SlideShare a Scribd company logo
1 of 132
Marketing in the Semantic Web
(“Semantic Marketing” / “Data Web Marketing”)


             Semantic Technology Conference
                     June 16, 2009




                    Scott Brinker
                    Marketing Technologist

                    Email: sbrinker@chiefmartec.com
                    Twitter: @chiefmartec
                    Blog: http://www.chiefmartec.com
Deafening silence
    Sweet sorrow
  Controlled chaos
   Organized mess
    Open secret
   Same difference
      Civil war
   Forward retreat
     Living dead

Semantic marketing
What will marketing be like
    in the semantic web? *

* Depends on your definition of “marketing” and “semantic web”.
Official definition of marketing
from the American Marketing Association web site



 Marketing is the activity, set of institutions,
 and processes for creating, communicating,
 delivering, and exchanging offers that have
 value for customers, clients, partners, and
 society at large.

 (Approved October 2007)
Informal definition of marketing
from the top of my head


Marketing is what you do to find
and win new customers, grow
your relationships with existing
customers, differentiate yourself
from the competition, and build a
“brand” that helps achieve those
goals.
Peter Drucker on marketing
                                      the father of modern management *



     Because the purpose of business is to
create a customer, the business enterprise
has two — and only two — basic functions:
              marketing and innovation.


  * Drucker argued in a 1984 essay that CEO compensation should be no
more than 20 times what the rank and file make — especially at companies
     where thousands of employees are being laid off. “This is morally and
      socially unforgivable,” he wrote, “and we will pay a heavy price for it.”
Marketing is continually evolving.
              In recent years, that evolution
              has been accelerating — with
              more changes ahead.
Marketing as a mission
spans the specific tactics
 by which it is executed.
Marketing tactics,
circa 1900
Marketing tactics,
circa 2000
100 years of
 progress?
Emerging marketing
tactics, circa 2009


              $1.4 billion of
              SEO in 2008




             1,254 APIs and
             3,852 mashups
Search engine optimization (SEO)
 and web APIs for mashups are a
   qualitatively different kind of
         marketing tactic.
Even
across
              …previous
shifts in
               marketing
medium…
                  tactics
                    were
                 crafted
                 directly
                      for
                 human
            consumption.
These new tactics are different.

  1st order:
  Directly crafted for computer
  consumption.

  2nd order:
  Indirectly crafted for human
  consumption.
This opens the
       door to
      data web
    marketing.
What is the semantic web?
                         from the W3C web site

        The Semantic Web is a web of data.

      The Semantic Web is about two things.
             It is about common formats for
              integration and combination
                  of data drawn from diverse
                    sources… It is also about
                      language for recording
                          how data relates to
                           real world objects.
iro•ny, noun, ˈī rə-
                -
nē:
Debating the
meaning of
“semantic web”.
What is the semantic web?
3 broad spheres



                           Document
                         Disambiguation




                  Structured          Linked
                     Data              Data
• Semantic technology that
                           doesn’t necessarily require
      Document             publisher cooperation
    Disambiguation
                         • Advances in text analysis for
                           context and sentiment

                         • “Semantic advertising”
                           (popular interpretation)

                         • Usually invisible to end-user

                         • Top-down semantic web

                         • Here today

…no fundamental change to marketing behavior, however.
Semantic marketing is about data
  —and the spread of that data.



       Structured   Linked
          Data       Data
Semantic Marketing
        =
Data Web Marketing

        * Is this a better name for it?
Marketing
 loves
  data.
…but it has only flowed in.




                •   CRM
                •   Point-of-Sale
                •   Market research
                •   Web analytics
…really flowed in.
Semantic technology can help
organize this data… but again, no
fundamental change to marketing.
Data web marketing is
about data flowing out.



            A simple yet
            revolutionary change
            in perspective.
Instead of data from the channel…




         Data is the
          channel.
Marketing
will make
data sexy.
Why should
marketing lead
the charge for
data web
adoption?
Somebody
needs to
consistently
beat the drum
for data web
initiatives.
Somebody needs to fund data web
support as an ongoing
commitment.
Who has the incentive?
If the data web can be
used to:
• help connect to new customers
• strengthen relationships
• differentiate from the competition
• build reputation and brand
Who does that align with?
Informal definition of marketing
from the top of my head


Marketing is what you do to find
and win new customers, grow
your relationships with existing
customers, differentiate yourself
from the competition, and build a
“brand” that helps achieve those
goals.
Marketing is willing
to experiment to
achieve its goals.
If marketing can tie the cause-and-
effect of data web initiatives to the
achievement of its objectives…




…there’s sustainable sponsorship.
Marketing
success will
cause business
to embrace the
data web.
So what exactly
should marketing
doin the dataweb?
Missions for
marketing in
the data web.
7 missions of data web marketing:
1. Champion production of data for external consumption.

2. Drive semantic/data branding across the organization.

3. Distribute and promote your data. (SEO++)

4. Convert data web initiatives into business relationships.

5. Track and attribute semantic/data web initiatives.

6. Make your own data mash-ups.

7. Control data quality and protect data/brand standards.
#1.
 Champion
 production
 of data for
  external
consumption.
Not just “brochure data.”
Not (primarily) pricing data.
Semantic “bargain hunter”
agents are not attractive to
most marketers.

      That vision of the
         semantic web is
              dystopian to
                   marketers.
Marketing is all about avoiding
commoditization.
• Price isn’t everything.
• Only one lowest-cost provider.
• Race to the bottom dynamics.
• Specs aren’t everything.
• Relationships have value.
• Quality matters.
• Context matters.
• Service matters.
• Trust matters a lot.
Pricing and product
specifications don’t do
justice to the potential
of sharing data in the
semantic web.
Discover data that is
valuable in:
• Domain of your expertise
• Domain of your partners’ expertise
• Domain of your customers’ expertise
• Application of your product/service
• Integration of your product/service
• Benchmarking related results
“You should take an inventory of what you
have got in the way of data, and you should
think about how valuable each piece of data
in the company would be if it were available
to other people across the company, or if it
were available publicly, and if it were
available to your partners.”
     — Tim Berners-Lee in Talis 2008 interview, answering the question
       from a CIO, “what does it mean, what should we do?”
Content Data is King
Ways to produce valuable data:

• Generate it internally
• Collect it from customers
• Collect it from partners
• License it externally
Thinking about
this kind of
data is hard —
because it’s
not been done
before.

But that’s the
opportunity.
Hypothetical example:
Major chain of nurseries producing the leading
reference of plant properties (climate, growth,
soil, water, feeding, compatibility, etc.) —
maybe specialized for a particular region.
Hypothetical example:

Marketing software company
aggregates performance data
across customers to offer
real-time industry
benchmarks.



