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Simplify360 eBook: Predictive Analytics The Future of Social Media

1 World’s First 360° Social Marketing Suit

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Table of Contents

PREFACE 3

WHAT ARE PREDICTIVE ANALYTICS? 5

ADITYA CHOWDHARY - CLIENT SERVICES DIRECTOR MARKETELLIGENT 5

BEYOND SENTIMENTS 9

ZISHAN ANSARI - SENIOR BUSINESS ANALYST, TARGET CORPORATION 9

SOCIAL MEDIA STRATEGIES FOR THE DATA DRIVEN NEWSROOM 16

DENNIS MORTENSEN – CEO, VISUAL REVENUE 16

TOO MUCH TALK IN ANALYTICS & TOO LITTLE ACTION! 23

AJAY KELKAR – COO, HANSA CEQUITY 23

ACTIONABLE ANALYTICS 27

JAMES TAYLOR – CEO, DECISION MANAGEMENT SOLUTIONS 27

UNDERSTANDING AND MEASURING SOCIAL INFLUENCE 32

ARUN SUNDARARAJAN - PROFESSOR AND NEC FACULTY FELLOW, NEW YORK UNIVERSITY’S STERN

SCHOOL OF BUSINESS 32

HOW SOCIAL MEDIA CAN REVEAL THE MYSTERY OF BRAND LOYALTY! 36

G.K SURESH - GENERAL MANAGER, ITC FOODS 36

SCRM IN 2013: NEXT GEN SOCIAL MEDIA ANALYTICS 42

BHUPENDRA KHANAL – CEO, SIMPLIFY360 42

SOCIAL MEDIA BEST PRACTICES 51

ANKITA GABA - CO-FOUNDER, SOCIAL SAMOSA 51

INSIDE BIG DATA – WHAT’S IN IT FOR MARKETING? 56

DEEP SHERCHAN – CMO, SIMPLIFY360 56

SOCIAL MEDIA PREDICTIONS FOR 2013 61

PRASHANT JAIN - SOCIAL MEDIA ANALYST, SIMPLIFY360 61



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Preface

Today enterprises are overwhelmed with the possibility of social media. It’s been

proven that it is no longer a fad and it means serious business. At this turning

event of realization, enterprises are not equipped with right tools and human

resources to leverage social media.

On the other hand, we are seeing a rapid innovation in the field of social media

tools and technologies – social monitoring, analytics, marketing, intelligence,

scrm, big data etc.

As a result, we at Simplify360 tried to connect with different professionals active

in this field of social analytics and learn from them about the future of social

media. In this process we kept hearing predictive analytics as a repeating term.

Hence we asked our team to reach out to the experts in the field and learn about

what does predictive analytics mean in social media and its role in the future of

social media.

We would like to thank all the people who have agreed to share their experience

and knowledge about social media.



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What Are Predictive Analytics?

Aditya Chowdhary

Aditya Chowdhary, has over 16 years of experience in areas of Application Development, Marketing and Social Media

Analytics. He has worked with global companies like GE, Dell. He was instrumental at Dell to setup the Social Media Analytics

practice and very recently has joined Marketelligent.



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What are predictive analytics?

Aditya Chowdhary - Client Services Director Marketelligent

Predictive analytics have been around for a long time and slowly these analytic

tools are finding their way into the marketing and social media arenas.

Predictive analytics use behavioural data from past

to predict how individuals will behave in the future.

For instance, your credit score is a predictive model including your

repayment history and other information to predict whether you're a good

credit risk or not.

Predictive models commonly include a number of variables, such as number of

late

payments, and weighing factors that reflect the importance of that variable

in predicting future behavior. These are commonly regression-type models.

Modern predictive analytics use similar kind of data to build models to classify

people into different groups or predict their behavior . For instance, we might

build a model that



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predicts how much of a product we'll sell if we lower (or raise) the price.

While we won't be able to predict WHO will buy at the new price, we really

don't care. We only need to know if we'll sell more at the new price. Thus,

predictive analytics help us determine which marketing strategies will

produce the best ROI (Return on Investment).

How businesses use predictive analytics?

Businesses use predictive analytics in a number of ways, one such way is

discussed above. In addition, a number of tools, such as CRM (Customer

Relationship Management) use predictive analytics to determine marketing

strategies. Another type of predictive analytic is CLV (Customer Lifetime Value)

which uses purchase information to classify customers into groups and

determine the level of profit reflected by each group, which is used to

build marketing strategies for each group.

Descriptive models and predictive analytics

Descriptive models are often overlooked as tools for generating predictive

analytics because they suggest strategies that will generate better results

without being able to quantify how much better the results will be.

Source: griibdesign.co.uk

An example is the TRA (Theory of Reasoned Action). This model states that

buying behavior is impacted by a consumers attitude and beliefs about the

products, as well as the norms related to that purchase. This theory, ofcourse,



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underpins how social media works. Social media helps in building attitude

toward products, based on the references from the most credible sources - our

friends – and establishes norms of behavior when we see all our friends buying

the product. So, why aren't these descriptive models being used more frequently

in businesses? In part, that's due to poor exchange between businesses and

academics ,who seem to speak different languages.

Predictive analytics and social media

Social media analytics is a powerful tool for uncovering customer sentiment

dispersed across the countless online sources. As businesses feel the pressure

to gain new insights from social media, they require the analytics expertise

to transform this flood of information into actionable strategies.

There is a lot of internet chatter about social media analytics to predict

the future. This field of predictive analytics is in its infancy, but there has

been enough success to generate excitement about its potential.

In case of social commerce, any kind of buzz is a good buzz because it directly

translates into customer demand. For example, keeping tap of all the trending

topics on Twitter can be a useful exercise to predict future demands. This allows

business to leverage social media and maximize sales. Though the concept is still

in its infancy, 2013 is an exciting time where we could see some of these

concepts being implemented.



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Beyond Sentiments

Zishan Ansari Zishan is a SAS certified predictive modeler with over 4 years' analytics consulting experience for global players in banking,

insurance and retail domain. Zishan is currently part of Target Corporation's enterprise business intelligence team based in

India that provides analytic solutions to problems in operational risk, loss prevention and profit protection area.



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Beyond Sentiments

Zishan Ansari - Senior Business Analyst, Target Corporation

Source - http://provalisresearch.com/uploads/Sentiment.jpg

If you are reading this, you probably are aware of how things in the social media

world usually work. You probably have used/seen/heard of tools that tells you

about the sentiment of your customers, by analyzing what they are writing over

various social media platforms. And I am sure many of you would have also seen

software providers making tall claims about how accurate their engines are in

predicting the correct sentiment of a company’s customer base. There is no

question about whether sentiment analysis is a powerful analysis technique or

not, because it certainly is. The bigger question is whether it is the right thing for

you or not? And if it is, then do you have the ability to apply it correctly or not?

If you are looking for an answer to the question whether investment on

sentiment analysis is the right thing for your business, then read further. In case

you have already spent loads of cash on buying a sentiment analysis package,

still read further to know how you can best utilize it.

Why sentiments?

Being a part of a smart and proactive organization that listens to all its

customers, you would want to build a strategy where you:

· Listen to all that your customers are saying about your brand or a newly

launched product

· Take actions based on customer sentiments

· Redress customer grievances by offering him or her some brownie points

· And in turn be loved by your customers for being a great listener

Well, this all works really well when you are running a ‘Mom and Pop Store’.

http://provalisresearch.com/uploads/Sentiment.jpg



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Why? Because:

· You know who your customers are

· You understand their language

· You understand their moods, their emotions

· You know their preferences

· You know what will please/displease them

How are things different in social media?

Simple answer to this would be – in more ways than one. It is important for you

to understand these differences to figure out whether you need sentiment

analysis or not. .

