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Your Analytics Are Only as Good as Your DataLearn How to Gain Clear Insight Into Customer Experience with a High-Quality Big Data Stream

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Your Analytics Are Only as Good as Your Data

Unlocking the Big Data Gold Mine

Your Analytics Are Only as Good as Your Data

An eBook by Cloudmeter

Unlocking the Big Data Gold Mine

Table of Contents

Introduction ...............................................................................................................................................................................................1

Part 1 The Age of the Customer, Enter Customer Insights .........................................................................................................2

The Age of the Customer, Entering Customer Insights................................................................................................................................. 3

Understanding your Customers ....................................................................................................................................................................................4

Having Good, Complete Data Ensures Relevant & Accurate Customer Insights ..........................................................................5

Part 2 Good Data Drives Customer Insights ....................................................................................................................................................................9

How CI drives value across the lifecycle .............................................................................................................................................................. 10

Part 3 Using Customer Insight to Drive Customer Service .......................................................................................................12

The Perpetually Connected Consumer and their New Requirements .............................................................................................13

Big Data Redefined...............................................................................................................................................................................................................15

Part 4 The Future of Customer Insights ..........................................................................................................................................16

What is High Quality Data? .............................................................................................................................................................................................17

A Checklist for your Data Capture Technologies .............................................................................................................................................18

Options for Data Capture ...............................................................................................................................................................................................20

Harvesting the Big Data Goldmine ............................................................................................................................................................................21

A New Approach to Data Capture & Processing ..............................................................................................................................................21

Conclusion .............................................................................................................................................................................................. 22

1Your Analytics Are Only As Good As Your Data

Unlocking the Data Gold Mine

Introduction

We all hear a lot about Big Data. But the problem is as marketing organizations race to better understand and interact

with customers, they don’t always have the “quality data” they need. They have lots of data, but how much of it is

relevant? Most of today’s firms don’t really know who their customers are. They don’t have the right data, the right

people to analyze it, or the right tools to analyze the data with. Enter the field of Customer Insights.

Companies need customer insights to drive customer experience and they’re wondering how they can get a good

understanding of their customers to better serve them? They need the right data to drive customers through the

Discover, Explore, Buy and Engage phases of the customer lifecycle and answer questions about retention, acquisition,

spending behavior, targeting and offer management. High quality data drives better customer insights which in turn can

improve both your customers’ experience and your business outcome.

Forrester predicts that “Big Data” will become “Right Data”! The future of Customer Insights is leveraging the right data

to drive insights. This means having a high quality data feed to the various analytics solutions in place in each stage of

the customer lifecycle.

What does it mean to have high quality data feed? It means that data needs to be complete, relevant and real-time. This

paper will discuss each of these in detail.

In the past, data capture was limited to methods such as web logs and page tags which can no longer keep up with the

pace of change.

Today, a new approach to data capture allows companies to capture the highest quality data, by unlocking the gold

mine hidden in customer’s networks and making it available for your analytics.

The Age of the Customer, Enter Customer Insights

Part 1



The Age of the Customer, Entering Customer Insights

We are living in the age of the customer. Firms moved from being very product and distribution focused to being

focused around the customer needs. Why is that? Data. Data is everywhere and initial analysis of the data showed

patterns in consumer behavior, so brands decided to adhere to the needs of the customers and refocused their business

strategy. Enter in the age of the customer, where the customer manages the relationships, informs brands of the right

content, offer and communication channel they want.

Ford, RCA, GE, Boeing, P&G, Sony

Walmart, Toyota, UPS, CSX

Amazon.com, Google, Intuit, MBNA

Contenders include Facebook, IBM, Best Buy, and Apple

Age of the manufacturing Mass manufacturing makes industrial power houses successful.

Age of the distribution Global connections and transportation systems make distribution key.

Age of the information Connected PCs and supply chains mean those who control information flow dominate.

Age of the customer Empowered buyers demand a new level of customer obsession.

1900–1960 1960–1990 1990–2010 2010–?

Sources of dominance

Successful companies



Although we are in the age of the customer, understanding the customer is extremely difficult to do. Why is that?

For one thing, more than 60% of consumers interact with brands they like across multiple channels. On the upside, this

means that more customers are always addressable, affording brands the potential opportunity to boost relevance and

engagement. But this makes it challenging to collect, manage and mine quality and meaningful data.

