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’.
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.
Consumer analytics is the process businesses adopt to capture and analyze customer data to make better business decisions via predictive analytics. It is a method of turning data into deep insights to predict customer behavior. It may also be regarded as the process by which data can be turned into predictive insights to develop new products, new ways to package existing products, acquire new customers, retain old customers, and enhance customer loyalty. It helps businesses break big problems into manageable answers. This paper is a primer on consumer analytics. Matthew N. O. Sadiku | Sunday S. Adekunte | Sarhan M. Musa "Consumer Analytics: A Primer" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33511.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/33511/consumer-analytics-a-primer/matthew-n-o-sadiku
In partnership with a leading global technology analyst firm, Dun & Bradstreet commissioned a new study to examine how Customer Data Management (CDM) impacts business development and overall performance. This exclusive study proves that smart CDM is essential for driving growth and staying ahead of the data explosion
In this presentation, learn how DNBi can help your business to prescreen and enable instant decisions to shorten the sales cycle, reduce credit holds and find upsell opportunities, and optimize and segment your portfolio to find the profile of your best customers.
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.
Consumer analytics is the process businesses adopt to capture and analyze customer data to make better business decisions via predictive analytics. It is a method of turning data into deep insights to predict customer behavior. It may also be regarded as the process by which data can be turned into predictive insights to develop new products, new ways to package existing products, acquire new customers, retain old customers, and enhance customer loyalty. It helps businesses break big problems into manageable answers. This paper is a primer on consumer analytics. Matthew N. O. Sadiku | Sunday S. Adekunte | Sarhan M. Musa "Consumer Analytics: A Primer" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33511.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/33511/consumer-analytics-a-primer/matthew-n-o-sadiku
In partnership with a leading global technology analyst firm, Dun & Bradstreet commissioned a new study to examine how Customer Data Management (CDM) impacts business development and overall performance. This exclusive study proves that smart CDM is essential for driving growth and staying ahead of the data explosion
In this presentation, learn how DNBi can help your business to prescreen and enable instant decisions to shorten the sales cycle, reduce credit holds and find upsell opportunities, and optimize and segment your portfolio to find the profile of your best customers.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
Take a look at the stories and statistics behind some of Dun & Bradstreet’s most successful analytics projects with our enterprise analytics case study look book.
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
• The definition of big data has grown beyond technical, i.e. “what it is,” to include “what it does.”
• A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
• Most of the focus is on driving top line growth.
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.
The Incidental Science of Organizational Growth via Digital Transformation RocketSource
Simply boosting top-line metrics, such as profitability, aren't enough to position digital transformation as a success. Pervasive access to data and insights are critical as consumer demands shift alongside technological advancements. We explore the mechanisms for knowledge dissemination that answer the rapid evolution of today's world and how to push organizations up the S Curve of Growth through digital transformation.
https://www.rocketsource.co/blog/organizational-growth-via-digital-transformation/?utm_source=slideshare&utm_medium=social&utm_campaign=profile-page&utm_term=digital-transformation
The D&B U.S. Economic Health Tracker exhibited resilience in May 2014. Readings on the small business community continued to stabilize although the anticipated bounce back has so far failed to materialize. In the meantime, some 297,000 new non-farm jobs were created, driven by strong gains in the business services and trade/transportation/utilities segments. Finally, the U.S. Business Health Index strengthened once again in May, registering a 54-percent index value, the highest recorded level since the index began in December 2010. U.S. businesses show sustained balance sheet and financial health, based on the weighted average of D&B's Viability Rating, Delinquency Predictor, and Total Loss Predictor. In spite of accelerating business expansion, lackluster economic growth and uncertainty remain significant restraints and should be monitored closely heading into the third quarter.
Target Better, Nurture Better and Close Better. Learn how Dun & Bradstreet data within Oracle Cloud can help businesses grow relationships and revenue.
Best Metrics to Optimize B2B Demand GenAsad Haroon
B2B marketers who need to do more than simply create brand awareness through outbound marketing have adopted Account Based Marketing (ABM) in order to focus on key accounts. Successful ABM campaigns can produce highly qualified, valuable prospects.
