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WORKSHOP
Applying BIG DATA to SALES - how you can watch your
revenue grow by using the right data and measurements
BERLIN – FEBRUARY 2018
INTRODUCTION
ABOUT THE SPEAKER
CHRISTIAN PALAU SANZ PROFILE
“ +15 YEARS OF INTERNATIONAL EXPERIENCE
IN THE ONLINE CLASSIFIEDS MARKET”
COMPUTRABAJO BESTJOBS JOBISJOB FOTOCASA SEGUNDAMANO
SCHIBSTED INFOJOBS BRASIL INFOJOBS ITALIA INFOJOBS ESPAÑA
EMAGISTER NIUMBAESPACIO DECO MARKETYOU ENALQUILER
Associated teacher at Business Schools
In-Company
Former
2014 – 2017: SVP BUSINESS DEVELOPMENT EN RED ARBOR: COMPUTRABAJO, BESTJOBS, MUBAWAB, INFOJOBS BRASIL
2012 – 2014: CSO/CMO EN JOBISJOB: Job Aggregator and BIG DATA data solution for the HR sector
2018 – TO DATE: SENIOR DIGITAL STRATEGY CONSULTANT
2013 – 2014: INNOVATION DIRECTOR AT ANUNTIS: FOTOCASA, COCHES.NET, SEGUNDAMANO, INFOJOBS, LECTIVA,...
2009 – 2012: FOTOCASA DIRECTOR: Real Estate top Classified site in Spain
2003 – 2009: MARKETING & STRATEGY DIRECTOR AT INFOJOBS ESPAÑA
https://www.youtube.com/watch?v=iANv_0ZQKDY
WHAT DOES
BIG DATA
MEAN?
WHAT DOES BIG DATA REALLY MEAN?
Extremely big data sets… that need from
computational analysis to reveal patterns,
trends, associations,....
Data alone, has very limited value... Basically the
value of owning it, and not allowing the access to
third...- Economy of information hiding.
Is needed to process it, to transform it into
information that is what really adds value as it is in
what business decisions are taken...
For processing it... We need technology and context to
give sense to the result obtained...
Thought	1
Thought	2
Thought	3
COLLECTING
DATA...
THE BIG PAIN
POINT?
https://www.youtube.com/watch?v=3Sk7cOqB9D k
COLLECTING DATA- THE BIG PAIN POINT
THE OBSESSION OF THE
“1 SHOT COLLECTION”
COLLECTING DATA- THE BIG PAIN POINT
LONG	FORMS NOT	LEARNING	FROM	USERSNOT	ADDED	VALUE	FROM	INFO1 2 3• Number of fields of information
• Type of fields- UI
• Category of info asked
• Relevance of info versus content
• Non connection between data and benefit
• Feeling of non personalisation
• Asking for info we already should know
• Recurrently asking for the same information
VOLUME OF DATA &
CONSISTENCY OF DATA
MOBILE ADOPTION &
SCREEN LESS EVOLUTION
GDPR - PRIVACY
COLLECTING DATA- THE BIG PAIN POINT
THE CLUE IS…
“GIVE BEFORE OBTAINING”
COLLECTING DATA- THE BIG PAIN POINT
“Users/ customers are overloaded by
information and demands of it…”
So, they approach in front an information demand- form,
call, mail, chat, bot,… is SKEPTICISM!!!
So, every time we try to collect information we should…
PAYS
OFF
IS GOING TO BE
RELEVANT INFO
QUALITY OF THE
COLLECTION
Which is the “driver” that moves
the user/ customer to give us the
information…
Which is the moment we
ask for the information and
how we do it...
Keeping in mind the ”driver” and
the moment... What we’re going to
obtain is differential?...
COLLECTING DATA- THE BIG PAIN POINT
The 4BIG challenges
#
#
#
#
What is the information we need?
Am I able to obtain it?
What is the cost? Does It pay off?
How will we be able to maintain it?
THE
DIFFERENCE
BETWEEN
DATA & INFO
THE DIFFERENCE BETWEEN DATA & INFO
ACCESSING TO HUGE
AMOUNTS OF DATA IS EASY…
WE’RE DATA OVERLOADED
THE DIFFERENCE BETWEEN DATA & INFO
Every day we generate 2.5 quintillion bytes of data…
3.8bPeople connected
5.2b daily Google searches
4M hours of content uploaded to Youtube every day
21.9b daily messages sent
67M daily photos uploaded to Instagram
1.0b daily facebook users
4.3b daily messages posted on Facebook
267b daily mails sent
373M daily Amazon sales
THE DIFFERENCE BETWEEN DATA & INFO
We’re completely
overloaded by data…
In this context it becomes more
relevant to be able to differentiate
data from info, and to choose the
right source of information
https://www.domo.com/learn/data-never-sleeps-5?aid=ogsm072517_1&sf100871281=1
THE DIFFERENCE BETWEEN DATA & INFOTHE DIFFERENCE BETWEEN DATA & INFO
DATA OBSOLESCENCE
90% of available data has
been generated in the last
24 months…
So, it is not only relevant to know which info we want, but to be able to access it…
It is very important to be able to feed from it in a constant mode...
THE DIFFERENCE BETWEEN DATA & INFO
- All big players are trying to take positions in the data access and control -
THE DIFFERENCE BETWEEN DATA & INFO
26.2b US$
Late incomers have to
pay the price for it..
In fact, all players are
afraid of a new incomer...
+2.000M profiles
#1
Worldwide in audience
and consumed online time
THE DIFFERENCE BETWEEN DATA & INFO
They have already won the
space of our private life...
But...
Will they also win the
professional one?
THE DIFFERENCE BETWEEN DATA & INFO
25%Facebook users
search for a job over
the platform
THE DIFFERENCE BETWEEN DATA & INFO
Building a full
ecosystem
around data
acquisition…
THE DIFFERENCE BETWEEN DATA & INFO
From an Aggregator to
Job Board… and from
Job board to full
Recruitment player...
