| 1. |
The Bottom Line on Bad Customer Data by Baseline Consulting
Abstract : You can blame your sales people all you want, but if the lead data is bad, they’re not going to bring in business. You can blame your product managers for ineffective promotions, but if the target lists are redundant, the pitches fall on deaf ears. You can blame your customer service representatives for low satisfaction scores, but if customer data is missing, then no wonder the complaint resolution pipeline is backed up. Think it’s your customer resource management (CRM) system? Think again. It’s bad data, and it’s costing you millions. Request your copy of The Bottom Line on Bad Customer Data that delivers detailed advice from Jill Dyche, partner and co-founder of Baseline Consulting, about what you can do to address the impact of bad data on your company. The report gives you insight into how bad data is impacting your company and what you can do about it. How to identify where the bad data is and quantify its impact, and different approaches to determine the sources and causes of bad data are all offered in this paper.
Type: White Paper
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| 2. |
A Definition of Data Warehousing (6 Pages)
by M. Reed
Aug 18, 2002
Abstract : There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
Type: Article
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| 3. |
A Definition of Data Warehousing (6 Pages)
by M. Reed
Aug 24, 2000
Abstract : There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.
Type: Article
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| 4. |
Data Quality: Cost or Profit? (4 Pages)
by Kevin Ramesan
Mar 8, 2004
Abstract : Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy. Looking beyond general approaches and company policies that set expectations and establish data management procedures, we will explore applications and tools that help reduce the negative impact of poor data quality. Some CRM application providers like Interface Software have definitely taken data quality seriously and are contributing to solving some data quality issues.
Type: Article
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| 5. |
More Data is Going to the Cleaners (3 Pages)
by M. Reed
Dec 1, 1999
Abstract : WESTBORO, Mass., November 29, 1999 - Ardent Software, Inc. (Nasdaq: ARDT) today announced a strategic partnership with Firstlogic, Inc., the developer of i.d.Centric data quality software that helps companies cleanse and consolidate data in database marketing, data warehousing, and e-business applications. Under the partnership agreement Firstlogic will develop and support a link between its customer data quality tools and Ardent's DataStage Suite.
Type: Article
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| 6. |
Business Basics: Unscrubbed Data Is Poisonous Data (4 Pages)
by J. Dowling
Nov 26, 2003
Abstract : Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data quality is low, and the short- and long-term benefits are great.
Type: Article
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| 7. |
Business Basics: Unscrubbed Data Is Poisonous Data (4 Pages)
by J. Dowling
Jun 13, 2001
Abstract : Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data quality is low, and the short- and long-term benefits are great.
Type: Article
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| 8. |
Data Mining: The Brains Behind eCRM (6 Pages)
by Steve McVey
Nov 6, 2000
Abstract : Data mining has emerged from obscure beginnings in artificial intelligence to become a viable and increasingly popular tool for putting data to work. Data mining is a set of techniques for automating the exploration of data and uncovering hidden truths.
Type: Article
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| 9. |
A CRM System Needs A Data Strategy (7 Pages)
by David McNamara
Jul 3, 2003
Abstract : A customer relationship management (CRM) system is inherently valuable for supporting customer acquisition and retention by gathering data from each contact with customers and prospects. Collecting data, however, cannot be isolated from a strategy for actually using that data. Here is an overview of how to evolve the focus of a data strategy to specifically suit both the acquisition and retention phases.
Type: Article
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