This document discusses improving data quality for marketing effectiveness. Typical data problems include duplicate records, incomplete data, and incorrect data. Marketing benefits from quality data through having an accurate view of customers to effectively target communications. The best way to address data quality is as close to the source as possible, such as validating data during web form submissions. Various opportunities for cleansing data exist, such as during transactional updates, from external data feeds, when migrating legacy data, and through regular maintenance of existing data. Ensuring high quality data is important for marketing success.
What Is CRM and How Can It Increase Your SalesScott McKissack
This document discusses customer relationship management (CRM) solutions and how they can help businesses increase sales. It defines CRM as a system that manages customer interactions across sales and marketing operations. The document outlines key benefits of CRM such as improved productivity, more organized processes, better management of leads and customers, and real-time mobile access to data. It recommends that businesses tailor CRM solutions to meet their specific needs and emphasizes that CRM solutions are accessible options for small and medium-sized businesses to stay competitive.
Helping Your Marketing Department Fly Higher 4 12 11Eric Webb
This white paper provides insight into the need to create a teaming environment to gain sales in professional services, leveraging relationship and technical staff in the firm to optimize success.
Big Data That Drives Marketing ROI Across All Channels & Campaigns-A Case Stu...Vivastream
The document discusses how Workday, a leading HR and financial software company, improved their digital marketing performance through closing the loop on data and attribution modeling.
Workday faced challenges with their complex B2B sales cycle that involved multiple decision makers over long periods of time. They sought to improve lead generation, close more business faster, and measure ROI.
The strategy started with closing the data loop to attribute the success of different marketing programs from awareness to engagement to conversion and sales. Analytics tools were connected to business tools like CRM to analyze multi-source data and gain insights to optimize performance.
Attribution modeling helped understand what was happening with the customer journey, why, and what actions to take as a
The document discusses the importance of marketing metrics and analytics for building accountability and respect within an organization. It argues that marketing should measure metrics that matter to executives like revenue, profits, and growth. The document also emphasizes that marketing should plan for ROI from the start of a program by establishing goals and estimating ROI, designing measurable programs, and focusing on decisions that can improve marketing performance.
- Forrester evaluated 18 leading CRM suite solutions against over 500 criteria to assess their suitability for large organizations. The solutions were grouped into leaders, strong performers, and a single contender.
- Oracle Siebel and SAP were found to still offer the most complete solutions for large enterprises, though other leaders like Salesforce.com and Microsoft are gaining ground with more flexible, quicker to implement solutions.
- While the leaders are challenged by strong performers like Oracle E-Business Suite and PeopleSoft CRM suited for ERP customers, as well as BPM-focused solutions from Chordiant, Pegasystems and Sword Ciboodle, the crowded market provides many choices for buyers to consider.
This document discusses the benefits of integrating front office and back office systems through a single CRM and ERP solution. It describes the challenges companies face with disconnected CRM and ERP systems like data silos and inefficient processes. Integrating these systems provides benefits like reduced costs, improved customer relationships and increased profitability by allowing seamless data sharing and automated workflows.
- Customer data management is important to understand customers better and improve service, but traditional data management tools create siloed and inconsistent data.
- NexJ Customer Data Management provides an "Enterprise Customer View" that integrates customer data from multiple sources to create a holistic understanding of each customer.
- This unified view of customer data can be used across an organization to drive digital transformation initiatives, enhance customer insights, and meet compliance requirements.
What Is CRM and How Can It Increase Your SalesScott McKissack
This document discusses customer relationship management (CRM) solutions and how they can help businesses increase sales. It defines CRM as a system that manages customer interactions across sales and marketing operations. The document outlines key benefits of CRM such as improved productivity, more organized processes, better management of leads and customers, and real-time mobile access to data. It recommends that businesses tailor CRM solutions to meet their specific needs and emphasizes that CRM solutions are accessible options for small and medium-sized businesses to stay competitive.
Helping Your Marketing Department Fly Higher 4 12 11Eric Webb
This white paper provides insight into the need to create a teaming environment to gain sales in professional services, leveraging relationship and technical staff in the firm to optimize success.
Big Data That Drives Marketing ROI Across All Channels & Campaigns-A Case Stu...Vivastream
The document discusses how Workday, a leading HR and financial software company, improved their digital marketing performance through closing the loop on data and attribution modeling.
Workday faced challenges with their complex B2B sales cycle that involved multiple decision makers over long periods of time. They sought to improve lead generation, close more business faster, and measure ROI.
The strategy started with closing the data loop to attribute the success of different marketing programs from awareness to engagement to conversion and sales. Analytics tools were connected to business tools like CRM to analyze multi-source data and gain insights to optimize performance.
Attribution modeling helped understand what was happening with the customer journey, why, and what actions to take as a
The document discusses the importance of marketing metrics and analytics for building accountability and respect within an organization. It argues that marketing should measure metrics that matter to executives like revenue, profits, and growth. The document also emphasizes that marketing should plan for ROI from the start of a program by establishing goals and estimating ROI, designing measurable programs, and focusing on decisions that can improve marketing performance.
- Forrester evaluated 18 leading CRM suite solutions against over 500 criteria to assess their suitability for large organizations. The solutions were grouped into leaders, strong performers, and a single contender.
- Oracle Siebel and SAP were found to still offer the most complete solutions for large enterprises, though other leaders like Salesforce.com and Microsoft are gaining ground with more flexible, quicker to implement solutions.
- While the leaders are challenged by strong performers like Oracle E-Business Suite and PeopleSoft CRM suited for ERP customers, as well as BPM-focused solutions from Chordiant, Pegasystems and Sword Ciboodle, the crowded market provides many choices for buyers to consider.
This document discusses the benefits of integrating front office and back office systems through a single CRM and ERP solution. It describes the challenges companies face with disconnected CRM and ERP systems like data silos and inefficient processes. Integrating these systems provides benefits like reduced costs, improved customer relationships and increased profitability by allowing seamless data sharing and automated workflows.
- Customer data management is important to understand customers better and improve service, but traditional data management tools create siloed and inconsistent data.
- NexJ Customer Data Management provides an "Enterprise Customer View" that integrates customer data from multiple sources to create a holistic understanding of each customer.
- This unified view of customer data can be used across an organization to drive digital transformation initiatives, enhance customer insights, and meet compliance requirements.
What Customer Relationship Management entails in the 21st CenturySameer Patel
CRM in the 21st century focuses on customer engagement rather than data. Customers now expect expert answers to their questions and want to interact with companies on social networks and blogs, rather than just through email. They also expect a consistent customer experience across all channels. Effective CRM requires breaking down silos between different business functions and prioritizing customer needs to provide the type of engaged, personalized experiences customers now demand across the entire customer lifecycle.
CRM projects typically take over a year to begin generating returns on investment. Most CRM initiatives are less than 12 months old, and only 11% have been in place for over two years. This is not enough time to fully realize the benefits, as it can take around a year to see any ROI from a CRM project. Companies initially focus on operational CRM through sales force automation and customer service integration, expecting quicker payoffs. But the full value comes from blending both operational and analytical CRM to develop a holistic understanding of customers. Patience is needed, as CRM aims to fundamentally change how companies interact with customers.
This document provides an overview and instructions for using Microsoft Dynamics CRM. It begins with an introduction to key concepts like records, record types, accounts, contacts, leads, opportunities, and cases. It then explains how to navigate the CRM interface and enter, view, filter, and export data. The document also covers activities like notes, tasks, emails, and how to track customer communications history through activities. The goal is to help users understand the basic functionality and organization of data in Microsoft Dynamics CRM.
