A new survey conducted by Consumer Goods Technology (CGT) and sponsored by Cognizant explores how consumer goods companies are approaching data management strategies and usage.
Few companies realize the full benefits of analytics initiatives to improve the customer experience. Here's a six-step guide for moving beyond operational reporting to enabling predictive insights.
Survey Results Age Of Unbounded Data June 03 10nhaque
Enterprises today can generate, collect and consider more data than ever before. New types of data can provide insight into previously opaque processes and motivations, but prodigious quantities of data present opportunity, as well as complexity and distraction. nGenera Insight’s 2010 Leading in an Age of Unbounded Data survey garnered responses from over 70 major organizations, including many global corporations, to provide a cross-industry pulse of the state of enterprise data.
Few companies realize the full benefits of analytics initiatives to improve the customer experience. Here's a six-step guide for moving beyond operational reporting to enabling predictive insights.
Survey Results Age Of Unbounded Data June 03 10nhaque
Enterprises today can generate, collect and consider more data than ever before. New types of data can provide insight into previously opaque processes and motivations, but prodigious quantities of data present opportunity, as well as complexity and distraction. nGenera Insight’s 2010 Leading in an Age of Unbounded Data survey garnered responses from over 70 major organizations, including many global corporations, to provide a cross-industry pulse of the state of enterprise data.
How to Leverage the Power of Data Analytics in Sales?Shaily Shah
Data is the DNA behind the robust analytics and insights supporting modern organizations to recognize new products, determine how to serve customers better, and enhance operational efficiencies.
This presentation provides a "first hand" look at how PR and marketing pros can raise their brand awareness by using Big Data and predictive analytics.
Nucleus Research found organizations can earn an incremental ROI of 241 percent by using Big Data capabilities to examine large and complex data sets. One driver of high returns was the ability to improve business processes and decisions by increasing the types of data that can be analyzed.
Data and analytics allow organizations to use intelligence from feedback to tailor offerings that improve customer satisfaction.
B2B are gaining the most since they are able to share data that directly strengthens their relationship.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
This infographic is about how banks can maximize the value of their customer data using big data analytics. While the volume of data has been increasing in recent years, many banks have not been able to profit from this growth. Several challenges hold them back.
The Fundamentals of Business Intelligence is a comprehensive overview of data and data analysis. The guide explains the types of data available to businesses and how these data types work with one another to provide insights to large companies. Look beyond the hype of big marketing to understand the role of all types of data and understand what big data is in the right context.
3 Steps for Measuring ROI of Data Quality for Data-Driven MarketersAlex Yastrebenetsky
In this one-time webinar, special guest speaker and analyst from Forrester, Richard Joyce, will helped us examine the rise of data-driven marketing and how the quality of digital data informs budgets while affecting advertising ROI.
Everyone that attends the webinar and reviews the slide will leave:
- Knowing the challenges that present themselves with data-driven marketing and how to overcome them
- Understanding how to be a data-driven marketer and why high-quality digital data is essential to successful marketing initiatives
- Aware of the impact of high-quality data and the ROI of improving data quality
- Able to explain the key components of data quality and how to design a framework of processes and procedures
- With actionable next steps and recommendations
This whitepaper is geared to help
bank marketing professionals
understand the scope of marketing
analytics and also on how it can
contribute value to the various
factions of a bank’s marketing
activities.
Marketing Data Renovators Guide: 10 Steps to Prime Your B2B Database for Anal...Shelly Lucas
What do a fixer-upper and your marketing database have in common? More than you think. Learn 10 clear steps for making your database analytics-ready in this e-book.
How to Leverage the Power of Data Analytics in Sales?Shaily Shah
Data is the DNA behind the robust analytics and insights supporting modern organizations to recognize new products, determine how to serve customers better, and enhance operational efficiencies.
This presentation provides a "first hand" look at how PR and marketing pros can raise their brand awareness by using Big Data and predictive analytics.
Nucleus Research found organizations can earn an incremental ROI of 241 percent by using Big Data capabilities to examine large and complex data sets. One driver of high returns was the ability to improve business processes and decisions by increasing the types of data that can be analyzed.
Data and analytics allow organizations to use intelligence from feedback to tailor offerings that improve customer satisfaction.
B2B are gaining the most since they are able to share data that directly strengthens their relationship.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
This infographic is about how banks can maximize the value of their customer data using big data analytics. While the volume of data has been increasing in recent years, many banks have not been able to profit from this growth. Several challenges hold them back.
