Presented at the "Social Media & Web Analytics Innovation" Conference, 25-26 April 2013: https://theinnovationenterprise.com/summits/social-media-web-analytics-sf/schedule
2. Outline
! Business & Technology context
! Social Graphs
! Implications for the Enterprise
! 5 Steps on the road to transforming
Enterprise Applications
3. We’ve come a long way since the
early days of the internet, which
thrived on anonymity
Marketing (online and offline) can
be tailored to individuals with
precision
4. Ad Targeting is just the tip of the
iceberg: better insight into a person’s
preferences &
social context
can help almost every functional
area in an organization
5. Marketing to the
Customer Decision Journey:
identifying influencers;
empowering advocates; predicting
customer behavior
Improving web experience and
goal attainment: product
discovery, user communities
6. Hiring: social referrals, evaluation
Talent management: identifying
“connectors”, leaders, etc
Business development: employee
alumni in other companies; new
hires from potential clients &
competitors
Org charts of clients, competitors
7. Even though this is a space that
did not exist
just 10 years ago,
the industry landscape has
evolved quickly
10. CEO, CMO and CIO priorities have
seen a confluence, with a focus on:
engagement
connections
collaboration
11. … all of which are in the sweet
spot for Social
Social Graphs and
Social Network Analysis
are the architectural foundations
for the use of Social technologies
16. On social networks, use of these
graphs has evolved to include
objects in addition to
people and
interests
when someone “Likes” an object,
they are implicitly – and instantly –
connected with everyone else who
“Likes” the object
17. most social networks started as
social graphs OR interest graphs
and have now started gravitating
to the space between those extremes
18. Beyond the rich graph visualizations,
its really all about data -
real insights are obtained through
social network analysis
via study of the underlying data
Source: digitaltoronto.com
19. Social data can drive insights &
recommendations that provoke the
desired interaction
20. Recommendation engines are now a
core feature in many social networks:
friends to connect with,
places to visit,
movies to see, and so on
These recommendations are driven
through a combination of context,
social graph data, and analytics
21. This is the promise of Social Software
aka Social-enabled software
aka Social-aware software:
Software that can use information
about (and from) your social
connections to enable discovery, and
promote outcomes
23. a frequent
challenge in such
systems is the
difficulty of
finding the most
relevant
content
Photo by Flickr user giladr, licensed under Creative Commons, Attribution 2.0 Generic
24. One way to address this problem is
by re-orienting the interface to be
designed around people
25. The use of social graphs to find the
most relevant information
can be applied to applications
across the enterprise
… but requires a set of
infrastructure components
to support it
26. The rapid rise and adoption of
Social Media has also led to a
disconnect between
social interactions and
business interactions
36. Look for places where user interaction
can be aided by
Discovery
Collaboration
Leverage activity streams
Don’t ignore privacy; don’t forget
analytics
37. avoid the trap of creating
social-driven interactions that
exist in isolation
improve existing interactions:
Make Social a layer, not a feature
5
Hinweis der Redaktion
Back in 1993, the New Yorker had a famous cartoon of a dog surfing the internet and telling a fellow canine, “on the Internet, no one knows I’m a dog”. There was a huge culture of anonymity, and it was complemented by the fact that neither the tech world nor the business world knew what to make of it.Fast forward to 2012. The New York Times had a much quoted article about how much marketing companies know about us. The centerpiece of the article was the accuracy of Target’s marketing, and the article described how the researcher could identify “…about 25 products that, when analyzed together, allowed him to assign each shopper a “pregnancy prediction” score. More important, he could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy. “
The flip side of knowing much more about customers of course, is a heightened sense of privacy. As long as privacy can be safeguarded, knowing more a person’s interests and preferences can help almost every part of the organization
McKinsey and the Harvard Business Review have opened a discussion about the buying habits of customers, and how it has changed from the funnel to a process where they are influenced not just by brand advertising and brand perception, but also influences in their environment such as their social network, post-purchase experience, etc
there are over 1.5 billion social networking users worldwide80% of total online users interact with social networks regularlyMcKinsey reported in a study that 70% of the companies they surved reporting using social technologies, and 90% of those reported some business benefit from themThe same McKinsey study assessed that the annual value that could be unlocked by the use of social technologies was $900 billion to $1.3 trillionThe marketing agency LumaScape Partners LLC put out a representation of the competitive in the social landscape, and in the "Social Intelligence" category alone there are 30 players. Then there's other areas like Social Marketing agencies, Social apps & games, Community platforms, Social TV, Social shopping, Social scoring, and so on
Other trends include: Gamification, Personal/wearable computing, changing attitudes and expectations towards privacy
IBM CEO Study 2011 and CMO Study surveyed executives from all over the world – an interesting trend towards recognition of the value of (a) in the external environment, engagement with customers and collaboration with partners; (b) in the internal environment, seeking better collaboration between employees and breaking down the silos
http://en.wikipedia.org/wiki/File:Interest_Graph_vs_Social_Graph_by_Socialize.pngSocialize Inc. for Wikipedia
Linkedin has a product called inMaps where they generate rich graphical representations of your professional graphThis is the realm of data scientists: degree of centrality, degree of closeness, etc
Netflix example: netflix is really good at recommending movies you may like, but it does more than just suggest movies of a similar genre – it analyses movies you liked, and the tastes of people who liked the same movies, to generate predictions about other movies you might like
Direct connections, indirect connections
About 10 years ago, IBM created a new collaboration platform to drive innovation across the enterprise worldwide. It was designed as a system where employees could submit ideas, but also comment & rate other people’s ideas. The objective was to tap the “wisdom of the crowds’ to identify the best ideas. Over 5 years, the system was a huge success. But as more ideas were submitted into the system, it became harder for employees to find the ideas they in their area of expertise.
These are both legacy components and newer web2.0 platforms
Systems of Engagement = interactions inside & outside firewallSystems of Record = data stores inside the firewall
Relationships between Employees, Clients, Partners, CompetitorsRelationships can also be inferred from enterprise meta data (directory, email, collaboration tools) or be user-submitted
Email, Company directory, Collaboration tools, Internal communities Analogous to Integrated Supply Chain, but for connections & relationships (of course, view of data is not shared outside enterprise)\\
Start with data you already have, for external (transactions with customers) and internal (collaboration between employees) how your customers use your products, how they interact with each other & youwhat kind of data exists in enterprise data storesMake sure you consider how they relate to your metrics and goalsDefine your social objects and interactions
Define social objects and interactions kinds of ties