80M CV’s
OBTAIN	THE	CONTENT- PARTNER	AGREEMENTS
SEO	+	SEM
AFFILIATION	PROGRAM
DIRECT	EMPLOYERS	RELATION
ATTRACT	CV’s
BUILD	BRAND
ENGAGE	PRODUCTS
BLOCK	JOB	BOARDS
RECRUITMENT	
SERVICES
ACTING	AS	AN		
AGGREGATOR
ACTING	AS	A	
JOB	BOARD
ACTING	AS	AN	
HR	COMPANY
Evolution inside
the value chain...
THE DIFFERENCE BETWEEN DATA & INFO
THE DIFFERENCE BETWEEN DATA & INFO
“DATA IS ONLY A SEED TO
OBTAIN INFORMATION”
For obtaining
information we need
the combination of
several points of
data…
THE DIFFERENCE BETWEEN DATA & INFO
25ºC
10
-3 35
1520
0 ºC
ºC
ºC
ºC
ºC
ºC
But it is not sufficient…
THE DIFFERENCE BETWEEN DATA & INFO
We need to give context… data when gets context is transformed
and allows us to build an interpretation over it...
CONTEXT A
SUMMER
13PM
SUNNY DAY
CONTEXT B
TEMPERATURE	AT	DIFFERENT	ALTITUDE
PYRENEES
https://www.youtube.com/watch?v=H4SpQqP2zuU
THE DIFFERENCE BETWEEN DATA & INFO
DATA INFOCONTEXT
INTERPRETATION = (S + K) x E
S: SKILLS K:	KNOWLEDGE E:	EXPERIENCE
Once we have an interpretation… we can take a decision...
THE DIFFERENCE BETWEEN DATA & INFO
The	BUS	PARADIGM
80% OF KIDS UNDER 10 YEARS OLD DIDN’T HAVE PROBLEM TO SAY IN WHICH WAY THE BUS GOES…
THE CHALLENGE:
HOW TO FLOW
FROM DATA TO
DECISIONS
HOW TO FLOW FROM DATA TO DECISSIONSHOW TO FLOW FROM DATA TO DECISIONS
VALIDATIONBuilding trust is an essential issue
1
HOW TO FLOW FROM DATA TO DECISIONS
ACCURACYNot finding “Black holes” that put
on doubt the rest of the info
2
HOW TO FLOW FROM DATA TO DECISSIONSHOW TO FLOW FROM DATA TO DECISIONS
PROCESSINGRough data needs to ne “cooked”,
de-duplicated, categorized & standardized…
3
HOW TO FLOW FROM DATA TO DECISIONS
CONSTANT FLOWOnce we build the trust we need to guarantee
the constant access over the data
4
HOW TO FLOW FROM DATA TO DECISIONS
VISUALISATIONThe consumption of information has
to be easy… If we don’t put focus
on it... However the info could be
very useful... It becomes a
showstopper...
5
HOW TO FLOW FROM DATA TO DECISIONS
Help to understand the information, giving
references that make it easy to assume it
6 GIVE CONTEXT
But sometimes...
However much we follow the 6
points... “magic” doesn’t happen...
And this is basically due to a “miss
gap” of the size of the project...
Differential value vs. Complexity
BIG DATA
SPECIFIC
PROBLEMS
SMART
SOLUTIONS
https://www.youtube.com/watch?v=FmMzlehzU8c
SPECIFIC PROBLEMS- SMART SOLUTIONS
DIFFERENTIAL
VALUE
COMPLEXITY/
DIFFICULTY
100%
HIGH RISK
OF FAILURE
NATURAL FORCES
- DATA ANALYSIS PARALYSIS -
SPECIFIC PROBLEMS- SMART SOLUTIONS
APPROACH A
We collect data, but we’ve not defined
a specific problem... So, although we
have sufficient information... We’re
not able to give it a clear value...
LOW VALUE = LOW USE
SPECIFIC PROBLEMS- SMART SOLUTIONS
APPROACH B
We define a huge problem... Which means a big complexity
in terms of time & resources... If we don’t achieve a
tangible output quickly, the project loses traction...
HIGH COMPLEXITY= HIGH CHURN RATE
SPECIFIC PROBLEMS- SMART SOLUTIONS
“When we introduce big data Philosophy/ Methodology inside the
company becomes critical to clearly define objectives &
problems to solve and assume that it is a learning path...”
It’s impossible to go
from blindness to
starlight in 1 jump...
The figure of the CDO
CHIEF DATA OFFICER
“Could be a good catalyser...”
“But if he doesn’t have the empowerment of the
top management and he is not able to give value
to all the levels of the organisation...
Definitely he will fail...”
BIG DATA
APPLIED TO THE
RECRUITMENT
SECTOR
TWO BIG DIFFERENT UNIVERSES
B2BB2C
Depending on the universe the value proposition
based on the data use changes drastically...
TWO BIG DIFFERENT UNIVERSES
B2C APPROACH
The main impact of big
data is related to the
definition of business
models...
PAY
x
PUBLISH
PAY
x
PERFORMANCE
EVOLVING
TWO BIG DIFFERENT UNIVERSES
The supports are not so open to
changing their business
model...
Performance is a less secure
business model than pay & pray
The change is
starting in the
publisher side...
TWO BIG DIFFERENT UNIVERSES
Optimisation of the
exposure of my ads
Obtaining a better distribution of
the investment between platforms
Obtaining a better optimisation of
the investment inside a platform
Obtaining a better optimisation of
the “talent acquisition”
Searching a clear improvement of the
investment in terms of ads x euro
paid or effective distribution
TWO BIG DIFFERENT UNIVERSES
THE THEORY OF THE
GLASS OF WATER
TWO BIG DIFFERENT UNIVERSES
- PROGRAMMATIC ADVERTISING -
TWO BIG DIFFERENT UNIVERSES
PROGRAMMATIC
ADVERTISING
Platforms (SaaS) that apply big data, deep learning and
AI strategies to maximize the return on the investment
of the advertisers
80%
Is expected
that the
Of the jobs will be posted
under this model in 2020
- However it is not a perfect system... -
TWO BIG DIFFERENT UNIVERSES
We’re talking
about people...
We’re talking about
on-boarding them in
our company
The	solution	is	a	little	bit	more	
“tricky”	than	when	we	buy	
visits/	users	to	our	sites...