Not every person is good in expressing themselves in text, and definitely not in

just hundred and forty characters. And this poses a big challenge.

Why? Because, there is no way to capture customer’s facial expression through

social media, nor is there a way to capture voice modulation to figure out

customer’s mood.

With deliberately excluding the discussion about misclassifications that majority

of the tools anyways do, there is one more aspect of language that I think should

be considered, and that is dialects. In this very world of ours, where spoken

languages change with every two hundred to three hundred kilometers, it will

only be illogical for us to expect everyone to express their sentiments in the

language in which our software’s NLP engine is trained.



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OK. So in that case will it be insane for us to demand for an NLP engine that has

the functionality of identifying the sentiments from any language/dialect. No, it

wouldn’t be completely insane. But it is very likely that you will be paying a

bomb to get such a service.

Let us assume that you get an NLP engine that has all these powers. Tell me who

writes a perfect language these days? If you think your customer does, then you

are absolutely wrong. Even Shakespeare would have had a hard time in

expressing himself in hundred and forty characters forget about an average Joe

(Pardon me if you are Shakespeare or Joe!). We are living in an era where even

native speakers are getting bad in grammar day by day. Languages are evolving,

and so are the NLP engines. And, more evolved an engine is, more dollars you

have to burn for it.

Knowing your objective

You will be solving the major part of the puzzle if you figured out what your

objective is behind sentiment analysis. Because, after this you just have to pick

the right approach to achieve your goal.

If you are managing a customer service center and you receive 100,000 e-mails

every day, and would like them to be classified as Positive, Neutral or Negative

then you can use software that has the capability to do the job.

That’s all the functionality you need to achieve your goal. Rest of the work will be

done by the executives to ensure each customer is satisfied.

Looking beyond sentiments

Say if you had kids. You find out on a Sunday morning that your kids were

annoyed about something and were not looking happy. Being a good parent you

give them permission to go out with friends. If you are a more involved parent,

you would yourself go out with your kids, to make their day. A parent very well

knows what to do to change the mood of their kids.



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As a kid I have really enjoyed that. Sometimes getting annoyed for no good

reason can also get you treats, just because your parents wants you to be happy

always.

But if you were a responsible parent, what else would you do? You would

probably try to understand, why were your kids upset at the first place? Have

they been getting annoyed quite often recently? What are the circumstances

which makes them unhappy?

A responsible company is no different from a responsible parent in this aspect. It

will do a root cause analysis of what actions led to all this. And they can take

actions to ensure that such circumstances do not arise in future. An organization

with a dedicated customer service team can probably do all what a responsible

parent do, given that they know who the customer is. It can spend resources to

get in touch with the customer, understand his/her concerns, identify the causes

of unhappiness and then act accordingly. It can also go ahead and analyze what

were the things that led to such circumstances.

So what should you do? Should you wait for a cheaper NLP engine with all the

functionality? Or should you wait until your company buys a foolproof text-

analytics software license?

It is important to be clear about what exactly is your objective to perform

sentiment analysis. You can then combine the results from a not so very

expensive tool with other free tools or with your own data visualization tools for

analysis.

Stream Graphs

One such freely available tool is stream graph. It helps you in analyzing what

people have been tweeting about a brand/product over a period of time.



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Figure: (Source - http://www.neoformix.com/Projects/TwitterStreamGraphs/view.php)

The Stream Graph shows the usage over time for the words, which are highly

associated with the search word. One of these series together with a time period

is in a selected state and colored red. The tweets that contain this word in the

given time period are shown below the graph. You can click on another word

series or time period to see different matches. In the match list you can click on

any word to create a different graph with tweets containing that word. You can

also click on the user or comment icons and any URL to see the appropriate

content in another window. If you see a large spike in one time period that hides

the detail in all the other periods it will be useful to click in the area to the left of

the y-axis in order to change the vertical scale.

The bad part is that the free version analyzes latest thousand tweets. The good

part is that there are open source resources (http://www.processing.org/)

available to help you develop such graphs. Probably you need to invest some

time to develop that. Remember, there are no free lunches and there are no free

graphs either.

You can combine the results of the sentiment analysis with the results of stream

graph analysis to infer what circumstances probably led to positive or negative

sentiments. So even if your sentiment analysis says that 80% of your customers

have neutral opinion and your sales figures are way below your forecasted sales,

http://www.neoformix.com/Projects/TwitterStreamGraphs/view.php

http://www.processing.org/



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a stream graph can help you identify what probably is causing the low sale.

Stream graphs present one way of visualizing the data. There can be multiple

such ways of analyzing it.

A good analyst will always find a suitable way of presenting the appropriate

information that you would like to have in order to validate your sentiment

analysis findings. And remember without validation, your results from sentiment

analysis in the worst case can be as bad as that from a random classifier.



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Social Media Strategies for the

Data Driven Newsroom

Dennis Mortensen

Dennis Mortensen is CEO & Founder of Visual Revenue, Inc., whose Editorial Support Platform helps editors to better place

content and provides real-time recommendations and predictive analytics to more than 250 global online publishers,

including Comcast, The Atlantic, NBC Universal and Le Monde. He is the author of Data Driven Insights from Wiley and sits

on the Board of the Digital Analytics Association.



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Social Media Strategies for the Data Driven Newsroom

Dennis Mortensen – CEO, Visual Revenue

Just as the Internet itself began to upend news and journalism in the mid-1990’s,

so too has social media added another layer to that upheaval. Perhaps even a

greater one that doesn’t just change the delivery and consumption of news and

information, but the creation and molding of the stories themselves. To compare

the changes, it would be one very large order of magnitude.

Social Media: Newswire or Newsroom

It’s agreed that the prevalence of mobile devices and social media tools has

turned everyone into a publisher of sorts. While not every individual can hope to

monetize their tweets like a celebrity, every last tweet out there has the potential

to affect journalists and the gathering of news. They may not lead the story, but

they’ve become parts of the stories told (man tweeting Bin Laden raid) and parts

of the newsgathering process (Egypt and the Arab Spring).

In the 24 months since Andy Carvin of NPR provided a model for futuristic

newsgathering by tweeting at potential sources and confirming reports from

afar, many, if not most, journalists have found their way onto Twitter and are

using it to the same effect.

In the same short span, this same move to the center of the news has happened

in the newsrooms themselves in the way that content is pushed out to an

audience. The Social Media Editor’s role was created to evangelize and

educate. With so many journalists of all stripes now savvy in social, it has

become critical to determine and assign both ownership of the social channel

within the newsroom, as well as ownership of the content that goes out under

each individual feed.

Defining Success in Editor and Publisher Terms

As more and more people in the newsroom have moved to publishing on the

many social platforms available to them, the movement to measure that activity



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has followed. For most individuals, a somewhat limited view of success in social

media is defined simply by response. Did I get re-tweeted? Favorited? How

many @ replies do I have? What’s my Klout score?

This level of measurement is fine for the individual, but not for media

companies – where activity must be measured by the way it delivers

audience, and by how that audience ultimately can be monetized.

For online properties, if you want to increase your audience, that content must

be exposed to new audiences on a regular basis. Publishers understand this, and

most quickly go to Facebook, Twitter or other social media channels to expand

their reach.

Yet the true impact on their business –

success or failure – is very difficult to

measure. Sure, they can measure

tweets and favorites and likes and other

vanity metrics. It’s easy and can be a

trap that is fallen into quickly. But re-

tweets and favorites and shares only

have a secondary effect upon the

business, and they hardly measure

audience interaction.

The editors in large newsrooms of leading editorial operations need to know

more. Just as with the content and activity on their own websites and properties,

they want and need to measure social media similarly.

