Book Review: Social Media Marketing
By Babar Bhatti | August 10, 2009 | No Comments
By 2012, 25% of all media will be created by end users – Nokia forecast, 2008.
I have been reading a very interesting book, Social Media Marketing by Ajit Jaokar, Brian Jacobs, Alan Moore and Jouko Ahvenainen. The book is about marketing, role of data and the the emergence and convergence of three distinct but connected (based on data and conversations) media types: Mass Media (such as TV or outdoor), Social Media (social networks) and Mobile Media. Its a must read for marketing professionals, technologists who are interested in marketing analytics and for executives who want to understand the big picture and to see where the opportunities are.
Social Media is defined as any media form that links people and communities – including many smaller sites, mobile internet services and telephony. This book is interested in approaching marketing communication from a social media perspective, and in the data and analytics (from online and from mobile telecommunications sources) that allow us the opportunity to improve that process.
Most of the media is (or used to be) in broadcast mode: “we talk, you listen.” The rise of online social media has changed perceptions. The book talks about Hot Media vs Cold Media and shows the opportunities available with the transition from the age of mass media to an age of networks.
Social media marketing can be used as a part of a two stage process: – first, to identify certain patterns in data, second to verify those observations by specific social media campaigns which also seek permission from the customers.
The provider sends personalised messages to the receiver, and over time, the visibility of the participant’s digital footprint grows and leads to better personalization. Therefore, we start with passive digital footprints (based on data patterns) and transition to active digital footprints (based on trust).
The Importance of Data – this is the key point and the value of this book. Here are some excerpts.
A data led approach to social media is universal because every organization has access to such data from the many touch points through which it engages with the customer.
Like the impact of the social media, the impact of mobility is also disruptive for the traditional media. The mobile operator faces a different problem from the broadcaster. The operator might know the customer individually, but not know much about the customer. Specifically, the operator does not know the user’s preferences, which can be used to create a more personalised message (and by extension a message that is more likely to be useful to the receiver).
Mobile media complements mass media (like television) by providing the individual with the personalization which mass media lacks.
This can happen in potentially three interconnected ways:
a) Patterns: Spotting behavioural patterns
b) Promotions: Specific marketing activity or promotions to validate observations from the patterns
c) Partnerships: Creating partnerships between traditional media and mobile media to get as wide a network as possible (or extend
your own network within a converged ecosystem)
The discussion about digital footprints is where the data and analysis starts making the connections.
There are two classifications for digital footprints: Passive Digital Footprints and Active Digital Footprints. A passive digital footprint is created when data is collected about an action without any client activation, whereas active digital footprints
are created when personal data is released deliberately by a user for the purpose of sharing information about himself/herself.
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August 10th, 2009 @ 12:02 pm
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August 10th, 2009 @ 12:39 pm
Apart from Social media, the user contribution will be quite significant in other fields as well..for instance creating the drama serial by accepting user feed back..
August 10th, 2009 @ 11:48 pm
Adnan – agreed. Once the users are empowered, there is no limit. The trick is to separate the useful content from all the noise which is generated. And thats where data (customer information and conversations) analysis helps.
August 11th, 2009 @ 1:57 am
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