How to Successfully Apply Data & AI in the Marketing Value Chain. In this session Artefact will be starting with the role of data in the current world and what it has lead to currently: Where are we with Data & Artificial Intelligence? the future is definitely here. We will make it concrete and explore where to apply Data & AI in digital marketing? What can AI do and what can't it do (yet)?Possible areas are automation, optimization and more. Artefact will make it practical to conclude and explain what using Data & AI means practically for Digital Marketing? What are the actionable next steps in Planning, setup/workflow, getting control and creative.
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Data & AI Master Class - Jan Klawer, Artefact
1. Jan Klawer
MANAGING DIRECTOR MIDDLE EAST AND AFRICA
ARTEFACT
DUBAI, UAE ~ OCTOBER 23 - 24, 2018
DIGIMARCONMIDDLEEAST.COM | #DigiMarConMiddleEast
Data & AI
Master Class
MASTERCLASS
2. How to Successfully apply Data & AI
in the Marketing Value Chain
Masterclass
23 October 2018
4. New consumer opinions - new industry
standards
World’s most innovative companies
Ranking
2017
Innovation is driven by
GAFAx who are
already well-prepared
for the future
Top 5 Market Capitalization, PWC
2017
Media business is
mainly owned by
GAFAx
Top 5 of Most Loved Global Brands
2017
Consumer loves
GAFAx
5. Technology has
transformed consumers’
lives
A new breed of brands such as Google, Apple, Facebook, Amazon, Netflix,
Airbnb etc have captured consumers hearts & minds by disrupting the status
quo across all sectors. These brands have defined higher standards of
customer experience by continuously improving their products and services
through digital, data & AI. All brands must now live up to these new
standards.
6. Artefact is a digital company celebrating the long
overdue marriage of marketers and engineers.
Artefact :
Marketing
Engineers
7. A squad operating
on all marketing
needs
Technologies
Our highly accredited experts have 20
years experience in leading award-
winning global digital marketing
campaigns.
Business oriented, data raised,
digital native, marketing minded
and IT trained unicorns, they live to
put together the perfect team of our
in-house talents.
Our Full-stack Engineers will set-up
end to end DataLake, with the right
trade-off between speed and
reversibility
AI specialists with PhDs in Machine
Learning developing unique
proprietary solutions to fit our clients’
needs and optimize in-house
processes.
Media &
Activation
Creation
DataLake
Ecosystem
Artificial IntelligenceStrategic Consulting
Data Science
Award-winning creatives, able to
design concepts from branding to
performance based on data.
Marketing
Consulting
First class data experts from the
largest international pool of giant
tech certified tracking experts,
Analytics Specialists, Data Consultants
and Data Scientists.
8. To achieve your Companies’ Vision all
Activities in the Data and AI Pyramid are
Enablers: how?
Choose the right technologies and
implement them successfully within expert
and non expert marketing teams.
VISION
USE CASES
Define the future state of the business, the role of data in the
transformation to come and help the organization change in order
to drive it.
Improve data accessibility, quality and
privacy by defining the right
infrastructure, processes and
governance, and by implementing them.
Create and launch new use cases to generate short
term or long term impacts on sales and costs, and
industrialize them.
Generate deep insights and KPIs on customers or
marketing operations to better understand who the
customers are and how the business is impacted by them.
ANALYTICS
DATA SCIENCE
TECHNOLOGIE
S
DATA INFRASTRUCTURE
AND DATA GOVERNANCE
AND TOOLS
11. Do you know?
What % of marketing
organizations are implementing
or expanding AI & machine
learning in 2018?
*According to Forrester research in 2017. Survey among 150 Martech professionals in the US.
12. Source: Forrester Research 2017
“Marketers have reached a point
where their ability to capture data
has exceeded their ability to take
data-driven action”
“They are confident that AI
enhances human decisions and
insights.”
84%
13. Do you know?
...the amount of customer
care interactions that will be
managed by AI in 2020?*
*as predicted by Gartner
16. Vast amounts of data are being produced and
processed every minute.
16
1.3K2.4M347K
142M
Half a trillion digital moments across devices processed by
Google Analytics each day
50K
Tweets Searches Uber rides
$203K
Amazon sales
App
Downloads
Emails
1 MINUTE
17. Accelerated growth of data production.
First even known
written document
information/volume
timetoday201020063000 BC 1450 1900 1992 1999
Invention of
Printing
London library (500
000 books)
Internet advent
Each person produces
around 250 Gb
12 times the distance
between planet earth
and the sun if we stock
all the data in book
format
We are
here!
90% of the data
available in the world
has been generated
between 2016 and
2018
Skyrocketing
quantity of data:
birth of data
science
21. What is AI?
Weak AIStrong AI
“The creation of computer programs (machines) that can (out)perform tasks
that are currently completed more satisfactorily by humans”
22. A machine that can do everything a
human can, including being self-aware
What is strong AI?