The D&B U.S. Economic Health Tracker showed dogged improvement in April 2014. Small business health stabilized after a number months of decline. Although wintry weather took its toll in the Northeast and Midwest earlier in the year, small businesses continue to demonstrate strong on-time bill and credit-card payments. Meanwhile, an estimated 208,000 new jobs were created, driven by strong gains in the retail and manufacturing segments. Finally, the U.S. Business Health Index strengthened yet again in April, registering a 53.7-percent index value, the highest recorded level since the index began in December 2010. U.S. businesses show sustained balance sheet and financial health, based on the weighted average of D&B’s Viability Rating, Delinquency Predictor, and Total Loss Predictor. Overall, the American economic recovery remains a choppy one, albeit with signs of hope in specific sectors.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
Arun Gupta, Customer Care Associate and Group Chief Technology Officer, Shoppers Stop presented at the Premier Business Leadership Series 2010, http://www.sas.com/theserieshk.
With many retailers worldwide struggling to maintain revenues, how do you grow in such a tough competitive landscape? As a leading Indian retailer and pioneer in using technology, especially business analytics, Shoppers Stop is not only thriving but has helped revolutionise the retail sector. Gupta will share insights on using analytics to drive business value, reduce operational costs and provide better products and customer experience.
Best Metrics to Optimize B2B Demand GenFrankAliyar
B2B marketers who need to do more than simply create brand awareness through outbound marketing have adopted Account-Based Marketing (ABM) in order to focus on key accounts. Successful ABM campaigns can produce highly qualified, valuable prospects.
Six Mistakes Companies Are Making Today And How You Can Avoid ThemFindWhitePapers
"Look for additional opportunities to use business intelligence to uncover value and drive
improvements. Consider advanced planning tools that can help close the gap between
strategy and execution. Expand the use of sophisticated what-if analyses to model the
operational and financial impact of multiple scenarios on revenue, costs, and cash flow."
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
Take a look at the stories and statistics behind some of Dun & Bradstreet’s most successful analytics projects with our enterprise analytics case study look book.
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
• The definition of big data has grown beyond technical, i.e. “what it is,” to include “what it does.”
• A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
• Most of the focus is on driving top line growth.
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.
The Incidental Science of Organizational Growth via Digital Transformation RocketSource
Simply boosting top-line metrics, such as profitability, aren't enough to position digital transformation as a success. Pervasive access to data and insights are critical as consumer demands shift alongside technological advancements. We explore the mechanisms for knowledge dissemination that answer the rapid evolution of today's world and how to push organizations up the S Curve of Growth through digital transformation.
https://www.rocketsource.co/blog/organizational-growth-via-digital-transformation/?utm_source=slideshare&utm_medium=social&utm_campaign=profile-page&utm_term=digital-transformation
The D&B U.S. Economic Health Tracker exhibited resilience in May 2014. Readings on the small business community continued to stabilize although the anticipated bounce back has so far failed to materialize. In the meantime, some 297,000 new non-farm jobs were created, driven by strong gains in the business services and trade/transportation/utilities segments. Finally, the U.S. Business Health Index strengthened once again in May, registering a 54-percent index value, the highest recorded level since the index began in December 2010. U.S. businesses show sustained balance sheet and financial health, based on the weighted average of D&B's Viability Rating, Delinquency Predictor, and Total Loss Predictor. In spite of accelerating business expansion, lackluster economic growth and uncertainty remain significant restraints and should be monitored closely heading into the third quarter.
Target Better, Nurture Better and Close Better. Learn how Dun & Bradstreet data within Oracle Cloud can help businesses grow relationships and revenue.
Best Metrics to Optimize B2B Demand GenAsad Haroon
B2B marketers who need to do more than simply create brand awareness through outbound marketing have adopted Account Based Marketing (ABM) in order to focus on key accounts. Successful ABM campaigns can produce highly qualified, valuable prospects.