Secondly, marketing organizations — in a race to better understand and interact with customers — have become

bloated. Firms leverage a slew of data providers and channel-specific tool providers while organizing into teams that

align by channel. Whether driven by the economy or by recognition that this is not just inefficient but ineffective, we

see more and more firms seeking to organize around the customer, consolidate providers, and streamline processes.

Finally, measuring and analyzing consumers is challenging and firms are too often focused on silos, on channel,

product and service reporting to really understand the customer. Firms just don’t know who their customers are. They

don’t have the right data, the right people to analyze and the right tools to analyze the data with.

As a result, a new field has emerged - Consumer Insights!

Forrester Research, Inc. defines Customer Insights (CI) as: The management and analysis of customer data from all sources, used to drive marketing performance and business strategy.

This means, all the challenges faced with data collection, data analytics is managed through the customer insights

resource. A major part of customer insight’s focus is ensuring their firms data is whole and complete; that they are

armed with the right data to make a deeper analysis of their customers. Why is this sometimes such a sticking point for

CI professionals? Sometimes the data captured is not good or accurate. Having good and accurate and complete data

enables CI pros to have a more focused customer insights.

Understanding your Customers



Having good, complete data gives an organization:

1. Deeper understanding of its customer base. Imagine if you had more data about your customer buying habits and

needs? You could target offers based on their behavior and what they value as important. Having the right data

enables this type of action and analysis.

2. Allows for greater efficiencies in marketing spend. For marketers, having a more complete view of customers and

channel performance guides their investment decisions. Based on more complete data they can determine how they

want to invest in, for instance, mobile—or how they want to reinvest in the website.

3. It helps craft more relevant experiences and messages. If firms knew the web to purchase patterns (such as moving

through the website), coupled with additional demographic and buying behavior, they can more accurately serve up

customized messages and offers. This develops a deeper, meaningful relationship with the customer.

4. Finally, more accurate data helps identifies potential cross-sell and up-sell opportunities. If firms had a sense of their

customers’ product needs, they can identify the right products to suggest, like Amazon does.

Having Good, Complete Data Ensures Relevant & Accurate Customer Insights



Inhibitors Which of the following challenges prevent your organization from making better use of customer analytics?

Base: 90 customer anlalytics professionals (multiple responses accepted) Source: Q1 2012 Global Customer Analytics Online Survey

Managing and Integrating data from a variety of sources

Ensuring data quality from a variety of sources

Getting staffing and management commitment for analytics projects

Communicating and interpreting results of analytics

Finding the right kind of analytics talent

Performing analytics in real time

Making analytical insights available at the point of customer interaction

Managing the velocity of data generation

Dealing with data protection and customer privacy

Receptivity of business stakeholders to use results of analytics

Others

50%

54%

42%

38%

37%

32%

31%

28%

21%

18%

7%



Drivers Which of the following challenges prevent your organization from making better use of customer analytics?

Improving data-driven focus of organization

Drive customer satisfaction

Improve customer retention

Drive customer loyalty

React to competitive pressures

Seek to build customer-centric organization

Reduce marketing budgets

Respond to regulatory environment

Change in customer interactions

Implement senior managment mandate

Others

51%

57%

51%

40%

34%

30%

28%

26%

22%

17%

16%

Base: 90 customer anlalytics professionals (multiple responses accepted) Source: Q1 2012 Global Customer Analytics Online Survey



Based on a recent Forrester Research study, a key driver to business success is to have a data-driven focused

organization. We are living in the era of customer—which means the customer produces big data. However, firms are

interested in having the right data to be data-centric.

Why does this matter?

They want to connect with customer in more relevant ways. If a firm has more accurate data-the right data, they

could address their biggest challenge, which is offering the right message to their consumer across channels. This will

develop a deeper relationship with the customer and provide a more relevant experience.

Given the state of customer insights, why is it important to have customer insights in an organization? It’s not solely to

learn more about the customer. In fact, it helps firms facilitate a more relevant customer experience. In the next section

we’ll discuss what CI groups are doing today to marry data and insights to enhance the customer experience.

