In this presentation, Andrew Covato talks about the uses of attribution modelling and Big Data within a large company like Google. Covato introduces himself and talks about his own working background before going on to talk about the ins and outs of marketing and digital marketing. As well as giving insight into attribution modelling with his experience.

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Attribution Modeling and
Big Data
Andrew Covato
June 21, 2013

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What’s on the menu for today?
Who am I?
Marketing 101: The Basics
Marketing 201: Digital Marketing
Whet your appetite for attribution
Conclusion: Digital marketing
today = finance in the 1980s

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Who am I? (i.e. am I at least somewhat credible?)

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Ready to go?
Let the fun
begin!

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The Basics
Marketing 101

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“Half the money I spend on advertising is wasted;
the trouble is I don’t know which half.”
--John Wanamaker: Retailer, business man, innovator,
“advertising genius”

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The question marketing
execs are seeking to
answer is…

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“What is the dollar value
of sales generated by
each of my marketing
initiatives?”

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“Traditional” offline marketing and advertising is
impossible to track at an un-aggregate level…

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MARKETING MIX MODELING
…but in the 1960s, big CPG firms developed a
framework for measuring marketing ROI

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The Basic Principles of Traditional Marketing Mix
Modeling (MMM)
Inputs
Controls
Response
Examples…
often other
metrics or
dimensions
included
Incremental Sales Volume

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MMM is great for describing macro behaviours, but
sales attribution to specific channels is dubious at
best—especially with new advertising technology

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Digital Marketing
Marketing 201

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What is this funnel you
speak of?

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Digital marketing allows
advertisements to align
with a specific person’s
instantaneous intent
This makes ads hyper-
contextual

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There are many more
dimensions by which to
accurately target an audience
at various stages in the funnel

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Ads (and advertising dollars) can be tailored
across a variety of such dimensions

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Taking bite-sized nibbles from a buffet of complexity
Whet your appetite for attribution

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Remember what we are
trying to quantify (ROI by
marketing channel)…now
let’s set up the problem

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Today, many marketers employ “last-click”, “first-
click”, or other weighting schemes to value their
channels

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But assigning weights will
not show you the true value
of each channel…the
weights need to be derived
using the data!

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Some things can
complicate this

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Probability of conversion
is path-dependent
People are in various
stages of awareness
when they interact with
an ad
Lots of exogenous
variables (e.g.
competitors’ response to
marketing)

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Technology is a further
complication—you need
very detailed data to
create a proper attribution
model!

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For each user, we
need a time-
stamped record of
each interaction with
each
advertisement…

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We also need
environmental data
(some sort of
competitive index)

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Oh, and we need to
develop a model to
project the users’
instantaneous
awareness state

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If you have all this,
however…
…you wield great power
(and responsibility)

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While respecting privacy, you can:
Calculate, in real-time, each user’s
instantaneous probability of converting
Determine the best creative to show a
user at 20% conversion probability to
bump her up to 80%
Understand how “upper-funnel” ads
impact sales farther down the funnel
Ultimately calculate a dead-
accurate ROAS for each digital
channel!

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How? Let’s get technical…
We can use a high-order Markov
model to calculate conversion
probabilities at each path
Or a first-order MM could be used to
move visitors between states
(Abhishek, Fader, Hosanagar)
Alternatively (and possibly
preferably), some sort of additive
model with a time-decay for touch-
points

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Who will develop the magic model?
Digital Marketing today is like Finance in
the1980s

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Questions?