The D&B U.S. Economic Health Tracker showed dogged improvement in April 2014. Small business health stabilized after a number months of decline. Although wintry weather took its toll in the Northeast and Midwest earlier in the year, small businesses continue to demonstrate strong on-time bill and credit-card payments. Meanwhile, an estimated 208,000 new jobs were created, driven by strong gains in the retail and manufacturing segments. Finally, the U.S. Business Health Index strengthened yet again in April, registering a 53.7-percent index value, the highest recorded level since the index began in December 2010. U.S. businesses show sustained balance sheet and financial health, based on the weighted average of D&B’s Viability Rating, Delinquency Predictor, and Total Loss Predictor. Overall, the American economic recovery remains a choppy one, albeit with signs of hope in specific sectors.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
Arun Gupta, Customer Care Associate and Group Chief Technology Officer, Shoppers Stop presented at the Premier Business Leadership Series 2010, http://www.sas.com/theserieshk.
With many retailers worldwide struggling to maintain revenues, how do you grow in such a tough competitive landscape? As a leading Indian retailer and pioneer in using technology, especially business analytics, Shoppers Stop is not only thriving but has helped revolutionise the retail sector. Gupta will share insights on using analytics to drive business value, reduce operational costs and provide better products and customer experience.
Best Metrics to Optimize B2B Demand GenFrankAliyar
B2B marketers who need to do more than simply create brand awareness through outbound marketing have adopted Account-Based Marketing (ABM) in order to focus on key accounts. Successful ABM campaigns can produce highly qualified, valuable prospects.
Six Mistakes Companies Are Making Today And How You Can Avoid ThemFindWhitePapers
"Look for additional opportunities to use business intelligence to uncover value and drive
improvements. Consider advanced planning tools that can help close the gap between
strategy and execution. Expand the use of sophisticated what-if analyses to model the
operational and financial impact of multiple scenarios on revenue, costs, and cash flow."
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Big data focuses on finding hidden threads, trends, or patterns from heaps of telecom data. It represents significant information which opens new avenues of opportunities.
This report looks at all the important Malaysia trends - mobile, social, ecommerce. Malaysia is clearly ahead of the pack in south-east Asia - it's higher income, better connected, and more affluent compared to its neighbours like Indonesia, Thailand, Vietnam and others.
Big Data and advanced analytics are critical topics for executives today. But many still aren't sure how to turn that promise into value. This presentation provides an overview of 16 examples and use cases that lay out the different ways companies have approached the issue and found value: everything from pricing flexibility to customer preference management to credit risk analysis to fraud protection and discount targeting. For the latest on Big Data & Advanced Analytics: http://mckinseyonmarketingandsales.com/topics/big-data
Unlocking the Value of Usage Data March 20, 2014
Dan McGaw, Director of Marketing KISSmetrics @danielmcgaw
Puja Ramani, Director of Product Management & Analytics Gainsight @pramani #customersuccess #KISSwebinar
1 The Case for User Analytics, 2 Making User Analytics Actionable, 3 Realizing ROI
We Have Entered The Age Of The Customer
Customer data is everywhere
Welcome to our world of Customer Analytics.
How it works (it’s simple and powerful)
Your customer is at the heart of KISSmetrics
How effective is my signup process?
“You can’t maximize your revenue and profit unless you are tracking the lifetime value of each of your customers. And that’s what KISSmetrics does better than anyone else.” !! — Thomas (Zappos).
Which of my marketing channels has the highest ROI?
What do my customers do before they sign up?
Are customers coming back on a regular basis?
Making User Analytics Actionable
We all know a data driven world is inevitability
We track everything from our health to our homes to our children
We have more data about our customers than ever before
So what’s stopping us?
38% of companies are not able to communicate and interpret customer analytics results.
54% can’t integrate and manage all their data sources.
The four pillar approach is your roadmap to ROI
People Objective Strategy Technology
So what can you do?
Data Science Alert Rules and Playbooks Confirm Intuition
Blend with other data sources to discover insights
Score customer health using usage data
Have one view of all your customers
Fire off tasks or outreach based on usage
Take action on early warnings and manage each event
Consistently collaborate to keep customer relationships healthy
Who’s getting ROI from usage data?
Reduce Churn
THANK YOU
Dan McGaw, Director of Marketing KISSmetrics @danielmcgaw
Puja Ramani, Director of Product Management & Analytics Gainsight @pramani
How Big Data Analytics Helps In Delivering More Value to Your CustomersSemaphore Software
BIG DATA, the entire business community seems to go gaga over the possibilities that this new concept offers to businesses. From refining customer experience to delivering products and services as the need arises, it is being termed as the next ‘big thing’ in the world of business.
