Smart Marketing
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The presentation illustrates the concepts, principles and significance of data driven marketing.
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Smart Marketing
- 1. > Smart Marke+ng < Smart data driven marke-ng
- 2. > Short but sharp history § Datalicious was founded late 2007 § Strong Omniture web analy-cs history § Now 360 data agency with specialist team § Combina-on of analysts and developers § Carefully selected best of breed partners § Evangelizing smart data driven marke-ng § Making data accessible and ac-onable § Driving industry best prac-ce (ADMA) March 2011 © Datalicious Pty Ltd 2
- 3. > Clients across all industries March 2011 © Datalicious Pty Ltd 3
- 4. > Wide range of data services Data Insights Ac+on Pla@orms Repor+ng Applica+ons Data collec+on and processing Data mining and modelling Data usage and applica+on Web analy+cs solu+ons Customised dashboards Marke+ng automa+on Omniture, Google Analy+cs, etc Media aLribu+on models Alterian, Trac+on, Inxmail, etc Tag-‐less online data capture Market and compe+tor trends Targe+ng and merchandising End-‐to-‐end data pla@orms Social media monitoring Internal search op+misa+on IVR and call center repor+ng Online surveys and polls CRM strategy and execu+on Single customer view Customer profiling Tes+ng programs March 2011 © Datalicious Pty Ltd 4
- 5. > Smart data driven marke+ng Metrics Framework Metrics Framework Media ALribu+on Benchmarking and trending Benchmarking and trending Op+mise channel mix Targe+ng Increase relevance Tes+ng Improve usability $$$ March 2011 © Datalicious Pty Ltd 5
- 6. 101011010010010010101111010010010101010100001011111001010101 010100101011001100010100101001101101001101001010100111001010 010010101001001010010100100101001111101010100101001001001010 > Metrics framework March 2011 © Datalicious Pty Ltd 6
- 7. > AIDA and AIDAS formulas Old media New media Awareness Interest Desire Ac+on Sa+sfac+on Social media March 2011 © Datalicious Pty Ltd 7
- 8. > Simplified AIDAS funnel Reach Engagement Conversion +Buzz (Awareness) (Interest & Desire) (Ac-on) (Sa-sfac-on) March 2011 © Datalicious Pty Ltd 8
- 9. > Marke+ng is about people People People People People reached 40% engaged 10% converted 1% delighted March 2011 © Datalicious Pty Ltd 9
- 10. > Addi+onal funnel breakdowns Brand vs. direct response campaign People People People People reached 40% engaged 10% converted 1% delighted New prospects vs. exis-ng customers March 2011 © Datalicious Pty Ltd 10
- 11. AU/NZ vs. rest of world
- 12. > Importance of calendar events Traffic spikes or other data anomalies without context are very hard to interpret and can render data useless March 2011 © Datalicious Pty Ltd 12
- 13. Calendar events to add context March 2011 © Datalicious Pty Ltd 13
- 14. > Addi+onal success metrics Click Through $ Click Add To Cart Through Cart Checkout ? $ Click Page Page Product Through Bounce Views Views $ Click Call back Store Through request Search ? $ March 2011 © Datalicious Pty Ltd 14
- 15. > Exercise: Metrics framework Level Reach Engagement Conversion +Buzz Level 1, people Level 2, strategic Level 3, tac+cal Funnel breakdowns March 2011 © Datalicious Pty Ltd 15
- 16. > Single source of truth repor+ng Insights Repor+ng March 2011 © Datalicious Pty Ltd 16
- 17. > Manual repor+ng s+ll prevails March 2011 © Datalicious Pty Ltd 17
- 18. 101011010010010010101111010010010101010100001011111001010101 010100101011001100010100101001101101001101001010100111001010 010010101001001010010100100101001111101010100101001001001010 > Media aLribu+on March 2011 © Datalicious Pty Ltd 18
- 19. > Complex campaign flows = Paid media Organic PR, WOM, search events, etc = Viral elements = Sales channels YouTube, Home pages, Paid TV, print, blog, etc portals, etc search radio, etc Direct mail, Landing pages, Display ads, email, etc offers, etc affiliates, etc CRM Facebook program TwiLer, etc POS kiosks, Call center, loyalty cards, etc retail stores, etc March 2011 © Datalicious Pty Ltd 19
- 20. > Duplica+on across channels Paid Bid Search Mgmt $ Banner Ad Ads Server $ Email Email Blast Pla@orm $ Organic Web Search Analy+cs $ March 2011 © Datalicious Pty Ltd 20
- 21. > Cookie expira+on impact Paid Bid Search Mgmt $ Banner Banner Ad Ad Click Ad View Server $ Email Email Expira+on Blast Pla@orm $ Organic Google Search Analy+cs $ March 2011 © Datalicious Pty Ltd 21
- 22. > De-‐duplica+on across channels Paid Search $ Banner Ads $ Central Analy+cs Pla@orm Email Blast $ Organic Search $ March 2011 © Datalicious Pty Ltd 22