TWO BIG DIFFERENT UNIVERSES
The solution is a little bit more
“tricky” than when we attract visits
to our site to sell shoes...
HR
“we’re buying talent”
BUSINESS > CONSUMER BUSINESS < CONSUMER$¿ ¿
TWO BIG DIFFERENT UNIVERSES
There is a human
component... That
can be measured
through close fields
of information...
TWO BIG DIFFERENT UNIVERSESTWO BIG DIFFERENT UNIVERSES
“The only way is to share internal info... To
enrich the algorythm... And teach it about what
matches or not with the organisation...”
And always remember...
“WE CAN OPTIMIZE MACHINE LEARNING... BUT WE
CAN’T FORGET HUMANS DON’T ACT AS MACHINES”
TWO BIG DIFFERENT UNIVERSES
Introduces Predictive
Sourcing Tool
“Put your sourcing
on autopilot”
• 500 million candidate profiles,
aggregated from 50+ data sources
• They examine how these profiles
change over time, then use AI to
predict future change. In other
words, the technology uses
candidate activity patterns to
determine how likely someone is
to leave a job, thus, how
“recruitable” the candidate is.
TWO BIG DIFFERENT UNIVERSES
They’re able to analyse emotions
just by watching you...
Through the use of AI-
analysing the look ad
facial factions, they’re
able to detect patterns of
behaviour/ preference/
engagement,...
Once you have this info... You
can take decisions based on the
behaviour
Let’s see it
in Action...
https://www.youtube.com/watch?v=8YD973AbmtM
TWO BIG DIFFERENT UNIVERSES
B2B APPROACH
Is where the big
competence is happening...
All players are fighting
to attract business to
their site... So knowledge
is a competitive advantage
that can make all the
difference...
In fact... Since a long time ago...
The B2B side has tried to apply “big
data” acquisition techniques...
PRESS
SCRAPING
WEB
SCRAPING
APP
SCRAPING
’90’’90’s
’00’s
’10’s
TWO BIG DIFFERENT UNIVERSES
“There is nothing worse for a seller,
not knowing who to call...”
TWO BIG DIFFERENT UNIVERSES
NO LEADS
NO QUALIFIED LEADS
NO MANAGED LEADS
NO PROPOSALS
NO SALES
NO SALES PAID
NO SELLER
NO BUSINESS
NO COMPANY
- It is critical to maintain the wheel turning round -
TWO BIG DIFFERENT UNIVERSES
Market segmentation and lead
discovering is something that,
traditionally, companies have been
doing “doors inside”- in a secret
way, with a lot of hand making a
very tailored to each department...
Knowledge is not flowing easily inside the organisations...
TWO BIG DIFFERENT UNIVERSES
Business based on “hiding
information” are losing sense...
The greatness is that data is
there... Most cases “public”...
And you only have to know how
to access it...
If data is there... And the
use of it is so great...
Why don’t companies
put focus on it?
The 6 main reasons...
TWO BIG DIFFERENT UNIVERSES
TWO BIG DIFFERENT UNIVERSES
MEANS A CHANGE IN THE
WAY OF WORKING...
1st HUMAN REACTION
VERSUS CHANGE IS...
NEGATION
TWO BIG DIFFERENT UNIVERSES
1
TWO BIG DIFFERENT UNIVERSES
2
THERE IS A LACK OF
CONFIDENCE THAT
KNOWLEDGE CAN
COME FROM OUTSIDE
CLOSED MENTALITY
TWO BIG DIFFERENT UNIVERSES
3
LACK OF LEADERSHIP
INTERNAL
DISAGREEMENTS
ABOUT WHO HAS TO
PILOT THE PROJECT
TWO BIG DIFFERENT UNIVERSES
4
WHY TO IMPROVE IF THIS
ALREADY WORKS
WE’RE IN THE MIDDLE OF A
“BLUE OCEAN” WITH
PLENTY OF OPPORTUNITIES
TWO BIG DIFFERENT UNIVERSES
5
LACK OF VISION OF
THE MANAGERS
MANY SALES
DEPARTMENTS ARE STILL
MANAGED IN AN OLD WAY
TWO BIG DIFFERENT UNIVERSES
6
SALES ARE EVOLVING FROM
AN ART TO A SCIENCE
AN EXCESS OF FOCUS ON THE
TACTIC– SPEECH/ CHANNELS
VERSUS STRATEGY
BIG DATA
TRYING TO KILL
THE PARADIGMS
ABOUT IT
LET’S BE HONEST…
HOW MANY OF YOU THINK THAT
SALES HEADCOUNT DECISIONS ARE
BASED ON FEELINGS?
AND HOW MANY DO IT BASED
ON INTERNAL DATA?
LET’S BE HONEST…
HOW MANY OF YOU THINK THAT
SALES OBJECTIVES ARE BASED ON
PAST PERFORMANCE?
WITHOUT KNOWLEDGE OF THE
REMAINING MARKET POTENTIAL...
LET’S BE HONEST…
HOW MANY OF YOU THINK THAT
SELLERS OBTAIN THE 80% OF
THE TOTAL POTENTIAL VALUE OF
THE CUSTOMERS?
THEY REALLY CONTROL CUSTOMER VALUE
TRYING TO KILL PARADIGMS…
OPEN MIND
TRYING TO KILL PARADIGMS…
We have to assume
that we’re blind...And data can show us a new perspective
TRYING TO KILL PARADIGMS…
We have to be prepared...
As data can show our weaknesses…
People don’t like “finger pointing”
TRYING TO KILL PARADIGMS…
We have to be creative
We have to sell the information inside the company
Data is 30%
Information is 40%
Visualisation is 30%
TRYING TO KILL PARADIGMS…
Understand that
data is dynamic…Generates evolutionary ecosystems
BIG DATA
APPLIED TO
OUR
DAY TO DAY
APPLIED TO OUR DAY TO DAY…
THE RULE OF
“COFFEE FOR ALL”
It doesn’t work... Every
hierarchic level of the
organisation should obtain
a specific benefit
APPLIED TO OUR DAY TO DAY…
HIGH ALTITUDE
BUSINESS VIEW
CEO / OWNERS / GENERAL MANAGERS/ VP’s /
MARKET ANALYSTS / INVESTMENT FIRMS /
RESEARCH FIRMS
HOW BIG IS THE MARKET MARKET COMPOSITION MARKET SPLIT
IS THERE A BUSINESS OPPORTUNITY?