Data-Driven Dynamics Leveraging Analytics for Business GrowthBryce Tychsen
Explore the dynamic landscape of data-driven growth and learn how analytics can propel businesses to success. Discover strategies, tools, and best practices for harnessing data insights to drive growth and innovation.
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.
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.
Using Big Data in Finance by Jonah EnglerJonah Engler
How can you utilize Big Data in the Financial Industry? To leverage Big Data - entrepreneur and finance expert Jonah Engler, has put together this presentation to help the slideshare community understand the value - and HOW TO - use big data in the financial campaigns.
Jonah Engler is a financial expert and stock broker based in NYC. Leveraging his experience in finance, Engler has gone on to have success in the franchise, coffee, startup industries and more. To connect with Jonah - checkout his profile on LinkedIn: https://www.linkedin.com/in/jonahengler
Business Intelligence (BI) for Recession on Digit Channel ConnectDhiren Gala
Business Intelligence (BI) is made for times like these! “When cash runs out that’s when thinking starts.” This statement is very true in downturn or recession times
- Sanjay Mehta on Digit Channel Connect
Similar to Acquire Grow & Retain customers - The business imperative for Big Data (20)
Analytics facilitates a cohesive banding together of the organization for execution-oriented
organizational alignment, enterprise agility and better performance enabling action. Smarter
decisions result leading to superior performance.
Organizations who are looking to work faster and with greater agility often look to a private cloud as a solution. Not only can a private cloud improve data security, but it can also make better use of your existing IT resources. Unless you’re using Platform as a Service (PaaS), you’re not getting the full value out of your private cloud implementation. IBM’s Private Modular Cloud removes the bottlenecks that result from manual setups of middleware provisioning.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
2. 2 SSS
Introduction
T
hroughout history, business leaders used previous positive performance
tomakedecisions.Theydidwhatworkedbeforeandstoppeddoingwhat
didn’t work. Analytics, where it existed, was rudimentary. Business leaders
relied on intuition driven by experience.
While this worked well much of the time, it also resulted in spec-
tacular failures, as well as frequent disconnects between the business and
the customer.
Now, all that is changing. We’re entering an era when the business deci-
sion-making process and results are being transformed, driven by big data and
analytics. Sure, intuition and experience are important – but in the end, business
decisions are becoming objective.
This revolution is particularly powerful in customer relationships – the most im-
portant business relationships. Big data and analytics change how businesses in-
teract with customers by helping them build long-term relationships, realize value,
and incorporate all sources of data.
Aholisticviewofthecustomerismadepossiblewitharobustbigdataandanalyt-
icsplatfromandcanensureuniqueexperiencesandpersonalizedcommunications.
2
3. December 20133 SSS
Effective use of big data and analytics with
regard to customer relationships requires a
systematic approach. Businesses must build on
the four basic structural components.
Acquire
Customers
Retain
Customer
Loyalty
Personalize
Interactions
Increase
Profitability
The Four
Benefits
Big data and analytics help identify potential
customers and bring them into the fold.
Big data and analytics
provide support for identifying
and preempting customer
defections.
Personalization is crucial to
acquiring, growing, and retaining
customers by converting insights
into relevance to deliver targeted
messages that fit customers’
individual needs.
Big data and
analytics
improve the
ability to grow
lifetime value of
ideal customers.
4. December 20134 SSS
Make Your Business
BIG DATA& Analytics-Driven
B
ig data and analytics don’t just improve profitability and
reduce costs (although those goals will be achieved). They
can be truly transformational.
Analytics enhance the entire customer lifecycle. Big data
and analytics provide metrics to gauge the effectiveness
of customer programs. These metrics include revenue, conversion rates,
satisfaction key performance indicators (KPIs), return on investment (ROI),
and progress through the purchasing pipeline.
Organizations should look to what they already know about current
customers to ensure the ideal, most profitable prospects are targeted
for acquisition. Businesses should use research tools such as data and text mining emails
and social analytics to acquire customers.
5. 5 SSS
Thenextstepisincreasingrevenue
per customer using tools such as
loyalty programs, upselling, and
cross-selling,and price optimization.
Companies also need to retain
customers by using big data and
analytics to identify those likely to
defect and entice them to stay.
