136. 136. Data > Insights > Action<br />

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