APPLIED TO OUR DAY TO DAY…
# What are the top recruiting channels? (free/ paid- offers & advertisers)
# How many companies are posting offers? (recruiting)
# What is the size of the market
- Published offers
- Active offers
# Level of activity of the market (offers x advertiser)
# Content distribution (x category, location, job title, salary,…)
# Advertisers distribution (x category, location, job title, salary,…)
# Top customer profiles (size, split & share of them)
HIGH ALTITUDE BUSINESS VIEW
MARKET: UK
PERIOD: JAN 2018
# Job offers evolution
last 12 months
# Market split by channel
CUSTOMER: INDEED
HIGH ALTITUDE BUSINESS VIEW
MARKET: DE
PERIOD: JAN 2018
# Top advertisers
# Market share versus
market
CUSTOMER: INDEED
HIGH ALTITUDE BUSINESS VIEW
MARKET: UK
PERIOD: Q4 2017
# Category distribution
# Category share
variation
CUSTOMER: INDEED
HIGH ALTITUDE BUSINESS VIEW
MARKET: UK
PERIOD: Q4 2017
# Salary distribution
# Compared to one of
the top players of the
market
CUSTOMER: INDEED
APPLIED TO OUR DAY A DAY…APPLIED TO OUR DAY TO DAY…
BUSINESS
RADIOGRAPHY
BIZ DEVELOPMENT / GROWTH MANAGER / CMO / COO / CSO
/ SALES DIRECTOR / SALES MANAGER / TEAM LEADERS
CUSTOMER SHARE CAPACITY OF GROWTH BUSINESS EVOLUTION
HOW HEALTHY IS OUR BUSINESS
HOW IS
CONTROLLING
A SPECIFIC NICHE
IS THIS NEW PLAYER
REALLY A
COMPETITOR
ARE WE LOOSING
ENGAGEMENT W/
CUSTOMERS
APPLIED TO OUR DAY TO DAY…
# How many companies post with us and how much content?
# Which is our market share?
- Advertisers
- Content
# Trends- evolution over time
- By company
- By location
- By job title
# Share by customer- % of total content and competitive fragmentation
# Share by category, location and job title
# Gain/ lost customers/ categories/ location
# Overlap with other players based on advertisers or offers
BUSINESS RADIOGRAPHY
MARKET: UK
PERIOD: JAN 2018
CUSTOMER: INDEED
# Analysis of the advertising profile of one of the TOP customers of the customer
# Share of customer by channel, and strategic position by category, location and job title
BUSINESS RADIOGRAPHY
MARKET: COL
PERIOD: JAN 2018
# Company distribution
# Compared to the
market… give us
vision of the weight of
the short/ long tail
CUSTOMER: INDEED
BUSINESS RADIOGRAPHY
MARKET: UK
PERIOD: JAN 2018
# Company with
engagement lost
CUSTOMER: INDEED
BUSINESS
DEVELOPMENT
SALES MANAGER / CSO / TEAM LEADERS / SALES TEAM
MISSING
CUSTOMERS
HOT
LEADS
PRIOR
LEADS
APPLIED TO OUR DAY TO DAY…
# How many companies post with us and how much content?
# Which is our market share?
- Advertisers
- Content
# Trends- evolution over time
- By company
- By location
- By job title
# Share by customer- % of total content and competitive fragmentation
# Share by category, location and job title
# Gain/ lost customers/ categories/ location
# Overlap with other players based on advertisers or offers
APPLIED TO OUR DAY TO DAY…
MARKET: UK
PERIOD: JAN 2018
# Hot leads…
vacancies being posted
on paid sites multiple
times with periods of
up to 2 weeks in-
between.
CUSTOMER: INDEED
APPLIED TO OUR DAY TO DAY…
MARKET: UK
PERIOD: JAN 2018
# Missing customers...
Companies that are not
publishing with us...
But YES with other
market players...
# Also gives
information of which of
them were with us in
the last 12 months
CUSTOMER: INDEED
APPLIED TO OUR DAY TO DAY…
MARKET: DE
PERIOD: JAN 2018
CUSTOMER: INDEED
# Potential to grow...
Companies ordered by
potential to grow...
BIG DATA
ONE
STEP
FORWARD
ONE STEP FORWARD…ONE STEP FORWARD
EXTERNAL
SOURCES
TRAFFIC SOURCES
SOCIO-DEMOGRAPHIC
MOBILITY
ECONOMICAL
To evaluate what a leadership position in traffic means
To evaluate the potential of a zone/ region
To evaluate the potential of a segment/ profile/ sector
To evaluate the impact of field sales
One key point is the capacity of evolve easily the ”big data ecosystem”
to adapt it to business needs...
ONE STEP FORWARDONE STEP FORWARD
How we traditionally segment
customers and assign accounts
What traditionally has been known as “swimming
pools”
ONE STEP FORWARD
Are you taking care
of how they’re
using your service?
How we grow
our farm?
ONE STEP FORWARD
But do we know the
potential of the customers?
Do we work with customers with high potential?
Are the higher potential customers assigned to the best sellers?
- THE DYNAMIC ACCOUNT ASSIGMENT -
ONE STEP FORWARD-THEDYNAMICACCOUNTASSIGMENT-
3
STEPS
PROCESS
BLOC 1 BLOC 2 BLOC 3
-COMPANY INFO - - SERVICE USE - - COMPANY POTENTIAL-
COMPANY SIZE
INDUSTRIAL SECTOR
LOCATION
CONTRACT STATUS
Nº OFFER PUBLISH LAST 12M
ACTIVE PRODUCT
LAST LOGIN
LAST PRODUCT BOUGHT
CUSTOMER VALUE (12M LTV)
IS MISSING CUSTOMER
GROWING POTENTIAL
CUSTOMER SHARE
COMPETITORS USE
ALGORITHM
CUSTOMER
VALUE
CUSTOMER
POTENTIAL POTENTIAL
GAP
“Leads/ customers are prioritized based on their
potential GAP and assigned to the seller based on their
capacity of management and conversion scoring…”
Life process… not closed segments... The system
optimizes resources and ROI of sales activity
CONCLUSIONS
CONCLUSIONS Data and the capacity to transform it into
relevant information has become a
critical issue for companies
1
DATA IS
POWER
INFO IS
AUTHORITY
DECISIONS ARE
GREATNESS
CONCLUSIONS All ”Big Data” process landing inside
a company requires…2
# Time
# Clear goals
# All company implication
# Consistent data sources
&... AN OPEN MIND!!!