But to achieve these ends,
companies need to understand the
basics of big data and analytics itself
(See Four Vs Graphic on right).
VOLUME
VARIETY
VELOCITY
VERACITY
Increased instrumentation and customer conversations generates staggering amounts
of data. Ninety percent of the data in the world today was created in the last two years. That’ll
likely increase 50-fold in the next decade.
Data is available in multiple formats. The two most important categories for this discussion:
• Structured data can be classified and put into rows and columns in a database. Customer
transactions are an example of structured data.
• Unstructured data includes video, voice, and free-form text like that which can be found in en-
terprise content management (ECM) systems. Unstructured data also includes social media content
such as tweets and Facebook updates. Unstructured data requires complex analysis to make sense
of it and make it useful. About 80 percent of data now available is unstructured.
The data just keeps coming faster and faster: transactions, social media updates, emails, phone
calls, notes from sales calls, and on and on. Businesses need to keep on top of all of it. They need
to analyze data in real-time (or as close to real-time as possible) to extract its value. For example,
timing is crucial to deliver the optimal, targeted retention offer to keep valued customers from
defecting to a competitor.
Businesses need to eliminate uncertainty about data. There may be multiple customer
IDs in the system for an individual customer, each perhaps with a slightly differently spelled
name or nickname. Businesses need to resolve those discrepancies to increase the efficiency
of marketing campaigns and not bother customers with the same message multiple times.
The Four
Vs
6. 6 SSS
Businesses need to use the following types of data
and content to get a 360 view of the customer:
• Descriptivedataincludesself-declaredinformation
and demographics.
• Behavioral data includes orders, transactions, and
other customer activity as recorded by the business.
• Interaction data includes email, chat transcripts,
recordsofcallsbetweenthebusinessandcustomers,
and web click streams.
• Attitudinal data includes opinions, preferences,
needs,anddesires.Theseareoftendiscoveredthrough
survey responses or social media data.
Businesses need to use data mining, data
management,anddataintegrationandgovernanceto
ensurealldataisincludedandorganizedappropriately
in order to get insights.
Being data and analytics driven also requires having
the right IT infrastructure in place, specifically an
optimizedinfrastructuretodeliverinsightsatthepoint
of impact to empower all employees. Effective use of
bigdataandanalyticsrequiresthatcompaniesoperate
inreal-timeortherighttime–acrossmultiplecustomer
touchpointsandinthefaceofcompetitivethreats.
Companies need to make sure analytics can access
dataandprovideinsightsquicklyandefficiently.Data
needs to be accessed as needed, no matter what its
format or where it may reside.
Visualization is needed to communicate
insights throughout the organization.
Human beings are wired to think visually.
Dashboards help decision makers
understand complex data quickly,
providing the big picture while
data exploration enables them to
quickly dig into the details in a visual
fashion. Custom reporting using color
coding, mapping, and other visual
formats helps decision makers process
information. And simulations display what-
if scenarios to help make decisions quicker and
with better results.
Customer interactions need to be repeatable and
consistent.Companiesneedtoembedandautomate
intelligent decisions into operational processes.
7. December 20137 SSS
W
oodyAllenobservedthatro-
mantic relationships are like
sharks – they need to keep
moving, or they die. Busi-
nesses are the same way.
They need to keep growing, and continued growth requires
bringinginnewcustomers.Bigdataandanalyticsdriveidentification
and recruitment of new customers, turning leads into revenue.
Big data and analytics provide several unique benefits in the customer
acquisition process. These go beyond the gains offered by conventional
marketing solutions by effectively leveraging all types of data and apply-
ing varying forms of analytics:
• Improved accuracy and response to marketing campaigns. Big
data and analytics are a new way to approach problem solving by being
more informed. Using big data and analytics, businesses are able to target
messagesto thecustomers most likely tobereceptive tothem.These tools
identifythepeoplemostlikelytobecomecustomersandhelpreelthemin.
• Reduced acquisition cost. It has been proven that it is far more
expensive to acquire customers than it is to retain them. Big data and
analytics can change this long-standing dynamic and help cut the costs
of acquiring customers by enabling businesses to target prospects more
accurately and efficiently.
