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Download the PDF: https://www.demandmetric.com/content/data-enhancement Marketing has changed radically in the past two decades. Instead of blasting messages to anonymous consumers of mass media, marketers increasingly manage direct interactions with known individuals. This change presents a huge opportunity to improve the effectiveness of marketing messages by tailoring each message to the person who will receive it. But it also means that marketers who fail to accurately target their communications increasingly risk being ignored by consumers who react only to relevant content. Simply put, individualized customer treatments are quickly changing from competitive advantage to baseline requirement. Marketers no longer have a choice about whether to do them, although they still control how well they are done. The foundation of effective targeting is customer data. Data drives the rules that determine who gets what treatment at what time. Other resources are also needed, including analytics to understand the data and execution systems capable of managing the interactions. But without adequate data, these other resources are like an actor without a script: they may look great, but they don’t know what to say. Most customer data is generated within the company itself, including contact information, response history, purchases, and customer service interactions. However, other important information exists outside the company. This includes personal or business details that the customer has not provided directly, as well as behaviors such as social media comments or visits to other companies’ Web sites. This information provides insights used to target communications based on each customer’s long-term needs and immediate interests. External data is most helpful for prospects and new customers, who have generated little or no data within company systems. This guide describes the kinds of external data available to marketers, how they can acquire this data, and how they can put it to best use. It will help you to improve the effectiveness of your marketing programs by expanding the base of information available for segmentation, targeting, and analysis. Let’s get started.
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Data Enhancement DATA ENHANCEMENT HOW-TO GUIDE
2 Data Enhancement How-to Guide Marketing has changed radically in the past two decades. Instead of blasting messages to anonymous consumers of mass media, marketers increasingly manage direct interactions with known individuals. This change presents a huge opportunity to improve the effectiveness of marketing messages by tailoring each message to the person who will receive it. But it also means that marketers who fail to accurately target their communications increasingly risk being ignored by consumers who react only to relevant content. Simply put, individualized customer treatments are quickly changing from competitive advantage to baseline requirement. Marketers no longer have a choice about whether to do them, although they still control how well they are done. The foundation of effective targeting is customer data. Data drives the rules that determine who gets what treatment at what time. Other resources are also needed, including analytics to under- stand the data and execution systems capable of managing the interactions. But without adequate data, these other resources are like an actor without a script: they may look great, but they don’t know what to say. Most customer data is generated within the company itself, including contact information, response history, purchases, and customer service interactions. However, other important infor- mation exists outside the company. This includes personal or business details that the customer has not provided directly, as well as behaviors such as social media comments or visits to other companies’ Web sites. This information provides insights used to target communications based on each customer’s long-term needs and immediate interests. External data is most helpful for prospects and new customers, who have generated little or no data within company systems. This guide describes the kinds of external data available to marketers, how they can acquire this data, and how they can put it to best use. It will help you to improve the effectiveness of your marketing programs by expanding the base of information available for segmentation, targeting, and analysis. Let’s get started. HOW-TO GUIDE Data Enhancement 2 Data Enhancement How-to Guide Marketing has changed radically in the past two decades. Instead of blasting messages to anonymous consumers of mass media, marketers increasingly manage direct interactions with known individuals. This change presents a huge opportunity to improve the effectiveness of marketing messages by tailoring each message to the person who will receive it. But it also means that marketers who fail to accurately target their communications increasingly risk being ignored by consumers who react only to relevant content. Simply put, individualized customer treatments are quickly changing from competitive advantage to baseline requirement. Marketers no longer have a choice about whether to do them, although they still control how well they are done. The foundation of effective