Catalog University Pub talk: Leveraging browsing behavior to improve catalog ...Sarah Fletcher
Working with Digital Browsing Behavior to Improve Customer Response
Incorporating digital predictors into a mailing strategy can help you make better print mailing decisions, and can increase revenue by two to three times. CohereOne is pioneering overlaying online browsing behavior on traditional circulation planning to target customers who would traditionally be considered unmailable in catalog circulation planning yet may actually be responding well within the response range needed to be profitable.
Smart multichannel merchants are leveraging their customer’s online behavior to see if they are still actively engaged with the brand even though they may not have made a recent catalog purchase. the information gleaned can also identify segments that will not respond and should be suppressed. Increasing catalog circulation to customers who are likely to make a catalog purchase and suppressing customers who are no longer engaged is the one-two punch that can really improve your bottom line.
Two Case Studies
CohereOne shares two case studies showing how they found opportunities for both increasing reactivation circulation and suppressing unproductive names. One retailer incorporated digital predictors and reactivated their older buyers by 83%. That’s pretty significant when you consider the cost of acquiring new buyers.
Join Travis Seaton, Vice President of Client Services, and Jude Hoffner, Vice President of Digital Product Management at CohereOne, as they explore how traditional selection criteria in circulation management (recency, frequency, monetary) is making room for a more targeted and ecommerce-centric approach.
Using Contextual Information to Understand Searching and Browsing BehaviorJulia Kiseleva
Julia Kiseleva's slides for PhD defense on June 13 2016.
The thesis is available by the following link -- https://www.researchgate.net/publication/303285745_Using_Contextual_Information_to_Understand_Searching_and_Browsing_Behavior
Catalog University Pub talk: Leveraging browsing behavior to improve catalog ...Sarah Fletcher
Working with Digital Browsing Behavior to Improve Customer Response
Incorporating digital predictors into a mailing strategy can help you make better print mailing decisions, and can increase revenue by two to three times. CohereOne is pioneering overlaying online browsing behavior on traditional circulation planning to target customers who would traditionally be considered unmailable in catalog circulation planning yet may actually be responding well within the response range needed to be profitable.
Smart multichannel merchants are leveraging their customer’s online behavior to see if they are still actively engaged with the brand even though they may not have made a recent catalog purchase. the information gleaned can also identify segments that will not respond and should be suppressed. Increasing catalog circulation to customers who are likely to make a catalog purchase and suppressing customers who are no longer engaged is the one-two punch that can really improve your bottom line.
Two Case Studies
CohereOne shares two case studies showing how they found opportunities for both increasing reactivation circulation and suppressing unproductive names. One retailer incorporated digital predictors and reactivated their older buyers by 83%. That’s pretty significant when you consider the cost of acquiring new buyers.
Join Travis Seaton, Vice President of Client Services, and Jude Hoffner, Vice President of Digital Product Management at CohereOne, as they explore how traditional selection criteria in circulation management (recency, frequency, monetary) is making room for a more targeted and ecommerce-centric approach.
Using Contextual Information to Understand Searching and Browsing BehaviorJulia Kiseleva
Julia Kiseleva's slides for PhD defense on June 13 2016.
The thesis is available by the following link -- https://www.researchgate.net/publication/303285745_Using_Contextual_Information_to_Understand_Searching_and_Browsing_Behavior
A beginner's guide to the world of online advertising. Find out what happens under the hood; find out how online advertising generates revenue and for whom; find out who the players are and their roles in the world of online advertisting.
We Are Social's Guide to Social, Digital and Mobile Around the World (Feb 2013)We Are Social Singapore
This is the February 2013 edition of We Are Social Singapore’s guide to Social, Digital and Mobile around the world. You'll find more in this series of reports at http://wearesocial.sg/tag/sdmw
This report presents all the key statistics, data and behavioural indicators for social, digital and mobile channels around the world. Alongside regional pictures that capture the stats for every nation on Earth, we also present in-depth analyses for 24 of the world's largest economies: Argentina, Australia, Brazile, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Nigeria, Poland, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Turkey, Thailand, the UAE, the UK, and the USA. For other reports in this series, please visit http://wearesocial.sg/tag/sdmw
We Are Social's comprehensive new report covers internet, social media and mobile usage statistics from all over the world. It contains more than 350 infographics, including global snapshots, regional overviews, and in-depth profiles of 30 of the world's largest economies. For a more insightful analysis of these numbers, please visit http://bit.ly/SDMW2015
We Are Social's comprehensive new Digital in 2016 report presents internet, social media, and mobile usage statistics and trends from all over the world. It contains more than 500 infographics, including global data snapshots, regional overviews, and in-depth profiles of the digital landscapes in 30 of the world's key economies. For a more insightful analysis of the numbers contained in this report, please visit http://bit.ly/DSM2016ES.
Social Media Listening come primo step di ingaggio nel customer journeySmarter Engagement
Paolo Trevisan / Marco Colusso - ESTILOS - Intervento a Smarter Engagement 2016: http://2016.smarterengagement.com/session/social-listening-come-primo-step-di-ingaggio-nel-customer-journey/
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.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
A beginner's guide to the world of online advertising. Find out what happens under the hood; find out how online advertising generates revenue and for whom; find out who the players are and their roles in the world of online advertisting.
We Are Social's Guide to Social, Digital and Mobile Around the World (Feb 2013)We Are Social Singapore
This is the February 2013 edition of We Are Social Singapore’s guide to Social, Digital and Mobile around the world. You'll find more in this series of reports at http://wearesocial.sg/tag/sdmw
This report presents all the key statistics, data and behavioural indicators for social, digital and mobile channels around the world. Alongside regional pictures that capture the stats for every nation on Earth, we also present in-depth analyses for 24 of the world's largest economies: Argentina, Australia, Brazile, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Nigeria, Poland, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Turkey, Thailand, the UAE, the UK, and the USA. For other reports in this series, please visit http://wearesocial.sg/tag/sdmw
We Are Social's comprehensive new report covers internet, social media and mobile usage statistics from all over the world. It contains more than 350 infographics, including global snapshots, regional overviews, and in-depth profiles of 30 of the world's largest economies. For a more insightful analysis of these numbers, please visit http://bit.ly/SDMW2015
We Are Social's comprehensive new Digital in 2016 report presents internet, social media, and mobile usage statistics and trends from all over the world. It contains more than 500 infographics, including global data snapshots, regional overviews, and in-depth profiles of the digital landscapes in 30 of the world's key economies. For a more insightful analysis of the numbers contained in this report, please visit http://bit.ly/DSM2016ES.
Social Media Listening come primo step di ingaggio nel customer journeySmarter Engagement
Paolo Trevisan / Marco Colusso - ESTILOS - Intervento a Smarter Engagement 2016: http://2016.smarterengagement.com/session/social-listening-come-primo-step-di-ingaggio-nel-customer-journey/
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.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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).
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.
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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.