Marketers have more data available than ever but struggle to pull in together in a usable format. Customer Data Platforms promise to solve this problem by offering easy-to-deploy systems specializing in data unification and sharing. But can CDP really deliver on its promise? This workshop will equip you to understand the definition of a CDP, how CDPs differ from other systems, which features are shared by all CDPs and which are found in only some, the most important CDP use cases, how to select the right CDP, how to manage a successful deployment and where to look next for more information.
A case for crm team 11 - beacon hill version 1.1 pptRicardo Moraes
CRM is a business strategy focused on customer relationships that has grown in adoption from 53% in 2003 to 75% in 2010. It involves collecting customer data, integrating it into meaningful information, and using it across sales, marketing, and service to develop stronger customer relationships. Analysts predict 33% of CRM spending will be on hosted on-demand services by 2015.
The document provides an agenda for a two-day seminar on database marketing. Day 1 will cover re-evaluating marketing database systems, an overview of different database technologies, and best practices for database content and metrics reporting. Day 2 will discuss leveraging databases for reporting and applications, modeling and analytics, navigating large amounts of data, integrating digital media data, and ensuring political and business success for database projects. The seminar is aimed at helping database marketers enhance operations by learning about current trends, technologies, and best practices in database marketing.
Microsoft Dynamics CRM and ERP solutions can provide a return on investment within the first year through several key strategies:
1) Boosting sales by retaining customers, maximizing revenue opportunities, and streamlining sales processes.
2) Providing business intelligence through real-time visibility, aligning business units, and reporting/tracking capabilities.
3) Offering cloud hosting options that reduce costs while providing flexibility and choice in deployment.
4) Functioning as an all-in-one product that increases existing systems' potential through seamless integration.
5) Giving competitive advantages like improving customer service capabilities.
Master Data Management (MDM) for Mid-MarketVivek Mishra
This document discusses master data management (MDM) solutions for mid-sized businesses. It begins by introducing MDM and its benefits, such as a single source of truth and improved data quality. It then outlines some common challenges for implementing MDM in mid-sized companies, such as high costs, maintaining multiple data domains, and the need for organizational change management. The document provides advice on overcoming these challenges by selecting flexible and affordable MDM platforms. It also describes key properties of effective MDM, like ongoing data governance and providing a 360-degree view of customers. Finally, it introduces Compunnel Digital's partnership with Profisee to offer modernized MDM solutions tailored for mid-sized organizations.
Remodista RetailSource Paper - Sophisticated CRM StrategiesRemodista
Customer relationship management—the name should speak for itself. Right? Well, companies all too often take this critical piece in the retail puzzle for granted, equating it to the technical components that support it and reducing it to a database of point-of-sale information. However, CRM is no longer just a back-office repository for client information; it’s assuming its place at the very center of the sales picture as consumer expectations evolve. It’s the key to a comprehensive strategy of brand engagement, with the customer at its core.
The D.A. Company - sforce crm overview 5-5-11.1danarchetti
The document describes a proposed Account Information Management Solution (AIMS) using the Salesforce.com CRM platform. It notes that while the pet supplies industry has evolved, data collection and management methods have lagged behind. Spreadsheets, word documents and email lead to disorganized "data black holes". The solution proposes implementing a web-based CRM like Salesforce.com to centralized data in a single, secure location accessible anywhere. The target users are field sales teams, managers and customer service who could benefit from improved account profiling, activity tracking and reporting.
B2B CRM and supply chain management are strongly connected, as ERP systems have automated key business processes and linked different departments. ERP vendors have recognized the importance of tighter integration between operations and customer satisfaction, releasing CRM modules. Measurement of CRM performance in B2B was traditionally focused on supplier metrics like revenue, but there is a shift towards more relationship-oriented metrics that are meaningful to customers, such as the number of senior executives contacted. Adopting metrics and incentives valued by customers is necessary for the success of B2B CRM.
International Journal of Business and Management Invention (IJBMI)inventionjournals
The document summarizes customer relationship management (CRM) strategies used by Airtel and Zain in the telecommunications industry. It finds that:
1) Airtel divides its customer care cell into four departments to handle different customer segments. It also implements CRM through customer care executives and measures effectiveness through a third party.
2) Airtel designs special loyalty programs and incentives, especially for privileged customers. It has a complaint handling system and incorporates customer feedback.
3) Zain collects customer personal information through its website to perform data mining and convert data into useful business insights. It aims to improve capabilities to acquire and retain customers to increase market share.
Independent analysis by The Optera Group found that banks using Microsoft Dynamics CRM saw tangible benefits including improved marketing, operations, and risk management. Six banks profiled showed how Dynamics CRM helped optimize existing customer relationships, drive efficiency, and cut costs through real-time data visibility, automated processes, and enhanced customer experience. The flexible software integrated with legacy systems and supported growth through mergers.
This document discusses how Microsoft Dynamics CRM can help retail banks meet challenges around business agility, relationship banking, and improving the customer experience. It describes how CRM strategies and solutions can enable banks to measure customer value, explore opportunities to develop customer-centric business models, and improve back-office efficiency. The document outlines how Dynamics CRM provides a platform for business process management, return on investment tracking, service-oriented architecture, and a 360-degree view of customers.
Like all channels of marketing, channel and data integration are keys to success. The more complex of the two is in the data.
If you're immersing into the world of mobile or location based marketing, familiarize yourself with location data management (LDP). To start read SIM Partners white paper "The CMO's Guide to Location Data Management."
Making the Journey to Customer Marketing 3_BIOPatrick Spencer
The document discusses the evolution of customer marketing over three eras:
1) Customer Marketing 1.0 (1990s-2002) was a tactical, non-strategic role focused on order taking to support sales, PR, and AR. References were tracked via spreadsheets with no centralized system. Success was measured by lack of complaints.
2) Customer Marketing 2.0 (2004-2011) saw automation of reference management through web-based systems. Third party software-as-a-service providers emerged to replace in-house solutions. Larger organizations consolidated fragmented customer marketing teams.
3) Customer Marketing 3.0 (2012-present) is described as more strategic and data-driven. Advanced
This document discusses trends that will shape the future of customer relationship management (CRM) systems by the year 2020. It argues that CRM will be transformed by collaboration, mobility, user-centric design, cloud computing, and social media integration. CRM will shift from a focus on managing contacts and reporting to helping teams collaborate, sell, and grow through more effective and interactive systems that can be accessed anywhere through mobile devices.
This document provides an overview of master data management (MDM) and describes how the Kalido MDM solution addresses common MDM challenges. It discusses how master data is critical context for business processes and analytics but is often inconsistent across systems. The Kalido MDM solution enables businesses to consolidate, govern, and maintain master data through capabilities like managing all data domains, sophisticated data modeling, a master data authoring environment, life cycle management, data matching, hierarchy management, and embedded workflow to guide the data stewardship process.
The document summarizes the Upper Colorado River Endangered Fish Recovery Program, which was established in the 1970s to protect endangered fish species in the Colorado River basin. The program involves federal agencies, states, and interest groups working cooperatively to manage water flows and habitats. Key activities include securing water flows, developing fish habitats, stocking endangered fish, and managing nonnative species. The program has helped protect winter and spring flows in Reach 2 of the Green River to maintain channels and floodplains.
Este documento instruye a la persona a agregar 5 monografías relacionadas con la Web 2.0 o competencias informacionales a su cuenta de RefWorks y luego crear una bibliografía de la lista en un formato uniforme.
El autor quiere darle un regalo a alguien lleno de cariño para ser amigos y compartir experiencias, tanto buenas como malas, cuyos esfuerzos traerán aprendizaje, el regalo más hermoso que puede ofrecer.
