Marketing concepts and terms

With iMIS Marketing, you can:

• Designate appropriate orders and donations as responses to the campaign
• Send personalized acknowledgments to the contact using their preferred method of communication
• Use responses to previous solicitations for future targeting and list segmentation

The following diagram illustrates the advanced integration that is possible between Campaign Management and other iMIS features.

Customer-focused marketing

Being customer-focused means that marketing efforts need to balance the goals of the organization with the needs of their "customers" (contacts, members, donors, prospects, legislators).

Customer satisfaction is a key metric that organizations seek to determine. Respect for the customer is the key to maintaining high customer satisfaction ratings. Ways to measure customer satisfaction include:

• Conducting a survey – Extract a list from your database, develop customer satisfaction questions, call or send the survey to your customers, record the responses, and analyze the results.
• Integrating short surveys into your customer service activities – Add questions to a donor reply device or a membership renewal package.
• Offering a survey on your website.
• Encouraging your customer service staff to ask questions when they are on the phone with your customer and to record the answers.

Closed-loop marketing

The closed-loop marketing approach measures the results of marketing and communication initiatives by tracking the response of targeted groups. The results of responses, such as completed surveys, are added to a database for tracking and evaluation to improve future marketing decisions. Simply put, marketers can develop and monitor targeted strategic campaigns based on a wide variety of customer histories and behaviors.

Closed-loop marketing involves a never-ending cycle of ongoing analysis, ongoing marketing, and ongoing response management. New market opportunities are identified through trend analysis. A new opportunity might address a weak area within a marketing plan or might identify a new group.

Closed-loop marketing refers to the cycle of:

• Developing metrics and benchmarks for the desired transactional behavior.
• Ensuring that business processes are in place to maximize the customer's experience and to build loyalty.

Understanding Segmentation

Segmentation is the science of dividing up the records in an organization's database into small groups that can be marketed to and measured over time. It is the way in which we apply demographic, mood, and transactional data to our marketing activities.

Segmentation usually begins by defining broad audience groups. However, audiences should not be considered as isolated groups; they might support the organization in a variety of ways. By recognizing that these relationships exist, an organization can offer personalized targeted marketing. Review the types of segmentation data below to learn more.

Demographics

Demographic data helps identify groups based on information like age, gender, geographic location and marital status. Demographic data is core to understanding what groups might be likely to perform in what way.

Acquiring demographic data about customers might not be easy to do. Some organizations require that date of birth and other demographic information be provided. Other organizations might be bound by privacy rules that can make it more difficult to capture this information.

Demographic data can be acquired from outside sources. For example, you can recruit the services of a vendor who has access to income tax data and other filed information.

Psychographics

Psychographics refers to how someone behaves: their likes, dislikes, interests, and key values. Although demographic data generally remains consistent, psychographics change. A key measurement of psychographics is customer mood. Customer moods change based upon how an organization interacts with a customer.

Psychographic data is usually gathered through polls and surveys.

Transactional data

Analyzing transactional data is critical to measuring customer satisfaction and loyalty.

RFM (Recency, Frequency, Monetary Value) is a common way of scoring transactions and determining loyalty and value. By establishing a matrix of values, you can measure where a customer ranks within the matrix and the direction they are migrating.

RFM is the science of developing this matrix of scores based on values we associate with the scores. In the end, records are grouped together based on their rankings. They share their support in common. Because the rankings are standardized, it is a very statistically valid way of building a standardized segmentation model. The RFM scoring process inherently converts flat data files into three-dimensional data files.

Other ways of looking at transactional data are available but they are one dimensional in nature:

• Last Year But Unfortunately Not This (LYBUNT)
• Second-to-Last Year But Unfortunately Not This (SYBUNT)
• Third-to-Last Year But Unfortunately Not This (TYBUNT)

This data measures only one RFM characteristic: Recency. You cannot use a LYBUNT, SYBUNT, TYBUNT report for identifying your best customers; its purpose is to identify the erratic donor.

Reports and analytics that focus on only one element of the transaction can be misleading. The RFM approach is preferred because of its ability to slice data three ways. RFM is also ideal because it can be implemented easily and regularly within a database.

A predictive model is used to consolidate all of the demographic, psychographic, and transactional data available to the organization into a data algorithm that can be used to target records that appear to be becoming a target market. For example, a "lapsing customer" model can identify customers whose loyalty is waning before they disappear. Similarly, a "planned giving" model can identify the point at which we've learned the two or three key criteria that we need to gather to qualify a planned giving prospect.

Using different types of data to enhance marketing efforts

Source Code assignments fall into three basic categories:

• Codes assigned to outgoing marketing efforts to track the incoming responses
• Generic codes assigned to the ongoing 'passive' ways in which a customer can support an organization, such as web transactions, social media interactions, or emails
• Unknown codes that are assigned to capture responses when the actual source code is not known

Source code tracking is important. To maintain the highest possible accuracy in recording the actual source code assigned to a contact's response, key processes must be highlighted.

Testing the marketing plan

It is important to test your organization's marketing plan. Review the following best practices:

• Market testing within your own database requires that you use random segmentation selections. This means that you establish a group that you would expect to perform in a particular way, and then randomly select the number of records you want to test against.
• Test groups must be measured against a control group.

To accurately determine whether a test is successful, it should be repeated. Future campaigns should repeat the test on new groups of randomly selected records. After the test has produced similar results three or four times, consider increasing the size of your test groups and introducing your new tactic on a permanent basis.

The following terms and phrases associated with campaign management. See the Glossary for full definitions.

Actual Cost Average Transaction Amount Campaign Type Count Date of First Response Drop Date Estimated Cost Highest Transaction Date Insert Type Last Drop Date List Type Net Revenue Output Process Package Costs Response Media Revenue Per Thousand Seed Lists Source Code Source Code Type Synchronize Responses Total Cost

Appeal Campaign Cost Per Thousand Current Response Rate Date of Last Response Dummy/Test Selects External File Name Insert Kill File List Member Type Lowest Transaction Amount Operational Costs Overhead Costs Predicted Response Rate Response State ROI Percentage Solicitation Source Code ID Mode Source List Target Revenue Total Revenue

N-Select Segments

A portion of the entire population that is the target for a campaign. The results returned by a selection filter are divided into a number (n) of segments, with the same number of contacts or prospects in each segment.

Segment

Portion of the entire population that is the target for a particular marketing campaign. A segment organizes customers and prospects according to demographic and behavioral patterns.

Segment Definition

Specifications for an individual segment within a segmentation job. A segment definition can be a query segment or an n-Select segment.

Segmentation Job

A mechanism for establishing all of the segments in a marketing campaign. This allows segments to be added, deleted, and tested. The segments can then be assigned to individual source codes and created in one process rather than individually creating each segment.

Frequency

Number of times a contact has transacted with an organization.

Monetary

Individual or cumulative value of a contact's transactions with an organization.

Population Query

Defines the population (contacts) used for RFM analyses. The population query references an IQA query that extracts users from an existing set.

Quintile

Any of the four values that divide the items of a frequency distribution into five classes with each containing one-fifth of the total population.

Recency

Period of time (in days or months) that has elapsed since the last transaction between a contact and an organization.

Transaction Query

Defines the transactions considered for RFM analysis. The transaction query references an IQA query.