targeting is customer data. Data drives the rules that determine who gets what treatment at what time. Other resources are also needed, including analytics to under- stand the data and execution systems capable of managing the interactions. But without adequate data, these other resources are like an actor without a script: they may look great, but they don’t know what to say. Most customer data is generated within the company itself, including contact information, response history, purchases, and customer service interactions. However, other important infor- mation exists outside the company. This includes personal or business details that the customer has not provided directly, as well as behaviors such as social media comments or visits to other companies’ Web sites. This information provides insights used to target communications based on each customer’s long-term needs and immediate interests. External data is most helpful for prospects and new customers, who have generated little or no data within company systems. This guide describes the kinds of external data available to marketers, how they can acquire this data, and how they can put it to best use. It will help you to improve the effectiveness of your marketing programs by expanding the base of information available for segmentation, targeting, and analysis. Let’s get started. HOW-TO GUIDE Data Enhancement
3 Data Enhancement How-to Guide What’s Available HOW-TO GUIDE Enhancement data falls into two broad categories: Attributes – Provide information that is more or less constant, such as birthdate for individ- uals and industry for businesses. Attributes that are stable in the short term but may change over time include marital status, household income, home value, company revenue, personal or business address, and employee job title. This type of information has long been available from traditional marketing data sources such as list compilers and directories. It is often based on a combination of sources, including public records, surveys, loyalty programs, and census data. Some of the information is origin- ally provided for specific individuals, while other information, such as geo-demographic cluster codes based on census data, is inferred from geography. Attributes are now also gathered by scanning public Web sites and social media profiles. Behaviors – Provide information that changes constantly. Catalog purchases and recent address changes are examples of behavioral data that have long been available. Digital inter- actions have recently provided a new and richer source of behaviors, including search terms, Web sites visited, products considered but not purchased, emails opened, blog post topics, physical location, and social media comments or recommendations. Although digital inter- actions are all based on the actions of individuals, the identity is not always known: it could be an anonymous Web site visitor linked only to a cookie or corporate Internet address. By their nature, behaviors reflect current interests, so their relevance decays much more rapidly than attributes. But behaviors are often extremely predictive of important states, such as actively shopping for a particular product. This can make them more valuable than most attribute data during the period the behaviors remain accurate. Changes in attributes can also signal major business opportunities. Technical data gleaned during Web interactions can provide information on, for example, a consumer who is moving to a new home getting married, or on a business that is launching a new product or hiring new managers. Data Enhancement 3 Data Enhancement How-to Guide What’s Available HOW-TO GUIDE Enhancement data falls into two broad categories: Attributes – Provide information that is more or less constant, such as birthdate for individ- uals and industry for businesses. Attributes that are stable in the short term but may change over time include marital status, household income, home value, company revenue, personal or business address, and employee job title. This type of information has long been available from traditional marketing data sources such as list compilers and directories. It is often based on a combination of sources, including public records, surveys, loyalty programs, and census data. Some of the information is origin- ally provided for specific individuals, while other information, such as geo-demographic cluster codes based on census data, is inferred from geography. Attributes are now also gathered by scanning public Web sites and social media profiles. Behaviors – Provide information that changes constantly. Catalog purchases and recent address changes are examples of behavioral data that have long been available. Digital inter- actions have recently provided a new and richer source of behaviors, including search terms, Web sites visited, products considered but not purchased, emails opened, blog post topics, physical location, and social media comments or recommendations. Although digital inter- actions are all based on the actions of individuals, the identity is not always known: it could be an anonymous Web site visitor linked only to a cookie or corporate Internet address. By their nature, behaviors reflect current interests, so their relevance decays much more rapidly than attributes. But behaviors are often extremely predictive of important states, such as actively shopping for a particular product. This can make them more valuable than most attribute data during the period the behaviors remain accurate. Changes in attributes can also signal major business opportunities. Technical data gleaned during Web interactions can provide information on, for example, a consumer who is moving to a new home getting married, or on a business that is launching a new product or hiring new managers. Data Enhancement