What Customer Relationship Management entails in the 21st CenturySameer Patel
CRM in the 21st century focuses on customer engagement rather than data. Customers now expect expert answers to their questions and want to interact with companies on social networks and blogs, rather than just through email. They also expect a consistent customer experience across all channels. Effective CRM requires breaking down silos between different business functions and prioritizing customer needs to provide the type of engaged, personalized experiences customers now demand across the entire customer lifecycle.
CRM projects typically take over a year to begin generating returns on investment. Most CRM initiatives are less than 12 months old, and only 11% have been in place for over two years. This is not enough time to fully realize the benefits, as it can take around a year to see any ROI from a CRM project. Companies initially focus on operational CRM through sales force automation and customer service integration, expecting quicker payoffs. But the full value comes from blending both operational and analytical CRM to develop a holistic understanding of customers. Patience is needed, as CRM aims to fundamentally change how companies interact with customers.
This document provides an overview and instructions for using Microsoft Dynamics CRM. It begins with an introduction to key concepts like records, record types, accounts, contacts, leads, opportunities, and cases. It then explains how to navigate the CRM interface and enter, view, filter, and export data. The document also covers activities like notes, tasks, emails, and how to track customer communications history through activities. The goal is to help users understand the basic functionality and organization of data in Microsoft Dynamics CRM.
Marketers have more data available than ever but struggle to pull in together in a usable format. Customer Data Platforms promise to solve this problem by offering easy-to-deploy systems specializing in data unification and sharing. But can CDP really deliver on its promise? This workshop will equip you to understand the definition of a CDP, how CDPs differ from other systems, which features are shared by all CDPs and which are found in only some, the most important CDP use cases, how to select the right CDP, how to manage a successful deployment and where to look next for more information.
A case for crm team 11 - beacon hill version 1.1 pptRicardo Moraes
CRM is a business strategy focused on customer relationships that has grown in adoption from 53% in 2003 to 75% in 2010. It involves collecting customer data, integrating it into meaningful information, and using it across sales, marketing, and service to develop stronger customer relationships. Analysts predict 33% of CRM spending will be on hosted on-demand services by 2015.
The document provides an agenda for a two-day seminar on database marketing. Day 1 will cover re-evaluating marketing database systems, an overview of different database technologies, and best practices for database content and metrics reporting. Day 2 will discuss leveraging databases for reporting and applications, modeling and analytics, navigating large amounts of data, integrating digital media data, and ensuring political and business success for database projects. The seminar is aimed at helping database marketers enhance operations by learning about current trends, technologies, and best practices in database marketing.
Microsoft Dynamics CRM and ERP solutions can provide a return on investment within the first year through several key strategies:
1) Boosting sales by retaining customers, maximizing revenue opportunities, and streamlining sales processes.
2) Providing business intelligence through real-time visibility, aligning business units, and reporting/tracking capabilities.
3) Offering cloud hosting options that reduce costs while providing flexibility and choice in deployment.
4) Functioning as an all-in-one product that increases existing systems' potential through seamless integration.
5) Giving competitive advantages like improving customer service capabilities.
Master Data Management (MDM) for Mid-MarketVivek Mishra
This document discusses master data management (MDM) solutions for mid-sized businesses. It begins by introducing MDM and its benefits, such as a single source of truth and improved data quality. It then outlines some common challenges for implementing MDM in mid-sized companies, such as high costs, maintaining multiple data domains, and the need for organizational change management. The document provides advice on overcoming these challenges by selecting flexible and affordable MDM platforms. It also describes key properties of effective MDM, like ongoing data governance and providing a 360-degree view of customers. Finally, it introduces Compunnel Digital's partnership with Profisee to offer modernized MDM solutions tailored for mid-sized organizations.
Remodista RetailSource Paper - Sophisticated CRM StrategiesRemodista
Customer relationship management—the name should speak for itself. Right? Well, companies all too often take this critical piece in the retail puzzle for granted, equating it to the technical components that support it and reducing it to a database of point-of-sale information. However, CRM is no longer just a back-office repository for client information; it’s assuming its place at the very center of the sales picture as consumer expectations evolve. It’s the key to a comprehensive strategy of brand engagement, with the customer at its core.
The D.A. Company - sforce crm overview 5-5-11.1danarchetti
The document describes a proposed Account Information Management Solution (AIMS) using the Salesforce.com CRM platform. It notes that while the pet supplies industry has evolved, data collection and management methods have lagged behind. Spreadsheets, word documents and email lead to disorganized "data black holes". The solution proposes implementing a web-based CRM like Salesforce.com to centralized data in a single, secure location accessible anywhere. The target users are field sales teams, managers and customer service who could benefit from improved account profiling, activity tracking and reporting.
B2B CRM and supply chain management are strongly connected, as ERP systems have automated key business processes and linked different departments. ERP vendors have recognized the importance of tighter integration between operations and customer satisfaction, releasing CRM modules. Measurement of CRM performance in B2B was traditionally focused on supplier metrics like revenue, but there is a shift towards more relationship-oriented metrics that are meaningful to customers, such as the number of senior executives contacted. Adopting metrics and incentives valued by customers is necessary for the success of B2B CRM.
International Journal of Business and Management Invention (IJBMI)inventionjournals
The document summarizes customer relationship management (CRM) strategies used by Airtel and Zain in the telecommunications industry. It finds that:
1) Airtel divides its customer care cell into four departments to handle different customer segments. It also implements CRM through customer care executives and measures effectiveness through a third party.
2) Airtel designs special loyalty programs and incentives, especially for privileged customers. It has a complaint handling system and incorporates customer feedback.
3) Zain collects customer personal information through its website to perform data mining and convert data into useful business insights. It aims to improve capabilities to acquire and retain customers to increase market share.
Independent analysis by The Optera Group found that banks using Microsoft Dynamics CRM saw tangible benefits including improved marketing, operations, and risk management. Six banks profiled showed how Dynamics CRM helped optimize existing customer relationships, drive efficiency, and cut costs through real-time data visibility, automated processes, and enhanced customer experience. The flexible software integrated with legacy systems and supported growth through mergers.
This document discusses how Microsoft Dynamics CRM can help retail banks meet challenges around business agility, relationship banking, and improving the customer experience. It describes how CRM strategies and solutions can enable banks to measure customer value, explore opportunities to develop customer-centric business models, and improve back-office efficiency. The document outlines how Dynamics CRM provides a platform for business process management, return on investment tracking, service-oriented architecture, and a 360-degree view of customers.
Like all channels of marketing, channel and data integration are keys to success. The more complex of the two is in the data.
If you're immersing into the world of mobile or location based marketing, familiarize yourself with location data management (LDP). To start read SIM Partners white paper "The CMO's Guide to Location Data Management."
Making the Journey to Customer Marketing 3_BIOPatrick Spencer
The document discusses the evolution of customer marketing over three eras:
1) Customer Marketing 1.0 (1990s-2002) was a tactical, non-strategic role focused on order taking to support sales, PR, and AR. References were tracked via spreadsheets with no centralized system. Success was measured by lack of complaints.
2) Customer Marketing 2.0 (2004-2011) saw automation of reference management through web-based systems. Third party software-as-a-service providers emerged to replace in-house solutions. Larger organizations consolidated fragmented customer marketing teams.
3) Customer Marketing 3.0 (2012-present) is described as more strategic and data-driven. Advanced
This document discusses trends that will shape the future of customer relationship management (CRM) systems by the year 2020. It argues that CRM will be transformed by collaboration, mobility, user-centric design, cloud computing, and social media integration. CRM will shift from a focus on managing contacts and reporting to helping teams collaborate, sell, and grow through more effective and interactive systems that can be accessed anywhere through mobile devices.
