• Save

Loading…

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Like this presentation? Why not share!

Like this? Share it with your network

Share
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
1,165
On Slideshare
1,165
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
0
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide
  • 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

Transcript

  • 1. [Analyse to optimise ]
    Campaign tracking and analytics digital certificate guest lecture
  • 2. [ Company history ]
    Datalicious was founded in late 2007
    Strong Omniture web analytics history
    1 of 4 Omniture Service Partners globally
    Now 360 data agency with specialist team
    Combination of analysts and developers
    Making data accessible and actionable
    Evangelizing smart data driven marketing
    Driving industry best practice (ADMA)
    October 2010
    © Datalicious Pty Ltd
    2
  • 3. [ Smart data driven marketing ]
    October 2010
    © Datalicious Pty Ltd
    3
    Media AttributionOptimise channel mix
    TargetingIncrease relevance
    TestingImprove usability
    $$$
  • 4. [ Clients across all industries ]
    October 2010
    © Datalicious Pty Ltd
    4
  • 5. [ AIDA and AIDAS formulas ]
    October 2010
    © Datalicious Pty Ltd
    5
    Old media
    New media
    Social media
  • 6. [ Simplified AIDAS funnel ]
    October 2010
    © Datalicious Pty Ltd
    6
  • 7. [ Marketing is about people ]
    October 2010
    © Datalicious Pty Ltd
    7
    Media and search data
    Website, call center and retail data
    40%
    10%
    1%
    Quantitative and qualitative research data
    Social media data
    Social media
  • 8. [ Google data in Australia ]
    October 2010
    © Datalicious Pty Ltd
    8
    Source: http://www.hitwise.com/au/datacentre
  • 9. [ Search and brand strength ]
    October 2010
    © Datalicious Pty Ltd
    9
  • 10. [ Search and the product lifecycle ]
    October 2010
    © Datalicious Pty Ltd
    10
    Nokia N-Series
    Apple iPhone
  • 11. [ Search and media planning ]
    October 2010
    © Datalicious Pty Ltd
    11
  • 12. [ Search driving offline creative ]
    October 2010
    © Datalicious Pty Ltd
    12
  • 13. [ Facebook insights ]
    October 2010
    © Datalicious Pty Ltd
    13
    Using Facebook Like buttons is a free and powerful way to gain additional insights into consumer preferences and enabling social sharing of content as well as possibly influence organic search rankings in the near future.
  • 14. [ Conversion funnel 1.0 ]
    October 2010
    Campaign responses
    Conversion funnel
    Product page, add to shopping cart, view shopping cart, cart checkout, payment details, shipping information, order confirmation, etc
    Conversion event
    © Datalicious Pty Ltd
    14
  • 15. [ Conversion funnel 2.0 ]
    October 2010
    Campaign responses (inbound spokes)
    Offline campaigns, banner ads, email marketing, referrals, organic search, paid search, internal promotions, etc
    Landing page (hub)
    Success events (outbound spokes)
    Bounce rate, add to cart, cart checkout, confirmed order, call back request, registration, product comparison, product review, forward to friend, etc
    © Datalicious Pty Ltd
    15
  • 16. [ Additional success metrics ]
    October 2010
    © Datalicious Pty Ltd
    16
    Click Through
    $
    Click Through
    Add To Cart
    $
    Cart Checkout
    ?
    Click Through
    Page Bounce
    $
    Page Views
    Product Views
    Click Through
    Call back request
    Store Search
    ?
    $
  • 17. How many survey responses do you need if you have 10,000 customers?
    How many email opens do you need to test 2 subject linesif your subscriber base is 50,000?
    How many orders do you need to test 6 banner executions if you serve 1,000,000 banners
    Google “nss sample size calculator”
  • 18. How many survey responses do you need if you have 10,000 customers?
    369 for each question or 369 complete responses
    How many email opens do you need to test 2 subject linesif your subscriber base is 50,000? And email sends?
    381 per subject line or 381 x 2 = 762 email opens