Good Data Drives Customer Insights

Part 2



Forrester Research, Inc. finds that firms leverage the right data across the customer lifecycle to answer key questions

around retention, acquisition, spending behavior, targeting, and offer management. By leveraging the right data to

help understand these core questions, firms are able to be prepared at every stage of the lifecycle to speak with their

customers in a more relevant way.

How CI drives value across the lifecycle

Value of analytics

Focus on recovery

Focus on retention, loyalty and engagement to drive profitability

Reduce number of unprofit-able customers

Cross-sell/upsell and drive revenue

Reduce cost to serve and drive margin

• Acquire profitable customers • Make customers profitable faster

Pro

fita

bili

ty

Customer Lifetime

Discover BuyExplore Engage



If we had the right data, marketers can make relevant outbound, proactive messages, at the right time, while being

prepared at the same time to be reactive in responses when customers are speaking with them. It allows for a deeper

conversation, while driving key business metrics, and customer growth. Given all this, it’s imperative for firms to have a

core CI function to manage data they have-and they need-to inform a more robust analysis.

Customer Insights today must help with the following:

• Keep and grow and develop customers—much like what Verizon and other mobile carriers do to prevent customer

from switching to another carrier.

• Recommend the right offers and options—the way Amazon recommends products.

• Prevent breakdowns by replacing parts before they shut down the production line. This means being proactive to

satisfy customers needs.

• Sell more—much like how retail places products and financial services identify opportunities to up-sell and replace

existing products.

Marketing messages: • Promotional and transactional emails

• Catalogs/direct mail/mailed statements

• Retail visits: point-of-sale messaging kiosks

• Mass media: TV, radio, publication

• Call center communications

• Display advertising

• Web site messaging cross-sell/upsell

• Opt-in SMS

• Social media: Facebook fan page, brand Twitter feed, company blog

• Coupon and deal-of-the-day sites

Non-Marketing messages: • Mobile localization services (e.g. Yelp), apps

• Send-a-friend emails

• Natural social network, interactions

• Editorial: online publications, blog reviews

• Ratings and on-site or third-party reviews

Using Customer Insight to Drive Customer Service

Part 3



The Perpetually Connected Consumer and their New Requirements

Perpetually connected customers are customers that are always connected with frequent access, on multiple devices

and multiple locations. But that opportunity can be a double-edged sword because consumers increasingly have

limited tolerance for irrelevant and ill-timed communications. To meet the requirement for timely, relevant, contextually

appropriate customer communications, CI professionals must tackle two issues:

1. Rethink how we “view” customers. Customers don’t understand — or care — that systems are disparate and that

data lives in silos. But in today’s environment of perpetual connectivity, and consumers’ desire to connect in any

channel from any device, it’s crucial that brands be able to recognize consumers at the point of interaction. We need

to think about recognition and identification. And how we can collect data from these different areas

Multiple devices Own and personally use at

least three connected devices

Multiple locations Go online from multiple physical locations, including at least one on the go

Frequent access Go online multiple times a day

The perpetually connected customer



To cater for this paradigm shift, marketers need strategies and systems in place to follow their consumers as they flit

from one channel to the next. CI professionals need to consider recognition — knowing who an individual actually is —

together with broader customer context — what we can know about them, all in a privacy-compliant way. And we must

be able to collect and act upon this data.

2. The “Internet of things” is turning product data into customer data. This means CI pros must capture product

data and use it to better understand its customers. Take Nike Fit Bit. The fit bit collects biometric data about the

user. The opportunity here is to use this information to identify relevant products to the current fit bit user. This is

allowing data to be shared across devices—to learn more about the customers.

But to maximize the value of this data, it must flow through CI teams that have experience testing, managing, and

quantifying the value of data to optimize customer communications. Without this level of rigorous evaluation, the use

of sensor data can be a greater liability than an asset.

My Computer

My tablet

My mobile

My friends

My data

My consumer identity

My home entertainment

Link to the source site here.

http://g3ict.org/resource_center/newsletter/news/p/id_395



Big Data Redefined

The value of Big Data will be redefined. As marketing organizations race to better understand and interact with customers, they don’t always have the “quality data” they need. They have lots of data, but how much of it is relevant? They need to make sure they have the right data available for analysis and watch out for blind spots. Blind spots can lead to missing critical information and a skewed overall picture of a customer’s experience. They need to capture everything that can influence the customer’s experience and behavior. After capturing everything, they can focus on feeding analytics solutions with the data that matters most.

