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LeapThought has found 139 LeapLines
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LeapLine |
Trend, Type, Function, Action | |
 |
Understand available data sources |
data analytics,
assessment activities,
marketing,
understand
|
|
|
Understand how data is collected and transferred from its original sources |
technology,
assessment activities,
IT,
understand
|
|
|
Identify sources of data |
database marketing,
technology assessment,
data analytics,
identify
|
|
|
Understand the importance to testing data for inconsistencies, anomalies and biases. |
data mining,
development activities,
IT,
understand
|
|
|
Understand existing data structures, formats and conventions |
data analytics,
assessment activities,
IT,
understand
|
|
|
Understand the applications of directed and undirected analysis in the data mining process, particularly in the support of a hypotheses |
data mining,
learning activities,
IT,
understand
|
|
|
Understand the marketing and business objectives of the data mining effort |
data analytics,
assessment activities,
marketing,
understand
|
|
|
Transfer data from sources |
data analytics,
technology activities,
data analytics,
transfer
|
|
|
Understanding and prioritizing content sources, internal and external |
content management,
content activities,
content,
understand
|
|
|
Understand how schemas and relationships are built and implemented |
data analytics,
development activities,
IT,
understand
|
|
|
Understand scoring and output conventions and techniques |
modeling,
learning activities,
data analysis,
understand
|
|
|
|
|
Understand company operating environment |
z - no trend,
assessment activities,
management,
understand
|
|
|
Understand explicit economic implications |
ROI,
business case activities,
finance,
understand
|
|
|
Understand media and trends |
z - no trend,
market assessment activities,
research,
understand
|
|
|
We understand our own revenue requirements |
z - no trend,
strategy development activities,
finance,
understand
|
|
|
Understand baseline implications of existing systems |
z - no trend,
technology assessment,
IT,
understand
|
|
|
Understand competitive landscape |
z - no trend,
assessment activities,
management,
understand
|
|
|
Understand products, services and customers |
CRM,
marketing assessment activities,
CRM,
understand
|
|
|
Understand breadth and depth |
z - no trend,
assessment activities,
consulting,
understand
|
|
|
Understand competitive and marketplace offering |
competition,
market assessment activities,
research,
understand
|
|
|
Understand concurrent programs |
business planning,
assessment activities,
project management,
understand
|
|
|
|
|
Understand core products and services |
z - no trend,
marketing assessment activities,
z - no function,
understand
|
|
|
Understand Company core offering and operations |
z - no trend,
assessment activities,
research,
understand
|
|
|
Understand history, brand and vision for the future |
branding,
marketing assessment activities,
management,
understand
|
|
|
Understand competitive offerings, both local and national |
competition,
market assessment activities,
research,
understand
|
|
|
Understand key constituent groups and marketplace objectives |
z - no trend,
market assessment activities,
management,
understand
|
|
|
Understand company’s current ability to fulfill on eCRM promises and messages |
CRM,
CRM assessment,
internet,
understand
|
|
|
Understand, map, and 'formalize' newsletter creation process |
sales force productivity,
marketing planning activities,
content,
understand
|
|
|
Understand how to fine-tune and enhance a technique to provide a deliverable model |
consulting,
learning activities,
project management,
understand
|
|
|
Ongoing updates for extraction, transformation and load for updated data |
data analytics,
data analysis techniques,
data analytics,
z - no action
|
|
|
A data quality report that outlines the usability and accuracy of the data. |
data analytics,
deliverable description,
data analytics,
z - no action
|
|
|
Understand Company core acquisition objectives goals |
z - no trend,
marketing assessment activities,
marketing management,
understand
|
|
|
Understand company staff’s current understanding of eCRM and company’s role |
leadership development,
CRM assessment,
consulting,
understand
|
|
|
Understand core business requirements and imperatives |
business planning,
strategy development activities,
z - no function,
understand
|
|
|
Understand retention goals and objectives |
customer loyalty,
marketing assessment activities,
marketing,
understand
|
|
|
Understand current operations |
business process redesign (BPR),
assessment activities,
operations,
understand
|
|
|
Archive and store data and models |
data mining,
data analysis techniques,
data analytics,
archive
|
|
|
Understand brand intentions |
branding,
brand development activities,
marketing,
understand
|
|
|
Understand Company existing marketing and brand approach, including tools, creative and established processes |
branding,
marketing assessment activities,
marketing,
understand
|
|
|
Understand impact on portal |
internet,
web development activities,
internet,
understand
|
|
|
Counts and-or indications of null or incomplete records |
data mining,
data report elements,
data analytics,
z - no action
|
|
|
Return data and data transfer materials |
data analytics,
data analysis techniques,
data analytics,
return
|
|
|
Understand constraints or advantages of changing company operations in terms of supporting company branding |
branding,
marketing assessment activities,
management,
understand
|
|
|
Understand marketing ROI |
ROI,
business case activities,
marketing,
understand
|
|
|
Understand what customers think of company |
CRM,
customer research,
research,
understand
|
|
|