                    (With permissions of
                    participants, of course.)
Look to
existing
“mash-up”
APIs as
inspiration for
data web
ideas.
Goals:
• Become the authoritative source.
• Popularize canonical references
  to your products, categories,
  competitive dimensions.
• Build reputation,
  goodwill,
  brand.
#2.
    Drive
semantic/data
  branding
 across the
organization.
Framing data with the right metadata
— your data brand standards:

• Establish canonical URIs for products, properties.
• Establish the organizing ontologies.
• Determine the ideal granularity of data structures.
• Embrace and extend existing external standards.
• Encourage data linking in the organization (DRY).
• Lobby for standards beyond your organization.
• Maintain and evolve this architecture.
Building for
linked data is
an art.
Linked data success depends on:
             • Consistency
               • Logical organization
                 • Stability
                    • Trust

                 Data consumers must be
                 able to rely upon your data
                 to use it as a foundation for
                 their own applications.
Ontology
   as
Strategy
Goal:
Shaping the
conversation in
your market
space.
Semantic spin
Framing references
with properties and
nomenclature that
are advantageous
to your brand.
Do the names of things
really matter that much?
Ask these brands:
Our
company is
 redefining
the market.

              A more literal
              interpretation of an
              old hype line.
First mover
advantage.
Authoritative
 references generate a
positive feedback loop,
    a virtuous cycle.
Gender bias in the semantic web?
     A kind of semantic branding.




         http://www.readwriteweb.com/archives/
         will_the_semantic_web_have_a_g.php
There are fascinating parallels between
the concept of brands and the semantic
web… but that’s a story for another day.




    http://www.chiefmartec.com/2008/03/brand-and-the-s.html
#3. Distribute and promote
    your data. (SEO++)
Just as SEO was about visibility
(and ranking and authority) in the
document web…
                  …there will be
                  an analogous
                  need in the
                  data web.
SEO++
       because it’s an
       incremental
       evolution of
       SEO practices
       now focused on
       data objects.

Alternatives:
Semantic Web Optimization (SWO)
Data Web Optimization (DWO)
Spreading your data:
• Build external links to your data
• Link reciprocally to other data
• Increase the findability of your data
• Optimize the format of your data
• Shape and adopt standards
• Promote your data in other channels
As with SEO, this
mission will require
continual nurturing.
You want to join the data graph.
You want your data to be utilized.
You want your data to help others
 find you.




For example, embedding data into your primary web site, such
as for Google Rich Snippets and Yahoo! Search Monkey.
And that’s going to
get harder as more
data comes online.
Surface web:
167 terabytes

Deep web:
91,000 terabytes

545-to-one
Bridge your
data with others
in semantic
communities
(data networks).
                   Networks:
                    • Global
                    • Vertical
                    • Private
Provide the glue to
connect to these
different networks.

This will probably be a
little messy for a while.
A new kind of semantic advertising




          Paid inclusion in other
        authoritative data networks.



      A.K.A.
 data advertising
Hypothetical example
semantic advertising
(data advertising)
                            semantic advertising
                              (paid inclusion)
I just made this idea up,
so whether or not Calais
actually does something
like this is purely
coincidental.




                            Sponsored
                               data
Goals:
• Include your data in more places
• Get links to your data in more places
• Win more overall visibility/authority
Data web marketing services
 are a logical evolution for
      search agencies.
#4.
 Convert data
web initiatives
into business
relationships.
Information
asymmetry
will still be
alive and
well.




Data web marketing must strategically decide
how much to share, when, and with whom.
Some data may be
better harnessed as
an incentive for
other business
goals:

• Become a subscriber
• Become a lead
• Become a partner
• Become a customer
• Become a data buyer
A continuum of data access choices.
          access if
          you pay
  value



                      access if
                      you qualify

                                    access if
                                    you sign-up




                                                       free
                                                       access

                                        availability
Data for nothing and links for free.
          (the SEO++ approach)




                         Capturing value via
                        visibility and authority.
Restricted “members only” data.
Exchange of value in permission
marketing, or an added benefit to
customers and partners.

Capturing value via lead
generation and customer
acquisition/retention.
Data as a direct revenue source.
           • Data more pragmatic in standardized format.
            • Paid data access as a stand-alone business.
             • Paid data access as a “add-on” business.




                               Capturing value
                               the old-fashioned
                               way: people pay
                               for it.
Balancing the
trade-offs in
data value
capture is a
marketing
decision.
Multiple “data packaging” options.
The same underlying data may be
packaged differently depending on
access level:
 • Granularity of data.
 • Depth of data.
 • Breadth of data.
 • “Freshness” of data.
Goal:
Harness the
value in
your data.
#5.
  Track and
   attribute
semantic/dataw
 eb initiatives.


                   “data web analytics”
How do you measure the
success of semantic
web/data web initiatives?

What are the right metrics?
Different than web analytics because…




…clients are not necessarily browsers.
Cookies—a staple of web analytics—may
not be as prevalent in data access tracking.
Referrer—a staple of web analytics—may
not be as prevalent in data access tracking.
Tracking is also
going to be hard
due to mashing
and caching.
How is data used
and redistributed
once someone gets
it from you?
Count subscribers to data feeds
or visits to URIs.




              • Measures 1st-order reach.
              • Measures frequency of access.
              • Measures new vs. repeat access.
              • But maybe limited to IP address.
Time-sensitive or frequently updated data
 is one way to encourage more visits to
              gauge usage.
Count inbound links to your URIs.




                • Measure authority (DataRank).
                • Measure findability.
                • Limited by who indexes you.
New methods of
tracking and
attribution?

Particularly
among
cooperative
parties?
Inspiration from Daniel Weitzner (MIT) and the policy-aware
web (PAW).
Goals:
• Discovering what data is popular.
• Discovering
  who your data
  audience is.
• Discovering how
  your audience
  uses that data.
• Keeping track of competitors
  and comparable benchmarks.
#6.
  Make
your own
  data
mashups.
Data web fluency is something
you learn by doing.




You must use data to understand how to use data.
Applications and mash-ups are where
 data surfaces into the visible web.
Leveraging data in
your own value-add
mash-ups.
          • For prospects
          • For customers
          • For partners
          • For internal use




                mashable
                marketing
Mash-ups for prospects
and customers.



To assist, educate,
entertain, orinform.
Mash-ups beyond Google Maps.
Mash-ups for internal use.
            • Market research
            • Customer monitoring
            • Marketing operations
Competitive intelligence mash-ups.