For example, what are the expectations of content published? If editors at The

Atlantic, publish a piece of content at 1pm, it would be fair to have an expectation

on how much direct output it will generate:

How many views should this content generate?

How many views does it actually receive?



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Is this content that should be shared on social media?

If so, when should it be shared to attain the maximum impact?

As a process, editors and their social media tools should essentially follow a

process of (1) finding and selecting the proper content; (2) pushing that content

into the social channels; (3) measuring success and/or failure, and (4) learning

and optimizing from it.

When editors begin to answer these questions and follow this process, they

make the definition of their success in social media more precise, and they move

away from the vanity metrics of the consumer marketplace. It is one of the things

that separate the genuine publishers from the “everybody’s a publisher”

publishers.

Determining Success and Failure in Real Time

The real-time nature of social media interaction makes it a natural complement

to the newsroom. It is, however, that same fleeting aspect that makes real-time

success measurements akin to capturing lightning in a bottle for them. It can

only be done with some of today’s more sophisticated tools.

With the proper tools in hand, news organizations can have more exact

measurements on social media. For example, they can have a means to

determine the difference between tweeting content at 4:23 p.m. and 4:35 p.m.,

followed by recommended actions based on real-time performance and



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consumption data. Additionally, the best tools can tell editors whether or not to

include photos when sharing or tweeting, which accounts to share on, and

sometimes, the value of sharing specific content multiple times.

This difference can be significant for some properties versus others. Patterns for

when and what to share exist, but they tend to be very much property-

specific. They are so specific that, for example, one news organization can share

content with equally powerful results from dawn ‘til dusk, while another will

only succeed in limited windows. What works for one news organization won’t

work for another, largely as a result of audience fragmentation having intensified

to the degree it has.

Figure 1: Historic Success Measurement for Leading Online Properties

A comparison of activity for two leading online properties, showing hourly clicks into

their article content via social media. Note that one property, in addition to an overall

larger number of clicks per hour, never truly falls to zero, while the other does so almost

every night.

For the editor and the newsroom, this makes their social media activity only

worth the time that they invest in measuring it -- not for the vanity metrics, but

for the deeper ones. This is where their ability to know true success from simple

failure will show whether their time spent sharing (to grow their audience) has

been well spent.

Using Predictive Analytics to Determine Your Next Step



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Editors today, particularly social media editors, live within what can be an

endless torrent of information, opinions and activity. They are called upon to

quickly whittle it all down, and make quick, yet significant decisions about the

placement and direction of content. Given social media’s real-time nature, the

use of predictive analytics can help data-driven editors to stay one step ahead of

the game.

Figure 2: Benchmark Performance Predicted for Two Leading Online Properties (24-

hour period)

A comparison of the expected social media activity for two leading online properties,

showing hourly clicks into their article content via social media. Note that one property,

carries a consistently higher level of activity that (a) peaks more sharply during key

periods, and (b) maintains a significant level of inbound clicks (views) throughout the

overnight period.

Whereas these decisions were once made based on intuition, skill and instinct,

there now exists a huge pool of data that, when properly applied, can enhance an

editor’s judgment with suggestions and the additional confidence to take

decisive action.

The genuine value of such predictive algorithms is in the ability to recommend

specific actions for an editor within an editorial framework outlined by the

organization. Separately, these two elements are important; together, they

provide a powerful engine for editors to act immediately, secure in both their

judgment and the interest of their publication.

These new tools simplify data and tell a newsroom when it should tweet and also

what it should be tweeting. The computerized suggestions take on the role of a



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deputy editor: someone who knows the history of the data, as well as editorial

values of the paper, and can therefore determine the best publishing strategy to

follow.

In the end, it is still the editor making judgment calls. They just happen to be

faster and better calls.

Conclusion

Today’s data-driven newsroom relies on many tools to keep pace with the real-

time nature of communications. Social media is a natural fit for the newsroom,

both in the collection and dissemination of the news, but it needs to be deployed

within a editorial framework. Without one, the publisher may as well be an

individual. But with a clearer, data-driven strategy for measuring the success and

failure of the outbound social media, the newsroom of today will be ready for the

news of tomorrow.



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Too much talk in Analytics &

too little action!

Ajay Kelkar

Ajay Kelkar, Co-Founder & COO of Hansa Cequity, has over 20 years of experience in customer-driven marketing across a

wide range of industries like Soft goods, Banking & Financial services & Retail. He has had exposure to a wide variety of

business styles & cultures across Procter & Gamble, Britannia, Marico, Shopper’ Stop & HDFC bank.



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Too much talk in Analytics & too little action!

Ajay Kelkar – COO, Hansa Cequity

Is analytics yet another fad? Is there much more talk about it than real solid

action. It does seem so when you look around you as a consumer.

Marketers still don’t care, as much, about being relevant to you. You get that

umpteenth credit card solicitation from the bank which has already sold you a

card. And nothing about a physical Retailer shopping experience makes it

personal for you!

And yet your online persona seems to be treated differently & when you go to

Amazon & other sites you do get a feeling of getting offers being recommended

for you. And as a consumer you flit between your online & offline avatars & this

becomes more & more obvious.

What’s the difference? Is there a category of organization which is able to

leverage “data” far more effectively?

Gartner says that only 20% of enterprise will use more than 50% of the total

data they collect to gain competitive advantage.

This is what software architect Grady Booch had in mind when he uttered that

famous phrase: "A fool with a tool is still a fool."



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Google-executive-turned-Yahoo-CEO-thought-leader Marissa Mayer declares "data

is apolitical" and that her old company succeeds because it is so data-driven: "It all

comes down to data. Run a 1% test [on 1% of the audience] and whichever design

does best against the user-happiness metrics over a two-week period is the one we

launch. We have a very academic environment where we're looking at data all the

time. We probably have somewhere between 50 and 100 experiments running on

live traffic, everything from the default number of results to underlined links to how

big an arrow should be. We're trying all those different things."

A recent Ad Age article carried this comment:

British Airways spent almost a decade corralling passenger data from 200 sources

into one database. It built infrastructure to support the number crunching, but

perhaps the harder piece, said Simon Talling-Smith, exec VP-Americas, is getting

in-flight personnel to use the technology and data to create better consumer

experiences. And BA introduced onboard iPads to send in-flight crews passenger-

specific information, but Talling-Smith said encouraging staff to use them is still a

challenge. "Probably half of the messages don't even get delivered," he said.

Maybe there are some learning’s here:

1. Analytics doesn’t need you to solve a technical problem but a “business &

social” problem. And most Business analysts have not spent much time in

business roles. They are super specialised number crunchers without a sufficient

exposure to business reality. Even if the managers have some exposure to

business through experience across a variety of analytics projects, is it

http://www.academicearth.org/lectures/data-is-apolitical

http://www.academicearth.org/lectures/data-is-apolitical



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enough? Does this bring the analytics career into some jeopardy? Would

analysts be able to grow in companies beyond a level or is it a parallel

consulting stream only?

2. Analyts need to “Story tell” to embed analytics into the fabric of the company.

But analysts are too one-dimensional & not embracing the intersection of

“technology, statistics & business”. So analysts struggle to tell stories. Often I see

journalists do a far better job with infographics in media. But information

journalists are not wanting a career in analytics & so there is a gap in “story

telling”.

3. Analytics is too theoretical. Not enough integration with systems has

happened to push decisions to the point at which consumers interact with the

business. This is far easier to do in new Online businesses which have built their

systems around this capability. CIOs & technology teams in large existing offline

businesses don’t see this as important.

4. Average age of employees in online business is far lower. Younger people are

adopting analytics far faster. They are getting exposed to it in their education &

they are consuming it through their “digital avatars”. They see this often as a “no

brainer”. Older executives are harder to convert to this line of thinking.