    How many orders do you need to test 6 banner executions if you serve 1,000,000 banners?
    383 sales per banner execution or 383 x 6 = 2,298 sales
    Google “nss sample size calculator”
  • 19. [ De-duplication across channels ]
    October 2010
    © Datalicious Pty Ltd
    19
    Paid Search
    $
    Bid Mgmt
    Central AnalyticsPlatform
    Banner Ads
    Ad Server
    $
    $
    Email Blast
    Email Platform
    $
    $
    Organic Search
    Google Analytics
    $
    $
  • 20. [ Exercise: Duplication impact ]
    Double-counting 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 reporting but once de-duplicated they each only contributed 50% of conversions
    What are the initial CPA values and what is the true CPA?
    Solution: $50 initial CPA and $100 true CPA
    $5,000 / 100 = $50 initial CPA and $5,000 / 50 = $100 true CPA (which represents a 100% increase)
    October 2010
    © Datalicious Pty Ltd
    20
  • 21. [ Success attribution models ]
    Banner Ad
    Paid Search
    OrganicSearch$100
    Success
    $100
    Last channel gets all credit
    Banner Ad$100
    Email Blast
    Success$100
    First channel gets all credit
    Paid Search
    Paid Search$100
    Banner Ad$100
    Affiliate Referral$100
    Success$100
    All channels get equal credit
    Print Ad$33
    Social Media$33
    Paid Search$33
    Success$100
    All channels get partial credit
    October 2010
    21
    © Datalicious Pty Ltd
  • 22. [ First and last click attribution ]
    October 2010
    © Datalicious Pty Ltd
    22
    Chart shows percentage of channel touch points that lead to a conversion.
    Paid/Organic Search
    Neither first nor last-click measurementwould provide true picture
    Emails/Shopping Engines
  • 23. Closer
    [ Full path to purchase ]
    Influencer
    Influencer
    SEM Generic
    Banner View
    October 2010
    23
    © Datalicious Pty Ltd
    $
    Introducer
    Banner Click
    $
    Direct Visit
    SEO Branded
    SEOGeneric
    AffiliateClick
    $
    Social Media
    TV Ad
    SEO Branded
    Direct Visit
    Email Update
    Abandon
  • 24. [ Understanding channel overlap ]
    October 2010
    © Datalicious Pty Ltd
    24
  • 25. [ Website entry survey ]
    October 2010
    © Datalicious Pty Ltd
    25
    De-duped Campaign Report
    Greatest Influencer on Branded Search / STS
    }
    Conversions attributed to search terms that contain brand keywords and direct website visits are most likely not the originating channel that generated the awareness and as such conversion credits should be re-allocated.
  • 26. The study examined data from two of the UK’s busiest ecommerce websites, ASDAand William Hill.
    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.
    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.
    [ Unique visitor overestimation ]
    October 2010
    © Datalicious Pty Ltd
    26
    Source: White Paper, RedEye, 2007
  • 27. [ Importance of calendar events ]
    October 2010
    © Datalicious Pty Ltd
    27
    Traffic spikes or other data anomalies without context are very hard to interpret and can render data useless
  • 28. © Datalicious Pty Ltd
    [ Useful analytics tools ]
    http://labs.google.com/sets
    http://www.google.com/trends
    http://www.google.com/insights/search
    http://www.google.com/sktool
    http://bit.ly/googlekeywordtoolexternal
    http://www.google.com/webmasters
    http://www.google.com/adplanner
    http://www.google.com/videotargeting
    http://www.keywordspy.com
    http://www.compete.com
    October 2010
    28
  • 29. © Datalicious Pty Ltd
    [ Useful analytics tools ]
    http://bit.ly/hitwisedatacenter
    http://www.socialmention.com
    http://twittersentiment.appspot.com
    http://bit.ly/twitterstreamgraphs
    http://twitrratr.com
    http://bit.ly/listoftools1
    http://bit.ly/listoftools2
    http://manyeyes.alphaworks.ibm.com
    http://www.wordle.net
    http://www.tagxedo.com
    October 2010
    29
  • 30. ADMA short course
    “Analyse to optimise” In Melbourne & Sydney
    October/November
    By Datalicious
  • 31. Contact uscbartens@datalicious.comFollow ustwitter.com/datalicious
    Learn moreblog.datalicious.com