Timeline: 30 to 1000 years
24. Todays examples of AI applications.
Siri 2011
Now 2012
Cortana 2014
Alexa 2015
M 2016
Assistant 2016
Bixby 2017
Personal assistants Self-driving cars Augmenting humans
Off-the-shelf AI for a wide range of
industries:
With Tesla taking the lead, they include
all AI bricks
● Sensing: The camera turns
video into objects and places
● Planning: I have to go from A to
B via the best route
● Learning: I learn to manage any
situation via millions of hours of
driving
● Knowing & Reasoning: Moral
driving rules
Natural language processing and use
of web resources
Sentient Ascend: Tech
to optimize the UX of e-
commerce sites
Khresterion: Real-time
voice analysis tech
Watson: Can help with
medical diagnoses
25. Map of AI.
Learning from a set of
examples, growing over
time
● Supervised
● Unsupervised
● Reinforcement
Learns to recognize
spam in an inbox
AI
Learning Sensing
Processing signals from
the outside world
● Computer Vision
● Speech recognition
● Natural Language
Processing
● Feature construction
● …
Planning
Moving in an environment
to attain a goal
● Monte-Carlo Tree
Search
● Markov decision
process*
● Genetic algorithms
● ....
Knowing &
Reasoning
Deducing facts from other
facts, rules, connections
● Rule-based engine
● Expert systems
● Ontologies
● ….
Camera of a
driverless car
The robot must go
charge itself then
leave home
I can prove a
mathematical
theorem from axioms
* Stochastic model used to study optimization problems using dynamic programming
or reinforcement learning algorithms
26. What is currently possible, and what isn’t (yet)?
In the years ahead,
specialists will keep
striving to let AI perform
tasks that the human
brain currently
processes in a
second.
Input Challenge
Output
What AI can do... What AI can't do...
Are there any human faces (0/1)?
Who’s on there?
Will they pay back the loan (0/1)?
What is that sound?
Who’s talking?
What’s the position of other vehicles
and objects?
Will it crash?
27. We’ve built AI solutions in order to inspire and free up time for
customers and marketers, removing errors and repetitive
tasks.
Our AI roadmap
Marketing
as an API
Automated
reporting
Siloed channels
& devices
customer vision
Omni-channel &
cross-device
customer vision
AI-based content
production
Media AI decision
making process
Automated
orchestration
29. Your challenge: What tasks are appropriate to
automate and optimize with AI?
522hours per year
lost on repetitive
tasks *
*DJS Research 2017
DUMB WORK GUESS WORK
Manual and time-consuming
tasks can disappear thanks
to AI
AI can confirm or deny human
intuition in the prediction of the
optimal customer dialogue / journey
522 hours per year lost on repetitive tasks*
30. Thanks to AI,
marketing departments
can concentrate on
higher value-added
work: strategy and
creativity
31. Tomorrow CMOs will
formulate strategic and
creative hypotheses and
machines will do the rest
of the job: it is our
marketing as an API
vision
32. Where to apply data & AI for marketing as an API?
WHO - Audience segmentation
Segment audiences based on:
- Behavioral / relational likeness
- Buying propensity
- Reasons to buy
- Churn propensity
- Interest or channel affinity
- Lead scores (engagement / conversion)
33. Activate message, content and offer based on:
- Dynamic creative optimization
- Dynamic content creation
- Recommendation engine
WHAT - Message / content / offer optimization
Where to apply data & AI for marketing as an API?
34. WHEN/WHERE - Channel optimization
Reallocate and activate budget based on:
- Conversion attribution
- Budget allocation and distribution
- Reception recognition (offline
impact)
- Brand perception
- Voice search / Personal assistants
Where to apply data & AI for marketing as an API?
35. Time
CustomerInteractionsandValue
REACH ACT CONVERT ENGAGE
Smart
Content
Curation
Programmatic
Media
Bidding
AI
Generated
Content
Voice
Search
Propensity
Modeling
Ad
Targeting
Predictive
Analytics
Lead
Scoring
Re-targeting
Dynamic
Pricing
Web & App
Personalisation
Chat
Bots Predictive
customer
Service
Marketing
Automation
1:1
Dynamic
content
emails
Who?
Where?
What?
Demand generation
and purchase intent
1st
Purchase
Indecisive Customer
Loyal
Customer
Lapsed
Customer
Repeat
Customer
Applications of AI & machine learning in the customer journey.
36. Score AI Readiness explained
Expert 31 > 40
Demonstrates excellent digital capabilities.
Experts have already invested in AI and
identified business cases for AI.
Opportunist 21 > 30
Demonstrates good digital capabilities.
Opportunist are already investing in AI, but
are not taking full advantage of all
possibilities.
Novice 11 > 20
Demonstrates good basic digital
capabilities. Perhaps already shown
interest in AI and taken basic steps
towards implementation.
Laggard 0 > 10
Demonstrates relative poor digital
capabilities. Laggards are probably in the
early stages of gaining information and
evaluating AI.
Compare your score against our threshold and the benchmark based on competitor
survey results, and see what you can do to adopt AI into your activities.
24
12.7
Threshold Current
Survey
Do the AI-readiness test!
Your personal
score
AI: How ready are you?
?