                Uncovering the pros and cons of
                data web marketing.
Opportunities for “joint venture”
data web initiatives — your
chocolate with someone else’s
peanut butter (exclusively?).
Goals:
• Cool applications for your customers.
• Advanced your own internal operations.
• By doing the above, better understand
  how data is consumed
  to be better at
  producing
  it.
#7.
Control data
quality and
   protect
 data/brand
 standards.
          “semantic police”
Data web marketing won’t be magic.
• Coordination challenges with distributed data management.
• Rules about what can be shared, when and with whom.
• Maintaining the accuracy of data (i.e., data entropy).
• Refereeing conflicting data silos coming together.
• Enforcing data brand standards.
Legal
questions:

Do we have the right
to share certain data?
What are the liabilities
from sharing data?
Does sharing certain data
constitute a risk to our
intellectual property?
“Marketing”
     Determining
     how much data
     to share…


              …or not to share.
“Legal”
Agreement on data standards may
be contentious among stakeholders.
When data was in
silos, inherently fewer
conflicts. As data web
marketing grows, this will
become a larger issue.
Remove bad or
  expired data.




It’s much more unattractive
when the public has come in
for U-pick-it data.
Detect misuse
and data theft.
Goal:
Achieve balance between
openness vs.
protection, distributed vs.
controlled, standardized
vs. loosely-coupled data
relationships.
7 missions of data web marketing:
1. Champion production of data for external consumption.

2. Drive semantic/data branding across the organization.

3. Distribute and promote your data. (SEO++)

4. Convert data web initiatives into business relationships.

5. Track and attribute semantic/data web initiatives.

6. Make your own data mash-ups.

7. Control data quality and protect data/brand standards.
Web 3.0 = Data Web 1.0
A more technical future for marketing?
                A role for “marketing technologists”
                in the organizational DNA of the
                marketing department & agencies.

                             The new leaders of
                             data web marketing?
Thank you for running this
marathon presentation with me.




    Scott Brinker
    Marketing Technologist

    Email: sbrinker@chiefmartec.com
    Twitter: @chiefmartec
    Blog: http://www.chiefmartec.com

More Related Content

What's hot

Tools for blue ocean strategy
Tools for  blue ocean strategyTools for  blue ocean strategy
Tools for blue ocean strategyLee Oi Wah
 
Product management and product life cycle
Product management and product life cycleProduct management and product life cycle
Product management and product life cycleDr. J. Jayapradha Varma
 
V47 Ch15 Designing And Managing Integrated Marketing Channels
V47 Ch15 Designing And Managing Integrated Marketing ChannelsV47 Ch15 Designing And Managing Integrated Marketing Channels
V47 Ch15 Designing And Managing Integrated Marketing ChannelsBriton33
 
EVOLUTION OF MARKETING CONCEPT
EVOLUTION OF MARKETING CONCEPTEVOLUTION OF MARKETING CONCEPT
EVOLUTION OF MARKETING CONCEPTSujeet TAMBE
 
Sales management
Sales managementSales management
Sales managementGurjit
 
Chapter 1 Marketing Management
Chapter 1 Marketing ManagementChapter 1 Marketing Management
Chapter 1 Marketing ManagementPeleZain
 
Case study on 4 p's
Case study on 4 p'sCase study on 4 p's
Case study on 4 p'sIMCOST
 
Marketing mix Place
 Marketing mix Place Marketing mix Place
Marketing mix PlaceManish Kumar
 
Personal selling
Personal sellingPersonal selling
Personal sellingGaurav Jain
 
Product and brand managment
Product and brand managmentProduct and brand managment
Product and brand managmentHamid Hussain
 
Product Management Roles - Briefly Explained
Product Management Roles - Briefly ExplainedProduct Management Roles - Briefly Explained
Product Management Roles - Briefly ExplainedBrainmates Pty Limited
 

What's hot (20)

Chapter 5 Product Strategy
Chapter 5   Product StrategyChapter 5   Product Strategy
Chapter 5 Product Strategy
 
Solomon
SolomonSolomon
Solomon
 
Tools for blue ocean strategy
Tools for  blue ocean strategyTools for  blue ocean strategy
Tools for blue ocean strategy
 
Product management and product life cycle
Product management and product life cycleProduct management and product life cycle
Product management and product life cycle
 
Consumer Behavior Chapter 2
Consumer Behavior Chapter 2Consumer Behavior Chapter 2
Consumer Behavior Chapter 2
 
Sales management
Sales managementSales management
Sales management
 
V47 Ch15 Designing And Managing Integrated Marketing Channels
V47 Ch15 Designing And Managing Integrated Marketing ChannelsV47 Ch15 Designing And Managing Integrated Marketing Channels
V47 Ch15 Designing And Managing Integrated Marketing Channels
 
Marketing strategy
Marketing strategyMarketing strategy
Marketing strategy
 
EVOLUTION OF MARKETING CONCEPT
EVOLUTION OF MARKETING CONCEPTEVOLUTION OF MARKETING CONCEPT
EVOLUTION OF MARKETING CONCEPT
 
Marketing Management
Marketing ManagementMarketing Management
Marketing Management
 
Sales management
Sales managementSales management
Sales management
 
Chapter 1 Marketing Management
Chapter 1 Marketing ManagementChapter 1 Marketing Management
Chapter 1 Marketing Management
 
Case study on 4 p's
Case study on 4 p'sCase study on 4 p's
Case study on 4 p's
 
Competitive Dynamics
Competitive DynamicsCompetitive Dynamics
Competitive Dynamics
 
Marketing mix Place
 Marketing mix Place Marketing mix Place
Marketing mix Place
 
Distribution strategy
Distribution strategyDistribution strategy
Distribution strategy
 
Competitor analysis
Competitor analysis Competitor analysis
Competitor analysis
 
Personal selling
Personal sellingPersonal selling
Personal selling
 
Product and brand managment
Product and brand managmentProduct and brand managment
Product and brand managment
 
Product Management Roles - Briefly Explained
Product Management Roles - Briefly ExplainedProduct Management Roles - Briefly Explained
Product Management Roles - Briefly Explained
 

Viewers also liked

Strategic Web Marketing
Strategic Web MarketingStrategic Web Marketing
Strategic Web MarketingRand Fishkin
 
Web 3.0 The Semantic Web
Web 3.0 The Semantic WebWeb 3.0 The Semantic Web
Web 3.0 The Semantic WebHatem Mahmoud
 
Webinar: It Is Good To Be First To Market - True or False
Webinar: It Is Good To Be First To Market - True or FalseWebinar: It Is Good To Be First To Market - True or False
Webinar: It Is Good To Be First To Market - True or FalseAli Zeeshan
 
Semtech a travel strategy for semantic technology 060611
Semtech   a travel strategy for semantic technology 060611Semtech   a travel strategy for semantic technology 060611
Semtech a travel strategy for semantic technology 060611thematixpartners
 
Hoja.inscripcion.clases.ingles.aux.2012
Hoja.inscripcion.clases.ingles.aux.2012Hoja.inscripcion.clases.ingles.aux.2012
Hoja.inscripcion.clases.ingles.aux.2012ampaelsol
 
Goldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizieren
Goldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizierenGoldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizieren
Goldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizierenGoldbach Group AG
 