4 Data Enhancement How-to Guide Linking With Customers HOW-TO GUIDE Most companies find it hard to link their internal data relating to each customer, so it’s no surprise that linking external data is also a challenge. However, the vendors providing external data typically include linking as part of their service, so marketers can usually rely on them for help. The nature of the linking depends in part on the type of data, such as Mailing addresses are typically linked through “fuzzy” matches that find similarities between the name and address in the company’s customer file and the name and address provided by the vendor. Both sets of data are first run through standardization routines that correct obvious input errors and place them into consistent formats. The matching process itself typically can overcome slight variations in spelling, missing words, or word order. Matching rules are often very elaborate and may be different for different countries, languages, or ethnicities. Some vendors also apply address change and name change files so they can link records for the same person at two locations or before and after marriage. Multiple identifiers may be provided directly to the company by the customer, such as address, telephone number, and email entered while placing an order or setting up an account. Any external data that provides one of those identifiers can then be linked to the master profile record. If the external data includes previously unknown identifiers, such as a second phone number, then this is added to the master record and becomes available to build additional linkages. Fuzzy matching may further expand the set of identifiers linked to one master record, although care is needed to avoid false matches. Identifiers may be provided by indirect permission, such as accepting a social network relationship that lets the company access the customer’s full profile on that network. These profiles often contain identifiers that the customer hasn’t provided directly, such as a secondary email address or employer. “Social sign-in” programs, where customers use their social network credentials to sign into accounts at other companies, are a particularly good method of gaining access to social profiles. Identifiers may be purchased from vendors who specialize in providing them, for example by appending an email address or phone number to a known mailing address. Govern- ment regulations, company policies, and consumer attitudes towards privacy impose some constraints on this type of matching. Government rules in particular vary by country. But, where permitted, this sort of matching can expand the set of identifiers on the master record and may let marketers deliver targeted messages to known customers in new channels. Linkages may be inferred from usage across multiple devices, such as signing into an account from different computers, smart phones, or tablets. All of those devices can then be associated with the same individual and added to the master record. This is a particularly useful approach for linking cookies on different devices to the same person. Data Enhancement 4 Data Enhancement How-to Guide Linking With Customers HOW-TO GUIDE Most companies find it hard to link their internal data relating to each customer, so it’s no surprise that linking external data is also a challenge. However, the vendors providing external data typically include linking as part of their service, so marketers can usually rely on them for help. The nature of the linking depends in part on the type of data, such as Mailing addresses are typically linked through “fuzzy” matches that find similarities between the name and address in the company’s customer file and the name and address provided by the vendor. Both sets of data are first run through standardization routines that correct obvious input errors and place them into consistent formats. The matching process itself typically can overcome slight variations in spelling, missing words, or word order. Matching rules are often very elaborate and may be different for different countries, languages, or ethnicities. Some vendors also apply address change and name change files so they can link records for the same person at two locations or before and after marriage. Multiple identifiers may be provided directly to the company by the customer, such as address, telephone number, and email entered while placing an order or setting up an account. Any external data that provides one of those identifiers can then be linked to the master profile record. If the external data includes previously unknown identifiers, such as a second phone number, then this is added to the master record and becomes available to build additional linkages. Fuzzy matching may further expand the set of identifiers linked to one master record, although care is needed