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Actionable Analytics

James Taylor

James is the CEO and a Principal Consultant of Decision Management Solutions. He is the leading

expert in how to use business rules and analytic technology to build Decision Management Systems. James

is passionate about using Decision Management Systems to help companies improve decision making

and develop an agile, analytic and adaptive business.



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Actionable Analytics

James Taylor – CEO, Decision Management Solutions

The use of analytics, especially predictive analytics, to improve business results

is a key focus for marketing departments around the world. The potential for

new sources of “big data”, such as social media, to improve analytics results is

getting attention too. To add value, though, any analytics must be actionable –

and acted on. Experience suggests that making analytics actionable is harder

than it looks, with far too many analytic models sitting unused or failing to have

a significant business impact.

Part of the reason that organizations struggle with making analytics actionable is

that they have a mistaken belief that using analytics will tell them how to change

their business. They believe they can do some analytics and get a great “aha

moment” that will tell them to start doing something differently or stop doing

something else. They believe that analytics will give them huge, one-time

improvements in their business. But they are wrong. Analytics will not tell you

how to change your business. Instead you must change your business so that

analytics can help you run it more effectively. You must change your business,

change the way you interact with prospects and customers, so that your

analytics can be actionable.

To make analytics actionable many

organizations are turning to Decision

Management. Decision Management is an

approach to analytics that focuses on decisions

first – identifying, modeling and managing

critical business decisions and applying analytics

to improve those decisions. Decision

Management does not begin by asking “what can

we measure” or even “what does this data tell us.” Decision Management begins

by asking which decisions matter to our business? Which decisions, if made



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correctly, will move our business performance in a positive direction? How,

exactly, do we move the dials on our dashboard?

By identifying the decisions that can be improved with analytics, Decision

Management identifies where your business will have to change to account for

analytics. It identifies the decisions that are made the same for every customer

where analytics could target or personalize those decisions. It identifies the

decisions where you segment customers by channel where analytics would

segment them by behaviour.

These decisions are often not the first ones that come to mind, however. Instead

of focusing on big strategic decisions or on management decisions, Decision

Management focuses on decisions about individual customers or prospects.

These “micro decisions” are often hidden in an organization - hidden because

although organizations realize they make a decision about their customers, they

do not realize how many they make.

For instance, if you decide to send a marketing email to a subset of your

customers you might think you have made just a couple of decisions such as

what to put in the email and who receives it. And you might think that you could



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use analytics to come up with a much better email or target list. While you have

made these two decisions, you have also made a decision for each customer to

either receive or not receive the email. Therefore, if you have 10,000 customers

you just made 10,000 decisions – one for each customer. Similarly, if your

website has a thousand visitors each day and you have decided on a promotion

to display then you have made a thousand additional decisions just today – to

display this promotion to each individual visitor.

Organizations are increasingly realizing that these micro decisions can be made

one at a time, treating each customer uniquely and relying on analytics to

personalize and target the promotion, message or content delivered. By changing

your business to think of these as micro decisions, decisions about a single

customer or prospect, you can make your analytics actionable. Now your

propensity models are actionable, for instance, because you make the email

content vary depending on what each customer is likely to buy. Because

predictive analytics tell you what’s likely to be true for a given customer, they are

actionable only in the context of a micro decision about that customer.

This focus on decisions addresses one of the biggest challenges in developing

actionable analytics. By focusing on decisions that must be made and by tying

these decisions to the way the business operates, the metrics that matter to it,

analytic teams ensure they understand the problem that must be solved and that

they can clearly see what success looks like – how they will measure the value of

their analytics. Decision Management also creates a shared framework and

collaboration environment for the business, IT and the analytics teams. Because

all three groups understand decisions and decision-making, they can come to an

understanding of the problem by identifying and prioritizing the micro decisions

that drive the organization's success. Decision Management links these decisions

to the business drivers and performance measures that have the most impact on

the business. Modeling the decisions to be analytically improved clarifies and

focuses analytic projects.

Predictive analytic models can now be built to influence these decisions,

predicting the risk or opportunity in each customer or prospect. Because these



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decisions are high volume even small improvements can make a big difference,

making it possible to begin showing a positive result from relatively simple

analytic models. These decisions often need to be made in real-time so these

predictive analytic models must be deployed into automated decisioning

solutions such as offer or ad engines.

Once built these solutions will need to evolve and improve both to increase the

quality of decisions and to ensure that changing circumstances are reflected in

the way decisions are made. Decisions are high change components, impacted by

changes in markets, consumer behavior, regulation and data. Collecting data

about what works, continually refining the predictive analytic models you use

and optimizing over time ensure the best possible outcomes.

Analytics are a potentially powerful tool in your toolkit, provided they are

actionable. Focusing on decisions first, and on micro decisions, will make sure

they are.



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Understanding and Measuring

Social Influence

Arun Sundararajan

Arun Sundararajan is a professor and NEC Faculty Fellow at New York University’s Stern School of Business, and an expert on

influence in social, economic and political networks. His award-winning research has been widely published in scientific

journals. His recent op-eds have appeared in outlets that include Bloomberg, Financial Times, Harvard Business Review, The

Mint and Wired.



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Understanding and Measuring Social Influence

Arun Sundararajan - Professor and NEC Faculty Fellow, New York

University’s Stern School of Business

A couple of weeks ago, I had an interesting classroom discussion with my MBA

students at the Indian School of Business about the relative “influence” of Shashi

Tharoor (1.67M Twitter followers, Klout score 84) and Priyanka Chopra (3.49M

Twitter followers, Klout score 85). That room full of digitally savvy future

business leaders concluded, among other things, that:

1. Yes, both were indeed both influential – Tharoor in the realms of politics

and literature, Chopra in the realm of fashion;

2. The actual content in their Twitter feeds had very little to do with their

domains of influence, and

3. Twitter (and thus Klout) was more a reflection of their real-world

influence rather than the channel by which they garnered their influence.

You might debate each of these points (as they did), and come to different

conclusions about points (2) and (3) for other “influencers”. And you might end

up being right. The point is, the science of measuring influence is still in its

infancy, and there are still substantial gaps between actual influence in the real

world, and what the data trails of our online networks capture. Here are three

simple lessons that can guide us in the interim:

Things that look like viral spread are often simply demographics

It is often exciting to see application downloads, advertisements or product

adoptions that appear to be spreading through a customer base, and makes all of

us want to identify the influencers. However, there are many different reasons

why such outcomes might “cluster” across customers who are connected via a

social media platform like Facebook or an email/IM network.

We have known for decades that “birds of a feather flock together”, or people

who have social connections tend to be similar, a phenomenon sociologists call



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“homophily”. When you see clusters of connected customers making similar

choices, it could simply be because they have similar tastes, which causes them

to be friends, and these tastes (or demographics) are driving the choices. Or it

could be even simpler. The choice itself -- for example, adopting Instagram --

could be causing the creation of the friendship ties, something we call “selection”.

The trouble is, in the data, both these explanations look identical, and exactly the

same as a third – that your product or idea is in fact spreading virally because of

genuine person-to-person social influence. But the marketing implications of

this difference are huge. If you have real influence, a viral marketing strategy is

the way to go the next time around. If not, a demographics-based approach

would be better.

Smart companies are therefore moving beyond network simulations, superficial

analysis and measures like Klout, delving deeper into capturing the flows of data

and measuring influence more precisely. The techniques aren’t too complex1,

and easily implemented – you just have to know to look out for them.

Lots of small contagions are generally better than one giant epidemic

A series of studies Yahoo and Microsoft Research have shown that an

overwhelming majority of influence-based spread over social media has very

little depth. That is, over 99.9% of the total volume of online social contagion

comprises one or two steps, and it is very rare for something to spread widely

over Twitter, Facebook or any other emerging digital platform.