Redes Sociales
Redes SocialesRedes Sociales
Redes Socialeskarlayc
 
T E M A 1 Antigo RéXime
T E M A 1  Antigo  RéXimeT E M A 1  Antigo  RéXime
T E M A 1 Antigo RéXimecamposseijo
 
La carmelina isla gourmet lau
La carmelina isla gourmet lauLa carmelina isla gourmet lau
La carmelina isla gourmet lauLaura Rosas
 
Presentation för SFI Bollnäs
Presentation för SFI BollnäsPresentation för SFI Bollnäs
Presentation för SFI BollnäsNiklas Östlund
 
Presentación Makyre Eventos
Presentación Makyre EventosPresentación Makyre Eventos
Presentación Makyre EventosCIT Marbella
 
Trabajo escrito
Trabajo escritoTrabajo escrito
Trabajo escritonatalia
 
Projekt Atelier Haskovec Navrhy A Realizace 2002az2008
Projekt Atelier Haskovec  Navrhy A Realizace 2002az2008Projekt Atelier Haskovec  Navrhy A Realizace 2002az2008
Projekt Atelier Haskovec Navrhy A Realizace 2002az2008Beata Haškovcová
 

Viewers also liked (20)

Online Marketing PPT
Online Marketing PPTOnline Marketing PPT
Online Marketing PPT
 
Strategic Web Marketing
Strategic Web MarketingStrategic Web Marketing
Strategic Web Marketing
 
Web 3.0 The Semantic Web
Web 3.0 The Semantic WebWeb 3.0 The Semantic Web
Web 3.0 The Semantic Web
 
Webinar: It Is Good To Be First To Market - True or False
Webinar: It Is Good To Be First To Market - True or FalseWebinar: It Is Good To Be First To Market - True or False
Webinar: It Is Good To Be First To Market - True or False
 
Semtech a travel strategy for semantic technology 060611
Semtech   a travel strategy for semantic technology 060611Semtech   a travel strategy for semantic technology 060611
Semtech a travel strategy for semantic technology 060611
 
Horarios Vigo.
Horarios Vigo.Horarios Vigo.
Horarios Vigo.
 
Hoja.inscripcion.clases.ingles.aux.2012
Hoja.inscripcion.clases.ingles.aux.2012Hoja.inscripcion.clases.ingles.aux.2012
Hoja.inscripcion.clases.ingles.aux.2012
 
Facelets
FaceletsFacelets
Facelets
 
Goldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizieren
Goldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizierenGoldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizieren
Goldbach Seminar: Converged Media - Erfolgreich im Social Web kommunizieren
 
Redes Sociales
Redes SocialesRedes Sociales
Redes Sociales
 
Marcel Claude: Trayectoria
Marcel Claude: TrayectoriaMarcel Claude: Trayectoria
Marcel Claude: Trayectoria
 
T E M A 1 Antigo RéXime
T E M A 1  Antigo  RéXimeT E M A 1  Antigo  RéXime
T E M A 1 Antigo RéXime
 
La carmelina isla gourmet lau
La carmelina isla gourmet lauLa carmelina isla gourmet lau
La carmelina isla gourmet lau
 
Presentation för SFI Bollnäs
Presentation för SFI BollnäsPresentation för SFI Bollnäs
Presentation för SFI Bollnäs
 
Presentación Makyre Eventos
Presentación Makyre EventosPresentación Makyre Eventos
Presentación Makyre Eventos
 
Folleto informativo Estudio Busca Talento
Folleto informativo Estudio Busca TalentoFolleto informativo Estudio Busca Talento
Folleto informativo Estudio Busca Talento
 
Trabajo escrito
Trabajo escritoTrabajo escrito
Trabajo escrito
 
Q80240
Q80240Q80240
Q80240
 
Projekt Atelier Haskovec Navrhy A Realizace 2002az2008
Projekt Atelier Haskovec  Navrhy A Realizace 2002az2008Projekt Atelier Haskovec  Navrhy A Realizace 2002az2008
Projekt Atelier Haskovec Navrhy A Realizace 2002az2008
 
Warehousing
WarehousingWarehousing
Warehousing
 

Similar to Data Web Marketing

360i Report: Big Data
360i Report: Big Data360i Report: Big Data
360i Report: Big Data360i
 
Omma metrics yuchun_lee
Omma metrics yuchun_leeOmma metrics yuchun_lee
Omma metrics yuchun_leeMediaPost
 
The Pragmatic Marketer: Volume 6, Issue 1
The Pragmatic Marketer: Volume 6, Issue 1The Pragmatic Marketer: Volume 6, Issue 1
The Pragmatic Marketer: Volume 6, Issue 1Pragmatic Marketing
 
Win Over Your Competitors with Data Driven Marketing
Win Over Your Competitors with Data Driven MarketingWin Over Your Competitors with Data Driven Marketing
Win Over Your Competitors with Data Driven MarketingBester Capital Media
 
PHX Media Labs Cybertising ebook
PHX Media Labs Cybertising ebookPHX Media Labs Cybertising ebook
PHX Media Labs Cybertising ebookPHX Media Labs
 
Dmc white paper data economics
Dmc white paper data economicsDmc white paper data economics
Dmc white paper data economicsmvsavage
 
Research Presentation: How Numbers are Powering the Next Era of Marketing
Research Presentation: How Numbers are Powering the Next Era of MarketingResearch Presentation: How Numbers are Powering the Next Era of Marketing
Research Presentation: How Numbers are Powering the Next Era of MarketingMediaPost
 
Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06BookStoreLib
 
Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06BookStoreLib
 
How Data, Relevance and Content are transforming B2B marketing
How Data, Relevance and Content are transforming B2B marketingHow Data, Relevance and Content are transforming B2B marketing
How Data, Relevance and Content are transforming B2B marketingMarketing Graham
 
Ghostery Enterprise - Best Practices White Paper
Ghostery Enterprise - Best Practices White PaperGhostery Enterprise - Best Practices White Paper
Ghostery Enterprise - Best Practices White PaperGhostery, Inc.
 
