Executive Summary 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 only react 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 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 that are available to marketers, how they can acquire this data, and how they can put it 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. This brief 11-page How-To Guide is designed to provide practical advice for Data Enhancement and outlines the following: Whats Available Linking With Customers Using The Data When Data Enhancement Makes Sense Action Plan Bottom Line Demand Metric's How-To Guides are designed to provide practical, on-the-job training and education and provide context for using our premium tools & templates. If there is a topic that you would like to see covered, please contact us at info@demandmetric.com (link sends e-mail) to make a content request.

1. B2B Data Management:
Best Practices & Insights
© 2015 Demand Metric Research Corporation. All Rights Reserved.
How-To Guide
By: David Raab, Research Associate – Demand Metric
August 2015

2. 3
4
6
7
8
10
Executive Summary
B2B Data Management Best Practices
B2B Data Management Maturity Levels
Taking Advantage of B2B Data Management
Action Plan
Analyst Bottom Line
Table of Contents
11 About the Analyst

3. EXECUTIVE SUMMARY
3
How-To Guide: B2B Data Management
The B2B buying process has changed in recent years, with customers doing more research on their own and delaying
engagement with sales teams until late in the purchase cycle. This has increased the need for marketers to reach customers early in
the buying cycle and to provide more information as their research progresses. The effort has multiplied further as the number of
interaction channels expands.
In this new environment, effective data management is essential for success. Balancing multiple opportunities to find the best
marketing investments relies on data as do finding and delivering the most effective treatments for each prospect. The sheer number of
choices means that only a data-driven approach can produce the right decisions.
Good data management isn’t easy. Data comes from many sources in many formats. It must be acquired, assembled and analyzed to
make sound marketing decisions. Then, the data must be made available to customer-facing systems in order to execute those decisions
on a one-to-one basis.
This How-To Guide will help you organize your data management efforts. You will learn how to define goals, specify requirements
and build a plan to meet those requirements. Then, you can begin your journey to data management success.
© 2015 Demand Metric Research Corporation. All Rights Reserved.

4. Business marketing data comes from many sources. Many are
controlled by marketing itself: display ads, website visits, email,
events and marketing automation. Others come from elsewhere in
the company, such as CRM, order processing or customer service,
while others are external data providers, such as Dun & Bradstreet.
This data helps marketers understand customer behavior, select the
right treatments for individual customers and prospects and
measure the results of marketing programs. But it must be
processed before it can be used effectively. The main steps are:
 Ingest data from multiple sources. This can be done by direct
database updates, API (Application Program Interface)
connectors that automatically move data between systems as
transactions occur, file transfers that move collections of data in
a periodic (batch) process or other techniques. In addition to
establishing the connection, ingestion also requires mapping data
elements from each source system into the marketing database so
they are stored consistently.
B2B DATA MANAGEMENT BEST PRACTICES
© 2015 Demand Metric Research Corporation. All Rights Reserved. 4
 Associate data from different sources that relates to the
same customer. This may mean matching on a shared identifier,
such as an email address or customer ID captured separately by
each system. Advanced methods may “stitch” together identities
by linking a customer to a device, and then attributing all
behavior on that device to the customer. Still other approaches
may infer linkages across devices, cookies, names or addresses by
correlating usage and location, or draw on outside services that
have identified such linkages using external data. Association is
more important with anonymous leads than with current
customers, who have more reason to identify themselves directly.
 Organize data to make it accessible for queries and
analysis. This requires physically storing the data in a structure
that identifies its contents to query and analysis tools. It often
also involves additional processing to make analysis more
effective. This may include tagging raw data with categories,
creating aggregated or derived variables, such as web visits in the
past week, or calculating predictive model scores. It also includes
How-To Guide: B2B Data Management

5. updating the data over time as new inputs imply changes in attributes, such as purchase history, interests or addresses.
 Expose data for use by customer-facing systems. This may involve access by campaign managers that select lists for outbound
promotions; by interaction managers that make decisions during web visits, mobile app sessions or call center conversions or by the
web, email, mobile, social or other delivery systems themselves. Since customer-facing systems often require sub-second response time
to function effectively, they often need data to be stored in different structures than analysis and reporting systems.
© 2015 Demand Metric Research Corporation. All Rights Reserved. 5
How-To Guide: B2B Data Management

6. B2B data supports many different applications, which are possible depending in part on the scope and sophistication of your data
management processes. The maturity model in Figure 1 describes how your capabilities can be expected to grow.
MATURITY LEVELS
B2B Data
Management
Stage 1:
Basic
Stage 2:
Marketing Automation
Stage 3:
Integrated Marketing
Stage 4:
Customer Management
Marketing Capabilities
Supported
Un-coordinated Prospecting Campaigns in Each
Channel
Coordinate prospect treatments between email
and web forms; Personalize email and web
forms; Report on marketing-generated leads
Coordinate and personalize prospect treatments
across email, web, call center & other channels;
Automatically pass leads from marketing to CRM;
Segmentation and campaign triggers based on
behavior across all channels
Coordinate & personalize prospect and customer
treatments across all channels for entire lifecycle;
Base treatments on data synchronized across all
channels in real-time; Select treatments during
real-time interactions on web, mobile apps, call
center, etc.
Ingestion (Data Shared
in Marketing Database)
None Email, web forms and website visitor behavior
Email, web forms & web visitor behavior; CRM,
call center & external enrichment; Include
unstructured data elements (e.g. search terms,
social media posts.)
Email, web forms, web visitor behavior, CRM, call
center & external enrichments; Company
operational systems (order processing, customer
service, accounting, product usage, etc.)
Association None
Associate anonymous behaviors with cookie;
Match email address to cookie after email
address is provided
Associate anonymous cookies with email from
MA and CRM; Use email to match data from MA,
CRM & other systems; Use external data to find
additional matches
Associate across anonymous cookies, email,
devices, CRM IDs, etc.; Use external data to find
additional matches
Organization None
Segments and behavior categories based on
user-defined queries against marketing
automation system
Segments are based on user-defined queries,
predictive model scores & behaviors across
channels
Segments are based on user-defined queries,
predictive model scores and behaviors across all
channels; System applies automated methods to
classify products, content and other items;
System tracks trends in model scores and other
derived variables over time
Exposure None
Email lists are extracted directly from marketing
automation; Reporting tools can access limited
marketing automation data; May be API access
to marketing automation data, usually limited
Lists for email, mobile, ad retargeting, social and
other sources extracted from marketing
database; CRM system receives limited contact
data (name, address, lead score, etc.) from
marketing database; CRM users can view
contact behavior details stored in MA, but details
are not loaded to CRM system; Reporting tools
can access full marketing database through APIs
Email, mobile, retargeting, social, CRM, and
other systems can extract data from marketing
database or connect via APIs; Automated
analysis tools can scan database for significant
events or predictive data relationships; Users can
construct personal custom dashboards and
receive alerts about specified events
Figure 1: B2B Data Management Maturity Model
How-To Guide: B2B Data Management