This has important implications for how you allocate your advertising money if

you are in fact targeting influencers to spread your message. In most cases, if you

spread your budget over targeting a large number of somewhat influential

people, rather than going after a few extremely highly connected ones, you will

get better returns.

1 1 See, for example, Aral, Muchnik and Sundararajan, PNAS 2009,

http://www.pnas.org/content/106/51/21544

http://www.pnas.org/content/106/51/21544



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It’s not just the network, it’s the content as well

When the lights went out during Superbowl 2013, the marketing brains at Oreo

rapidly generated the following ad content rapidly:

A link to this ad, tweeted from @Oreo (which had, at the time, a mere 65,000

followers) generated 16,000 re-tweets and 6,000 favorites, (more than triple

what President Obama’s most successful tweet generated after the State of the

Union speech), making this perhaps the most successful advert of the Superbowl.

Often, in our quest for influencers, we forget that good content can create its own

viral spread. Some companies like Buzzfeed are building a business on this idea.

Extreme humor like theirs isn’t always necessary – what’s critical to remember is

that even in our brave new world of social marketing, the message is still at least

as important as the maven.



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How Social Media Can Reveal

The Mystery Of Brand Loyalty!

G.K Suresh

Mr. G. K. Suresh is the General Manager - Brands with the Foods Business of ITC Limited looking after

the categories of Staples, Snacks, Confectionery, Noodles and Ready to Eat products. GK has worked in a

variety of roles from Sales to Trade Marketing to Brand Management. In his prior assignment, he was

Head - Brands and Business Development with the Personal Care business where he oversaw the launches of brands like

Fiama Di Wills, Vivel and Vivel Active Fair - across the intensely competitive categories of Soaps, Shampoos and Fairness

Creams. He was also Trade Marketing Development Manager responsible for the development of Distribution and IT strategy

for all ITC's FMCG products.



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How Social Media can reveal the mystery of brand loyalty!

G.K Suresh - General Manager, ITC Foods

Let’s face it. Customers are no longer loyal or rather they are loyal but to brands

that understand and engage with them in the new world. The messages carried

by the advertisements are no longer compelling. For years, brands were able to

suppress the consumers’ voice. But now, all it takes is a Tweet or a Facebook

update from an irate customer and the world knows about it. Honesty has

become most brands’ top priority.

Maintaining brand loyalty has suddenly become the biggest challenge. Moreover,

the entire concept of loyalty is vague. All thanks to Facebook, where one person

is interacting with several competing brands, all at once. In such a scenario,

traditional branding exercises are no longer effective in getting the attention of

customers. This is further complicated by the variety of devices where such

micro eco-systems exist.

This is the result of the digital convergence of culture, business and economy

into bits and bytes. So, this is where lie not only the challenges but also huge

opportunities for brands to understand their customers. Digging into the wealth

of social media data, brands can today discover consumer insights like never

before.

There are 4 steps to understanding customer insights through social media:

· Find out what people are talking about and why

· Find out who is talking and influencing the crowd

· Use this intelligence to optimize your brand’s message to impact in real-time.

· Measure your interaction and influence of the messages and optimize them.

One brand that has successfully utilized the above steps is Bingo! with the launch

of Bingo! Tangles on Facebook. Snacks is a category where the customers seek

variety and Facebook fans like to participate in the contest and win gratification.

Taking both the insights we decided to launch the new Bingo Tangles first on



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Facebook and give a chance to loyal Bingo! fans to discover the product and also

taste it before it hit the market. A teaser contest was created for Facebook fans

which encouraged them to decipher the brand name and the winners could taste

the product before it was made available in the market. Thousands of fans

participated in the contest and packs of Bingo Tangles were couriered to the

winners. This campaign helped us connect with the brand advocates and also use

Facebook as a launch platform for various other brands.

Data is a vital raw material for building the business infrastructure in the

information age. Brands that can put systems in place to access, process and

utilize the data will be the most successful in connecting with the customers and

influence their decisions.

The key idea behind customer loyalty is customer retention. There are already

different programs, which businesses employ like reward programs, referral

programs and 1-to-1 marketing campaigns to ensure that customers stay with

the brand. But social networks are taking over these programs in terms of

gaining a deeper relationship with the brand.

There are 4 ways to use social media data to improve and make social programs

much more effective:



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1. The Brand should genuinely care

When you embark on the social media journey, be prepared to respond to

negative as well as positive feedback and genuinely do something about

consumer problems. To explain, let’s look at a scenario that we faced on

Aashirvaad where one of the fans brought to our notice an unavailability of

Aashirvaad atta in a particular store in his area. We asked the fan to give us more

details on the location and the store so that we could look at resolving the issue.

Once we investigated the issue we figured out that this was an issue due to the

sales person operational in that area. We immediately replaced the existing sales

person and appointed a new senior sales person to take care of the region and

resolve the unavailability issue. Thus listening to a single fan, who was

representing a cluster of consumers in that region, we were able to resolve

issues faced by many such consumers in that region.

2. Engage without losing focus on your brands

Many times the focus on the content posted on Social Media platform goes to

extremes. Either it is too generic or it is too brand centric. There should be a

proper balance.

3. Harness the power of Social Media

Brand Social Media presence is a strong platform for Brand advocates and they

do not leave a chance to defend their brand.

Eg. Once there was a complaint posted by a fan on Aashirvaad Atta regarding a

packaging problem. It so happened that before the brand owners replied to the

post there were many comments from other fans trying to address the issue and

also recommended the steps to be taken. A few fans also replied saying that this

might be an exception to the norm, as in the case with Aashirvaad and they never

faced any issue and also advised the fan to check the storage in his kitchen which

could have led to the problem.

4. Brands have to learn to converse with consumers as equals.



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Brands are too used to speaking to consumers from a position of authority &

knowledge and not as a friend. But today brands need to learn to converse with

the consumers logically & be seen as an enabler.

So we now know why and how social media can help decipher the mystery of

brand loyalty. But the last portion and the most vital one, is to understand how

to measure this in social media. There are 4 factors, which one must consider

while looking into brand loyalty in social media:

1. First of all, what are customers talking about your brand and how? What are

their attitudes and sentiments towards your brand? What is their feeling

towards your brand? Are they neutral, friendly, hostile or ignorant? This helps

brand not only understand the emotion but also map them along the brand

attributes and identify the missing bits.

2. Secondly, to understand the emotional connection between a customer and

your brand and measuring the strength of the bond. Most often an out-burst by a

customer is temporary, and can be mitigated easily. Hence, identifying such

customers is vital.

3. Thirdly understand that the customer is likely to buy more than one segment



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of products from the brand. This sends much a stronger signal of loyalty.

4. And finally, know which platforms are more effective in communicating with

the customer. Email, Social Networks, Mobile, TV, Tablets and the list goes on.

The avenues where customers are present are wide. Hence identifying the top

engaging platforms and optimizing them is vital.

Mining social data and building your decision systems on top of it is the secret of

successful customer retention. The main goal is to make an emotional connection

with the customer in each interaction to increase referrals, retention and

acquisition.



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SCRM in 2013: Next Gen

Social Media Analytics

Bhupendra Khanal

Bhupendra is the co-founder and Chief Executive Officer of Simplify360. Prior to this he was a manger and founding member

at Marketelligent, an Analytics Consulting company. Earlier he worked at Fair Isaac (now FICO) as Marketing Analytics

Consultant and served clients like Hartford Insurance, Smith and Hawkins, and Coca-Cola. Before FICO, Bhupendra

worked at Global Analytics as Business Analyst, and lead a team of 6 people to develop and implement Enterprise Decision

Management System for Sub-prime Banking in United States.