ABOUT
CHRISTIAN PALAU SANZ
SENIOR STRATEGIC BUSINESS DEVELOPMENT ADVISOR
TELF: +34 620 89 31 62
MAIL: CPALAU@JOBISJOB.COM
SKYPE: CERKDTI
Visit us- www.jobmarketinsights.com

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Workshop- Applying big data to Sales

  • 1. WORKSHOP Applying BIG DATA to SALES - how you can watch your revenue grow by using the right data and measurements BERLIN – FEBRUARY 2018
  • 3. ABOUT THE SPEAKER CHRISTIAN PALAU SANZ PROFILE “ +15 YEARS OF INTERNATIONAL EXPERIENCE IN THE ONLINE CLASSIFIEDS MARKET” COMPUTRABAJO BESTJOBS JOBISJOB FOTOCASA SEGUNDAMANO SCHIBSTED INFOJOBS BRASIL INFOJOBS ITALIA INFOJOBS ESPAÑA EMAGISTER NIUMBAESPACIO DECO MARKETYOU ENALQUILER Associated teacher at Business Schools In-Company Former 2014 – 2017: SVP BUSINESS DEVELOPMENT EN RED ARBOR: COMPUTRABAJO, BESTJOBS, MUBAWAB, INFOJOBS BRASIL 2012 – 2014: CSO/CMO EN JOBISJOB: Job Aggregator and BIG DATA data solution for the HR sector 2018 – TO DATE: SENIOR DIGITAL STRATEGY CONSULTANT 2013 – 2014: INNOVATION DIRECTOR AT ANUNTIS: FOTOCASA, COCHES.NET, SEGUNDAMANO, INFOJOBS, LECTIVA,... 2009 – 2012: FOTOCASA DIRECTOR: Real Estate top Classified site in Spain 2003 – 2009: MARKETING & STRATEGY DIRECTOR AT INFOJOBS ESPAÑA
  • 6. WHAT DOES BIG DATA REALLY MEAN? Extremely big data sets… that need from computational analysis to reveal patterns, trends, associations,.... Data alone, has very limited value... Basically the value of owning it, and not allowing the access to third...- Economy of information hiding. Is needed to process it, to transform it into information that is what really adds value as it is in what business decisions are taken... For processing it... We need technology and context to give sense to the result obtained... Thought 1 Thought 2 Thought 3
  • 9. COLLECTING DATA- THE BIG PAIN POINT THE OBSESSION OF THE “1 SHOT COLLECTION”
  • 10. COLLECTING DATA- THE BIG PAIN POINT LONG FORMS NOT LEARNING FROM USERSNOT ADDED VALUE FROM INFO1 2 3• Number of fields of information • Type of fields- UI • Category of info asked • Relevance of info versus content • Non connection between data and benefit • Feeling of non personalisation • Asking for info we already should know • Recurrently asking for the same information VOLUME OF DATA & CONSISTENCY OF DATA MOBILE ADOPTION & SCREEN LESS EVOLUTION GDPR - PRIVACY
  • 11. COLLECTING DATA- THE BIG PAIN POINT THE CLUE IS… “GIVE BEFORE OBTAINING”
  • 12. COLLECTING DATA- THE BIG PAIN POINT “Users/ customers are overloaded by information and demands of it…” So, they approach in front an information demand- form, call, mail, chat, bot,… is SKEPTICISM!!! So, every time we try to collect information we should… PAYS OFF IS GOING TO BE RELEVANT INFO QUALITY OF THE COLLECTION Which is the “driver” that moves the user/ customer to give us the information… Which is the moment we ask for the information and how we do it... Keeping in mind the ”driver” and the moment... What we’re going to obtain is differential?...
  • 13. COLLECTING DATA- THE BIG PAIN POINT The 4BIG challenges # # # # What is the information we need? Am I able to obtain it? What is the cost? Does It pay off? How will we be able to maintain it?
  • 15. THE DIFFERENCE BETWEEN DATA & INFO ACCESSING TO HUGE AMOUNTS OF DATA IS EASY… WE’RE DATA OVERLOADED
  • 16. THE DIFFERENCE BETWEEN DATA & INFO Every day we generate 2.5 quintillion bytes of data… 3.8bPeople connected 5.2b daily Google searches 4M hours of content uploaded to Youtube every day 21.9b daily messages sent 67M daily photos uploaded to Instagram 1.0b daily facebook users 4.3b daily messages posted on Facebook 267b daily mails sent 373M daily Amazon sales
  • 17. THE DIFFERENCE BETWEEN DATA & INFO We’re completely overloaded by data… In this context it becomes more relevant to be able to differentiate data from info, and to choose the right source of information https://www.domo.com/learn/data-never-sleeps-5?aid=ogsm072517_1&sf100871281=1
  • 18. THE DIFFERENCE BETWEEN DATA & INFOTHE DIFFERENCE BETWEEN DATA & INFO DATA OBSOLESCENCE 90% of available data has been generated in the last 24 months… So, it is not only relevant to know which info we want, but to be able to access it… It is very important to be able to feed from it in a constant mode...
  • 19. THE DIFFERENCE BETWEEN DATA & INFO - All big players are trying to take positions in the data access and control -
  • 20. THE DIFFERENCE BETWEEN DATA & INFO 26.2b US$ Late incomers have to pay the price for it..
