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What to expect
in this presentation
• An in-depth, technical review of the core
features of the Enhance Ecommerce platform
• Tactical implementation examples and how to
use the resulting data
• My current take on the platform.
@analyticsninja
Product Lists
Product List Performance
• Category Pages
• Search Results Pages
• Cross Sells
• Up Sells
• Promoted products (like homepage
splashes)
Merchandising
Product Scope
Impression list #1 / product impression #9 / ID, Name, Position
Product Scope
• With the product scope, you can send
data for multiple products on a single hit.
• For example, the pageview will now
contain data that allows you to answer
the question  show all products that
were displayed on a category page that
are almost out of stock and what
position were they in.
Import dimensions to enhance data
Custom dimensions to enhance data
• Product freshness
– season / added to inventory date
• Product level promotional descriptions
– On sale, featured item, etc.
• Current product stock amount
• Product reviews
• Product level profit margins
• Product attributes such as color, size, weight,
manufacturer, distributor, warranty
Cross sells
Cross sells
Up sells
Product List Name
Impressions and Actions
• Impressions are meant to model the
choices the user can make.
• Actions are meant to model the decisions
the user made.
Product clicked
Product list position
What do we do with it?
• Cross Sell / Up Sell performance the most
exciting aspect of product list “impression” data
– Recommendation engine optimization (@fastbloke)
• Insights regarding merchandising placement
within category pages can be gleamed, though
sales data is a stronger indicator of when to
highlight products (as we shall see later).
• Revenue from a product list view is reported via
a “last action” attribution.
Product Detail Views
Product Detail Views
Product Performance Reports
Product Performance Standard Metrics
• Good use of standard dimensions that include 5
levels of product taxonomy and brand.
• Big benefit of providing Cart to Detail and Buy to
Detail Rates – many businesses wouldn’t be
accessing those metrics. Propensity to purchase!
• For now, those metrics are based on VIEWS
instead of unique views, which I believe doesn’t
model shopping behavior in the optimal way.
Calculated Cart to Detail
Calculated Buy to Detail Rate
Mix in Product Scoped Custom Metrics
Dimensions vs. Metrics
• Show me all product views that for products that
have a profit margin of 40% or higher
– CUSTOM DIMENSIONS
• Show me the top 10 profit generating products
– CUSTOM METRICS
Enhanced Product Performance Reports
What do we do with it?
• Advertise. Duh!
– Product Listing Ads
– Keyword bidding
• Product placement on category pages and
homepage splashes.
• Help guide merchandising decisions
Overall Shopping / Checkout Behavior
Overall Shopping / Checkout Behavior
Not really different than horizontal funnels
but DOES make these setups available to more users
Quick segmentation capability
from within the interface
Additional Standard Dimension of
Checkout Options
Overall Shopping / Checkout Behavior
Same basic funnel in KissMetrics, but the
denominator is “people”
Current issues with checkout funnel
• Rigid
– Not all sites follow the same checkout funnel, this just
models the most common use case.
– Different payment options have different checkout process
that happen offsite (PayPal).
– Users may log in an automatically bypass many of the
predefined steps.
• Sessionized
– Purchases process may not be within a 30 minute window
• :-/
Refunds – I don’t have data,
but it looks like it’s good!
Internal Promotions
Internal Promotions
Discounts
Discounts
Discounts
Discounts
• Track total value of discounts on order and
product level using custom metrics.
• Discounts may increase demand, but may not be
increasing profitability.
• Make sure to apply the order level discount
across the Product Price for all products being
purchased. A common error is to leave the
product price as a static value at point of sale,
and not apply the discount to the Product
Revenue.
• Follow @minethatdata (Kevin Hillstrom)
Now what?  Segmentation
Now What?  Segmentation
Now What?  Segmentation
Now What?  Segmentation
Now What?  Segmentation
• Prioritize owned, earned, and paid marketing
efforts by page type and product type.
• Create meaningful GDN retargeting audiences in
GA based on segments (winners and losers)
• RLSAs need to be served via pixel to include the
“conversion label”. Armed with a strong GTM
implementation and GA data, create awesome
RLSA lists with a few clicks.
Final thoughts
• Being able to send a large amount of impression
data (including promotions) on a single hit is a huge
improvement in GA architecture.
• Product lists, especially for cross sells and upsells, is
a great feature. Internal promotion tracking also
very good.
• Much of the merchandising related data model in
Enhanced Ecommerce was “doable” before product
launch, but is a very welcome addition to the
platform now that it is built in. User adoption.
Final thoughts
• Session based data is still “meh”, same with Buy to
Detail rates being based on views.
• Vocabulary of product related “verbs” (like add to
cart, purchase) is solid, but a bit rigid (no native
way to track ‘add to wishlist’, ‘social share’, ‘video
play’.
• Product scoped custom metrics for profit metrics
are relatively easy to implement and major in
terms of data value.
Final thoughts
• Generally speaking, I think that there are lots of
“actionable items” that come out of the new
platform.
– Product level advertising insights
• especially good for PLAs
– Smart Remarketing
– On site merchandising decisions
– On site promotional decisions
– Improve performance of recommendation engines
Current @AnalyticsNinja Rating