Data Activation For (Not So Much) Dummies
Data Activation For (Not So Much) DummiesData Activation For (Not So Much) Dummies
Data Activation For (Not So Much) DummiesCory Treffiletti
 
ACCELERATED DIGITAL MARKETING PROGRAME 2018
ACCELERATED DIGITAL MARKETING PROGRAME 2018ACCELERATED DIGITAL MARKETING PROGRAME 2018
ACCELERATED DIGITAL MARKETING PROGRAME 2018Stephen Dube
 
Module 4 - Data as a Business Model - Online
Module 4 - Data as a Business Model - OnlineModule 4 - Data as a Business Model - Online
Module 4 - Data as a Business Model - Onlinecaniceconsulting
 
Data, design and delivery the 3 d’s of today’s digital marketing world
Data, design and delivery  the 3 d’s of today’s digital marketing worldData, design and delivery  the 3 d’s of today’s digital marketing world
Data, design and delivery the 3 d’s of today’s digital marketing worldFinancial Publishing Services
 
Future of Digital Marketing [Free Download]
 Future of  Digital Marketing  [Free Download] Future of  Digital Marketing  [Free Download]
Future of Digital Marketing [Free Download]Visitor Analytics
 
Magenta advisory: Data Driven Decision Making –Is Your Organization Ready Fo...
Magenta advisory: Data Driven Decision Making  –Is Your Organization Ready Fo...Magenta advisory: Data Driven Decision Making  –Is Your Organization Ready Fo...
Magenta advisory: Data Driven Decision Making –Is Your Organization Ready Fo...BearingPoint Finland
 

Similar to Data Web Marketing (20)

360i Report: Big Data
360i Report: Big Data360i Report: Big Data
360i Report: Big Data
 
Omma metrics yuchun_lee
Omma metrics yuchun_leeOmma metrics yuchun_lee
Omma metrics yuchun_lee
 
The Pragmatic Marketer: Volume 6, Issue 1
The Pragmatic Marketer: Volume 6, Issue 1The Pragmatic Marketer: Volume 6, Issue 1
The Pragmatic Marketer: Volume 6, Issue 1
 
Win Over Your Competitors with Data Driven Marketing
Win Over Your Competitors with Data Driven MarketingWin Over Your Competitors with Data Driven Marketing
Win Over Your Competitors with Data Driven Marketing
 
PHX Media Labs Cybertising ebook
PHX Media Labs Cybertising ebookPHX Media Labs Cybertising ebook
PHX Media Labs Cybertising ebook
 
Dmc white paper data economics
Dmc white paper data economicsDmc white paper data economics
Dmc white paper data economics
 
Research Presentation: How Numbers are Powering the Next Era of Marketing
Research Presentation: How Numbers are Powering the Next Era of MarketingResearch Presentation: How Numbers are Powering the Next Era of Marketing
Research Presentation: How Numbers are Powering the Next Era of Marketing
 
Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06
 
Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06Laudon traver ec10-im_ch06
Laudon traver ec10-im_ch06
 
Future Of Advocacy
Future Of AdvocacyFuture Of Advocacy
Future Of Advocacy
 
How Data, Relevance and Content are transforming B2B marketing
How Data, Relevance and Content are transforming B2B marketingHow Data, Relevance and Content are transforming B2B marketing
How Data, Relevance and Content are transforming B2B marketing
 
Ghostery Enterprise - Best Practices White Paper
Ghostery Enterprise - Best Practices White PaperGhostery Enterprise - Best Practices White Paper
Ghostery Enterprise - Best Practices White Paper
 
Data Activation For (Not So Much) Dummies
Data Activation For (Not So Much) DummiesData Activation For (Not So Much) Dummies
Data Activation For (Not So Much) Dummies
 
Big data is a popular term used to describe the exponential growth and availa...
Big data is a popular term used to describe the exponential growth and availa...Big data is a popular term used to describe the exponential growth and availa...
Big data is a popular term used to describe the exponential growth and availa...
 
ACCELERATED DIGITAL MARKETING PROGRAME 2018
ACCELERATED DIGITAL MARKETING PROGRAME 2018ACCELERATED DIGITAL MARKETING PROGRAME 2018
ACCELERATED DIGITAL MARKETING PROGRAME 2018
 
uae views on big data
  uae views on  big data  uae views on  big data
uae views on big data
 
Module 4 - Data as a Business Model - Online
Module 4 - Data as a Business Model - OnlineModule 4 - Data as a Business Model - Online
Module 4 - Data as a Business Model - Online
 
Data, design and delivery the 3 d’s of today’s digital marketing world
Data, design and delivery  the 3 d’s of today’s digital marketing worldData, design and delivery  the 3 d’s of today’s digital marketing world
Data, design and delivery the 3 d’s of today’s digital marketing world
 
Future of Digital Marketing [Free Download]
 Future of  Digital Marketing  [Free Download] Future of  Digital Marketing  [Free Download]
Future of Digital Marketing [Free Download]
 
Magenta advisory: Data Driven Decision Making –Is Your Organization Ready Fo...
Magenta advisory: Data Driven Decision Making  –Is Your Organization Ready Fo...Magenta advisory: Data Driven Decision Making  –Is Your Organization Ready Fo...
Magenta advisory: Data Driven Decision Making –Is Your Organization Ready Fo...
 

More from Scott Brinker

The Stackies 2018: Marketing Tech Stack Awards
The Stackies 2018: Marketing Tech Stack AwardsThe Stackies 2018: Marketing Tech Stack Awards
The Stackies 2018: Marketing Tech Stack AwardsScott Brinker
 
Hacking Marketing Q&A Session
Hacking Marketing Q&A SessionHacking Marketing Q&A Session
Hacking Marketing Q&A SessionScott Brinker
 
2016 Stackies Awards: 41 Marketing Technology Stacks
2016 Stackies Awards: 41 Marketing Technology Stacks2016 Stackies Awards: 41 Marketing Technology Stacks
2016 Stackies Awards: 41 Marketing Technology StacksScott Brinker
 
Hacking Marketing at SXSW 2016
Hacking Marketing at SXSW 2016Hacking Marketing at SXSW 2016
Hacking Marketing at SXSW 2016Scott Brinker
 
The Stackies: Marketing Technology Stack Awards, June 2015
The Stackies: Marketing Technology Stack Awards, June 2015The Stackies: Marketing Technology Stack Awards, June 2015
The Stackies: Marketing Technology Stack Awards, June 2015Scott Brinker
 
Navigating the Marketing Technology Rapids
Navigating the Marketing Technology RapidsNavigating the Marketing Technology Rapids
Navigating the Marketing Technology RapidsScott Brinker
 
Combining Art & Science in Modern Marketing
Combining Art & Science in Modern MarketingCombining Art & Science in Modern Marketing
Combining Art & Science in Modern MarketingScott Brinker
 
Agile Marketing in 5 Minutes
Agile Marketing in 5 MinutesAgile Marketing in 5 Minutes
Agile Marketing in 5 MinutesScott Brinker
 
Creative Technologists Meet Marketing Technologists
Creative Technologists Meet Marketing TechnologistsCreative Technologists Meet Marketing Technologists
Creative Technologists Meet Marketing TechnologistsScott Brinker
 
Everything Is Marketing, Everyone Must Be Agile
Everything Is Marketing, Everyone Must Be AgileEverything Is Marketing, Everyone Must Be Agile
Everything Is Marketing, Everyone Must Be AgileScott Brinker
 
Rise of the Marketing Technologist (And What It Means For Agencies)
Rise of the Marketing Technologist (And What It Means For Agencies)Rise of the Marketing Technologist (And What It Means For Agencies)
Rise of the Marketing Technologist (And What It Means For Agencies)Scott Brinker
 