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SCRM in 2013: Next Gen Social Media Analytics

Bhupendra Khanal – CEO, Simplify360

The time when people discussed tools is long past. 2013 will talk about business

outcomes, KPIs and unified systems that streamline business functions. Social

Media is moving towards becoming a general utility medium much like Phone or

Email. Remember, even though these mediums are used for customer service, no

one refers to them as such exclusively.

Social Media is highly misrepresented in business circles. It is regarded as an

advertising medium to amass Facebook fans and Twitter followers. This should

end now.

We should start looking at the business functions and use Social Media to achieve

the business goals. The KPIs needs to be defined and best practices built up. And

to make all these things happen, Analytics has a major role to play.

Here are some of my recommendations.

1. Social Media is more than Engagement. Social means business.

Enough and more has already been said about Social Media Engagement. Let us

outgrow it. Let us talk about the real business impact. Obviously, the same

business metrics work for Social Media that work for other mediums. The value

has to be in one or more of the following:

a. Increased Revenue

There are multiple avenues of revenue realization through Social Media.

Companies are trying offering discount coupons and cross-selling products in



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each other’s Social Channels.

Most companies have not been able to generate leads for business. But this was

true for all earlier adopted channels – Television, Radio, Email etc. The leads are

best generated and tracked with high confidence through PPC Ads.

For Social Media to be successful, it is very important to have clear revenue goals

and a strategy to back it. We, at Simplify360, have been very successful in

generating a good number of leads from Slideshare. It works great for a B2B

Model.

b. Increased Buzz

Social Media does not only have consumers. It has resonators too. And this can

be highly leveraged by properly building a community and keeping them active.

The message once gone viral is more powerful than several passively played ads

in other channels. Reason – the message flows in the form of recommendations

between friends and connected individuals. The trust factor is thus high enough

to show some amazing output.

c. Cost Savings

Take the example of a BPO operation. The average cost per call from a BPO

company to the consumer costs an average of USD $0.1 (INR 5), while the cost of

receiving a call on time from a customer is USD $1 (INR 50).

The difference in the price occurs as the BPO Company needs to charge for

resources waiting for the call too. This adds to the phone bill charge.



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Now take the example of a Social Media Contact Centre. Several people may post

complaints on Facebook or Twitter, a few reps can quickly handle it and respond

like an Internet Messenger. The benefit here is no one needs to remember each

other’s phone number or email id. Bonus – huge savings on manpower cost. Add

to it the removal of phone bills. Simple internet connection will suffice. This

results in huge savings overall.

2. Integration is the way to go. Social CRM is the future.

You might have a million fans on Facebook and you probably have a few million

customers. And a million times, you have asked your Social Media Agency how

many of those fans are your customers and how many sign-ups you received

through the medium. You have been a badass towards your agency.

Here is the bad news – your agency does not have the answer. But there is good

news too – you can have those answers. The answer surfaces when you start

looking at it closely and ask your IT guys to work closely with the CMOs office

and to do proper CRM Integration.

You may choose to outsource it too. And I feel, this is a better solution as when

two C Level officers get involved, the work hardly gets done on time. Let the CMO



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take on an outsourced partner and get the CRM integration bit done.

Now get your customer service guys, HR guys and Finance guys involved, and

quickly move towards making the whole Enterprise fully Social. The future, and

your unfair advantage over competition starts here.

3. Need to rise above the MIS Reports. Predictive Analytics is the way to

go.

You have Social Media data, and you may have some good MIS reports that show

the historical trend and some behaviour graphs. Do not assume that you have

enough intelligence required to run the business.

You probably have the intelligence to run the business but you might be just

missing enormous opportunities by not mining this valuable data and getting

business insights.

After the data mining and insights extraction, another window opens and that is

for predictive analytics and forecasting. The Social Media data is a not only an

indicator of existing issues or

opportunities, it might be pointing to a

huge market shift.

Had Blackberry focused enough on

Social Media and mined the incoming

data for iOS and Android, it wouldn’t

have been left behind till now, in the

Smartphone war. All it needed was

time to counter the two biggies with a

good PR campaign and launch some

quiality touch screen phones. They ignored this and kept ignoring it till the CEOs

office got into a crisis with both the top-line and bottom-lines being badly hit.

4. KPIs of Social Media. ROI in focus.



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We talked about direct business impact. Now let me talk about some direct KPIs

that show real business impact.

a. Increased Revenue

The KPIs here need to be:

i. No. of leads

Youtube, Facebook, Twitter need landing pages and links to track the number of

leads that get realized. Slideshare provides a way to capture leads through form

submission.

It is important to realise that such social media leads are mostly the leads that

show interest in your product and not necessarily an interest in buying the

product. This does not hold true and there can be a direct buying interest in

leads if a coupon is downloaded through a Facebook App, for example.

ii. Quality of leads

It is important to track the quality of leads in terms of further communication

that goes with the generated lead. The conversion rate is the best metric to judge.

Do not get carried away with the noise about Social Media and look for other

metrics. Simple business metrics work great here.

iii. Volume of business generated

Together with conversions, keep a tab on your volume of business. This is



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simple.

Volume of business = Sum (converted leads * revenue from the leads)

If I have to look at Simplify360, most of our business conversions have happened

from the leads received through our Social efforts. The number currently stands

at slightly over 50%.

b. Increased Buzz

Increased buzz is best measured using the PR logic. The price that a company

would end up paying for ads on various digital or non-digital channels.

Remember buzz is not merely the number of mentions on the web and no. of

retweets or shares. But this has to reflect in the form of actual money gained or

saved by the company.

Here is an example:

Tata Docomo gets a coverage of 10 news mentions a month on the front pages of

major national dailies for being the most followed Facebook page in India. The sum

of the ad cost for those 10 spaces is a direct saving for the company.

Now add to that the total amount of digital ads that Tata Docomo would have paid

for, in getting ads across the digital formats of those national dailies. The amount is

not small.



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You should further move ahead and add the PPC rate for all the clicks that you

receive from any Social Channels.

5. In the Social Era, Intelligence is real time.

The time has gone when you would visit a Market Research agency, ask them to

do a survey, collect the results in a month or two, analyse the data and get the

report in 3 to 4 months. The pace at which innovation happens now and markets

shift, the traditional market research reports will be as good as useless.

Current business scenarios call for a real time intelligence monitoring system,

and no medium can deliver it better than Social Channels. The Social Media

stream is real-time and there are enough systems like Simplify360,that provide

intelligence on brands, competitors and markets in real time. Waiting for reports

is a part of history now. Welcome to the intelligence revolution.

6. Social Media is no more CMO’s problem. It is the CEO’s problem.

You are making a Big mistake if you consider Social Media as just a part of Digital

Media Marketing. It is not. Social Media is a part of Digital Media, but it is not

limited to Marketing Functions. It is more like Email and Phone. It is a resource

that the whole company needs to play with and take benefit from.

Social Media is thus, a CEO’s problem. It is a brand reputation problem, it is a

social media marketing problem, it is a customer service problem, it is a human

resources problem, and it is an investor relations problem.

At Nestle, the Communications Vice President is responsible for Social Media

efforts throughout the company. For ITC Foods, it is the marketing head and

individual brand heads who take the call. For Coffee Day, CMO Ramki himself

gets involved. And for Mahindra Group, Group Chairman Anand Mahindra

himself leads the Social Army. The way companies use Social media varies

greatly, and this, I feel, is the outcome of a lack of defined best practices in the

Social Media industry.



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More and more companies are now following the Anand Mahindra Model or

Michael Dell model. The CEO leads the charge.

Make no mistake. Take Social Media seriously. It is a CXO problem. Without a

senior level involvement, Social Media can be a disaster as much as it results in

the loss of huge opportunity.