to avoid false matches. Identifiers may be provided by indirect permission, such as accepting a social network relationship that lets the company access the customer’s full profile on that network. These profiles often contain identifiers that the customer hasn’t provided directly, such as a secondary email address or employer. “Social sign-in” programs, where customers use their social network credentials to sign into accounts at other companies, are a particularly good method of gaining access to social profiles. Identifiers may be purchased from vendors who specialize in providing them, for example by appending an email address or phone number to a known mailing address. Govern- ment regulations, company policies, and consumer attitudes towards privacy impose some constraints on this type of matching. Government rules in particular vary by country. But, where permitted, this sort of matching can expand the set of identifiers on the master record and may let marketers deliver targeted messages to known customers in new channels. Linkages may be inferred from usage across multiple devices, such as signing into an account from different computers, smart phones, or tablets. All of those devices can then be associated with the same individual and added to the master record. This is a particularly useful approach for linking cookies on different devices to the same person. Data Enhancement
5 Data Enhancement How-to Guide HOW-TO GUIDE Data Enhancement Identifiers may link customers to anonymous audiences without explicitly revealing their identities. This happens on Web advertising networks, which maintain lists of cookies asso- ciated with specified behaviors, such as visiting a particular Web site or showing interest in a particular type of product. These cookies are not linked to a specific individual using personally identifiable information (PII) such as name or address. In some cases, the network can associate its own cookies with cookies the marketer’s company has linked to its own customers. This allows the ad network to deliver targeted advertising without knowing which individual is associated with each cookie. The mechanics of the linking process are generally similar across all linking techniques. First, the marketer’s company sends a list of customer identifiers (name, address, phone number, email, etc.) to the data vendor. The vendor then finds matches with its own files. Finally, the vendor returns the original customer list with additional data appended. This approach avoids the enhancement vendor having to share information on unmatched customers and limits the data that the company must share with the vendor. Sometimes the matching is done by a “trusted third party” so neither participant shares its customer identifiers with the other. This matching may be done in a periodic process involving a batch of customer records, or it may be done on demand for a one customer record at a time. Because different enhancement data may be matched on different identifiers, it’s still up to the marketer’s company to build the master record that holds all identifiers linked to each individual and links that individual to the enhancement data from all different sources. When the same data element comes from multiple sources, the company system also typically decides which value to use if the sources provide different answers. 5 Data Enhancement How-to Guide HOW-TO GUIDE Data Enhancement Identifiers may link customers to anonymous audiences without explicitly revealing their identities. This happens on Web advertising networks, which maintain lists of cookies asso- ciated with specified behaviors, such as visiting a particular Web site or showing interest in a particular type of product. These cookies are not linked to a specific individual using personally identifiable information (PII) such as name or address. In some cases, the network can associate its own cookies with cookies the marketer’s company has linked to its own customers. This allows the ad network to deliver targeted advertising without knowing which individual is associated with each cookie. The mechanics of the linking process are generally similar across all linking techniques. First, the marketer’s company sends a list of customer identifiers (name, address, phone number, email, etc.) to the data vendor. The vendor then finds matches with its own files. Finally, the vendor returns the original customer list with additional data appended. This approach avoids the enhancement vendor having to share information on unmatched customers and limits the data that the company must share with the vendor. Sometimes the matching is done by a “trusted third party” so neither participant shares its customer identifiers with the other. This matching may be done in a periodic process involving a batch of customer records, or it may be done on demand for a one customer record at a time. Because different enhancement data may be matched on different identifiers, it’s still up to the marketer’s company to build the master record that holds all identifiers linked to each individual and links that individual to the enhancement data from all different sources. When the same data element comes from multiple sources, the company system also typically decides which value to use if the sources provide different answers.