This document provides an overview of master data management (MDM) and describes how the Kalido MDM solution addresses common MDM challenges. It discusses how master data is critical context for business processes and analytics but is often inconsistent across systems. The Kalido MDM solution enables businesses to consolidate, govern, and maintain master data through capabilities like managing all data domains, sophisticated data modeling, a master data authoring environment, life cycle management, data matching, hierarchy management, and embedded workflow to guide the data stewardship process.
The document summarizes the Upper Colorado River Endangered Fish Recovery Program, which was established in the 1970s to protect endangered fish species in the Colorado River basin. The program involves federal agencies, states, and interest groups working cooperatively to manage water flows and habitats. Key activities include securing water flows, developing fish habitats, stocking endangered fish, and managing nonnative species. The program has helped protect winter and spring flows in Reach 2 of the Green River to maintain channels and floodplains.
Este documento instruye a la persona a agregar 5 monografías relacionadas con la Web 2.0 o competencias informacionales a su cuenta de RefWorks y luego crear una bibliografía de la lista en un formato uniforme.
El autor quiere darle un regalo a alguien lleno de cariño para ser amigos y compartir experiencias, tanto buenas como malas, cuyos esfuerzos traerán aprendizaje, el regalo más hermoso que puede ofrecer.
This document provides information about the Greek island of Samos and the village of Marathokampos. It discusses the natural beauty of Samos through quotes from famous poets and includes pictures of landmarks in Marathokampos such as the local school, church, and wind farm. It also introduces 5th and 6th grade students from the Marathokampos Primary School who are participating in an international program to communicate with students abroad. In conclusion, it discusses the school's efforts to measure and reduce its ecological footprint as part of a nationwide initiative in Greek schools.
This document outlines the key objectives and timetable for a school's specialization program for years 6-8 in 2012. The objectives are to continue offering a diverse range of learning experiences, differentiate activities by year level, and introduce careers education for years 7-8. The timetable shows the rotations of different subject areas over the four terms, including robotics, languages, visual arts, food technology, careers, media studies, and performing arts. Variations in rotations are provided for each year level.
Ceip luis cernuda castilleja de la cuestaPepi Nikova
Castilleja de la Cuesta is a small town located 6km from Seville, Spain. It has a population of around 19,000 inhabitants who mostly work in the nearby city of Seville. The town is known as the place where Spanish conquistador Hernán Cortés died in 1547, though his remains were returned to Mexico. It is also known for a type of thin olive oil wafer called "Tortas de Aceite de Ines Rosales" that is exported internationally.
Learn three tools to improve E-mail marketing campaigns, increase conversions, and boost your marketing effectiveness. From our friends at BlueWolf and Oracle.
Identifying causes, business impact, and techniques to eliminate bad data fro...AkashSingh388720
determining the root reasons, the effects on the business, and the methods to remove erroneous data from CRM Frequently Used Busting Fail-Proof Ways to Hire A-Listers in Sales: 5 Common CRM Myths Recommendations from Us Where does innovation lead us with respect to retail redefined?
Unified Customer Views can help marketers organise, analyze and execute their one-on-one marketing and conversion strategies better. Plumb5, a path-breaking, real time, marketing platform helps them do just that. This write up, gives a glimpse into how the platform achieve this.
Scalable B2C lead generation is what we do. Every client we work with has different objectives. However, acquiring quality sales leads within affordable CPL’s and being able to accurately track conversions come as standard.
We have access to countless lead sources throughout the world and we know what works and doesn’t work!
At Progressive Sales we generate quality leads on a daily basis where numbers can be relied on each day. We are proud of the fact that the majority of agencies and brokers we work with refers to us as one of their preferred suppliers.
The document discusses the benefits of centralizing customer data into a single database. It notes that while customer data provides important insights, it is often scattered across different departments and systems, making it difficult to develop a comprehensive view. Centralizing data allows companies to better understand customers, target them across channels, and improve marketing efficiency. However, the database must be regularly maintained and enhanced with things like address updates to ensure the data remains accurate and useful over time.
The document discusses how centralizing customer data into a single database can provide numerous benefits for companies. It notes that currently customer data is often scattered across different departments and systems, making it hard to get a full view of customers. A centralized database allows companies to gain valuable insights into customers by combining all their information in one place. This makes it easier to better target customers, improve marketing efforts, identify new opportunities, and enhance customer service. The document also stresses the importance of regularly updating and enhancing the customer data to ensure its accuracy over time.
The document discusses how investing in data quality can provide a significant return on investment for companies. It outlines five tenets that leading companies embrace to realize this ROI from quality data: 1) view data quality as a business issue, not just an IT issue, 2) establish an explicit data governance strategy, especially at the point of data entry, 3) use a third-party data provider to consolidate and cleanse data, 4) address the challenge of maintaining accurate data given the rapid rate of data changes, and 5) strive for a 360-degree view of customers and suppliers across the organization.
An integrated CRM and ERP solution can provide many benefits to businesses by connecting disparate systems and departments. Some of the key challenges that businesses face with disconnected systems include inaccurate information as data is entered in multiple places, unnecessary paperwork as processes are stitched together manually, and inefficient processes when customer information is not centralized. However, with an integrated solution, businesses can transform the customer experience through faster issue resolution, market more effectively with targeted campaigns, and empower employees to be more productive by avoiding duplicate work.
Columbus is a listed IT services and consulting company with 2,000 employees serving customers worldwide. It helps ambitious companies transform, maximize and futureproof their business digitally, with expertise in retail, food, distribution and manufacturing industries. Columbus has over 28 years of experience helping more than 4,200 customers globally, and is headquartered in Denmark with offices worldwide.
Can you afford to let software append and clean the most crucial B2B informat...BizProspex
Data decay is a big challenge affecting millions of B2B businesses, can you afford to let software append and clean the most crucial part of your sales process - data.
Pipeline
Finding time to bring in a steady flow of new customers can be quite the challenge for a small
business sales team. This is often caused by issues such as:
•
Inability to route leads to the appropriate sales rep
•
Lack of information on potential clients
•
Inadequate knowledge about a prospect before calling
•
Poor visibility and forecasting of future pipeline.
A CRM app allows sales reps to store the data on prospects so the information’s ready at each
interaction. Plus, it quickly provides metrics related to visibility and forecasting.
5 WAYS TO CREATE AND MANAGE B2B DATABASE EFFECTIVELYtechnodatagroup
In today's business scenario, budgets are static while goals are increasing. As a B2B marketer with big growth goals, you need to focus on the markets that matter.
5 WAYS TO CREATE AND MANAGE B2B DATABASE EFFECTIVELYtechnodatagroup
In today's business scenario, budgets are static while goals are increasing. As a B2B marketer with big growth goals, you need to focus on the markets that matter.
This article offers works as a guide that will give you actionable steps and preferred business practices for B2B marketing professionals. Run the following practices in comparison to your old traditional methods and see the difference for yourself:
5 WAYS TO CREATE AND MANAGE B2B DATABASE EFFECTIVELYtechnodatagroup
In today's business scenario, budgets are static while goals are increasing. As a B2B marketer with big growth goals, you need to focus on the markets that matter.
This article offers works as a guide that will give you actionable steps and preferred business practices for B2B marketing professionals. Run the following practices in comparison to your old traditional methods and see the difference for yourself:
1) Businesses often outgrow spreadsheets as their key data management tool as the amount of data grows and becomes too complex to manage across multiple spreadsheets.
2) When data entry becomes a bottleneck, sales and marketing teams spend too much time manually inputting and sharing data across spreadsheets instead of more productive tasks.
3) Important business decisions are difficult when managers cannot access a full, real-time picture of key customer and sales information spread across various spreadsheets. Moving this information into a centralized CRM system allows for easier reporting and analysis.
Has your business outgrown spreadsheets eBookAustin Maguire
1) Businesses often outgrow spreadsheets as their key data management tool as the amount of data grows and becomes too complex to manage across multiple spreadsheets.