37. Creation
of new uses
(Chatbots)
Algorithmic
Omnichannel
Orchestration
Sales
Predictio
n
Dynamic
Persona
Creation
The way we use AI in our day to day activities at Artefact.
Predictive life
moments detection
Client
segmentation
Dynamic Creative
Optimisation (DCO)
Content
Indexation
Automated Mix Media
Optimization
Automated
Trafficking
Bid
Optimization
Automated
Reporting
Cross-channel
Synergy detection
ROPO
Measurement
INSIGHTS
CREATIO
N
ACTIVATION
MEASUREMENT
39. The marketing value chain is composed
of repetitive tasks that are prone to error.
Plan. Setup. Control. Optimize.
• Identify the best
audiences to target
• Find the best budget
allocation
• Ad creation
• Ad trafficking
• Consistent campaign
tagging
• Tracking consistency
• Data verification
• Data (PII) leakage
• Error tracking (payment,
404)
• Attribute value across
channels & reallocate
budgets
• Optimize for the best
audiences, creative,
content & offer
• Automated reporting
40. Common challenges in the planning phase.
Plan. Setup. Control. Optimize.
• Identifying the best target audience
• Finding the best budget allocation and
distribution
41. We have automated audience clustering combined
with creative optimization.
RESULTS
Conversions ROI
Reach
x2 x2,3
x1,4
ACTIVATE THE BEST
SEGMENTS WITH THE
BEST MESSAGES
44. Common challenges in the setup phase.
Plan. Setup. Control. Optimize.
• Ad creation
• Ad trafficking
• Consistent campaign tagging
45. Tasks performed by an Ad Trafficker in
DoubleClick.
Time-consuming Manual
Create a campaign Upload creativeCreate placements
Create ads Verify impressionsDownload tags
47. Media plan is ingested and
processed by our algorithm
into a traffic sheet
RELIABLE
Easily prevent human
mistakes
FASTER
Automatically launch
campaigns within
minutes, in a few clicks
Trafficking 2.0: 3 steps to reduce complexity
Automate 98% of your campaigns.
USER-
FRIENDLY
1 easy-to-use interface
Errors are automatically
detected and detailed within
the interface
Detect errors
that impact
performance
Turn media
plans into
campaigns
21
Automatic campaign setup:
the algorithm creates ads
and their backups.
Traffic
campaigns at
scale
3
48. Common challenges in the Control phase.
Plan. Setup. Control. Optimize.
• Tracking consistency
• Data verification
• Data (PII) leakage
• Error tracking (payment, 404)
49. PowerScan: validate quality of tag
implementation through actionable reports.
Automate tags verification at scale
Detect wrongly implemented
tags and variable labels and
values
Automatically scans
thousand of URLs
DETECT TAG
ERRORS
SCAN ALL URLS
ON YOUR
WEBSITE
21
Detailed reporting with
actionable insights:
- Errors: no call, wrong
variable label, wrong
value
- Cause: technical or
analytics
- Evaluate and refine
GET A FULL
REPORTING AND
TAKE REQUIRED
ACTIONS
3
50. Common challenges in the Optimize phase.
Plan. Setup. Control. Optimize.
• Attribute value across channels & reallocate
budgets
• Optimize for the best Audiences, Creative,
Content & Offer
• Automated reporting
51. 1
Demand is sent
to the agency
2
The agency
writes a new
scenario
3
Preview link is
sent to the
client
4
Validation of
the scenario
by the client
5
The new
scenario is
activated
8 emails
2 calls
3 mobilized resources
3 days of process & work
BEFOREBEFORE
The creative optimization process.
53. Intuition is being compared to historical
performance and machine learning
algorithm.
54. At Artefact, we have built a suite of AI-based products
OUR PROPRIETARY TECHNOLOGY IS AT THE HEART OF OUR DAILY DECISIONS
Audience Builder
Media Plan
Recommendation
SEAds Generator
URL Builder
Trafficking 2.0
PowerScan
PII Tracking
URL Checker
Octopus
SEA Optimization
SEA/SEO Synergies
SEA exclusion/targeting
Automated Reportings
Artefact Ingestion ToolDPP
Display Optimization
Plan Setup Control Optimize
Activation
MyDCO
Infrastructure
Log File Scan
Page Speed Check
55. Plan. Setup. Control. Optimize.
• Identify the best
audiences to target
• Find the best budget
allocation
• Ad creation
• Ad trafficking
• Consistent campaign
tagging
• Tracking consistency
• Data verification
• Data (PII) leakage
• Error tracking (payment,
404)
• Attribute value across
channels & reallocate
budgets
• Optimize for the best
audiences, creative,
content & offer
• Automated reporting
By automating tasks in all these phases...
56. ...we gain time to re-focus
on Data-Driven Strategy &
Creativity
56
57. Key takeaways.
Start breaking down you every day activities into clusters of
repetitive tasks that could potentially be automated.
Determine where you could introduce some 'intelligence' to support
decision making. Start deploying algorithms for clustering/predicting
what could be a profitable audience, message/creative or media mix.
Don't be intimidated by the hype around AI/machine learning.