6 Data Enhancement How-to Guide HOW-TO GUIDE Data Enhancement Assigning segments and personas – Most marketers divide their customers and prospects into multiple segments and personas, each having different needs, responding to different treatments, and presenting different potential values. These distinctions are based primarily on static attributes such as income, life stage, industry, job title, and location. Because the attributes are often used to customize Web treatments, marketers often want to identify them immediately when a new visitor reaches their Web site. Some, but not all, enhance- ment vendors can do this by using identifiers such as the visitor’s corporate Web address or existing cookies on their browser. Tracking customer life stages – Behaviors such as email clicks and Web pages viewed are good measures of engagement and a customer’s specific stage in the buying cycle. Many of these behaviors involve the company’s own Web site and email, where external data is not needed. But information on what a prospect is doing on other Web sites and social media gives a more complete picture of what’s on their mind. Selecting offers – Perhaps the most important application for external data is targeting offers based on the combination of attributes and behaviors. Attributes help determine which prod- ucts a customer might want, the most suitable price and service levels, and what types of messages they would best respond to. Behaviors can help marketers refine those selections, react to specific events, and take advantage of new opportunities. They may also be used as content in personalized messages, although it can be dangerous to show customers you know things about them that they didn’t tell you directly. Finding advocates and detractors – External behaviors are especially useful in finding customers who are active participants in social media and, thus, potentially powerful advo- cates if they’re happy or detractors if they’re dissatisfied. This enables marketers to focus outreach on the most productive targets. Social messages can also identify specific issues that represent strengths or weaknesses and can identify customers who might be at risk of taking their business elsewhere. Using the Data It’s great that all this new data is available, but you still need a reason to assemble it. Marketers must have specific uses in mind before they make the necessary investments. Typical applica- tions include Identifying opportunities – Behaviors are a particularly powerful tool for identifying oppor- tunities for new sales, among both prospects and existing customers. Key behaviors include Web searches for relevant terms, visits to relevant Web sites, and downloading relevant content. Attributes are generally less useful, although attribute changes such as a new address or product launch can be significant. When behaviors identify a prospect who is not already a customer, for the information to be useful the data vendor must also provide a way for the company to contact them. 6 Data Enhancement How-to Guide HOW-TO GUIDE Data Enhancement Assigning segments and personas – Most marketers divide their customers and prospects into multiple segments and personas, each having different needs, responding to different treatments, and presenting different potential values. These distinctions are based primarily on static attributes such as income, life stage, industry, job title, and location. Because the attributes are often used to customize Web treatments, marketers often want to identify them immediately when a new visitor reaches their Web site. Some, but not all, enhance- ment vendors can do this by using identifiers such as the visitor’s corporate Web address or existing cookies on their browser. Tracking customer life stages – Behaviors such as email clicks and Web pages viewed are good measures of engagement and a customer’s specific stage in the buying cycle. Many of these behaviors involve the company’s own Web site and email, where external data is not needed. But information on what a prospect is doing on other Web sites and social media gives a more complete picture of what’s on their mind. Selecting offers – Perhaps the most important application for external data is targeting offers based on the combination of attributes and behaviors. Attributes help determine which prod- ucts a customer might want, the most suitable price and service levels, and what types of messages they would best respond to. Behaviors can help marketers refine those selections, react to specific events, and take advantage of new opportunities. They may also be used as content in personalized messages, although it can be dangerous to show customers you know things about them that they didn’t tell you directly. Finding advocates and detractors – External behaviors are especially useful in finding customers who are active participants in social media and, thus, potentially powerful advo- cates if they’re happy or detractors if they’re dissatisfied. This enables marketers to focus outreach on the most productive targets. Social messages can also identify specific issues that represent strengths or weaknesses and can identify customers who might be at risk of taking their business elsewhere. Using the Data It’s great that all this new data is available, but you still need a reason to assemble it. Marketers must have specific uses in mind before they make the necessary investments. Typical applica- tions include Identifying opportunities – Behaviors are a particularly powerful tool for identifying oppor- tunities for new sales, among both prospects and existing customers. Key behaviors include Web searches for relevant terms, visits to relevant Web sites, and downloading relevant content. Attributes are generally less useful, although attribute changes such as a new address or product launch can be significant. When behaviors identify a prospect who is not already a customer, for the information to be useful the data vendor must also provide a way for the company to contact them.