The Fundamentals of Business Intelligence is a comprehensive overview of data and data analysis. The guide explains the types of data available to businesses and how these data types work with one another to provide insights to large companies. Look beyond the hype of big marketing to understand the role of all types of data and understand what big data is in the right context.
3 Steps for Measuring ROI of Data Quality for Data-Driven MarketersAlex Yastrebenetsky
In this one-time webinar, special guest speaker and analyst from Forrester, Richard Joyce, will helped us examine the rise of data-driven marketing and how the quality of digital data informs budgets while affecting advertising ROI.
Everyone that attends the webinar and reviews the slide will leave:
- Knowing the challenges that present themselves with data-driven marketing and how to overcome them
- Understanding how to be a data-driven marketer and why high-quality digital data is essential to successful marketing initiatives
- Aware of the impact of high-quality data and the ROI of improving data quality
- Able to explain the key components of data quality and how to design a framework of processes and procedures
- With actionable next steps and recommendations
This whitepaper is geared to help
bank marketing professionals
understand the scope of marketing
analytics and also on how it can
contribute value to the various
factions of a bank’s marketing
activities.
Marketing Data Renovators Guide: 10 Steps to Prime Your B2B Database for Anal...Shelly Lucas
What do a fixer-upper and your marketing database have in common? More than you think. Learn 10 clear steps for making your database analytics-ready in this e-book.
Democratising data by igniting a crowd powered movement.Steve Jennings
How do we democratize data by igniting a crowd powered global movement with the aim of building a collaborative social fabric-enabling layer across diverse cultures and markets?
To do this during times of unprecedented social, economic, environmental, demographic, and political uncertainty will require us to take a bold approach and step outside of the way we normally do things.
What we need is a radical change in attitudes in the society of which we are a part. What we really need is a cultural revolution.
We're suffering from a compassion and integrity deficit. And this matters a lot more to most of us than we dare to admit.
Learn to manipulate strings in R using the built in R functions. This tutorial is part of the Working With Data module of the R Programming Course offered by r-squared.
Learn Business Analytics with R at edureka!Edureka!
This is a 6-week course for professionals who aspire to learn 'R' language for Analytics. Practical approach of learning has been followed in order to provide a real time experience and make you think like an analyst. Our course will cover not only the basic concepts but also the advanced concepts like Data Visualization, Data Mining, Model Building in R, Web Analytics and so on.
27 Aug 2013 Webinar High Performance Predictive Analytics in Hadoop and R presented by Mario E. Inchiosa, PhD., US Data Scientist and Kathleen Rohrecker, Director of Product Marketing
An Interactive Introduction To R (Programming Language For Statistics)Dataspora
This is an interactive introduction to R.
R is an open source language for statistical computing, data analysis, and graphical visualization.
While most commonly used within academia, in fields such as computational biology and applied statistics, it is gaining currency in industry as well – both Facebook and Google use R within their firms.
This presentation, by big data guru Bernard Marr, outlines in simple terms what Big Data is and how it is used today. It covers the 5 V's of Big Data as well as a number of high value use cases.
Bridging the Gap Between Business Objectives and Data StrategyRNayak3
Explore the fundamental elements of a robust data strategy that aligns with business objectives, from defining goals to prioritizing data architecture.
Integrated Demand Management-When Will We Start Using Downstream Data-7 Nov 2012Lora Cecere
For the purposes of this report, downstream data is defined as data that originates downstream on the demand side of the value chain. It can include point-of-sale data, T-log data, distributor data, social and unstructured data sources, retail withdrawal data and retail forecasts. Integrated demand signal management is the use of this data in a more holistic and integrated demand management process.
The use of channel data is evolving and this report is designed to give the industry an update on progress. Data for this report is based on two inputs: quantitative survey data from twenty-nine respondents (manufacturers) that use downstream data for integrated demand signal management, and qualitative input from attendees at an Integrated Demand Signal Management event that was attended by eleven manufacturers and four retailers. Data was collected in the fall of 2012.
While the study demographic is a small number, the respondents represent an experienced panel group. In the study, 90% of the respondents were using downstream data. The average time of usage is four years.
Broken links: Why analytics investments have yet to pay off, sponsored by ZS, draws on the survey findings, interviews with senior corporate executives and desk research to explore the current state of sales and marketing analytics.