Basic frequency distributions and calculations, showing means, skews, spikes, exceptions and standard deviations |
data mining,
data report elements,
data analytics,
z - no action
|
|
|
Understand and formalize core strategic objectives both in the short-term and long-term as its tied to the core business model, marketing activities, and revenue impact |
ROI,
strategy development activities,
management,
understand
|
|
|
Tables and graphs showing counts and percentages of customers for each dimension |
data analytics,
data report elements,
data analytics,
z - no action
|
|
|
Cross-tab tables and graphs for each meaningful combination of the key customer-facing dimensions |
data analytics,
data report elements,
data analytics,
z - no action
|
|
|
Repeatedly train model until confidence level is acceptable |
data mining,
data analysis techniques,
data analytics,
train
|
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Results from the LeapThought © Document Database: Understand available data sources LeapThought has found 93 files.
| Data Management is central to Marketing Operations- 1 Powerpoint slide |
 |
This slide provides an illustration of how data sources can be managed and analyzed to benefit marketing operations. This illustration compares the process to a funnel, with raw data entering the system and applied data exiting as useful marketing to
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|
| Definition of Data Analytics - Data mining overview- 1 Powerpoint slide |
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This mixed process/entity diagram shows a high-level, marketing view of how data analytics operates.
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|
| Acquisition and retention map- 1 Powerpoint slide |
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This simple map shows sources of data to fuel a data analytics program and types of analysis that might be completed.
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|
| The process of training/knowledge systems- 1 Powerpoint slide |
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This complicated chart shows a map (and within it, a process), that shows how training/knowledge systems gather data, process it, and pass it on to the right user.
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|
| Understand customer behavior: Finding answers using historic data- 1 Powerpoint slide |
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This is a top-level process flow diagram that shows how to conduct market data analysis by ‘training’ a data model.
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|
| Sources of content for a content-driven intranet site- 1 Powerpoint slide |
 |
This combination map/list shows many different content categories and how they would be assembled on an intranet and delivered to users on a filtered, customized basis.
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|
| Building the system environment: Stage I- 1 Powerpoint slide |
 |
This large roadmap shows a full first phase technology build out, in this case, a knowledge management system. It has three main stages: assessment and business planning, design and develop, deploy.
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|
| Marketing strategy and planning- 1 Powerpoint slide |
 |
This elaborate project process diagram gives a pretty complete view of a marketing strategy and planning project. The output of this project would be a comprehensive marketing strategy and plan.
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|
| Understand customer behavior: Finding answers using historic data- 1 Powerpoint slide |
 |
This slide illustrates how a trained data model can guide two fundamental marketing decisions: determining what the right tactics are (such as creating a specific offer) and identifying the right customers to market to (i.e., picking the right lis
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|
| Capturing and delivering training and intelligence through systems- 1 Powerpoint slide |
 |
This combination map/list shows a (illustrated) company information/intelligence system . Its three parts are: uses of intelligence, compilation storage and dissemination of intelligence, and sources of intelligence.
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|
| Segments vs. clusters- 1 Powerpoint page |
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This is a neat comparison between segments and clusters, which are often confused/misused by marketers who don’t understand them.
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|
| Multi-track project approach: Marketing and data analytics- 1 Powerpoint slide |
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This plan shows the steps/phases in a combined marketing strategy and data analytics project.
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| Data analytics investment cycle- 1 Powerpoint slide |
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This chart shows how financial benefits of data mining projects rise as their costs shrink over time.
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| The customer data corruption cycle- 1 Powerpoint slide |
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This is a neat slide to describe to fussy marketers why data is incomplete, non-existent, or corrupted. It shows real, easy-to-understand data corruption events. Additionally, it creates formal ‘names’ for each phase of the cycle.
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| Marketing and data analytics project approach- 1 Powerpoint slide |
 |
This 9-step marketing project approach takes a group through the marketing planning phases while simultaneously conducting a data analytics (data mart) project.
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