7 Data Enhancement How-to Guide When Data Enhancement Makes Sense HOW-TO GUIDE Data enhancement isn’t necessarily for everyone. Costs are substantial for the data itself and for an infrastructure that can use it effectively. Consider external data enhancement if You’re selling to high value customers – External data can increase the value you receive from prospects and existing customers, but it won’t be worth the investment if each customer adds little profit to begin with. Industries with high customer value include financial services, retail, travel, telecommunications, technology, and manufacturing. Lower customer value industries include consumer packaged goods, restaurants, and utilities. Targeting and differentiated treatment make sense – External data is used primarily to guide differentiated treatments for individual customers. If your customers all have the same needs and generate the same value, you’ll probably treat them the same regardless of what much you know about them. In that case, you’d gain little return from adding external data. You can interact with customers directly – You must be able to act on the knowledge that external data provides. This means you need to be in an industry that can identify its customers as it interacts with them, your company must have the systems and processes to execute personalized interactions and those systems must be able to integrate and apply the external data External data adds value – The information provided by external data must actually make a difference. This means that treatments using the data must generate more value than treat- ments selected without the data. It assumes the external data contains significant information that would otherwise not be available. This is most likely the case with prospects and new customers, for whom little internal data is available. It may also be true if the external data captures substantially different information from internal systems. Data Enhancement Marketing today is increasingly driven by data and some of the most useful data is outside of your company. Taking advantage of this data requires adequate systems to manage it and creative marketing programs use it effectively. Follow a careful process to ensure that you acquire the right data, have the tools to deploy it, and can measure your results. Used correctly, external data can be an important tool in your company’s struggle to capture the business of current and future customers. Bottom Line 7 Data Enhancement How-to Guide When Data Enhancement Makes Sense HOW-TO GUIDE Data enhancement isn’t necessarily for everyone. Costs are substantial for the data itself and for an infrastructure that can use it effectively. Consider external data enhancement if You’re selling to high value customers – External data can increase the value you receive from prospects and existing customers, but it won’t be worth the investment if each customer adds little profit to begin with. Industries with high customer value include financial services, retail, travel, telecommunications, technology, and manufacturing. Lower customer value industries include consumer packaged goods, restaurants, and utilities. Targeting and differentiated treatment make sense – External data is used primarily to guide differentiated treatments for individual customers. If your customers all have the same needs and generate the same value, you’ll probably treat them the same regardless of what much you know about them. In that case, you’d gain little return from adding external data. You can interact with customers directly – You must be able to act on the knowledge that external data provides. This means you need to be in an industry that can identify its customers as it interacts with them, your company must have the systems and processes to execute personalized interactions and those systems must be able to integrate and apply the external data External data adds value – The information provided by external data must actually make a difference. This means that treatments using the data must generate more value than treat- ments selected without the data. It assumes the external data contains significant information that would otherwise not be available. This is most likely the case with prospects and new customers, for whom little internal data is available. It may also be true if the external data captures substantially different information from internal systems. Data Enhancement Marketing today is increasingly driven by data and some of the most useful data is outside of your company. Taking advantage of this data requires adequate systems to manage it and creative marketing programs use it effectively. Follow a careful process to ensure that you acquire the right data, have the tools to deploy it, and can measure your results. Used correctly, external data can be an important tool in your company’s struggle to capture the business of current and future customers. Bottom Line