Organizations hoard data because they fear missing out on some potentially valuable insight at some completely undefined point in the future. But most of that data doesn’t provide business value; it actually opens the business up to lots of potential problems: breaches, “analysis paralysis,” and unnecessary costs of management and maintenance. To optimize and protect this valuable asset, CI teams need to:

Shift the focus from “big data” to “right data.” For all the hype of big data, there are some serious problems with the narrative. What does “big data” really mean, in what context, and to whom? And the resources required to make those Exabyte’s of data meaningful — data scientists, decision engines, and text and natural language processing tools — are still out of reach for many organizations.

As a result, instead of capturing every last tweet and call center transcript, firms need to take an ROI-based test-and-learn approach to data sources. In 2013, CI teams should assess the data they generate — and the data they acquire — on the basis of actual cost, potential risk, usability, and business value.

The Future of Customer Insights

Part 4



The Current State of Customer Insights

In the end, the future of CI really comes down to

Leveraging the right data to drive meaningful insights.

It’s imperative for CI to align and rally on collecting the right, meaningful data to drive analysis. Without it, your analysis,

your recommendations, your insights, is completely invalid.

How to assure you are feeding your analytics solutions with the highest quality data for optimal customer insights?

What is High Quality Data?

What does it mean to have high quality data feed?

First, It means complete. It means that you should be able to capture everything related to the customer experience and

behavior. It is important to avoid any blind spots.

Second, although you should capture everything, you don’t want to feed your analytics solution with everything. You

want to feed it with the most relevant information. Meaning, that on the fly, you should be able to filter, transform, and

enrich the data with the most relevant information before feeding it to your analytics solution of choice.

And finally, your customers operate in real time, so should your analytics. To get there, it’s not enough to have an

analytics solution that operates in real time, you also need to feed it with real time data.



A Checklist for your Data Capture Technologies

We discussed what high quality data is. Full insight requires assuring your analytics/big data solutions are fed with the

highest quality data. After all, your analytics are really only as good as the data you feed it. Or, in other words, garbage

in garbage out, gold in – gold out.

So, when looking at data capture technologies, what should you look for? How can you assure you capture and feed

your analytics solution with the highest quality data? Let’s look at a list of requirements to help assure you capture and

feed your analytics solutions with the highest quality customers’ behavior and experience data.

1. Make sure you capture all your customers’ data (experience & behavior)

Don’t assume you know what’s important, don’t compromise the data you can capture. Capture everything. For example, if you are an eCommerce site, do you know what was presented on the page when the customer decided to click on a specific item? Do you know what the price range of the other products on the page? How were the reviews? If not, how can you optimize the page to get better financial outcome?

2. Focus on the relevant information and feed it to your analytics solutions

Capturing all the data is important, but at the same time it’s also important not to feed you analytics solutions with all that data. Focus on the data that is relevant for you and feed your analytics solution that data.

3. Capture, process and enrich your data in real-time

Do as much processing and data enrichment at the point of capture. Transform & enrich the data in real time and feed you analytics solution with the most relevant data. For example, add a location to the customer information by enriching the data captured with location information.

4. Data capture technology should not require code change to your application

For many reasons from TCO to impact on performance, and ability to adjust data capture requirements on the fly. Your data capture technology should not require code change to your application

Continued on next page »



5. Allow users to adjust capture requirements on the fly

Your analytics requirements are constantly changing, you should be able to adjust the data capture on the fly and not wait few weeks to keep up with the changing requirements

6. Own all the granular data. Its priceless, and it belongs to you

The data is yours and its king. Your ability to own the granular customers behavior & experience data is not just nice to have – it’s a must have. Don’t compromise it. Make sure you analyze the granular data not only the aggregated information.

7. Make sure your capture technology doesn’t impact your web application performance

Although this should go without saying, reality is that the majority of the capture technologies available today do impact the site performance. These technologies (such as page tags / java scripts) sit in-line with the application and impact the site performance

8. Your solution should provide support for any implementation methods

Your site implementation should have no impact on your ability to capture all the data you are interested in.

9. One install, many integration. You should be able to use one capture solution to feed data into as many back products (analytics, data bases, etc.)