7
8. December 20138 SSS
• Predict lifetime value of a customer. Big
data and analytics help companies predict how
much a lead is likely to spend as a customer by
comparing that prospect with the characteris-
tics of current customers. This analysis enables
businesses to acquire customers selectively.
Businesses can focus on acquiring high-value
customers and exclude low-value customers
who drain resources and produce reduced or
even negative profitability.
And there are other benefits to big data
and analytics. The capabilities that comprise
a comprehensive big data and analytics solu-
tion provide insight into competitor activity.
In particular, social media analytics can help
businesses compare how often they’re be-
ing discussed in a positive and negative light
compared with competitors. Businesses can
measure customer mindshare as well as sen-
timent in comparison with their competition.
But that’s just the beginning. Big data and
analytics can allow businesses to interpret
the signs of a competitor making a significant
change, such as a new pricing strategy, prod-
uct launch, or strategic direction, achieving a
big customer win or losing a customer.
Having this background means that, with
big data and analytics, companies can accu-
rately feed customers with customized offers
throughout the customer’s relationship with
the business, beginning with acquisition and
continuing with growth and retention.
This helps cut marketing costs by improving
targeting efficiency and reducing spray-and-
pray marketing. A business not using big data
and analytics and relying on spray-and-pray
sends every offer to every potential customer
in its marketing database, hoping a few offers
– or enough – will prove fruitful. Spray-and-
pray marketing has always been an expensive,
wasteful proposition. And it’s getting worse.
Only a few years ago, marketing was limited
to a few primary channels, mainly direct mail,
phone, broadcast advertising, and print. Now,
the channels are exploding: all of the old chan-
nels plus email, social media, online advertising,
mobile, and more.
The value of big data and analytics is dis-
played not only by helping marketing maintain
consistency across all those channels and use
all of them effectively, but also, and even more
importantly, by using all information created
by these additional channels to make decisions
more intelligently.
Acquiring high-value customers is a multi-
step process, and big data and analytics can
guide you every step of the way:
Facilitate progression through the mar-
keting pipeline. Before they become custom-
ers, consumers and business buyers start by
identifyingtheirneedsandresearchingpossible
solutions. They then move on to research spe-
cific products and services. Later, they contact
companies to begin the sales process. Big data
and analytics help businesses guide potential
customers every step of the way.
9. December 20139 SSS
Developpersonasbasedoncharacteristicsofcustomermicro-segments.
Some customers are more concerned about pricing, others about quality, others
about service, and more. Many will be receptive to emotional messages evoking
family, beauty, health, and so on. (That’s particularly true for consumer products
and services.) Big data and analytics identify the common, finely grained charac-
teristics of potential customers and group like characteristics with like customers.
Executeindividualizedmarketingstrategies.Onceyou’veusedbigdataand
analytics to identify high-value sales leads and their needs, now comes the time to
deliver the messages most likely to work with each potential customer.
Compare performance of marketing campaigns. How did you do? Which
campaigns worked best? Which campaigns worked least well? Which campaigns
can be more effective when tuned for better performance? Big data and analytics
is the guiding star to help constantly adjust direction to reach the goal of improved
business performance.
Know the attributes of your current high-value customers. A great way
to find new high-value customers is to cultivate relationships with individuals and
businesses that resemble your current best customers. Big data and analytics can
help build profiles of the most profitable current customers.What are their charac-
teristics?What are their qualities and special needs? Do they require a great deal of
customer service? Are they strongly influenced by social media?
Understanding current customers helps with the acquisition of new ones.
Discovering the attributes of high-value customers helps focus efforts on leads
with similar characteristics.
As an example of how big data and analytics can
help, consider RFM analysis. This is a relatively
simple tool that grades customers on three criteria:
Customers with high RFM scores are the best
customers, and the leads that most closely
resemble those customers are the ones to target.
RECENCY
When was the last time the
customer purchased something?
FREQUENCY
How often do they visit?
MONETARY VALUE
What’s the average spend?
10. December 201310 SSS
A
cquiringcustomersisnecessarybutexpensive.Another
vital way to increase revenue and profit is to make your
current customers more valuable.
Big data and analytics help achieve this goal by using
advanced association methods that deliver targeted
upselling and cross-selling offers in real-time and optimizing use of
marketing resources.