8 Data Enhancement How-to Guide 1 2 3 4 5 6 Identify Use Cases Define the Data You’ll Need Check Your Infrastructure Assess the Available Data Build a Business Case Define specific marketing programs that would benefit from external data. Identify the specific data they would use and the systems that would deliver the programs. Then make sure the data you want is actually available and your systems could use it as intended. Finally, estimate the value that those programs might create and compare it to estimated costs. Neither estimate will be very accurate at this stage, but you want to confirm that there is a reasonable balance between cost and benefit. Action Plan STEP 1 - Identify Use Cases The Balance of Cost and Benefit Deploy, Measure and Expand 8 Data Enhancement How-to Guide 1 2 3 4 5 6 Identify Use Cases Define the Data You’ll Need Check Your Infrastructure Assess the Available Data Build a Business Case Define specific marketing programs that would benefit from external data. Identify the specific data they would use and the systems that would deliver the programs. Then make sure the data you want is actually available and your systems could use it as intended. Finally, estimate the value that those programs might create and compare it to estimated costs. Neither estimate will be very accurate at this stage, but you want to confirm that there is a reasonable balance between cost and benefit. Action Plan STEP 1 - Identify Use Cases The Balance of Cost and Benefit Deploy, Measure and Expand
9 Data Enhancement How-to Guide 1 2 3 4 5 6 Identify Use Cases Define the Data You’ll Need Your use cases have already suggested specific data elements. Now take a broader look at long-term needs and sources. It may turn out that the data available isn’t the data your use cases required, but it could still add other value in other ways. Take a broad view of the possibilities so you have a good idea of what you need your systems to handle. Bear in mind that the future is almost certain to bring new data sources we can barely imagine today. Action Plan STEP 2 - Define the Data You’ll Need Build a Business Case Check Your Infrastructure Assess the Available Data Growing New Data Sources and Long-Term Needs Deploy, Measure and Expand 9 Data Enhancement How-to Guide 1 2 3 4 5 6 Identify Use Cases Define the Data You’ll Need Your use cases have already suggested specific data elements. Now take a broader look at long-term needs and sources. It may turn out that the data available isn’t the data your use cases required, but it could still add other value in other ways. Take a broad view of the possibilities so you have a good idea of what you need your systems to handle. Bear in mind that the future is almost certain to bring new data sources we can barely imagine today. Action Plan STEP 2 - Define the Data You’ll Need Build a Business Case Check Your Infrastructure Assess the Available Data Growing New Data Sources and Long-Term Needs Deploy, Measure and Expand
. 10 Data Enhancement How-to Guide 1 2 3 4 5 6 Check Your Infrastructure In addition to execution systems that can employ the new data, you’ll need a central database to store it. If you have a customer database in place, check that it can send the necessary extracts to enhancement vendors, can import their results, can store the new information, and can make it accessible. If your use cases require real-time inter- actions, make sure your central database can handle them. If you don’t have a central customer database, you might need to tackle that problem first or append the data directly to an existing system such as your email lists or Web-user profiles. Action Plan STEP 3 - Check Your Infrastructure Identify Use Cases Build a Business Case Define the Data You’ll Need Assess the Available Data The Right Database for the Right Interaction Deploy, Measure and Expand
. 11 Data Enhancement How-to Guide 1 2 3 4 5 6 Assess the Available Data Reach out to potential data vendors and take a close look at what they offer in terms of cost, coverage, accuracy, and response time. Run tests to see how much of your customer file they can actually match, how many of the matches seem valid, and how much of their data seems correct. Be sure to find out where their data is coming from so you can judge whether you’re comfortable with their approach and whether there are significant risks that they could lose access to their sources. Finding the Right Match with Your Database Vendor Action Plan STEP 4 - Assess the Available Data Identify Use Cases Build a Business Case Define the Data You’ll Need Check Your Infrastructure Deploy, Measure and Expand
. 12 Data Enhancement How-to Guide 1 2 3 4 5 6 Build a Business Case Now you’re ready for more detailed estimates of the cost of the data itself, of the system changes to manage it, of the marketing programs that would use it, and the results you might hope to expect. You may want to run some test programs using external systems to get a more reliable idea of the value the data is likely to provide. Action Plan STEP 5 - Build A Business Case Identify Use Cases Define the Data You’ll Need Check Your Infrastructure Assess the Available Data Deploy, Measure and Expand A Business Case for Your Database Strategy Business Case Template V I E W R E S O U R C E
. 13 Data Enhancement How-to Guide 1 2 3 4 5 6 Deploy, Measure, and Expand Action Plan STEP 6 - Deploy, Measure, and Expand Deploy in small phases to the degree this is possible. In particular, try to avoid building a massive new customer database and rewiring all your systems to connect with it. You might keep the volume down at first by enhancing only your most valuable customers or a small set of prospects. Be sure to measure results so you can see what’s working. Once you’ve gained experi- ence and proven value, you can expand the project to a larger portion of your universe, to more channels, and to more programs. Identify Use Cases Build a Business Case Define the Data You’ll Need Check Your Infrastructure Assess the Available Data Launch Simply and Expand Only As Needed
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