The Case for a Chief Marketing Technologist
The Case for a Chief Marketing TechnologistThe Case for a Chief Marketing Technologist
The Case for a Chief Marketing TechnologistScott Brinker
 
Marketing in the Cloud
Marketing in the CloudMarketing in the Cloud
Marketing in the CloudScott Brinker
 
Rise of the Marketing Technologist
Rise of the Marketing TechnologistRise of the Marketing Technologist
Rise of the Marketing TechnologistScott Brinker
 
Web 3.0 Data Marketing
Web 3.0 Data MarketingWeb 3.0 Data Marketing
Web 3.0 Data MarketingScott Brinker
 
Marketing with Linked Data (MIT)
Marketing with Linked Data (MIT)Marketing with Linked Data (MIT)
Marketing with Linked Data (MIT)Scott Brinker
 
3 Landing Page Myths Debunked
3 Landing Page Myths Debunked3 Landing Page Myths Debunked
3 Landing Page Myths DebunkedScott Brinker
 

More from Scott Brinker (18)

The Stackies 2018: Marketing Tech Stack Awards
The Stackies 2018: Marketing Tech Stack AwardsThe Stackies 2018: Marketing Tech Stack Awards
The Stackies 2018: Marketing Tech Stack Awards
 
Hacking Marketing Q&A Session
Hacking Marketing Q&A SessionHacking Marketing Q&A Session
Hacking Marketing Q&A Session
 
2016 Stackies Awards: 41 Marketing Technology Stacks
2016 Stackies Awards: 41 Marketing Technology Stacks2016 Stackies Awards: 41 Marketing Technology Stacks
2016 Stackies Awards: 41 Marketing Technology Stacks
 
Hacking Marketing at SXSW 2016
Hacking Marketing at SXSW 2016Hacking Marketing at SXSW 2016
Hacking Marketing at SXSW 2016
 
The Stackies: Marketing Technology Stack Awards, June 2015
The Stackies: Marketing Technology Stack Awards, June 2015The Stackies: Marketing Technology Stack Awards, June 2015
The Stackies: Marketing Technology Stack Awards, June 2015
 
Navigating the Marketing Technology Rapids
Navigating the Marketing Technology RapidsNavigating the Marketing Technology Rapids
Navigating the Marketing Technology Rapids
 
Combining Art & Science in Modern Marketing
Combining Art & Science in Modern MarketingCombining Art & Science in Modern Marketing
Combining Art & Science in Modern Marketing
 
Agile Marketing in 5 Minutes
Agile Marketing in 5 MinutesAgile Marketing in 5 Minutes
Agile Marketing in 5 Minutes
 
Creative Technologists Meet Marketing Technologists
Creative Technologists Meet Marketing TechnologistsCreative Technologists Meet Marketing Technologists
Creative Technologists Meet Marketing Technologists
 
Everything Is Marketing, Everyone Must Be Agile
Everything Is Marketing, Everyone Must Be AgileEverything Is Marketing, Everyone Must Be Agile
Everything Is Marketing, Everyone Must Be Agile
 
Rise of the Marketing Technologist (And What It Means For Agencies)
Rise of the Marketing Technologist (And What It Means For Agencies)Rise of the Marketing Technologist (And What It Means For Agencies)
Rise of the Marketing Technologist (And What It Means For Agencies)
 
Semantic web summit
Semantic web summitSemantic web summit
Semantic web summit
 
The Case for a Chief Marketing Technologist
The Case for a Chief Marketing TechnologistThe Case for a Chief Marketing Technologist
The Case for a Chief Marketing Technologist
 
Marketing in the Cloud
Marketing in the CloudMarketing in the Cloud
Marketing in the Cloud
 
Rise of the Marketing Technologist
Rise of the Marketing TechnologistRise of the Marketing Technologist
Rise of the Marketing Technologist
 
Web 3.0 Data Marketing
Web 3.0 Data MarketingWeb 3.0 Data Marketing
Web 3.0 Data Marketing
 
Marketing with Linked Data (MIT)
Marketing with Linked Data (MIT)Marketing with Linked Data (MIT)
Marketing with Linked Data (MIT)
 
3 Landing Page Myths Debunked
3 Landing Page Myths Debunked3 Landing Page Myths Debunked
3 Landing Page Myths Debunked
 

Recently uploaded

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...FIDO Alliance
 
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...FIDO Alliance
 
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdfHow Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdfFIDO Alliance
 
What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024Stephanie Beckett
 
Powerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara LaskowskaPowerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara LaskowskaCzechDreamin
 
Google I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGoogle I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGDSC PJATK
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxJennifer Lim
 
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...FIDO Alliance
 
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdfLinux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdfFIDO Alliance
 
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlFuture Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlPeter Udo Diehl
 
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Free and Effective: Making Flows Publicly Accessible, Yumi IbrahimzadeFree and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Free and Effective: Making Flows Publicly Accessible, Yumi IbrahimzadeCzechDreamin
 
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераIntro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераMark Opanasiuk
 
Speed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in MinutesSpeed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in Minutesconfluent
 
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyDemystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyJohn Staveley
 
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftOauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftshyamraj55
 
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfWhere to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfFIDO Alliance
 
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & IrelandUsing IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & IrelandIES VE
 
How we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdfHow we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdfSrushith Repakula
 
AI revolution and Salesforce, Jiří Karpíšek
AI revolution and Salesforce, Jiří KarpíšekAI revolution and Salesforce, Jiří Karpíšek
AI revolution and Salesforce, Jiří KarpíšekCzechDreamin
 
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomSalesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomCzechDreamin
 

Recently uploaded (20)

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
 
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
 
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdfHow Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
How Red Hat Uses FDO in Device Lifecycle _ Costin and Vitaliy at Red Hat.pdf
 
What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024
 
Powerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara LaskowskaPowerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara Laskowska
 
Google I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGoogle I/O Extended 2024 Warsaw
Google I/O Extended 2024 Warsaw
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
 
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
 
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdfLinux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
Linux Foundation Edge _ Overview of FDO Software Components _ Randy at Intel.pdf
 
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo DiehlFuture Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl
 
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Free and Effective: Making Flows Publicly Accessible, Yumi IbrahimzadeFree and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade
 
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераIntro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджера
 
Speed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in MinutesSpeed Wins: From Kafka to APIs in Minutes
Speed Wins: From Kafka to APIs in Minutes
 
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyDemystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John Staveley
 
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftOauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoft
 
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfWhere to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
 
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & IrelandUsing IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & Ireland
 
How we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdfHow we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdf
 
AI revolution and Salesforce, Jiří Karpíšek
AI revolution and Salesforce, Jiří KarpíšekAI revolution and Salesforce, Jiří Karpíšek
AI revolution and Salesforce, Jiří Karpíšek
 
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone KomSalesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom
 