Artificial intelligence, customer journeys, and paid analytics
Quest to be more data-centric and insights-driven
Data-driven CMOs drive omnichannel customer intelligence
Companies turn to paid analytics for enhanced capabilities
The power of now: customer journey analytics rely on integrated data
Harnessing AI for more insight-driven marketing and better customer experiences
We conducted a groundbreaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
Find out:
Why nearly a third of IT Directors feel their organisation uses data poorly
What the hybrid data manager of the future will look like
Why understanding customer behaviour remains the holy grail for so many
We conducted a ground-breaking survey of the UK’s data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
We conducted a survey of the UK's data and business professionals to get a snapshot of the state of the world of data, uncover some of the issues facing the industry and get a sense of the changes on the horizon. The results were enlightening, and in some cases, very surprising.
The enterprise marketer's playbook: Building an integrated data strategy.
An integrated data strategy can help any business see customer journeys more clearly ― and then give customers more relevant ads and experiences that get results. So why doesn't everyone have such a strategy? We look at what sets the marketing leaders apart.
Let marketing data be your guide
If you've ever felt too swamped by data to find the customer insights you need, you're not alone. But there's a new and better approach to gaining deeper audience insights: building an integrated data strategy.
Read this report to learn how:
86% of senior executives agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.
75% of marketers agree that lack of education and training on data and analytics is the biggest barrier to more business decisions being made based on data insights.
Leading marketers are 59% more likely to use digital analytics to optimize the user experience in real time.
The BRITE '12 conference (March 5-6) marked the unveiling of the Center on Global Brand Leadership and the New York American Marketing Association (NYAMA)'s first BRITE-NYAMA Marketing Measurement in Transition Study entitled, Marketing ROI in the Era of Big Data.
The aim of the study was to gain a better understanding of changing practices among large corporate marketers in the following areas: data collection and usage, marketing measurement and ROI, and the integration of digital and traditional marketing.
In surveying 253 marketing executives from large corporations, the study found both widespread adoption of new digital tools, and support for the use of new data to drive marketing decisions and measure marketing ROI. However, significant gaps exist between desire and execution as companies strive to measure marketing ROI. The overall picture of marketing by large corporations revealed significant need for improvements in the use of data, the measurement of digital marketing, and the assessment of marketing ROI.
http://gsb.columbia.edu/globalbrands
http://www.nyama.org
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
Data analytics environment enables the shortest and most viable route to make use of critical data for making business decisions and much more. For more info visit: https://www.raybiztech.com/blog/data-analytics/how-can-data-analytics-boost-your-business-growth
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CGT Research May 2013: Analytics & Insights
1. 28 cgt | may 2013 | consumergoods.com
custom research
All we seem to hear about these days is Big
Data, but is it more hype than reality? Com-
panies in the consumer goods (CG) industry
have been leveraging data and insights for
years, but the journey has not been easy for
many. It has taken a tremendous amount of
effort to get the right data to the right users
intheappropriateformatforittoreallymake
a difference.
This month, CGT once again partnered
with Cognizant to take a look at how compa-
niesareapproachingdatamanagementstrat-
egies in order to understand how the data is
actually being used. Last year, we found that
analytics capabilities didn’t exactly match
up with the perceived importance in specific
areas, and unfortunately, the survey results
this year are not much more optimistic.
Despite the importance of analytics capa-
bilities, data and insights are still not being
leveraged to make better decisions by end
users. Our survey of CG executives revealed
that only 4 percent of respondents have a re-
porting and analytical environment that al-
lows them to access relevant information in a
user-friendlyandtimelymanner(seeFigure1).
That means that an overwhelming major-
ity of users from CG companies of all sizes
are struggling to leverage important data: 28
percent need to rework the data to get it into
a usable form, another 28 percent create their
owndatapulls,andalmostone-quarterreport
that there are too many systems and that this
adds to the confusion.
Even worse, for all but the largest CG
companies surveyed, user confidence in the
data from the reporting and analytical sys-
tems environments is weak (see Figure 2). At
48percent,almosthalfofsurveyrespondents
claim the confidence level is moderate to
low, reporting that business users only use
it for routine decisions but prefer to use data
from other sources or do their own addi-
tional analysis for making critical decisions.
More than one-third rate their organization’s
confidence level as moderate to high, where
business users take the information but get it
validated before using it for important deci-
sions. Remarkably, this number jumps from
36 percent overall to 67 percent for CG com-
panies with more than $10 billion in annual
revenue, suggesting better usage by larger
organizations.
