Facebook
connected us in a vast network – this is only a first step. The deep reason for the fascination with social
networking can be understood from an example. Shoppers are enmeshed in an
ever-changing network of social interactions and preferences; desirable
behavior can be made to emerge by perturbing the interactions within the
network.
Insight #1: Network embedded
data.
Today
in Analytics, data are treated as isolated bits of information. In reality, data exist in *embedded* forms
in preference and influence networks of the shopper as well as distributed in
time and space. There are few if any analytics techniques that explicitly exploit
embedding – if new ones do, such
techniques will be very powerful.
Insight #2: Closing the
Analytics Loop.
Analytics extract
meaningful patterns and information from raw data. But what do we do with those
insights? The promise of Analytics will be fulfilled only when we close
the loop via actions that lead to profitability in the broad sense.
Emergent Marketing is an example of closing the loop of “analytics” drawn from
retail data and shopper network activity back to the customer generating purchase
activity and additional new analytics.
Insight #3: Emergent
Marketing.
Emergent
Marketing is a low-level multi-node
intervention in a human social network that creates the emergence of a
ground-swell of a desirable activity (“emergent” activity) without
identifiable one-to-one causality. In a “crawl-walk-run” approach to developing
full-fledged Emergent Marketing techniques, JIT Branding is a “slow crawl”.
Insight #4: Just-in-time
Branding.
JIT Branding using Linear Influence Model (LIM)
is a primitive Emergent Marketing tool. LIM models minimally incorporate the
dynamics and the ability to perturb the network in a fine-grained manner. The
design and number of “contagions” for the emergence of desirable
“ground-swells” of activity are also open issues at this time.
·
The
true value of LIM modeling for JIT Branding is that key shoppers’ influence
functions are estimated from historical data. In general,
these influence functions are not available and naïve guesses have to be
employed (such as exponential decay).
Closed-loop Analytics:
Insights
from analytics can be “closed” in multiple ways: via the shopper, via
merchandising and via many stages of the supply chain. Our focus is on closing
the loop via the shopper; they involve advertisements, discounts or loyalty
programs plus new approaches.
1.
Proximity Marketing using
Passive Organic Search™ - implemented
(New).
2.
Viral Marketing using Shop
Ally™ - ready for implementation (relatively NEW).
3.
Emergent Marketing using JIT Branding™ -
technology ready (brand NEW).
More details at . . .
o “Emergent Marketing: A New Force in
Social Commerce”http://pgmadblog.blogspot.com/2012/10/emergent-marketing-new-force-in-social.html
o “What does ‘Emergent Properties
in Network Dynamics’ have to do with Shopping?” http://pgmadblog.blogspot.com/2012/10/what-does-emergent-properties-in.html
o
“Social-Mobile-Cloud Framework” http://pgmadblog.blogspot.com/2012/07/so-mo-clo-framework-for-cus-dr.html
o
"Business IPTV Service – A New Cloud Business Vertical" http://pgmadblog.blogspot.com/2009/09/advertisers-are-always-looking-for-ways.html
Dr.
PG Madhavan was CTO Software Solutions at Symphony Teleca
Corp. Previously, he was the CTO & VP Engineering for Solavei LLC and
the Associate Vice President--Technical Advisory for Global Logic Inc. PG
has 20+ years of software products, platforms and framework experience in
leadership roles at major corporations such as Microsoft, Lucent, AT&T and
Rockwell and startups, Zaplah Corp (Founder and CEO), Solavei and Aldata.
Application areas include retail, mobile, Cloud, eCommerce, banking,
enterprise, consumer devices, M2M, digital ad media, medical devices and social
networking in both B2B and B2C market segments. He is an innovation
leader driving invention disclosures and patents (12 issued US patents)
with a Ph.D. in Electrical & Computer
Engineering. More about PG at www.linkedin.com/in/pgmad
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