Cross-selling suggests products that are often bought together. Up-
selling adds additional features to a product or service.You’re familiar
with both cross-selling and upselling if you’ve ever visited a fast-food
restaurant. “Would you like fries with that?” is an example of cross-
selling.“Would you like to super-size your order?”is upselling. Big data
andanalyticstoolscanhelpaggregateinformationtomakeintelligent
upselling and cross-selling offers across a broad portfolio of products.
Grow
10
11. December 201311 SSS
Simple upselling and cross-selling begins with,
“If customer buys Product A, then offer Product
B.” But big data and analytics enables much
more sophisticated opportunities. It looks at the
world of information available to business, looking
deeper at customer attributes and outside circum-
stances surrounding the purchase – weather, day of the
week, time of year, social conversations, and more.
Improving customer value adds to profitability and
loyalty. The process starts with comparing customers’
purchase behavior against similar customers. Also, look
outside the company. Understand emerging customer
buying behaviors.
Consistency is key to increasing customer value. The
most effective use of big data and analytics requires consis-
tency and collaboration across the enterprise. Enterprises
need to provide a consistent experience to the customers,
no matter what channel is being used for communication:
email, in person, online, mobile, apps, or voice telephony.
Defining the customer lifetime value (CLV) is also impor-
tant. A business can’t grow what it can’t measure.
Big Data &
Analytics
Intelligent Upselling
and Cross-Selling Offers
Similar Customer Behavior
Emerging Buying BehaviorsPrevious Behavior
12. 12 SSS
The components of CLV are:
• Acquisition costs
• Margin generated by the customer
• Retention rate
• Social influence – the value the customer pro-
vides through social interactions
CLV helps target campaigns to achieve several
beneficial goals: increasing profitability, driving cus-
tomer acquisition, identifying customers who may
defect or who are a drain on internal resources, and
qualifying inbound sales leads.
CLV improves marketing by defining how much
you actually spend to acquire a customer or to
keep that customer from defecting.
Big data and analytics can provide several ben-
efits to drive marketing to current customers. It
sends the right message to the right customer
through the right channel at the right time. And
it maps customer behavior to the buying cycle,
thereby enabling the business to serve an offer or
content that matches the customer’s buying stage
and helps progress that customer to a purchase.
Businessesneedtomeasuretoensuretheirmarket-
ing efforts toward current customers are paying off.
Businesses also need to test offers to optimize ROI.
Businesses should use predictive modeling to an-
ticipate the future behaviors of individual custom-
ers. Predictive modeling takes two forms:
• Predictive modeling can identify a set of clusters
describing how cases in a dataset are related, iden-
tifying which items are purchased together (often
called a market basket analysis or affinity modeling).
• It can also take the form of a decision tree,
which predicts an outcome and describes how
different criteria affect that outcome, identifying
indicators affecting a propensity to respond, pur-
chase, or defect.
To create the predictive model, the algorithm first
analyzes data looking for specific patterns or trends.
Then, the algorithm applies the model across the
entire dataset to extract useful patterns and de-
tailed statistics.
December 2013
13. December 201313 SSS
Retain
L
osing customers is a big problem for any busi-
ness. Customers may become dissatisfied or an-
gry, and they may take their business elsewhere.
Losing one customer is bad enough, but a
single dissatisfied customer has new channels
to spread the word and bring other customers
with them. Customers can, and do, vent their dissatisfaction
through social channels such as Twitter and Facebook. A sin-
gle pebble can cause an avalanche.
Businesses need to identify at-risk customers and head off de-
fections of valuable customers. Big data and analytics can help
by improving retention and customer satisfaction through sen-
timent analysis and scoring to make tailored offers proactively.
14. December 201314 SSS
Retention looks for behavioral anomalies,
or behavior contrary to acceptable practices,
which could result in a defection decision. After
identifying those patterns, businesses can take
action to make sure customers are retained.
(But only retain the most profitable customers.
Let competitors have customers who require
a large investment of resources but generate
minimal profits.)
Big data and analytics help spot behavioral
anomalies that indicate a customer is at risk of be-
ing lost. For example, until recently, the first sign
a telephone company received that a customer
was at risk of defecting was when that customer
called to cancel service. At that point, the com-
pany would try to talk the customer out of the
decision, but by then, it was usually too late to
win the customer back.