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Social Media Best Practices

Ankita Gaba A Social Media strategist and consultant, Ankita Gaba has co-founded her second

start up, Socialsamosa.com, An Indian Social Media Knowledge Portal.She loves networking, meeting

new people and is a big time shoeoholic.



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Social Media Best Practices

Ankita Gaba - Co-Founder, Social Samosa

You probably have got your brand on board social media and are working with

your team or agency on taking it ahead. You have great expectations from social

media and want it to work wonders for you.

But will it be of any help to you? Of course it will be, if you follow the following

best practices.

Organizational adaptions:

Involve all departments:

Social Media marketing is passé. Social business is in. Social Media cannot work

in a silo, it cannot be used as a push marketing tool anymore. It is and it will be a

two way conversation. On social media, you will get customer queries and

complaints. So you need to have an alert customer service department in your

organization and a one who is trained and equipped to handle queries on social

media, before they become a big PR crisis.

The sales team will also have to jump in, to nurture leads that come in from

social media. The product innovation team will get the necessary feedback from

the consumer conversations for free, where they tune in to listen that is, which

will help them redesign the products or services to increase performance. The



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mine of conversations, if analyzed, will help the market research team

understand the consumer behaviour and consumption patterns.

The idea is to think beyond one department and one benefit of being active and

harnessing the power of social media.

Train your HOD’s:

You cannot expect active participation from all the departments if you don’t train

and encourage the leaders. The objective should be to make them comfortable

with the medium, to make them understand the importance of jumping into

social media.

Hands on training will facilitate the process of converting the rigid lean

organization style functioning into a more free flowing one. Social media can be

the catalyst for encouraging HOD’s to work closely with each other.

Internal Social Network:

On the above note, encouraging social interactions at the workplace through an

enterprise social network will boost the flow of information within the

organization, make it a more humane place to work at and thus increase

efficiency and productivity. If this interests you read on here.

Strategy level adaptions:

Have a personality

Simply broadcasting content will not take you anywhere. It is essential to have a

brand conversation style, a pattern and a personality. It is this personality that

will help the brand stand out in the ocean of conversations online.

Flipkart is known for its quick and witty reply. F&B brand Hippo for its one liner

puns. This helps consumers remember and recall. It breaks the monotony in the

overload of conversations.

If you have a personality for your brand in all your offline communication plans,

you only need to either duplicate or improvise on that. The personality will also

http://beckercv.wordpress.com/2010/10/10/ibm/



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help you have a sustainable strategy in place.

Sync offline strategy and positioning

You don’t want to be one brand offline and an entirely different brand online. In

today’s age of advertising overkill it is essential to spread out the same message

across all mediums. The promises offered offline need to be carried forward

online too. The digital team should work closely with the branding and

communications team. Even hygiene factors like using the same colour scheme

as that of the brand, the same punch lines etcetera should be taken care off.

Even in a standalone digital/social media campaign the above mentioned

hygiene factors will need to be on your checklist.

Engage with influencers

In any purchase behavior, peer recommendations play a very important role. All

the more so now that we have easy access to our friends and family's opinions on

one click. It becomes of an utmost importance to a brand when the purchase

decision is being influenced by a current customer or someone who has

expertise in the product vertical rather than the brands marketing efforts.

The idea would be to influence these influencers positively so that they can

influence the masses. However, jumping into this without a strong blueprint and

crisis management plan would be foolishness. The influencers will not support

the brand if they aren’t convinced themselves about it. A very tactical approach

for interacting with them is essential.



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Analytics at the core:

Mine, Monitor and Analyse to improvise

Unfortunately very few brands are doing this. There is a gold mine of brand and

consumer insights hidden under the dust of conversations waiting to be tapped.

You can understand who is talking about you or your competitors, where are

they talking from, what are they talking about. Are they happy with the product,

the pre sales service, the after sales service, the variety of options available, etc.

Basically any business problem can be solved by investing time and effort in the

analysis of data. Not only will it solve business problems, analyzing and studying

insights will help increase product performance and efficiency.

Enterprise grade tools like Simplify360.com, Boxmytalk.com etc help in making

the job easier.

Analyse performance periodically

Running campaigns and having huge budgets of media spend is the pattern that I

see with brands. While media spends is relatively easier to calculate, social

media isn’t. But it is essential to set internal metrics like engagement rate,

sentiment improvement, grievances resolved, traffic on site increase, actual sales

figure to measure the performance of all social media activities.

Analyzing these periodically eliminates resource wastage and further

strengthens the belief in social media.

As you can see for yourself, there are so many aspects to social media apart from

just marketing. And following the above practices will help you leverage this

amazing medium.

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http://boxmytalk.com/



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Inside Big Data – What’s in it

for Marketing?

Deep Sherchan

Deep Sherchan is the co-founder and Chief Marketing Officer at Simplify360. He is one of the thought

leaders in social media analytics and has published numerous research reports on implementation of

social media in business systems.



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Inside Big Data – What’s in it for Marketing?

Deep Sherchan – CMO, Simplify360

"Data! Data! Data!" he cried. "I can't make bricks without clay."

Sherlock Holmes

-The Adventure of the Copper Beeches

And this is exactly how most marketers feel before they start designing their

marketing campaigns. Consumer insights are the most important element for

driving marketing decisions. Without them, most enterprises would stop

functioning. Big data is one of the manifestations of today’s consumer trends -

proliferation of social actions, platforms and devices.

There are three important aspects of big data that are challenging marketers –

volume, variety and velocity. Millions of dollars are spent in setting up robust

data centers to tackle these challenges. These infrastructures have given rise to

new methods and technologies to handle and process data, which are efficient

and fast. And marketers are only just starting to realize the power of this

efficiency and the opportunity to leverage data.

In order to maximize profitability, marketers are always looking for ways to

optimize their media spending, communication strategy, and customer segment.

· Who are we targeting?

· What are we saying?

· When and where are we saying?

These questions need definite answers, which can only be produced through

analysis of customer data. And we are lucky that we have the technology and

data to work on.

Today, there are a variety of customer touch points that are generating data

every second – likes, shares, comments, tweets, updates, videos, voice, mouse

clicks, location, meta tags, customer transactions etc. All this unstructured data

calls for an extensive analysis and integration with structured data available



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with the enterprise.

Besides these challenges, marketing in particular has more to benefit from this

paradigm shift.

How marketers can use Big Data?

1. Customer Insights, Segmentation or targeting.

Understanding customers has never been easier than this. The data collected

from a variety of customer touch points can be mined for 360 degree profiling

and segmentation.

2. Optimizing the communication message.

In today’s fast paced communication highways, messages travel at the speed of

light, reaching millions. As the message moves from one person to another, it

creates a lot of feedback that can be gathered in real-time. Analysis of such

feedback gives marketers a clearer look into the performance of the message and

the kind of optimization it might need. This can enable marketers carry out A/B

testing on messages and increase their impact.

3. Real-time Recommendation Generation

The retail sector is one area which can benefit hugely from big data analytics,

because compared to any other industry, it creates huge data from different

offline and online transactions.



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Big data can allow e-commerce sites to crunch a huge amount of data in seconds

and provide recommendations to the visitors on the kind of products they might

be interested to buy. This kind of real-time analytics implementation can hugely

increase the sales count. Google, Amazon and now even Facebook, have been

experimenting with such methods to make effective Ads and product

placements.

4. New product Strategies

Starting from mobile devices to clothes to shoes, you can

buy anything online. As a result, there are numerous

dedicated blogs and communities that discuss specific

products. This provides huge opportunities for

marketers to analyze the conversation and produce

strong correlations between the kinds of product people

might want to buy. These kinds of feedback can be sent

back to the product team to make any edits and changes.