2) When data entry becomes a bottleneck, sales and marketing teams spend too much time manually inputting and sharing data across spreadsheets instead of more productive tasks.
3) Relying on spreadsheets makes it difficult for business managers to get an accurate, real-time view of key business data and metrics needed to make important decisions.
The document provides guidance on ensuring data quality in CRM and marketing automation solutions. It discusses the four main components of bad data: incorrect information, inaccurate information, missing information, and duplicate data. It then covers analyzing the state of one's database, cleaning data through standardization, duplicate removal, and completing missing data, and protecting data going forward through validation and prevention of duplicates entering the system. The goal is to have high quality, clean data to improve marketing and sales efforts.
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1. WHITE PAPER
DATA QUALITY: A SURVIVAL GUIDE
FOR MARKETING
Improving Your Customer Data for Marketing Effectiveness
CONTENTS EXECUTIVE SUMMARY
1 Executive Summary
Direct marketing is about communicating a message to a specific prospect
2 Typical Data Problems in a
Marketing Campaign or customer. The success of that communication, measured in terms of a
2 Duplicate Account Records qualified lead that generates a sale, depends on accurately identifying the
3 Incomplete Data prospect. Once you’ve identified the prospect, you need to contact and convince
3 The Wrong Data them your message is worth their time. There is nothing like misspelling
4 How Marketing Benefits from
their name, using the wrong title, mailing to an old address, or mailing multiple
Quality Data
5 But How Do I Find My Data copies to instantly lose credibility. But ensuring data quality can be a significant
Quality Problems? challenge if you have 500,000 or a million or 10 million prospect records in
7 Attacking the Data Quality Problem at your customer relationship management (CRM) system and you are trying to
the Source target the right prospect. The challenge becomes matching the target audience
9 Transactional Updates
of your upcoming marketing campaign to the records in your database. How
10 Operational Feeds
10 Purchased Data do you select the correct prospects? Data quality, data integration, and other
11 Legacy Migration functions of enterprise information management (EIM) are crucial to this endeavor.
11 Regular Maintenance
12 Mapping the Opportunities Demographics of the prospects are certainly key to mapping your CRM records
to Cleanse to the campaign selection, but have you applied the right demographic codes
14 Data Quality Functions in a Marketing to the right prospects? In past eras, when mass marketing was in vogue,
Environment it was standard practice to just mail out the 10 million marketing flyers and
16 Delivering Data Quality Functionality
hope for the best. In those days, marketing budgets were constructed to
16 On-Premise Software
17 Internal Hosting via Web Services support the printing and postage fees of massive mailing campaigns. Not so
17 On-Demand today, where marketing is compelled to be significantly more efficient and
18 Service Bureaus cost-effective at reaching the right customers.
19 Tying It All Together
19 About Business Objects Ultimately, even with the finest marketing organizations, the success of marketing
comes down to the data. Surrounding the data and storage application are
people, processes, standards, and technologies used to manage that data.
This white paper from Business Objects, an SAP company, focuses on these
concepts as they pertain to marketing, and particularly as they are supported
by data quality functions inside of the broader EIM framework.
Author: Frank Dravis, Six Factors Consulting
2. TYPICAL DATA PROBLEMS IN A
MARKETING CAMPAIGN
Perhaps you recognize or have suffered at the hands of some of these problems. We
list and discuss them briefly here to establish a common understanding of what we face.
One thing that becomes apparent is data quality problems exacerbate each other. For
example, if you have duplicate records, some of the duplicates will not be reconciled if
crucial data elements such as addresses are incorrect or not standardized.
DUPLICATE ACCOUNT RECORDS
Which record do you choose? I have often seen an 8:1 duplication ratio between
customer records. That is, for every one Ford Motor customer record that you
think is the master, you could have seven more records in the same file, as well
as others across your enterprise in disparate systems. How does this happen? In
many ways–and those of us who capture, create, and store customer data are still
inventing new ways.
Mergers and acquisitions (M&A) is certainly one large contributor to duplicate
records. I’ve seen it over and over where IT is saddled with merging two versions
of accounts payable, billing, shipping, fulfillment, order entry, and CRM systems,
and is either given too little time, has its original scheduled shortened, or lacks
adequate resources to merge the systems without creating duplicates. In truth,
even the best M&A integration projects still create some duplicate records, but
more often overburdened IT shops–in order to make their deadlines–are forced to
just merge two systems together and let operations clean up the mess after the
deadline has passed.
Account managers are another popular source of duplicate account records.
For myriad reasons, some of them illogical, when creating a customer record an
account manager sees an existing record that matches a customer’s, but ignores
it and creates a new record. Often this duplicate effort is driven by data control or
even compensation issues.
A third source for duplicate records–and there are more–is poor visibility and linkage
across systems. This happens in highly segmented enterprises where each business
unit, function, or department has its own customer data repository. In this case, if the
account manager for hoists and lifts wants to add new data to the existing derricks
and cranes customer record, they can’t because they don’t have access to it.
Business Objects. Data Quality: A Survival Guide For Marketing
3. INCOMPLETE DATA
Incomplete data–such as blank data fields–causes a variety of problems for the
marketer. First, and most obvious, when the address, email, or phone number field
is blank, your ability to deliver the message is impacted. Second, if a field such as
title, salutation, job code, or ethnicity is blank, your ability to segment prospects
into the correct categories or demographics is impacted. And third, if any of those
fields–and others like social security, account number, log-in ID, or account name–
are blank, your ability to identify similar or related records across systems, or even
within the same repository, is impacted–accentuating your duplicate record problem
because you needed those fields to match against to identify similarities.
THE WRONG DATA
Wrong data is simply that–the data is incorrect. There are a number of ways
that wrong data grows within your system. Age is one. People move (change
addresses), change phone numbers, change jobs, and so on. Over time, these
changes accumulate. Managers experienced with using data are often skeptical
of data that has not been updated for six months or a year or more because they
understand the compounding effect of data aging. System migrations are another
source of wrong data. Incorrect field mappings from source to target, or trying to
merge a larger field into a shorter field, can result in cryptic abbreviations that are
understandable only to the person doing the migration and are easily misinterpreted
by the end user. And then, of course, poor data capture procedures may allow the
placement of the third phone number for an office in the second email address
field. To the account manager who recorded the data and manages the account
today, everything is understandable and known, but for the account manager who
takes over tomorrow, nothing is known and these data shortcuts become problems.
A more insidious form of wrong data is fraud, where the supplier of information
purposefully enters the wrong data to mislead the business–for example, when a
terminated customer with a delinquent mobile phone account opens a new account
by supplying fictitious information.
Business Objects. Data Quality: A Survival Guide For Marketing
4. HOW MARKETING BENEFITS FROM
QUALITY DATA
Data quality is crucial to knowing who your customers are and reaching them in an
effective manner. In order for marketing efforts to gain the greatest benefits, a clear
and single view of the customer is necessary. Without this view, contacts are made
with the wrong prospects and the right prospects either are missed or have multiple
touches that are confusing and costly. A goal of marketing is to cross-sell and up-sell
existing customer accounts, which is not achievable if the multiple accounts for the
same customer are not matched and consolidated into a single view. This is where
data quality plays a direct role in delivering value through marketing efforts.
Usually, the way an organization first experiences the need for data quality and
other EIM capabilities is when they build a CRM or customer data integration (CDI)
system, and find that the data they’ve loaded into the system is far less than expectations.
Throughout this paper, we use CRM as the surrogate for marketing data repositories
in general. Somewhere, somehow, customer and prospect data must be stored
and accessed, and CRM/CDI systems, whether homegrown or vendor-supplied,
are the common repositories for this data.