Big data and analytics does better by helping
spot early warning signs – for example, flagging
customers who make an increased number of
service calls, complain about dropped calls, and
then visit the FAQ on the company website to
find out how to terminate a contract early. Big
data and analytics tools spot anomalies, mine
call log text, and identify at-risk customers before
they are ever lost.
Gaining a 360° view of the customer can pro-
vide organizations with valuable information
about how to serve customers better and foster
brand loyalty. Companies can build information
about customers using sentiment information
from surveys, interactions, and social media to
gain insight. Using that data, companies should
tailoroffers,trackrelationships,andidentifywhere
customers reside within the purchase funnel.
The best businesses have been getting 360°
views of their customers for a long time. It’s a
scientific means to an old business principle:
Get to know your customers better. You already
know how your customers have behaved in the
past and how they are behaving now. But you
really want to know what’s in their heart, their
experience, and their deepest desires in the ar-
eas where you can serve them.
Big data and analytics can give you that.
Gaining a 360° view
of the customer can
provide organizations
with valuable
information about how
to serve customers
better and foster
brand loyalty.
15. December 201315 SSS
Personalize
P
ersonalization is the fuel driving the engines of acquisi-
tion, growth, and retention. Personalization ensures that
each customer interaction is unique and moves the cus-
tomer along the buying journey. By using big data and
analytics, businesses can predict the best communica-
tion method, channel, message, and time of delivery to reach each
individual customer.
Businesses need to achieve a deep understanding of customers, in-
cluding all types of information about them. By using that information,
businesses can acquire, grow, and retain customers.
The alternative to personalization is mass marketing – spray-and-pray,
which has been covered previously and is not viable. It’s expensive and
inefficient. Too many messages go out to customers who just don’t care.
Perhapsworse,theyreducethesizeofthemarketingdatabaseascustom-
ers and leads opt out of receiving messages.
15
16. December 201316 SSS
Personalization goes far beyond sending
messages. It extends to all parts of the com-
pany: the website, interactions over the phone,
face-to-face communications, email, social me-
dia – all channels.
In every communication, customers require
personalized messaging tailored to their desires,
needs,andindividualcharacteristics.Personaliza-
tion incorporates all customer data, structured
and unstructured, inside the firewall and exter-
nal, to provide a custom message to every cus-
tomer and lead. Moreover, messages and inter-
actions must be unique and granular, beginning
with the initial contact and following up with
contacts after the initial purchase, to increase
profitability and loyalty.
Personalization goes beyond segmenting
groups to segmenting individuals. This kind of
micro-segmentation identifies each individual
customer’s preferences, needs, and behaviors.
Personalizing offers at that level maximizes
marketing campaign dollars and enhances the
customer relationship.
For example, neural networks and decision
trees can be effectively applied to micro-seg-
mentation. Neural networks uncover complex
patterns in types of customers and rank each
by scoring their likelihood to respond to a spe-
cific offer. Decision trees use branching graphs
to portray decisions and their likely outcomes.
Conclusion
Big data and analytics can help businesses de-
liver on customer needs, acquire customers,
increase current customers’ profitability, and
retain the most valuable customers by keeping
them from churning. To achieve those goals,
businesses need to deliver personalized, rel-
evant messages driven by the insights derived
from big data and analytics.
But that’s just the beginning of what big data
and analytics can do for your organization. It
can help you streamline operations, find new
sources of revenue, manage risk, and prevent
fraud and counterfeiting. Organizations today
analyze less than 1 percent of the vast supply
of incoming data. Using big data and analytics,
smarter enterprises can change how they work,
serve more customers, and enhance the prod-
ucts and services they offer.
Get started today.
About IBM
IBM is the world’s largest information technology company, with 80
years of leadership in helping clients innovate. Drawing on a breadth
of capabilities and best practices from across IBM and our extensive
partner ecosystem, we offer clients within every industry, a wide range
of services, solutions and technologies that can help them improve
productivity, respond rapidly to the needs of their business and reduce
development and operations costs. www.ibm.com
, For more information about using Big Data & Analytics to acquire,
grow and retain customers visit our website at http://www.ibm.com/
big-data/us/en/big-data-and-analytics/marketing.html
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