- 23. > Exercise: Duplica+on impact § Double-‐coun-ng of conversions across channels can have a significant impact on key metrics, especially CPA § Example: Display ads and paid search – Total media budget of $10,000 of which 50% is spend on paid search and 50% on display ads – Total of 100 conversions across both channels with a channel overlap of 50%, i.e. both channels claim 100% of conversions based on their own repor-ng but once de-‐duplicated they each only contributed 50% of conversions – What are the ini-al CPA values and what is the true CPA? § Solu-on: $50 ini-al CPA and $100 true CPA – $5,000 / 100 = $50 ini-al CPA and $5,000 / 50 = $100 true CPA (which represents a 100% increase) March 2011 © Datalicious Pty Ltd 23
- 24. > First and last click aLribu+on Chart shows percentage of channel touch points that lead Paid/Organic Search to a conversion. Neither first Emails/Shopping Engines nor last-‐click measurement would provide true picture March 2011 © Datalicious Pty Ltd 24
- 25. > Full path to purchase Introducer Influencer Influencer Closer $ SEM Banner Direct SEO Online Generic Click Visit Branded Banner SEO Affiliate Social Offline View Generic Click Media TV SEO Direct Email Abandon Ad Branded Visit Update March 2011 © Datalicious Pty Ltd 25
- 26. > Understanding channel mix March 2011 © Datalicious Pty Ltd 26
- 27. > Adjus+ng for offline impact -‐5 -‐15 -‐10 +5 +15 +10 March 2011 © Datalicious Pty Ltd 27
- 28. 101011010010010010101111010010010101010100001011111001010101 010100101011001100010100101001101101001101001010100111001010 010010101001001010010100100101001111101010100101001001001010 > Targe+ng and tes+ng March 2011 © Datalicious Pty Ltd 28
- 29. > Increase revenue by 10-‐20% Capture internet traffic Capture 50-‐100% of fair market share of traffic Increase consumer engagement Exceed 50% of best compe-tor’s engagement rate Capture qualified leads and sell Convert 10-‐15% to leads and of that 20% to sales Building consumer loyalty Build 60% loyalty rate and 40% sales conversion Increase online revenue Earn 10-‐20% incremental revenue online March 2011 © Datalicious Pty Ltd 29
- 30. > New consumer decision journey The consumer decision process is changing from linear to circular. March 2011 © Datalicious Pty Ltd 30
- 31. > New consumer decision journey The consumer decision process is changing from linear to circular. Online research Change increases the importance of experience during research phase. March 2011 © Datalicious Pty Ltd 31
- 32. > Combining targe+ng pla@orms Off-‐site targe-ng Profile On-‐site targe-ng targe-ng March 2011 © Datalicious Pty Ltd 32
- 33. > Combining technology On-‐site Off-‐site segments segments CRM March 2011 © Datalicious Pty Ltd 33
- 34. > SuperTag code architecture § Central JavaScript container tag § One tag for all sites and plagorms § Hosted internally or externally § Faster tag implementa-on/updates § Eliminates JavaScript caching § Enables code tes-ng on live site § Enables heat map implementa-on § Enables redirects for A/B tes-ng § Enables network wide re-‐targe-ng § Enables live chat implementa-on March 2011 © Datalicious Pty Ltd 34
- 35. > Combining data sets Website behavioural data Campaign response data + The whole is greater than the sum of its parts Customer profile data March 2011 © Datalicious Pty Ltd 35
- 36. > Maximise iden+fica+on points 160% 140% 120% 100% 80% 60% −−− Probability of iden-fica-on through Cookies 40% 20% 0 4 8 12 16 20 24 28 32 36 40 44 48 Weeks March 2011 © Datalicious Pty Ltd 36
- 37. > Sample customer level data March 2011 © Datalicious Pty Ltd 37
- 38. > Affinity re-‐targe+ng in ac+on Different type of visitors respond to different ads. By using category affinity targe-ng, response rates are lijed significantly across products. CTR By Category Affinity Message Postpay Prepay Broadb. Business Blackberry Bold - - - + Google: “vodafone 5GB Mobile Broadband - - + - omniture case study” Blackberry Storm + - + + or hLp://bit.ly/de70b7 12 Month Caps - + - + March 2011 © Datalicious Pty Ltd 38
- 39. > Ad-‐sequencing in ac+on Marke-ng is about telling stories and stories are not sta-c but evolve over -me Ad-‐sequencing can help to evolve stories over -me the more users engage with ads March 2011 © Datalicious Pty Ltd 39
- 40. > Exercise: Targe+ng matrix Purchase Segments: Colour, price, Media Data Cycle product affinity, etc Channels Points Default, awareness Research, considera+on Purchase intent Reten+on, up/cross-‐sell March 2011 © Datalicious Pty Ltd 40
- 41. > Quality content is key Avinash Kaushik: “The principle of garbage in, garbage out applies here. [… what makes a behaviour targe;ng pla<orm ;ck, 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.” March 2011 © Datalicious Pty Ltd 41
- 42. > ClickTale tes+ng case study March 2011 © Datalicious Pty Ltd 42
- 43. > Exercise: Tes+ng matrix Test Segment Content KPIs Poten+al Results March 2011 © Datalicious Pty Ltd 43
- 44. Contact us cbartens@datalicious.com Learn more blog.datalicious.com Follow us twiLer.com/datalicious March 2011 © Datalicious Pty Ltd 44
- 45. Data > Insights > Ac+on