Business Objects. Data Quality: A Survival Guide For Marketing
5. BUT HOW DO I FIND MY DATA
QUALITY PROBLEMS?
Your position within the marketing organization determines your visibility into the
data and the perceptions of the quality of that data. The higher in the organization,
the more removed a manager is from the data that drives their operations. A chief
marketing officer (CMO), for example, may be the person to ask the question, “How
do I know my data is defective?” The field-marketing specialist is most likely to
wonder, “I know the types of problems, I need the counts.” Fortunately, no matter
who is asking, the solution to both situations and other data integrity questions
is the same: Conduct a data quality assessment. Without the findings from an
assessment, you’ll have a number of issues to deal with:
• You won’t know the scope and depth of your problems. For example, are they
systemic or superficial?
• You won’t know the cause of the defects. Without knowing the types of problems,
you can’t track back in the process to isolate the source.
• You won’t know how effective the resulting cleansing operation was.
• The cleansing operation may very well miss whole categories of problems.
• You won’t be able to report on progress because no baseline was established.
That means no ROI calculation for the cleansing.
• You won’t be able to conduct trend analysis over time to see how your data is
regressing or progressing.
Many data quality problems are processed-based. That is, the problems result from
non-standard practices, no validation of data entry procedures, or just faulty
application design. The results of a data quality assessment often uncover process
issues as you work through the cause and effect. The assessment exposes the
effect, and it’s a relatively simple matter for the marketing manager to backtrack
through the data distribution chain to, for example, the account management system
and verify field edits are being used or enforced.
A data quality assessment is something marketing managers can do themselves,
especially if they have an assessment tool suitable for business users. Another
alternative is for the marketing manager to engage IT to conduct the assessment,
or even contract with a third-party information management-consulting firm.
Regardless, there is little mystery to conducting a data quality assessment. The
hardest part belongs with the business–that is, marketing–to articulate the business
rules that define good or bad. What are the rules that govern a specific field, such
as product name? For example, is it a mandatory field, can the field have abbreviations,
is there a maximum length, are special characters allowed, how many generations
Business Objects. Data Quality: A Survival Guide For Marketing
6. of products are allowed to be listed, and what is the relationship with the other fields,
such as SKU code? At the very least, these rules rest in the minds of the marketing
specialists, also known as subject matter experts (SMEs). SMEs need to compose
the rules, agree on them, and then load them into whatever tool is used, be it a commercial
profiling tool or custom SQL code that is used to explore the data.
Probably the most important part of an assessment, other than the initial rules
gathering, is the reporting of the findings. Graphical or tabular reports are crucial
to delivering and communicating the impact of the defects. Once armed with this
information, marketing management can now make an informed decision as to what
fields of what dimensions or tables need to be cleansed. There is no need to “boil
the ocean,” that is, cleanse every field of every table. At any given time, certain fields
of specific tables will be of primary concern, and those are the fields that should
be first assessed and then cleansed, because they are the ones that will deliver the
greatest value the soonest.
Business Objects. Data Quality: A Survival Guide For Marketing
7. ATTACKING THE DATA QUALITY
PROBLEM AT THE SOURCE
The best place for direct marketers to cleanse their data is as close to the point of
creation as possible. Consider if you will an information supply chain where at the
very beginning the data is captured from the prospect, perhaps at a trade show or
from a Web site registration form. See Figure 1.
The farther upstream you start cleansing, the earlier the ROI counter starts ticking
Total Benefit
Data Quality Investment $1,000 $500 $300 $300 $200
Point of Creation,Start of Web Site ODS
Call CRM/ Mailing
Information Value Chain Center CDI List
Information Supply Chain
Figure 1: Information Supply Chain Data Quality ROI
Captured data is propagated through numerous data repositories, processes,
and is perhaps even sold and purchased, then merged into a data warehouse
where it is ultimately loaded into the CRM system from which the direct marketing
campaign will be driven. This long chain of processes and migrations is an information
supply chain. It should be the goal of the marketer to work with the IT department
to institute cleansing functions in this supply chain as close to the point of creation
as possible. The reason is the further upstream the data is validated, cleansed, and
consolidated, the greater the number of downstream marketing and other operations
benefit, and the fewer problems defective data will cause.
If we examine the information supply chain graphic in Figure 1, we see a declining
level of data quality investment the further into the supply chain you progress. The
reason is that upfront and early data cleansing benefits all downstream operations,
and makes subsequent cleansing easier and less complicated. At the Web site,
for example, a hypothetical $1,000 is spent on cleansing a set of records (in this
case, ensuring the fields are correctly filled in, ZIP Codes are correct, as are the
street address and city/state names). The benefit at that point in the supply chain
Business Objects. Data Quality: A Survival Guide For Marketing
8. is to the Web site order entry process. However, as the data is propagated beyond
order entry, other functions (such as the operational data store or ODS) that use
the data immediately benefit from the previous data quality work. Managers of
the ODS still need to do their own cleansing, such as checking field formatting,
matching the data to existing records, or consolidating like records, but they don’t
have to do as much if they were starting from scratch, and the complexity of issues
are less. This cascading data quality (DQ) benefit works its way through the entire
supply chain and all the branches that derive value from the data. The benefit of
that initial $1,000 is magnified at each link in the chain until at the very end where
the mailroom sending out the promotional piece need only adjust the data, such as
applying the right salutation and selecting the applicable address before mailing
the piece.
Another reason to manage data quality at the point of creation is it is much easier to
validate data and ask the contributor to confirm details as they provide them, rather
than months or years later when you actually want to use the data. The picture below
(Figure 2) shows an example of how Adobe Systems has implemented real-time data
cleansing at the point of capture in its Web order entry process to both automatically
validate the data and then to ask the customer which address they prefer.
Figure 2: Real-Time Data Cleansing Within Adobe’s Web Order-Entry Process
Business Objects. Data Quality: A Survival Guide For Marketing
9. However, we understand that the marketer is often the inheritor of data and may not
have the opportunity to institute a function to cleanse the data as soon as it is captured.
After all, the information supply chain can extend many steps and even years from
where the data was originally created. Because of this, marketing managers must
be prepared to improve data quality anywhere in their process that they have the
availability. In general, there are five common opportunities to cleanse data that will
occur in information management processes. They are as follows:
• Transactional updates–often at the point of creation
• Operational feeds–upstream and before the data enters your system
• Purchased data–if you’re buying it, demand that it is clean
• Legacy migration–data is in the enterprise, but not in your system yet
• Regular maintenance–as your data ages, you need to cleanse it
We discuss each in these next sections.
TRANSACTIONAL UPDATES
This opportunity fits well with organizations that take a proactive approach to data
cleansing. Organizations can identify the entry points of information into the
organization–in this case, during transactions, such as a new customer login or
order entry–and where exposure to flawed data may occur. When a transaction is
processed, organizations have an opening to validate the data before it is saved to an
operational system. Transactional updating also affords the chance to validate data
as it arrives in its information packet rich with contextual information. Since this
contextual setting is lost as soon as the data is sent down stream, it is therefore
important to leverage it.
By their very nature, transaction updates force organizations to handle individual
information packets as they become available, which implies real-time processing,
low volumes, and a potentially wide distribution of implementation. In other words,
the cleansing functionality must be connected to or embedded in the transactional
environment and be able to respond in milliseconds, and also be able to service
multiple transactional applications.
Business Objects. Data Quality: A Survival Guide For Marketing
10. OPERATIONAL FEEDS
The second opportunity to cleanse and consolidate data is during operational feeds.
These are regular weekly, nightly, hourly, or even sub-hourly updates supplied from
distributed sites to a central data store. A nightly upload from a subsidiary’s CRM
system to the corporate data warehouse is just one example. Regular operational
feeds allow an organization to implement batch-oriented data quality functions in the
path of the data stream, and volumes can be from the few thousands of changed
records, as in change data capture, or can be in the millions, even hundreds of millions.