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Yehoshua Coren - Analytics Ninja (All Things Data 2015)

  • 1.
  • 2. What to expect in this presentation • An in-depth, technical review of the core features of the Enhance Ecommerce platform • Tactical implementation examples and how to use the resulting data • My current take on the platform. @analyticsninja
  • 4. Product List Performance • Category Pages • Search Results Pages • Cross Sells • Up Sells • Promoted products (like homepage splashes)
  • 6. Product Scope Impression list #1 / product impression #9 / ID, Name, Position
  • 7. Product Scope • With the product scope, you can send data for multiple products on a single hit. • For example, the pageview will now contain data that allows you to answer the question  show all products that were displayed on a category page that are almost out of stock and what position were they in.
  • 8. Import dimensions to enhance data
  • 9. Custom dimensions to enhance data • Product freshness – season / added to inventory date • Product level promotional descriptions – On sale, featured item, etc. • Current product stock amount • Product reviews • Product level profit margins • Product attributes such as color, size, weight, manufacturer, distributor, warranty
  • 10.
  • 15. Impressions and Actions • Impressions are meant to model the choices the user can make. • Actions are meant to model the decisions the user made.
  • 18. What do we do with it? • Cross Sell / Up Sell performance the most exciting aspect of product list “impression” data – Recommendation engine optimization (@fastbloke) • Insights regarding merchandising placement within category pages can be gleamed, though sales data is a stronger indicator of when to highlight products (as we shall see later). • Revenue from a product list view is reported via a “last action” attribution.
  • 22. Product Performance Standard Metrics • Good use of standard dimensions that include 5 levels of product taxonomy and brand. • Big benefit of providing Cart to Detail and Buy to Detail Rates – many businesses wouldn’t be accessing those metrics. Propensity to purchase! • For now, those metrics are based on VIEWS instead of unique views, which I believe doesn’t model shopping behavior in the optimal way.
  • 24. Calculated Buy to Detail Rate
  • 25. Mix in Product Scoped Custom Metrics
  • 26. Dimensions vs. Metrics • Show me all product views that for products that have a profit margin of 40% or higher – CUSTOM DIMENSIONS • Show me the top 10 profit generating products – CUSTOM METRICS
  • 28. What do we do with it? • Advertise. Duh! – Product Listing Ads – Keyword bidding • Product placement on category pages and homepage splashes. • Help guide merchandising decisions
  • 29. Overall Shopping / Checkout Behavior
  • 30. Overall Shopping / Checkout Behavior
  • 31. Not really different than horizontal funnels but DOES make these setups available to more users
  • 32. Quick segmentation capability from within the interface
  • 33. Additional Standard Dimension of Checkout Options
  • 34. Overall Shopping / Checkout Behavior
  • 35. Same basic funnel in KissMetrics, but the denominator is “people”
  • 36. Current issues with checkout funnel • Rigid – Not all sites follow the same checkout funnel, this just models the most common use case. – Different payment options have different checkout process that happen offsite (PayPal). – Users may log in an automatically bypass many of the predefined steps. • Sessionized – Purchases process may not be within a 30 minute window • :-/
  • 37. Refunds – I don’t have data, but it looks like it’s good!
  • 43. Discounts • Track total value of discounts on order and product level using custom metrics. • Discounts may increase demand, but may not be increasing profitability. • Make sure to apply the order level discount across the Product Price for all products being purchased. A common error is to leave the product price as a static value at point of sale, and not apply the discount to the Product Revenue. • Follow @minethatdata (Kevin Hillstrom)
  • 44. Now what?  Segmentation
  • 45. Now What?  Segmentation
  • 46. Now What?  Segmentation
  • 47. Now What?  Segmentation
  • 48. Now What?  Segmentation • Prioritize owned, earned, and paid marketing efforts by page type and product type. • Create meaningful GDN retargeting audiences in GA based on segments (winners and losers) • RLSAs need to be served via pixel to include the “conversion label”. Armed with a strong GTM implementation and GA data, create awesome RLSA lists with a few clicks.
  • 49. Final thoughts • Being able to send a large amount of impression data (including promotions) on a single hit is a huge improvement in GA architecture. • Product lists, especially for cross sells and upsells, is a great feature. Internal promotion tracking also very good. • Much of the merchandising related data model in Enhanced Ecommerce was “doable” before product launch, but is a very welcome addition to the platform now that it is built in. User adoption.
  • 50. Final thoughts • Session based data is still “meh”, same with Buy to Detail rates being based on views. • Vocabulary of product related “verbs” (like add to cart, purchase) is solid, but a bit rigid (no native way to track ‘add to wishlist’, ‘social share’, ‘video play’. • Product scoped custom metrics for profit metrics are relatively easy to implement and major in terms of data value.
  • 51. Final thoughts • Generally speaking, I think that there are lots of “actionable items” that come out of the new platform. – Product level advertising insights • especially good for PLAs – Smart Remarketing – On site merchandising decisions – On site promotional decisions – Improve performance of recommendation engines

Hinweis der Redaktion

  1. Picture from: http://upwell.com.br/blog/google-analytics/google-analytics-lanca-nova-funcionalidade-para-ecommerce/