Customers can connect with your site/application from different devices, make sure you capture it all. Whether your site/applications are running in a private, public, or traditional networks, you should be able to capture the data.



Options for Data Capture

Let’s look at the different technologies used today to access business information, in the context of the two main requirements:

1. Data Quality: getting access to the most complete and highest quality data in a timely manner

2. Low TCO and risk to your production environment and customer experience

The first traditional method is web logs, which record technical information and have not changed much in over 20

years. Using web logs typically is low-risk because there is not much that can be changed. However web logs are very

limited source of information – knowing that your “/cart.jsp” file was requested 100 times tells you nothing at all about

the experience of your customers.

The second category is page tags or JavaScript and Application server logs. These two are very similar because one

involves writing code that runs client-side and the other involves writing code that runs server-side. The more code you

write, the more you can track but the slower your application becomes because they run in-line with your applications.

The more they capture, the slower your application will run. Changes have to go through R&D which means you fall

victim to their time, process and schedule. One company who has a highly tuned agile development team recently told

us that it takes them 6 weeks to make a change. At other companies it’s not uncommon to have to wait months. This

might not be so bad if you knew beforehand all the metrics you’d ever want to track

In practice what we’ve found is that a company’s analytics demands are constantly changing – once you learn one

thing it unlocks new questions that you want answered. And, as you sit applications are constantly changing. These

data capture methods simply cannot keep up with today’s pace of change!



A New Approach to Data Capture & Processing

Cloudmeter harvests the Big Data goldmine available in network traffic to create actionable information companies can

use to understand and optimize their end users’ experiences and business results

Cloudmeter Stream combines state-of-the-art data capture with event processing, and seamlessly integrates real-time

information with many databases, business intelligence and Big Data products to help organizations conquer their most

demanding analytics needs.

With everything moving towards web applications and services, we at Cloudmeter, realized that there is no bigger

source of valuable data than the information contained in network traffic, but in the past this data was not easily

accessible. Our product Cloudmeter Stream harvests the Big Data goldmine available in companies networks to create

actionable information companies can use to understand and optimize their end users’ experience and business results.

Harvesting the Big Data GoldmineCloudmeter Stream allows companies to capture the highest quality data by looking at network traffic. It doesn’t just

“capture everything”- too much data is not a good thing! - but it captures the most relevant information for your needs.

As mentioned earlier, the trend is a move from big data to quality data. You want to make sure you feed your analytics

solution with the highest quality data. Cloudmeter Stream enables customers to pinpoint exactly what they want. It

processes and applies business rules to the traffic while capturing it, enabling customers to contextualize the data and

immediately turn it into something meaningful and all this happens in real-time time before anything gets stored to disk.

With Cloudmeter Stream you can choose whether you use ultra-light software agents that run completely independent of

your application or connect to the network. It also integrates easily with other big data solutions like Splunk and GoodData.

An intuitive web UI lets you change your capture and business rules on the fly without any impact to your applications.

Cloudmeter Stream includes also functionality that allows users to replay customers’ sessions. Leveraging the wealth

of information we capture and process, we also built a session replay solution. In addition to feeding you analytics

solution with the highest quality data, you can also use the product to search for and replay customers sessions for

better insight into your customers behavior and experience.



Conclusion

Forrester predicts that “Big Data” will become “Right Data”! The future of Customer Insights is leveraging the right data

to drive insights, which in turn drive better customer experience. This means having a high quality data feed to the

various analytics solutions in place in each stage of the customer lifecycle.

What does it mean to have high quality data feed?

1. First, it means complete. It means that you should be able to capture everything related to the customer experience

and behavior. It is important to avoid any blind spots.

2. Second, although you should capture everything, you don’t want to feed your analytics solution with EVERYTHING.

You want to feed it with the most relevant information. On the fly, you should be able to filter, transform, and enrich

the data with the most relevant information before feeding it to your analytics solution of choice.

3. And lastly, your customers operate in real-time, so should your analytics. To get there, it’s not enough to have an

analytics solution that operates in real-time. You also need to feed it with real-time data.

In the past, data capture was limited to methods such as web logs and page tags which can no longer keep up with the

pace of change! Today, Cloudmeter Stream allows companies to capture the highest quality data, by unlocking the gold

mine hidden in customer’s networks and making it available for your analytics.

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