Operational cleansing utilizes a predefined cleansing job or project selected from
a library of potentially hundreds of jobs. The appropriate job is usually triggered
or scheduled to run automatically on a specific data flow (flat file, database table,
input stream, and so forth) with an established mapping to the data model of the
input stream.
PURCHASED DATA
The third opportunity to cleanse is when you purchase data from a third party. Many
organizations erroneously assume data to be clean when purchased. Not so. Buying
third-party data is in many ways like buying a used car. Do you really know what the
previous owner has done to it? Of course not, that’s why you take the car to your
mechanic to have him pop the hood and put it on the hoist. You should do the same
thing with purchased data; otherwise, you are essentially abdicating your data quality
standards to those of the vendor.
In the case of a purchased list for a marketing campaign, you can ask for a random
sample from the prospect list and conduct your own data quality assessment.
Rudimentary tests for field completion and validation are simple to run. Validating
purchased data extends to matching the purchased data against your current data
set. The merging of two clean data sets is the equivalent of pouring a gallon of red
paint into blue. A merge will not equate to 1+1 = 2, but is more like 1.5. The reason
being duplication between data sets, and the duplication may not be easily recon-
ciled. Two records may appear the same, but one record might have a crucial field
that is different. The merged data sets must be matched and consolidated as one
new, entirely different set to ensure continuity. A hidden danger with purchased data
is it occurs as an ad hoc event, which means no regular process (a cleansing job
with business rules) exists to incorporate the data into an existing system. The lack
of regularly occurring processes raises the specter that in the rush to get the file
loaded, “expedient” shortcuts may be taken.
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11. LEGACY MIGRATION
The fourth opportunity to improve the quality of data is during legacy migration.
Any time data from an existing system is exported to a new system, the data must
be robustly checked and validated. A common problem to look for is legacy fields
plagued with overuse, such as the contract type field used by a leasing firm. Over
the years the definition of “contract type” had changed and fallen out of favor. Yet
sometimes it held important data such as the previous lease duration–important
data to migrate, but obscured in an antiquated data model. Another problem was
uncovered when a manufacturing company during a data quality assessment discovered it
had three types of addresses (site location, billing address, and corporate headquarters)
but only one address record per account. In order to capture all three addresses,
the CRM analysts were duplicating account records. What they needed to do was
extend their data model to hold three separate address records for each account,
which impacted the data model of the new system being built. Had it not assessed
its data beforehand, the manufacturer would not have discovered this problem until
after the initial migration.
In resolving legacy migrations, an interesting relationship appears between data
modeling and data quality. As the previous examples show, you can’t have good
data quality with a deficient data model, and you can have a good data model with
bad data quality. They are like the yin and the yang of data management. The two
are inseparable.
When conducting a legacy migration, the data quality job takes on the form of an
operational data cleanse project except the project is usually run just once. The
same amount of initial thought is dedicated to mapping the source to target fields
and defining the rules governing those target data elements. Test runs can be conducted
to see how well the job conforms to the desired output.
REGULAR MAINTENANCE
The fifth opportunity is during regular maintenance. Even if an organization starts
with perfect data today, tomorrow it will be flawed. Data ages–and ages more quickly
that most expect. For example, 17% of U.S. households move each year, and in some
years, as many as 60% of phone records change in some way. Moreover, every day
people get married, divorced, have children, have birthdays, get new jobs, get promoted,
and change titles. And if that wasn’t enough, the companies we work for start up, go
bankrupt, merge, acquire, rename, and spin-off. To account for this irrevocable
aging process, organizations must implement regular data cleansing and consolidation
processes, be they nightly, weekly or monthly. The longer the interval between
regular data quality activities, the lower the overall value of your data.
Business Objects. Data Quality: A Survival Guide For Marketing 11
12. Of the five opportunities to cleanse data, regular maintenance is perhaps the easiest
and most important to perform. It’s easier in that there are no real time constraints
as in transactional processing. The data is in a single place, the host repository, and
it’s staying there–that is, it’s not being moved at the time of cleansing, and you have
schedule flexibility. Data such as prices can be checked and updated in place.
What makes maintenance the most important of the five is that you know the data
will age, and hence defects will grow. Also, consider that there are numerous connections
to the data repository and any number of them can be supplying defective data. A
regular maintenance process is your insurance, your backstop if you will, that any
defect data that leaks into the system will be caught in the next maintenance sweep.
MAPPING THE OPPORTUNITIES TO CLEANSE
In the following diagram, a typical lead-generation process is used to map each of
the five cleansing opportunities and highlight how they relate to each other. Most
occur multiple times, as they will in any marketing operation. Each of the opportunities
sits astride a data flow where the data moves from one function or repository to
another. We call them opportunities because in order to move the data, a software
program, IT process, marketing task, or all three must occur, and within that action
a data quality function can be readily inserted. These are opportunities. What
immediately becomes obvious is in this relatively simple lead-generation operation
there are numerous locations to invoke a DQ process. These locations offer
substantial flexibility to marketing managers when planning their data integrity
strategy. Depending on span of control (who owns what tasks or data stores),
budget, availability of resources, and time frame, the marketing manager can choose
to implement DQ checks in all possible locations or just one and plan to build from
there. The manager’s IT department will be crucial in guiding the strategy and even
implementing the final plan. IT will be able to provide feedback, for example, on the
complexity of implementing DQ maintenance procedures in a CRM system, and
how long it would take to prepare for the legacy migration of data from the obsolete
call center that is being replaced by the CRM system.
Business Objects. Data Quality: A Survival Guide For Marketing 1
13. Data Flows
Maintenance
Obsolete,
Home-grown Legacy CRM System
Call Center Migration
Purchased Operational Transactional Operational Transactional
Lists Feeds Updates Feeds Updates
List of Raw Contact Qualified Sales Active
Attendees Leads Prospect Prospect Prospect
Records Lists Records
Records
Trade Collect Store Qualify Distribute Engage
Show Leads Leads Leads Leads Prospects
Lead Generation Work Flow
Figure 3: Lead Generation Workflow
Business Objects. Data Quality: A Survival Guide For Marketing 1
14. DATA QUALITY FUNCTIONS IN A
MARKETING ENVIRONMENT
There are nine data quality functions marketers call upon to cleanse their data. As
shown below and depicted in Figure 4, in order of their occurrence in a data quality
project, those functions are:
1. Measure
2. Analyze
3. Identify (Parse)
4. Standardize
5. Correct
6. Enhance
7. Match
8. Consolidate
9. Monitor
Figure 4: Nine Functions of Data Quality
Business Objects. Data Quality: A Survival Guide For Marketing 1
15. These functions will usually be conducted in this order because they support each other.
For example, to standardize the elements of a customer record, those elements–such
as title, salutation, or phone number–need to be identified or parsed out from the contact
data. Many marketing campaigns will receive data that comes straight from a mainframe
in a multiline record with no fielding, as in the following example:
Tom Jones
Director of Cybernetics, Formalux
Acetera Corporation, Formalux Divson
1900 Corporate Way N
Cincinatti, OH, 58999
For the record to be useful, it needs its various components identified and standardized–
as in changing corporation to corp and correcting divson to division. It then must
match and consolidate with the other records pulled from the source systems.
Measuring and analysis kick off the process by providing metadata as to the level
and types of defects found in the source data, so subsequent cleansing operations
can be tailored for the greatest effect.