  • 21. In fact, all players are afraid of a new incomer... +2.000M profiles #1 Worldwide in audience and consumed online time THE DIFFERENCE BETWEEN DATA & INFO
  • 22. They have already won the space of our private life... But... Will they also win the professional one? THE DIFFERENCE BETWEEN DATA & INFO 25%Facebook users search for a job over the platform
  • 23. THE DIFFERENCE BETWEEN DATA & INFO Building a full ecosystem around data acquisition…
  • 24. THE DIFFERENCE BETWEEN DATA & INFO From an Aggregator to Job Board… and from Job board to full Recruitment player... 80M CV’s
  • 26. THE DIFFERENCE BETWEEN DATA & INFO “DATA IS ONLY A SEED TO OBTAIN INFORMATION” For obtaining information we need the combination of several points of data…
  • 27. THE DIFFERENCE BETWEEN DATA & INFO 25ºC 10 -3 35 1520 0 ºC ºC ºC ºC ºC ºC But it is not sufficient…
  • 28. THE DIFFERENCE BETWEEN DATA & INFO We need to give context… data when gets context is transformed and allows us to build an interpretation over it... CONTEXT A SUMMER 13PM SUNNY DAY CONTEXT B TEMPERATURE AT DIFFERENT ALTITUDE PYRENEES
  • 30. THE DIFFERENCE BETWEEN DATA & INFO DATA INFOCONTEXT INTERPRETATION = (S + K) x E S: SKILLS K: KNOWLEDGE E: EXPERIENCE Once we have an interpretation… we can take a decision...
  • 31. THE DIFFERENCE BETWEEN DATA & INFO The BUS PARADIGM 80% OF KIDS UNDER 10 YEARS OLD DIDN’T HAVE PROBLEM TO SAY IN WHICH WAY THE BUS GOES…
  • 32. THE CHALLENGE: HOW TO FLOW FROM DATA TO DECISIONS
  • 33. HOW TO FLOW FROM DATA TO DECISSIONSHOW TO FLOW FROM DATA TO DECISIONS VALIDATIONBuilding trust is an essential issue 1
  • 34. HOW TO FLOW FROM DATA TO DECISIONS ACCURACYNot finding “Black holes” that put on doubt the rest of the info 2
  • 35. HOW TO FLOW FROM DATA TO DECISSIONSHOW TO FLOW FROM DATA TO DECISIONS PROCESSINGRough data needs to ne “cooked”, de-duplicated, categorized & standardized… 3
  • 36. HOW TO FLOW FROM DATA TO DECISIONS CONSTANT FLOWOnce we build the trust we need to guarantee the constant access over the data 4
  • 37. HOW TO FLOW FROM DATA TO DECISIONS VISUALISATIONThe consumption of information has to be easy… If we don’t put focus on it... However the info could be very useful... It becomes a showstopper... 5
  • 38. HOW TO FLOW FROM DATA TO DECISIONS Help to understand the information, giving references that make it easy to assume it 6 GIVE CONTEXT
  • 39. But sometimes... However much we follow the 6 points... “magic” doesn’t happen... And this is basically due to a “miss gap” of the size of the project... Differential value vs. Complexity
  • 42. SPECIFIC PROBLEMS- SMART SOLUTIONS DIFFERENTIAL VALUE COMPLEXITY/ DIFFICULTY 100% HIGH RISK OF FAILURE NATURAL FORCES - DATA ANALYSIS PARALYSIS -
  • 43. SPECIFIC PROBLEMS- SMART SOLUTIONS APPROACH A We collect data, but we’ve not defined a specific problem... So, although we have sufficient information... We’re not able to give it a clear value... LOW VALUE = LOW USE
  • 44. SPECIFIC PROBLEMS- SMART SOLUTIONS APPROACH B We define a huge problem... Which means a big complexity in terms of time & resources... If we don’t achieve a tangible output quickly, the project loses traction... HIGH COMPLEXITY= HIGH CHURN RATE
  • 45. SPECIFIC PROBLEMS- SMART SOLUTIONS “When we introduce big data Philosophy/ Methodology inside the company becomes critical to clearly define objectives & problems to solve and assume that it is a learning path...” It’s impossible to go from blindness to starlight in 1 jump... The figure of the CDO CHIEF DATA OFFICER “Could be a good catalyser...” “But if he doesn’t have the empowerment of the top management and he is not able to give value to all the levels of the organisation... Definitely he will fail...”
  • 46. BIG DATA APPLIED TO THE RECRUITMENT SECTOR
  • 47. TWO BIG DIFFERENT UNIVERSES B2BB2C Depending on the universe the value proposition based on the data use changes drastically...
  • 48. TWO BIG DIFFERENT UNIVERSES B2C APPROACH The main impact of big data is related to the definition of business models... PAY x PUBLISH PAY x PERFORMANCE EVOLVING
  • 49. TWO BIG DIFFERENT UNIVERSES The supports are not so open to changing their business model... Performance is a less secure business model than pay & pray The change is starting in the publisher side...
  • 50. TWO BIG DIFFERENT UNIVERSES Optimisation of the exposure of my ads Obtaining a better distribution of the investment between platforms Obtaining a better optimisation of the investment inside a platform Obtaining a better optimisation of the “talent acquisition” Searching a clear improvement of the investment in terms of ads x euro paid or effective distribution
  • 51. TWO BIG DIFFERENT UNIVERSES THE THEORY OF THE GLASS OF WATER
  • 52. TWO BIG DIFFERENT UNIVERSES - PROGRAMMATIC ADVERTISING -
  • 53. TWO BIG DIFFERENT UNIVERSES PROGRAMMATIC ADVERTISING Platforms (SaaS) that apply big data, deep learning and AI strategies to maximize the return on the investment of the advertisers 80% Is expected that the Of the jobs will be posted under this model in 2020 - However it is not a perfect system... -
  • 54. TWO BIG DIFFERENT UNIVERSES We’re talking about people... We’re talking about on-boarding them in our company The solution is a little bit more “tricky” than when we buy visits/ users to our sites...
  • 55. TWO BIG DIFFERENT UNIVERSES The solution is a little bit more “tricky” than when we attract visits to our site to sell shoes... HR “we’re buying talent” BUSINESS > CONSUMER BUSINESS < CONSUMER$¿ ¿
  • 56. TWO BIG DIFFERENT UNIVERSES There is a human component... That can be measured through close fields of information...
