• Setting Your Sights on Data Intelligence

  A navigation guide to improving data-driven decision-making in the cloud.

• Six Strategic Steps to Democratizing Data

  A Chief Data Officer’s checklist for enabling data-driven decisions

• TDWI Checklist Report | Optimizing Data Quality for Big Data

  Checklist report on data quality for big data

• Ten Data Quality Dividends

  How data quality drives business value across the entire enterprise

• The Business Case for Contact Data Verification

  How clean, accurate, dependable customer contact data pays dividends for customer experience.

• The Contact Data Enrichment Checklist

  It takes accurate contact data to deliver the best customer experiences. It’s why the most effective marketers make sure their contact data is verified and enriched. In this checklist, we’ll show you how to do that in three simple steps.

• The Contact Data Enrichment Primer for Marketers

  How marketers can use contact data verification and enrichment

• The Cost of Bad Contact Data: A Workbook to Define and Present the Business Case for Contact Data Verification

  Trusted contact data is a game-changer for organizations trying to improve their customer experiences. The Cost of Bad Contact Data workbook is full of facts, stats, and practical exercises to help you build the business case for a more intelligent approach to handling your customer data: contact data verification.

• The Data Governance Program Workbook

  A practical resource for pivotal data leaders

• The Four Big-Time Benefits of Building a Data Marketplace

  Key Considerations for CDOs Who Want to Deliver Organizational Value

• The Salesforce Manager’s Guide to Verifying Customer Data

  A step-by-step guide to the quick and easy way to make your Salesforce contact data more reliable—without leaving Salesforce.

• Three Ways to Measure Address Quality

  What you can do to manage your address data and ensure data quality

• Turn GDPR into an opportunity

  Become more agile, transparent, and customer-centric.

• Address Validation: Best Practices for Interpreting and Analyzing Address Data Quality Results

  Inaccurate addresses can be a costly problem for your organization and not just because they prevent prompt, accurate delivery of mailed communications. Correcting them manually involves significant time and expense while still leaving room for human error. This white paper offers best practices for interpreting and analyzing the results generated by Informatica AddressDoctor, which uses reference data from reputable sources to evaluate the accuracy and deliverability of physical postal addresses.

• A Road Map to Successful Customer Centricity in Financial Services

  This paper discusses three key areas of focus for delivering the right data to enable customer centricity in financial services: Master data management for authoritative customer information; data quality for trusted and accurate business information; and cross-channel data integration for service consistency.

• Surprising Tactics B2B Marketers Can Learn from B2C Marketing

  Dig deep into the B2C experience to learn what you could apply to your B2B strategies with this white paper from the experts at Informatica.

• Using SMS for Marketing: A Beginner’s Resource

  Use this buyer’s guide to learn about one of the simplest forms of communication and how businesses are using it to interact with customers. This innovative tool is the text message, or SMS messaging.

• Great Data – The Key to Building and Sustaining Customer Relationships

  In an ideal world, marketers would leverage their data to identify, segment, and target customers and prospects when and where they are most likely to respond, and with the best possible messaging to drive engagement, response, and sales conversations. Marketers don’t live in that ideal world. Garter finds that 82% of CMOs don’t feel prepared to deal with large sets of data. How can data enrichment help marketers get to that ideal world/overcome these challenges? See how to put data to work for you, the key challenges you need to understand, and how to solve these challenges with a strategy that combines data infrastructure and the content of your data itself.