Data Web Marketing

  • 1. Marketing in the Semantic Web (“Semantic Marketing” / “Data Web Marketing”) Semantic Technology Conference June 16, 2009 Scott Brinker Marketing Technologist Email: sbrinker@chiefmartec.com Twitter: @chiefmartec Blog: http://www.chiefmartec.com
  • 2. Deafening silence Sweet sorrow Controlled chaos Organized mess Open secret Same difference Civil war Forward retreat Living dead Semantic marketing
  • 3. What will marketing be like in the semantic web? * * Depends on your definition of “marketing” and “semantic web”.
  • 4. Official definition of marketing from the American Marketing Association web site Marketing is the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offers that have value for customers, clients, partners, and society at large. (Approved October 2007)
  • 5. Informal definition of marketing from the top of my head Marketing is what you do to find and win new customers, grow your relationships with existing customers, differentiate yourself from the competition, and build a “brand” that helps achieve those goals.
  • 6. Peter Drucker on marketing the father of modern management * Because the purpose of business is to create a customer, the business enterprise has two — and only two — basic functions: marketing and innovation. * Drucker argued in a 1984 essay that CEO compensation should be no more than 20 times what the rank and file make — especially at companies where thousands of employees are being laid off. “This is morally and socially unforgivable,” he wrote, “and we will pay a heavy price for it.”
  • 7. Marketing is continually evolving. In recent years, that evolution has been accelerating — with more changes ahead.
  • 8. Marketing as a mission spans the specific tactics by which it is executed.
  • 11. 100 years of progress?
  • 12. Emerging marketing tactics, circa 2009 $1.4 billion of SEO in 2008 1,254 APIs and 3,852 mashups
  • 13. Search engine optimization (SEO) and web APIs for mashups are a qualitatively different kind of marketing tactic.
  • 14. Even across …previous shifts in marketing medium… tactics were crafted directly for human consumption.
  • 15. These new tactics are different. 1st order: Directly crafted for computer consumption. 2nd order: Indirectly crafted for human consumption.
  • 16. This opens the door to data web marketing.
  • 17. What is the semantic web? from the W3C web site The Semantic Web is a web of data. The Semantic Web is about two things. It is about common formats for integration and combination of data drawn from diverse sources… It is also about language for recording how data relates to real world objects.
  • 18. iro•ny, noun, ˈī rə- - nē: Debating the meaning of “semantic web”.
  • 19. What is the semantic web? 3 broad spheres Document Disambiguation Structured Linked Data Data
  • 20. • Semantic technology that doesn’t necessarily require Document publisher cooperation Disambiguation • Advances in text analysis for context and sentiment • “Semantic advertising” (popular interpretation) • Usually invisible to end-user • Top-down semantic web • Here today …no fundamental change to marketing behavior, however.
  • 21. Semantic marketing is about data —and the spread of that data. Structured Linked Data Data
  • 22. Semantic Marketing = Data Web Marketing * Is this a better name for it?
  • 24. …but it has only flowed in. • CRM • Point-of-Sale • Market research • Web analytics
  • 26. Semantic technology can help organize this data… but again, no fundamental change to marketing.
  • 27. Data web marketing is about data flowing out. A simple yet revolutionary change in perspective.
  • 28. Instead of data from the channel… Data is the channel.
  • 30. Why should marketing lead the charge for data web adoption?
  • 31. Somebody needs to consistently beat the drum for data web initiatives.
  • 32. Somebody needs to fund data web support as an ongoing commitment.
  • 33. Who has the incentive?
  • 34. If the data web can be used to: • help connect to new customers • strengthen relationships • differentiate from the competition • build reputation and brand
  • 35. Who does that align with?
  • 36. Informal definition of marketing from the top of my head Marketing is what you do to find and win new customers, grow your relationships with existing customers, differentiate yourself from the competition, and build a “brand” that helps achieve those goals.
  • 37. Marketing is willing to experiment to achieve its goals.
  • 38. If marketing can tie the cause-and- effect of data web initiatives to the achievement of its objectives… …there’s sustainable sponsorship.
  • 40. So what exactly should marketing doin the dataweb?
  • 42. 7 missions of data web marketing: 1. Champion production of data for external consumption. 2. Drive semantic/data branding across the organization. 3. Distribute and promote your data. (SEO++) 4. Convert data web initiatives into business relationships. 5. Track and attribute semantic/data web initiatives. 6. Make your own data mash-ups. 7. Control data quality and protect data/brand standards.
  • 43. #1. Champion production of data for external consumption.
  • 46. Semantic “bargain hunter” agents are not attractive to most marketers. That vision of the semantic web is dystopian to marketers.
  • 47. Marketing is all about avoiding commoditization. • Price isn’t everything. • Only one lowest-cost provider. • Race to the bottom dynamics. • Specs aren’t everything. • Relationships have value. • Quality matters. • Context matters. • Service matters. • Trust matters a lot.
  • 48. Pricing and product specifications don’t do justice to the potential of sharing data in the semantic web.
  • 49. Discover data that is valuable in: • Domain of your expertise • Domain of your partners’ expertise • Domain of your customers’ expertise • Application of your product/service • Integration of your product/service • Benchmarking related results
  • 50. “You should take an inventory of what you have got in the way of data, and you should think about how valuable each piece of data in the company would be if it were available to other people across the company, or if it were available publicly, and if it were available to your partners.” — Tim Berners-Lee in Talis 2008 interview, answering the question from a CIO, “what does it mean, what should we do?”
  • 52. Ways to produce valuable data: • Generate it internally • Collect it from customers • Collect it from partners • License it externally
  • 53. Thinking about this kind of data is hard — because it’s not been done before. But that’s the opportunity.
  • 54. Hypothetical example: Major chain of nurseries producing the leading reference of plant properties (climate, growth, soil, water, feeding, compatibility, etc.) — maybe specialized for a particular region.
  • 55. Hypothetical example: Marketing software company aggregates performance data across customers to offer real-time industry benchmarks. (With permissions of participants, of course.)
  • 57. Goals: • Become the authoritative source. • Popularize canonical references to your products, categories, competitive dimensions. • Build reputation, goodwill, brand.
  • 58. #2. Drive semantic/data branding across the organization.
  • 59. Framing data with the right metadata — your data brand standards: • Establish canonical URIs for products, properties. • Establish the organizing ontologies. • Determine the ideal granularity of data structures. • Embrace and extend existing external standards. • Encourage data linking in the organization (DRY). • Lobby for standards beyond your organization. • Maintain and evolve this architecture.
  • 61. Linked data success depends on: • Consistency • Logical organization • Stability • Trust Data consumers must be able to rely upon your data to use it as a foundation for their own applications.
  • 62. Ontology as Strategy
  • 64. Semantic spin Framing references with properties and nomenclature that are advantageous to your brand.
  • 65. Do the names of things really matter that much?