  • 57. TWO BIG DIFFERENT UNIVERSESTWO BIG DIFFERENT UNIVERSES “The only way is to share internal info... To enrich the algorythm... And teach it about what matches or not with the organisation...” And always remember... “WE CAN OPTIMIZE MACHINE LEARNING... BUT WE CAN’T FORGET HUMANS DON’T ACT AS MACHINES”
  • 58. TWO BIG DIFFERENT UNIVERSES Introduces Predictive Sourcing Tool “Put your sourcing on autopilot” • 500 million candidate profiles, aggregated from 50+ data sources • They examine how these profiles change over time, then use AI to predict future change. In other words, the technology uses candidate activity patterns to determine how likely someone is to leave a job, thus, how “recruitable” the candidate is.
  • 59. TWO BIG DIFFERENT UNIVERSES They’re able to analyse emotions just by watching you... Through the use of AI- analysing the look ad facial factions, they’re able to detect patterns of behaviour/ preference/ engagement,... Once you have this info... You can take decisions based on the behaviour
  • 60. Let’s see it in Action...
  • 62. TWO BIG DIFFERENT UNIVERSES B2B APPROACH Is where the big competence is happening... All players are fighting to attract business to their site... So knowledge is a competitive advantage that can make all the difference...
  • 63. In fact... Since a long time ago... The B2B side has tried to apply “big data” acquisition techniques... PRESS SCRAPING WEB SCRAPING APP SCRAPING ’90’’90’s ’00’s ’10’s TWO BIG DIFFERENT UNIVERSES
  • 64. “There is nothing worse for a seller, not knowing who to call...” TWO BIG DIFFERENT UNIVERSES
  • 65. NO LEADS NO QUALIFIED LEADS NO MANAGED LEADS NO PROPOSALS NO SALES NO SALES PAID NO SELLER NO BUSINESS NO COMPANY - It is critical to maintain the wheel turning round - TWO BIG DIFFERENT UNIVERSES
  • 66. Market segmentation and lead discovering is something that, traditionally, companies have been doing “doors inside”- in a secret way, with a lot of hand making a very tailored to each department... Knowledge is not flowing easily inside the organisations... TWO BIG DIFFERENT UNIVERSES
  • 67. Business based on “hiding information” are losing sense... The greatness is that data is there... Most cases “public”... And you only have to know how to access it...
  • 68. If data is there... And the use of it is so great... Why don’t companies put focus on it? The 6 main reasons... TWO BIG DIFFERENT UNIVERSES
  • 69. TWO BIG DIFFERENT UNIVERSES MEANS A CHANGE IN THE WAY OF WORKING... 1st HUMAN REACTION VERSUS CHANGE IS... NEGATION TWO BIG DIFFERENT UNIVERSES 1
  • 70. TWO BIG DIFFERENT UNIVERSES 2 THERE IS A LACK OF CONFIDENCE THAT KNOWLEDGE CAN COME FROM OUTSIDE CLOSED MENTALITY
  • 71. TWO BIG DIFFERENT UNIVERSES 3 LACK OF LEADERSHIP INTERNAL DISAGREEMENTS ABOUT WHO HAS TO PILOT THE PROJECT
  • 72. TWO BIG DIFFERENT UNIVERSES 4 WHY TO IMPROVE IF THIS ALREADY WORKS WE’RE IN THE MIDDLE OF A “BLUE OCEAN” WITH PLENTY OF OPPORTUNITIES
  • 73. TWO BIG DIFFERENT UNIVERSES 5 LACK OF VISION OF THE MANAGERS MANY SALES DEPARTMENTS ARE STILL MANAGED IN AN OLD WAY
  • 74. TWO BIG DIFFERENT UNIVERSES 6 SALES ARE EVOLVING FROM AN ART TO A SCIENCE AN EXCESS OF FOCUS ON THE TACTIC– SPEECH/ CHANNELS VERSUS STRATEGY
  • 75. BIG DATA TRYING TO KILL THE PARADIGMS ABOUT IT
  • 76. LET’S BE HONEST… HOW MANY OF YOU THINK THAT SALES HEADCOUNT DECISIONS ARE BASED ON FEELINGS? AND HOW MANY DO IT BASED ON INTERNAL DATA?
  • 77. LET’S BE HONEST… HOW MANY OF YOU THINK THAT SALES OBJECTIVES ARE BASED ON PAST PERFORMANCE? WITHOUT KNOWLEDGE OF THE REMAINING MARKET POTENTIAL...
  • 78. LET’S BE HONEST… HOW MANY OF YOU THINK THAT SELLERS OBTAIN THE 80% OF THE TOTAL POTENTIAL VALUE OF THE CUSTOMERS? THEY REALLY CONTROL CUSTOMER VALUE
  • 79. TRYING TO KILL PARADIGMS… OPEN MIND
  • 80. TRYING TO KILL PARADIGMS… We have to assume that we’re blind...And data can show us a new perspective
  • 81. TRYING TO KILL PARADIGMS… We have to be prepared... As data can show our weaknesses… People don’t like “finger pointing”
  • 82. TRYING TO KILL PARADIGMS… We have to be creative We have to sell the information inside the company Data is 30% Information is 40% Visualisation is 30%
  • 83. TRYING TO KILL PARADIGMS… Understand that data is dynamic…Generates evolutionary ecosystems
  • 85. APPLIED TO OUR DAY TO DAY… THE RULE OF “COFFEE FOR ALL” It doesn’t work... Every hierarchic level of the organisation should obtain a specific benefit
  • 86. APPLIED TO OUR DAY TO DAY… HIGH ALTITUDE BUSINESS VIEW CEO / OWNERS / GENERAL MANAGERS/ VP’s / MARKET ANALYSTS / INVESTMENT FIRMS / RESEARCH FIRMS HOW BIG IS THE MARKET MARKET COMPOSITION MARKET SPLIT IS THERE A BUSINESS OPPORTUNITY?