The first six functions–including enhancement where additional data is appended
like demographic or geo codes–improve data to the point where it can be matched
and consolidated. Matching and consolidation is where a tremendous amount of value
is delivered to marketing in that duplicate records are eliminated, best of records
are built, and the manager now has a single view of each prospect or customer
within the context of the applied source data. Now able to build a corporate or
retail household for target marketing, the marketing manager can identify the top
20% of the customer base or form demographic groups for segmentation in the
next campaign.
Last, monitoring uses the business rules and definitions created in the measure and
analyze phases to create an automated profiling project that provides managers with
defect information (metadata) at any time, so they can make decisions as to whether
the data is good enough to use or needs to be improved for the next operation.
Business Objects. Data Quality: A Survival Guide For Marketing 1
16. DELIVERING DATA QUALITY
FUNCTIONALITY
Once the marketing manager has determined the nature and scope of data problems
and has determined the data quality functionality needed, there are a number of
options available for connecting the functionality to the data. In broad terms, those
options are:
• On-premise software
• Internal hosting via Web services
• On-demand (for example, Software as a Service (SaaS))
• Service bureaus
These options range from having the greatest control and largest footprint (on-premise
software) to least control and no footprint (service bureau). From a cost basis one
might suspect that on-premise software would be the most expensive. However, the
cost of maintaining a level of data quality is not limited to the initial expenditure.
Consider that the data and its usage will extend as far into the future as the organization
remains in existence. Maintenance fees, per record charges (otherwise known as
click charges), or subscription fees over time will exceed initial software license
fees. What becomes important when calculating the cost of data quality processing
is the breadth and depth of functionality needed and the volume of records processed
each month.
ON-PREMISE SOFTWARE
Next to service bureaus, on-premise software is the oldest form of data quality delivery
mechanism. Early data quality software vendors such as Postalsoft began selling
and distributing on-premise data quality software in the mid 1980s. On-premise
software is simply that: a software application—either commercial or hand-coded—
that resides in your facility and is run by IT or the marketing staff. Sometimes the
software is run by third-party consulting or contracting agencies and can be operated
locally or remotely via a virtual private network (VPN) or Internet connection. The
advantages of on-premise software are you control the application, the parameter
settings, the computing environment, processing schedule, and so on. The disadvantage
is that your organization is responsible for all of the above. You need to have the
system resources, personnel, and training to run the software. For most firms, however,
the advantages far outweigh the disadvantages. Basically, if a firm has grown to the
size where it has any sort of customer data management system and an IT staff to
match, it usually has the capabilities to host and run data quality software internally.
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17. INTERNAL HOSTING VIA WEB SERVICES
Internal hosting of data quality functionality was made possible by the advent of
Web services. Today, most commercial data quality software packages support
Web services to some level. With Web services, a corporate IT group can install
a centralized data quality server, such as Business Objects Data Services, and
publish the data quality functionality to departments and business units within
the enterprise. IT does not need to install its own software. The elegance of this
approach is that the marketing department, for example, can see and leverage the
customer processing rules and jobs established by the sales operations department.
This business rules reuse dramatically cuts project development time and allows
corporate data governance to create data standards and common definitions to be
applied across the enterprise. The advantages and disadvantages of internal hosting
are the same as on-premise software with the exception that the advantages are
magnified by each department or operation that connects to the service. Each new
connection and project leverages the single installation, thus keeping IT complexity
and maintenance burdens to a minimum. Moreover, when demand begins to exceed IT
capacity, rather than having to add another server or deployment, IT can increase the
size of the existing server, thus keeping the installation footprint to one deployment.
ON-DEMAND
On-demand software is the newer form of what previously was known as an application
service provider, or ASP. With on-demand software, the marketing manager contracts
with a third–party service provider and accesses the contracted software via the
Internet. The advantage of on-demand is the service provider bears the complete
burden of installing, running, and maintaining the software at its own facilities. The
disadvantage is the user must trust the provider to safeguard any data that is
stored at the provider’s facility, and functionality offered by the provider may be
limited when compared to on-premise software. With Internet reliability constantly
improving, access to contract software is rarely a problem, and almost always the
user interface is Web-enabled and therefore accessible via an Internet browser. A
downside of on-demand for data quality processing is the customer’s data must be
uploaded to the service and then returned after cleansed. This round-tripping of data
adds latency to processing times. However, if the marketing manager is not inter-
ested in real-time processing, the added latency may be of little concern.
On-demand actually allows the marketing manager the option of creating a hybrid
solution. Look at address cleansing as an example. A firm may have 5 million
customer and prospect records, 80% of which have U.S. addresses, 15% have
European addresses, and the remaining 5% have Japanese addresses. At the
volumes and frequency of processing the firm averages per month, in addition to
Business Objects. Data Quality: A Survival Guide For Marketing 1
18. the complexity of cleansing, the marketing manager, with guidance from IT, may
determine it is more practical to process the records for both the United States
and Europe in house. But the additional cost of adding Japanese processing given
the fewer number of records and the fewer number of campaigns run against those
records dissuades the marketing manager from purchasing that capability for that
region. On-demand allows managers to contract out their Japanese records and
process the data when they need to. These types of hybrid solutions are expected
to increase in frequency as globalization continues to expand and more and more
customers come from outside of the firm’s nation of origin.
SERVICE BUREAUS
Service bureau processing is yet one step further removed from when compared to
on-demand. With a service bureau a complete project including data file, processing
rules and delivery instructions is sent to a third party agency that processes the job
in batch with relatively little interaction with the customer. The advantage of a service
bureau is the marketing manager or their IT counterpart need not run any software,
either on-premise or on-demand. Once the initial effort is taken to establish the
contract and job requirements, the hard work is done. The files are delivered to the
service bureau and the customer awaits either their return or, in the case of a direct
mail/email campaign, the marketing pieces are sent to the prospects. The disadvantage
of using a service bureau is the client must trust the bureau to follow all the requirements
and perform the proper cleansing, and the work performed is largely on the service
bureau’s schedule. There are ways, of course, to validate that the bureau has complied
with all the requirements, and when negotiating the contract the customer can set
the desired delivery date of the finished product.
Business Objects. Data Quality: A Survival Guide For Marketing 1
19. TYING IT ALL TOGETHER
In the grand scheme of things, marketing managers have numerous options for ensuring
and uplifting the quality of their data. EIM provides a framework for deploying those
options together in one streamlined process flow. The EIM framework contains everything
from data integration–extract, transform, and load (ETL) or enterprise information
integration (EII)–through metadata management, data quality, and building specialized
reporting marts. Data integration applications are a primary deployment mechanism for
data quality functionality, which makes it convenient to cleanse data when it is being
moved into or out of your CRM/CDI system.
Today’s data quality vendors have built rich and deep functionality that can
remediate almost any customer data problem, and they’ve structured their deployment
mechanisms to give you the greatest flexibility in deciding when, where, and how
to cleanse data. On-premise, internal hosting, on-demand, service bureaus, or any
combination thereof are the options that can be tailored to infrastructure and
marketing needs. With the latitude of options available, there is really no reason
why suboptimal data should be used to deliver suboptimal results in your marketing
efforts, whether you’re identifying cross-sell opportunities or distributing leads to
the appropriate sales person. The question for marketing managers becomes: Why
marginalize your marketing efforts when better results lie in improving your data?
ABOUT BUSINESS OBJECTS
As an independent business unit within SAP, Business Objects transforms the way
the world works by connecting people, information, and businesses. Together with
one of the industry’s strongest and most diverse partner networks, the company
delivers business performance optimization to customers worldwide across all
major industries, including financial services, retail, consumer-packaged goods,
healthcare, and public sector. With open, heterogeneous applications in the areas
of governance, risk, and compliance; enterprise performance management; and
business intelligence; and through global consulting and education services,
Business Objects enables organizations of all sizes around the globe to close the
loop between business strategy and execution.
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