There doesn’t seem to be one overriding
factorthatispreventingcompaniesfrombet-
ter leveraging data for sales and marketing
insights in particular. Rather, respondents
cite several barriers with only an eight-point
difference, starting with data quality at 23
percent, data availability and user adoption
of tools at 19 percent each, and data mining
to derive insights and insight delivery to us-
ers at 15 percent. Data timeliness was less of
Analytics and Insights
Disappointing User Confidence Persists for Consumer Goods companies
expert perspective • by Neva Flaherty, Consumer Goods Consulting Manager, Cognizant
Data Strategy: The Fuel for Better Business Decisions
Think data strategy is not a worthy
priority? Consider this: 90 percent
of the world’s data was created
in the past two years, including
2.7 billion “likes” on Facebook
each day1
. To stay current with
consumer sentiment for product
development and relevant mes-
saging and promotions, CG firms
must manage and utilize data
across the enterprise to enable
improved decision-making: faster,
better and tightly aligned to strat-
egy. In our work, there are three
key success factors for building a
robust data strategy:
Business decisions drives data
strategy: Data strategy work can-
not succeed without 50/50 part-
nership from business partners
to articulate what insights drive
decisions and execution of strat-
egy. The link to strategy is critical
to “dimensionalizing” the value
potential of adding additional data
sets and analytic capability and,
ultimately, project ROI.
Formalized data policies and
processes: Define and document
available data sets and business
decisions they support. Articulate
which groups fund data acquisi-
tion, own data management and
integration, as well which groups
own analysis and delivery of in-
sights. Define data quality stan-
dards and audit procedures. Pub-
lish policies for data collaboration
among business units, functions,
customer teams, and with suppli-
ers and retail customers.
Proactive organizational change
initiative: An analytics capabil-
ity requires skillsets that are not
readily available in CG companies
such as deep modeling skills or
using new combinations of data
for predictive analytics. A cross-
functional “Analytics Center of
Excellence” often provides the
best organizational model to pro-
vide the highest level of sophisti-
cated analytics services to busi-
ness units while minimizing the
breadth of change required.
1
Edgell Knowledge Network,
“Big Data in Consumer Goods –
September 2012”
2. consumergoods.com | may 2013 | cgt 29
a factor at 8 percent, perhaps influenced by
the many retailers who are sharing timely
point-of-sale data.
There does, however, seem to be prog-
ress with some capabilities that depend
on data and insights to improve sales and
marketing performance (see Figure 3). Shop-
per insights, which is also rated the most
important capability, leads the list of ac-
complishments, followed closely by assort-
ment planning. Digital marketing return on
investment analysis is the furthest behind
in maturity, with social listening and price
optimization also lagging in adoption.
Thisresearchalsoaskedaboutownership,
enablement and use of data by job function,
revealing that business users overall are pri-
mary users of data insights, while IT is an
enabler and dedicated groups or centers of
excellence often own the insights.
Consumer or shopper insights are the
basis for collaborative planning between
retailer and vendor for more than half of
survey participants, enabling the collabo-
ration capability that 54 percent deemed
mission critical.
For more details, visit consumergoods.
com/research to download the full re-
search report.
by kara romanow
“Only 4 percent of respon-
dents have a reporting and
analytical environment that
allows them to access rel-
evant information in a user
friendly and timely manner.”
figure 3
Relative Maturity of Business Capabilities
(Respondents used a 5 point scale where 1 = no capability, 3 = some customers,
good progress, 5 = how we do business)
Capability 1 2 3 4 5
Shopper Insights 12% 12% 38% 23% 15%
Assortment Planning 23% 12% 31% 19% 15%
Price Optimization 15% 38% 12% 27% 8%
Social Listening/Web Sentiment 19% 35% 27% 19% 0%
Digital Marketing ROI Analysis 24% 48% 20% 8% 0%
figure 2
Business User Confidence Rating in Reporting/Analytical Data
28%
28%
24%
4%
16%
I need to rework information to get it into a usable form.
I create my own data pulls from the source data.
There are too many systems and it adds to the confusion.
Environment enables our enterprise to access all
relevant info in a user-friendly and timely manner.
Not Applicable/Can’t Say
CAPABILITY
figure 1
Ability to Leverage Data to Make Business Decisions
36%0%
Very High Moderate to High
48%
Moderate to Low
12%
Very Low
4%
Not Applicable/
Can’t Say
36%0%
Very High Moderate to High
48%
Moderate to Low
12%
Very Low
4%
Not Applicable/
Can’t Say