  • 67. Our company is redefining the market. A more literal interpretation of an old hype line.
  • 69. Authoritative references generate a positive feedback loop, a virtuous cycle.
  • 70. Gender bias in the semantic web? A kind of semantic branding. http://www.readwriteweb.com/archives/ will_the_semantic_web_have_a_g.php
  • 71. There are fascinating parallels between the concept of brands and the semantic web… but that’s a story for another day. http://www.chiefmartec.com/2008/03/brand-and-the-s.html
  • 72. #3. Distribute and promote your data. (SEO++)
  • 73. Just as SEO was about visibility (and ranking and authority) in the document web… …there will be an analogous need in the data web.
  • 74. SEO++ because it’s an incremental evolution of SEO practices now focused on data objects. Alternatives: Semantic Web Optimization (SWO) Data Web Optimization (DWO)
  • 75. Spreading your data: • Build external links to your data • Link reciprocally to other data • Increase the findability of your data • Optimize the format of your data • Shape and adopt standards • Promote your data in other channels
  • 76. As with SEO, this mission will require continual nurturing.
  • 77. You want to join the data graph.
  • 78. You want your data to be utilized.
  • 79. You want your data to help others find you. For example, embedding data into your primary web site, such as for Google Rich Snippets and Yahoo! Search Monkey.
  • 80. And that’s going to get harder as more data comes online.
  • 81. Surface web: 167 terabytes Deep web: 91,000 terabytes 545-to-one
  • 82. Bridge your data with others in semantic communities (data networks). Networks: • Global • Vertical • Private
  • 83. Provide the glue to connect to these different networks. This will probably be a little messy for a while.
  • 84. A new kind of semantic advertising Paid inclusion in other authoritative data networks. A.K.A. data advertising
  • 85. Hypothetical example semantic advertising (data advertising) semantic advertising (paid inclusion) I just made this idea up, so whether or not Calais actually does something like this is purely coincidental. Sponsored data
  • 86. Goals: • Include your data in more places • Get links to your data in more places • Win more overall visibility/authority
  • 87. Data web marketing services are a logical evolution for search agencies.
  • 88. #4. Convert data web initiatives into business relationships.
  • 89. Information asymmetry will still be alive and well. Data web marketing must strategically decide how much to share, when, and with whom.
  • 90. Some data may be better harnessed as an incentive for other business goals: • Become a subscriber • Become a lead • Become a partner • Become a customer • Become a data buyer
  • 91. A continuum of data access choices. access if you pay value access if you qualify access if you sign-up free access availability
  • 92. Data for nothing and links for free. (the SEO++ approach) Capturing value via visibility and authority.
  • 93. Restricted “members only” data. Exchange of value in permission marketing, or an added benefit to customers and partners. Capturing value via lead generation and customer acquisition/retention.
  • 94. Data as a direct revenue source. • Data more pragmatic in standardized format. • Paid data access as a stand-alone business. • Paid data access as a “add-on” business. Capturing value the old-fashioned way: people pay for it.
  • 95. Balancing the trade-offs in data value capture is a marketing decision.
  • 96. Multiple “data packaging” options. The same underlying data may be packaged differently depending on access level: • Granularity of data. • Depth of data. • Breadth of data. • “Freshness” of data.
  • 98. #5. Track and attribute semantic/dataw eb initiatives. “data web analytics”
  • 99. How do you measure the success of semantic web/data web initiatives? What are the right metrics?
  • 100. Different than web analytics because… …clients are not necessarily browsers.
  • 101. Cookies—a staple of web analytics—may not be as prevalent in data access tracking.
  • 102. Referrer—a staple of web analytics—may not be as prevalent in data access tracking.
  • 103. Tracking is also going to be hard due to mashing and caching. How is data used and redistributed once someone gets it from you?
  • 104. Count subscribers to data feeds or visits to URIs. • Measures 1st-order reach. • Measures frequency of access. • Measures new vs. repeat access. • But maybe limited to IP address.
  • 105. Time-sensitive or frequently updated data is one way to encourage more visits to gauge usage.
  • 106. Count inbound links to your URIs. • Measure authority (DataRank). • Measure findability. • Limited by who indexes you.
  • 107. New methods of tracking and attribution? Particularly among cooperative parties?
  • 108. Inspiration from Daniel Weitzner (MIT) and the policy-aware web (PAW).
  • 109. Goals: • Discovering what data is popular. • Discovering who your data audience is. • Discovering how your audience uses that data. • Keeping track of competitors and comparable benchmarks.
  • 110. #6. Make your own data mashups.
  • 111. Data web fluency is something you learn by doing. You must use data to understand how to use data.
  • 112. Applications and mash-ups are where data surfaces into the visible web.
  • 113. Leveraging data in your own value-add mash-ups. • For prospects • For customers • For partners • For internal use mashable marketing
  • 114. Mash-ups for prospects and customers. To assist, educate, entertain, orinform.
  • 116. Mash-ups for internal use. • Market research • Customer monitoring • Marketing operations
  • 117. Competitive intelligence mash-ups. Uncovering the pros and cons of data web marketing.
  • 118. Opportunities for “joint venture” data web initiatives — your chocolate with someone else’s peanut butter (exclusively?).
  • 119. Goals: • Cool applications for your customers. • Advanced your own internal operations. • By doing the above, better understand how data is consumed to be better at producing it.
  • 120. #7. Control data quality and protect data/brand standards. “semantic police”
  • 121. Data web marketing won’t be magic. • Coordination challenges with distributed data management. • Rules about what can be shared, when and with whom. • Maintaining the accuracy of data (i.e., data entropy). • Refereeing conflicting data silos coming together. • Enforcing data brand standards.
  • 122. Legal questions: Do we have the right to share certain data? What are the liabilities from sharing data? Does sharing certain data constitute a risk to our intellectual property?
  • 123. “Marketing” Determining how much data to share… …or not to share. “Legal”
  • 124. Agreement on data standards may be contentious among stakeholders.
  • 125. When data was in silos, inherently fewer conflicts. As data web marketing grows, this will become a larger issue.
  • 126. Remove bad or expired data. It’s much more unattractive when the public has come in for U-pick-it data.
  • 128. Goal: Achieve balance between openness vs. protection, distributed vs. controlled, standardized vs. loosely-coupled data relationships.
  • 129. 7 missions of data web marketing: 1. Champion production of data for external consumption. 2. Drive semantic/data branding across the organization. 3. Distribute and promote your data. (SEO++) 4. Convert data web initiatives into business relationships. 5. Track and attribute semantic/data web initiatives. 6. Make your own data mash-ups. 7. Control data quality and protect data/brand standards.
  • 130. Web 3.0 = Data Web 1.0
  • 131. A more technical future for marketing? A role for “marketing technologists” in the organizational DNA of the marketing department & agencies. The new leaders of data web marketing?
  • 132. Thank you for running this marathon presentation with me. Scott Brinker Marketing Technologist Email: sbrinker@chiefmartec.com Twitter: @chiefmartec Blog: http://www.chiefmartec.com