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Simplify360 eBook: Predictive Analytics The Future of Social Media

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Table of Contents

PREFACE .......................................................................................... 3

WHAT ARE PREDICTIVE ANALYTICS? ........................................................ 5

ADITYA CHOWDHARY - CLIENT SERVICES DIRECTOR MARKETELLIGENT ..................................... 5

BEYOND SENTIMENTS ......................................................................... 10

ZISHAN ANSARI - SENIOR BUSINESS ANALYST, TARGET CORPORATION ................................... 10

SOCIAL MEDIA STRATEGIES FOR THE DATA DRIVEN NEWSROOM ..................... 17

DENNIS MORTENSEN – CEO, VISUAL REVENUE ........................................................ 17

TOO MUCH TALK IN ANALYTICS & TOO LITTLE ACTION! .............................. 24

AJAY KELKAR – COO, HANSA CEQUITY ............................................................. 24

ACTIONABLE ANALYTICS .................................................................... 28

JAMES TAYLOR – CEO, DECISION MANAGEMENT SOLUTIONS ........................................... 28

UNDERSTANDING AND MEASURING SOCIAL INFLUENCE ................................ 34

ARUN SUNDARARAJAN - PROFESSOR AND NEC FACULTY FELLOW, NEW YORK UNIVERSITY’S STERN SCHOOL OF BUSINESS ....................................................................................... 34

HOW SOCIAL MEDIA CAN REVEAL THE MYSTERY OF BRAND LOYALTY! ............ 37

G.K SURESH - GENERAL MANAGER, ITC FOODS ..................................................... 37

SCRM IN 2013: NEXT GEN SOCIAL MEDIA ANALYTICS .................................. 44

BHUPENDRA KHANAL – CEO, SIMPLIFY360 .......................................................... 44

SOCIAL MEDIA BEST PRACTICES ............................................................ 53

ANKITA GABA - CO-FOUNDER, SOCIAL SAMOSA ....................................................... 53

INSIDE BIG DATA – WHAT’S IN IT FOR MARKETING? ..................................... 57

DEEP SHERCHAN – CMO, SIMPLIFY360 ............................................................. 57

SOCIAL MEDIA PREDICTIONS FOR 2013 ................................................... 62

PRASHANT JAIN - SOCIAL MEDIA ANALYST, SIMPLIFY360 ............................................. 62

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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.

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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

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.

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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, 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.

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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 SentimentsZishan 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

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



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

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

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

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

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parent very well knows what to do to change the mood of their kids.

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

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time.

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.

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http://www.processing.org/

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



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,

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 NewsroomDennis MortensenDennis 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

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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 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?

• Is this content that should be shared on social media?

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• 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 consumption data. Additionally, the best tools can tell editors whether

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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 PropertiesA 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

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

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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

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role of a 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 KelkarAjay 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.

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.

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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."

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

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



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 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

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line of thinking.

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Actionable Analytics

James TaylorJames 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.

Actionable Analytics

James Taylor – CEO, Decision Management Solutions

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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 correctly, will move our business

performance in a positive direction? How, exactly, do we move the dials on

our dashboard?

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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 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

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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,

31



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

these 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 InfluenceArun 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

34



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 “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 eas ily 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.

1

ä

See, for example, Aral, Muchnik and Sundararajan, PNAS 2009, http://www.pnas.org/content/106/51/21544

35

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



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.

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 SureshMr. 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.

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.

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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. With over 3 million fans, Facebook

offered Bingo! a great window into understanding consumers conversations.

Consumers use these forums to talk about their likes & dislikes and welcome

new information on product as they find it appetizing, tempting & satisfies

their need for variety. Consequently we decided to launch the new Bingo

Tangles first on 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

38



Bingo Tangles were sent 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 3 ways to use social media data to improve and make social

programs much more effective:

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

39



consumer problems. On the Aashirvaad Multigrains Facebook page one of

the fan brought to our notice unavailability of Aashirvaad Multigrains atta in

her area. We used this info to investigate the issue with our sales team and

figured out that there was an issue with the sales person operational in that

area. Action was taken immediately and we called back the consumer to

validate that her problem had been addressed.we figured out that this was

an issue due to the sales person operational in that area. 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. Brands have to learn to converse with consumers as equals.

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 on equal terms & be seen as an enabler.

The key thing is to do it without compromising on the brand “personality”.

Hence the voice of Bingo! is more youthful & contemporary; the voice for

Aashirvaad is always joyful & optimistic while that of Kitchens of India is

authentic & welcoming.

40



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. Many a times the reverse is true as well.

There was once a complaint on Facebook by a consumer on the quality of

Atta. Before we could begin to address the problem, 3 other consumers had

responded asking the fan to check the storage conditions at the outlet of

purchase as well as her kitchen.

41



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

segment 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.

42



SCRM in 2013: Next Gen Social Media AnalyticsBhupendra 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.

43



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

44



There are multiple avenues of revenue realization through Social Media.

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

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.

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

45



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 take on an outsourced partner and get the CRM integration bit

done.

46



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.

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

47



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

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

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.

49



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

50



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.

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.

51



Social Media Best PracticesAnkita 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

52



new people and is a big time shoeoholic.

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

53



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 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

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



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 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/

http://www.simplify360.com/



Inside Big Data – What’s in it for

Marketing?Deep SherchanDeep 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.

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

57



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 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.

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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.

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.

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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

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

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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 2013Prashant JainPrashant 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.

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

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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 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.

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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 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

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



$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.

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.

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

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



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]

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.

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

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

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



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

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



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