7. Data management processes by themselves are not enough to
produce results. Marketers need other capabilities in place to take
advantage of their data. These include:
 Related Systems. Other systems must feed data into the central
marketing database and deliver the coordinated, personalized
messages that result. Customer-facing systems in particular must
be open to integration so they can accept centralized inputs. The
exact method of integration will vary by system; but in most
cases, an API connection is preferred.
 Business Processes. The company must have processes that
allow it to design and deploy customer treatments across
channels. This means that channel managers, such as advertising,
web, email and call center teams, may have less autonomy than
before. It encompasses campaign design, content creation,
reporting and other processes. Full coordination across the
customer lifecycle also involves sales, service and support teams.
TAKING ADVANTAGE OF B2B DATA MANAGEMENT
7
How-To Guide: B2B Data Management
© 2015 Demand Metric Research Corporation. All Rights Reserved.
 Staff Skills. More advanced levels of data management involve
creating new types of coordinated campaigns. Some team
members may need new skills in planning, analysis, execution and
reporting to manage these effectively. Companies should plan to
invest in assessment and training to ensure the necessary skills
are available when needed.
 Measurement Techniques. Working across channels requires
measurement of cross-channel results. This means channel-
specific metrics, such as email open rates and web click rates,
must be supplemented with channel-neutral metrics, such as
conversion to sales-ready leads and incremental lifetime value.
Marketers also need to master advanced attribution methods that
help them to understand the net contribution that each
marketing program makes to the final results. Data management
also has its own operational metrics to assess data quality in
many dimensions, such as coverage, accuracy and currency.

8. ACTION PLAN
1. Assess your current situation. Compare your existing marketing programs, systems and data management practices with the
maturity model in Figure 1 to find your current level.
2. Select a target. The most advanced level isn’t for everyone. Make an honest judgement of how much change is possible given your
company’s resources and management support. Bear in mind that you can always raise targets after you have achieved initial success.
3. Estimate the cost and value of reaching your goals. Start by identifying the specific marketing programs you would like the
improved systems to support. Then, estimate the value of those programs to your business, identify the technical and business
changes needed to execute them and estimate the costs of those changes. This will be the foundation of a financial business case that
you will need to present to management.
4. Build detailed technology and business plans. These will define how you expect to manage the necessary system and business
changes. Plan to make the changes in small steps, with each step ideally providing a concrete business benefit. Be sure that each
intermediate change is also compatible with your ultimate target. You don’t want to find yourself ripping out a new system because it
can’t grow with you.
© 2015 Demand Metric Research Corporation. All Rights Reserved. 8
How-To Guide: B2B Data Management

9. ACTION PLAN
5. Execute, measure and repeat. Find systems that meet your requirements and deploy them, making sure you also address the
process, staffing and measurement issues needed for a complete solution. Measure your results, learn from any failures and build on
your successes. Continue to make improvements until you’ve met your target. Then, consider whether you should set a more
ambitious target or make changes elsewhere in your business.
6. Identify use cases. 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 can 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.
© 2015 Demand Metric Research Corporation. All Rights Reserved. 9
How-To Guide: B2B Data Management

10. ANALYST BOTTOM LINE
B2B data is one component of your entire marketing technology universe, which in turn is only part of your marketing
department’s technology, human and organizational resources. You need to match your data management level to your larger
marketing program, while recognizing that better data management may in itself open doors to new and more advanced techniques.
Use the maturity model in Figure 1 to understand your current situation, identify gaps to fill and build a practical execution plan. Then,
move carefully but steadily to improve your data management capabilities and your overall marketing results.
© 2015 Demand Metric Research Corporation. All Rights Reserved. 10
How-To Guide: B2B Data Management

11. ABOUT THE RESEARCH ANALYSTS
11
David Raab, Research Associate – Demand Metric
With an MBA from Harvard, David is an expert in both B2B & B2C marketing strategy & technology. He has advised
The Gap, JC Penney, Lowe's, Blue Cross/Blue Shield, Williams-Sonoma, Scholastic, Unisys, Sprint and Verizon
Wireless. He also publishes the Raab Guide to Demand Generation Systems and the Marketing Performance
Measurement Tool-Kit.
© 2015 Demand Metric Research Corporation. All Rights Reserved.
How-To Guide: B2B Data Management

12. © 2014 Demand Metric Research Corporation. All Rights Reserved.
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How-To Guide