  • 87. APPLIED TO OUR DAY TO DAY… # What are the top recruiting channels? (free/ paid- offers & advertisers) # How many companies are posting offers? (recruiting) # What is the size of the market - Published offers - Active offers # Level of activity of the market (offers x advertiser) # Content distribution (x category, location, job title, salary,…) # Advertisers distribution (x category, location, job title, salary,…) # Top customer profiles (size, split & share of them)
  • 88. HIGH ALTITUDE BUSINESS VIEW MARKET: UK PERIOD: JAN 2018 # Job offers evolution last 12 months # Market split by channel CUSTOMER: INDEED
  • 89. HIGH ALTITUDE BUSINESS VIEW MARKET: DE PERIOD: JAN 2018 # Top advertisers # Market share versus market CUSTOMER: INDEED
  • 90. HIGH ALTITUDE BUSINESS VIEW MARKET: UK PERIOD: Q4 2017 # Category distribution # Category share variation CUSTOMER: INDEED
  • 91. HIGH ALTITUDE BUSINESS VIEW MARKET: UK PERIOD: Q4 2017 # Salary distribution # Compared to one of the top players of the market CUSTOMER: INDEED
  • 92. APPLIED TO OUR DAY A DAY…APPLIED TO OUR DAY TO DAY… BUSINESS RADIOGRAPHY BIZ DEVELOPMENT / GROWTH MANAGER / CMO / COO / CSO / SALES DIRECTOR / SALES MANAGER / TEAM LEADERS CUSTOMER SHARE CAPACITY OF GROWTH BUSINESS EVOLUTION HOW HEALTHY IS OUR BUSINESS HOW IS CONTROLLING A SPECIFIC NICHE IS THIS NEW PLAYER REALLY A COMPETITOR ARE WE LOOSING ENGAGEMENT W/ CUSTOMERS
  • 93. APPLIED TO OUR DAY TO DAY… # How many companies post with us and how much content? # Which is our market share? - Advertisers - Content # Trends- evolution over time - By company - By location - By job title # Share by customer- % of total content and competitive fragmentation # Share by category, location and job title # Gain/ lost customers/ categories/ location # Overlap with other players based on advertisers or offers
  • 94. BUSINESS RADIOGRAPHY MARKET: UK PERIOD: JAN 2018 CUSTOMER: INDEED # Analysis of the advertising profile of one of the TOP customers of the customer # Share of customer by channel, and strategic position by category, location and job title
  • 95. BUSINESS RADIOGRAPHY MARKET: COL PERIOD: JAN 2018 # Company distribution # Compared to the market… give us vision of the weight of the short/ long tail CUSTOMER: INDEED
  • 96. BUSINESS RADIOGRAPHY MARKET: UK PERIOD: JAN 2018 # Company with engagement lost CUSTOMER: INDEED
  • 97. BUSINESS DEVELOPMENT SALES MANAGER / CSO / TEAM LEADERS / SALES TEAM MISSING CUSTOMERS HOT LEADS PRIOR LEADS
  • 98. APPLIED TO OUR DAY TO DAY… # How many companies post with us and how much content? # Which is our market share? - Advertisers - Content # Trends- evolution over time - By company - By location - By job title # Share by customer- % of total content and competitive fragmentation # Share by category, location and job title # Gain/ lost customers/ categories/ location # Overlap with other players based on advertisers or offers
  • 99. APPLIED TO OUR DAY TO DAY… MARKET: UK PERIOD: JAN 2018 # Hot leads… vacancies being posted on paid sites multiple times with periods of up to 2 weeks in- between. CUSTOMER: INDEED
  • 100. APPLIED TO OUR DAY TO DAY… MARKET: UK PERIOD: JAN 2018 # Missing customers... Companies that are not publishing with us... But YES with other market players... # Also gives information of which of them were with us in the last 12 months CUSTOMER: INDEED
  • 101. APPLIED TO OUR DAY TO DAY… MARKET: DE PERIOD: JAN 2018 CUSTOMER: INDEED # Potential to grow... Companies ordered by potential to grow...
  • 103. ONE STEP FORWARD…ONE STEP FORWARD EXTERNAL SOURCES TRAFFIC SOURCES SOCIO-DEMOGRAPHIC MOBILITY ECONOMICAL To evaluate what a leadership position in traffic means To evaluate the potential of a zone/ region To evaluate the potential of a segment/ profile/ sector To evaluate the impact of field sales One key point is the capacity of evolve easily the ”big data ecosystem” to adapt it to business needs...
  • 104. ONE STEP FORWARDONE STEP FORWARD How we traditionally segment customers and assign accounts What traditionally has been known as “swimming pools”
  • 105. ONE STEP FORWARD Are you taking care of how they’re using your service? How we grow our farm?
  • 106. ONE STEP FORWARD But do we know the potential of the customers? Do we work with customers with high potential? Are the higher potential customers assigned to the best sellers? - THE DYNAMIC ACCOUNT ASSIGMENT -
  • 107. ONE STEP FORWARD-THEDYNAMICACCOUNTASSIGMENT- 3 STEPS PROCESS BLOC 1 BLOC 2 BLOC 3 -COMPANY INFO - - SERVICE USE - - COMPANY POTENTIAL- COMPANY SIZE INDUSTRIAL SECTOR LOCATION CONTRACT STATUS Nº OFFER PUBLISH LAST 12M ACTIVE PRODUCT LAST LOGIN LAST PRODUCT BOUGHT CUSTOMER VALUE (12M LTV) IS MISSING CUSTOMER GROWING POTENTIAL CUSTOMER SHARE COMPETITORS USE ALGORITHM CUSTOMER VALUE CUSTOMER POTENTIAL POTENTIAL GAP “Leads/ customers are prioritized based on their potential GAP and assigned to the seller based on their capacity of management and conversion scoring…” Life process… not closed segments... The system optimizes resources and ROI of sales activity
  • 109. CONCLUSIONS Data and the capacity to transform it into relevant information has become a critical issue for companies 1 DATA IS POWER INFO IS AUTHORITY DECISIONS ARE GREATNESS
  • 110. CONCLUSIONS All ”Big Data” process landing inside a company requires…2 # Time # Clear goals # All company implication # Consistent data sources &... AN OPEN MIND!!!
  • 111. ABOUT
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  • 117. CHRISTIAN PALAU SANZ SENIOR STRATEGIC BUSINESS DEVELOPMENT ADVISOR TELF: +34 620 89 31 62 MAIL: CPALAU@JOBISJOB.COM SKYPE: CERKDTI Visit us- www.jobmarketinsights.com