These adjustments can increase the effectiveness of the

product by large margins.

5. Lead/Prospect Identification

Currently many automated marketing tools are coming up

with the implementation of big data analytics, which

allows marketers to understand how people are

interacting with their marketing campaigns and identify

prospects. With information generated from engagement on

Facebook, Twitter, Blogs and other platforms, such tools can

effectively identify leads which are more likely to convert.

6. Improving customer experience

CRM tools and contact centers are under huge challenges to resolve online

customer complaints originating from hundreds of different platforms and

portals. Besides responding to messages, analytics can be implemented to



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predict future issues and trends to avoid any escalation. This can help marketers

be prepared with active measures and improve the customer experience with

the service or products.

The great debate among experts and technologists is still between how much

should marketers depend on big data analytics. Many traditional marketers still

believe that most campaigns are based on gut feeling and instinct, and less data

driven. But I believe, at the end it is what you want to achieve through your

campaigns and to what extent you can optimize them through data analytics.

There will always be a portion of understanding, which will be based on instincts

and human experience.

With time and money, every enterprise comes under a certain phase where

optimization becomes a key factor in winning a competition or making a jump to

new heights. In such scenarios big data can provide marketers with an

instrumental tool to bring the most and best out of the campaign.



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SOCIAL MEDIA PREDICTIONS

FOR 2013

Prashant Jain

Prashant Jain is a social media analyst at Simplify360. Social Media according to him is a just the digitization of real world

conversations; hence it should be done cautiously.



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Social Media Predictions for 2013

Prashant Jain - Social Media Analyst, Simplify360

Acquisitions, Innovations, IPO’s and Content! These four tops the list for laying

the groundwork for Social Media Predictions in 2013. With social media

marketers focusing more and more on customer service through social media

channels, the platform which does it the best will definitely be the winner.

Here are some predictions which I think are going to get realized in 2013.

Content Marketing becomes top priority for Marketers

With ever growing content sharing from brands and users, having unique

content will become top priority for the marketers. Now is the time for brilliant

videos, clever info graphics, decent comics and other visually appealing content.

Growing popularity of platforms such as Pinterest, Instagram is making this need

even more crucial.

Visual Content will be a must have

With Facebook’s acquisition of Instagram and an

unprecedented rise in Pinterest community, it is

quite visible that the online users are now

getting more and more inclined towards visual

content.

May be, the reason behind this would be that

visual content is not only shareable but it can be

kept for reference later on. So, refined content

along with classic visualization will emerge as

winner of the hearts of online consumers.

Slideshare becomes even more important

If you talk about content marketing and you

don’t mention Slideshare then it won’t be right.

Slideshare is turning up to be the most preferred



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destination for business

owners when it comes to

content sharing, and it has

overpowered giants like

Facebook, Twitter as the

world’s largest professional

content sharing community.

And, it won’t be difficult to

understand the reason behind Linkedin’s decision of acquiring Slideshare in

2012.

Data science for Social Media Marketing Tactics

Social Media platforms are turning out to be a very relevant data source for

organizations, and many brands are eyeing data scientists as their first choice to

work in their social media marketing teams.

With the advent of big data and many affordable techniques for retrieving data,

the combination of data science and social media will take the digital marketing

strategy to an altogether new level.

Search for better metrics for measuring Social Media ROI

Organizations are finding it tough to tie dollars with their social media marketing

returns. For budget planners it will be highly relevant to know that what kind of

tangible returns they are getting with their social media marketing strategy.

And, hence brands will definitely call for some comprehensive and robust

metrics for measuring their Social Media ROI.

Google+ might become the favorite place to hang out

Recently Google Plus became the No.2 social network in the world. The most

powerful feature of Google Plus is the Communities, which in fact is fully capable

of replacing forums.

It is an excellent way to bring like minded people together. It is turning out to be

http://www.ibtimes.com/google-plus-becomes-worlds-no-2-social-network-after-facebook-knocking-twitter-1042956



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a great boon for businesses as it facilitates private work communication, training

and support, client communication and many other useful features. All Kudos to

engineers at Google who slowly and steadily making this possible!

Is there a big acquisition on the list?

With Facebook getting hold of Instagram, LinkedIn buying Slideshare for $119

mn, we see a visionary approach of social media giants as they are very well

aware of the fact that content sharing is going to be the key in this business and

the platforms which are producing visually enticing and knowledgeable data can

be their launch pads to the top.

With so much innovation and creative concepts which have come in the past two

years in the world of social media, it won’t be too speculative to think that a big

acquisition is on the minds of some CEO’s.

More industries will consider entering into Social Media

Organizations see Social Media Platforms like Facebook, Twitter as the best way

for maintaining relationships with their consumers. And, with such grueling

competition they are feeling the need of a comprehensive and robust digital

strategy more than ever.

A report from Gartner confirms the fact that digital technologies are now a top

priority for brands in 2013. Here are some excellent social media engagement

campaigns which were launched in 2012.

http://www.gartner.com/newsroom/id/2304615

http://socialfresh.com/the-5-most-innovative-social-media-campaigns-of-2012/



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Will the world see an IPO from Twitter?

When Facebook was going to announce its IPO last year, everyone was expecting

that this will start a wave of IPO’s by other Internet giants. But as the IPO was

announced it tumbled from $38 to $20. This of course forced the web companies

to put their plans on hold.

But just imagine, what will happen if twitter announces its IPO? The business

model of twitter is more reliable and robust as compared to that of Facebook as

it doesn’t rely on third parties.

With twitter ad revenues reaching new heights since its launch, it’s predicted

that twitter will sweep of nearly 13% of total social ad revenue of US. [See the

graph]

But, the top brass of twitter is denying any possibility of an IPO, but it looks like

that by the end of 2013 the most active online community of the world will be all

set to get listed.

LinkedIn – The Underdog

Social Media Gurus across the globe agree to the statement that LinkedIn is the

real social network. With new features like personal endorsements, news feed

and a more classical new look of user profile; LinkedIn is all set to win hearts.

[Must Read]

http://www.emarketer.com/Article/Twitter-Increases-Share-of-Social-Ad-Revenues/1009344

http://www.emarketer.com/images/chart_gifs/144001-145000/144546.gif

http://mashable.com/2012/10/16/linkedin-update/



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With its acquisition of Slideshare it has certainly become the engine for

generating top quality professional content of the world.

So, with its growing relevance amongst the students and job seekers it won’t be

wrong to say that 2013 might witness some surprising and unprecedented

announcements from LinkedIn.

Pinterest will try to tap the male demographic

Pinterest in a very short time has experienced exponential growth and it has

reported highest increase in unique users across PC, mobiles and apps.

But, there is one thing which is worrisome for Pinterest’s growth plans and it is

that the social platform hasn’t been able to entice male users and it is being seen

as the major challenge the virtual pin board provider faces.

With more than 75% of Pinterest users being female, it will be definitely be a

uphill task for the Pinterest team.

Possibilities of tying up with men’s brands appear to be realistic in 2013 as it will

encourage male demographic to start pinning.

So, the world awaits a stunning launch from Pinterest and so do I. Go through

this Social Media Report for 2012 by Nielsen for knowing about what happened

in 2012 and predicting that who will be leading the social media army in 2013.

Will Social Media fraternity see a revolutionary platform in 2013?

With emphasis on customer service through digital platforms increasing like

http://www.nielsen.com/content/dam/corporate/us/en/reports-downloads/2012-Reports/The-Social-Media-Report-2012.pdf



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never before and the ever growing demand of personalization and localization,

there is a huge scope for a new product which will revolutionize the way people

engage online.

And after seeing the great response an innovative social platform gets from the

online community I can surely say the development process is already under

pipeline.



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