Abstract
This project aims to assess the reliability
of the MapInfo software aligned with the CRM ecosystem. MapInfo uses a range of
desktop GIS functions to extend and visualize spatial data structures in the
CRM ecosystem and Value Chain Model through geographic analysis patterns. Over 100
CRM Systems exist in the business market, with and without GIS technology.
Individual Business Enterprises align a CRM framework with a Geographic
Coordinate System to identify customer data within a specific geographic area. CRM
solutions can develop traceability for customers' needs; therefore, they employ
data mining techniques to analyze customer data.
The CRM ecosystem collaboration is the
software architecture that automates customer-driven data through ERP systems
and Supply Chain Management software applications within the Enterprise.
A geographic information system is a
conceptual framework for storing, mapping, and analyzing spatial data. GIS
applications can control query execution in a database and display metadata in
a map format for end-users. Besides, GIS can translate implicit geographic data
(such as a street address) into a specific map location regarding x and y
coordinates.
The CRM Value Chain coordinates and
promotes decision-making, focusing on adding value to Products and Services in
the CRM ecosystem through map visualization. The CRM Value Chain identifies
critical steps in product development within the CRM ecosystem. It determines
how an optimal customer strategy aligns with various business models. An
innovative CRM Value Chain can be created to ensure high-value products and
low-cost performance. Besides, it delivers a competitive advantage and develops
flexibility for customers.
The project assesses the reliability of
MapInfo alignment within the CRM ecosystem through three case studies.
Alignment benefits would boost the transparency of the "CRM
ecosystem" and value chain process through geographic analysis patterns.
Effective use of the CRM value chain process enhances customer lifecycle
profitability. The project concept initiates a theoretical framework and
narrows it down into hypotheses. The implementation method joins the table in
MapInfo (customer metadata) and (customer geographic map). Apply a set of
synthetic matching scenarios in three case studies showing real-life events
because of privacy and data protection. The customer service team can use GIS
buffer and proximity analyses to capture data in the CRM ecosystem and value
chain process. Case studies were developed on "manufacturing efficiency
and product synchronization," "logistical performance," and
eventually, "marketing assessment."
Key Words:
Customer Relationship Management (CRM), Geographic Information System (GIS)
MapInfo
Professional extends the traceability approach to the CRM value chain and
neighborhood partners.
General implementation
Map implementation
Three
case studies
This project explores three case studies to assess the
reliability of MapInfo within the CRM ecosystem. It examines the visualization
of spatial data structures in the CRM ecosystem and value chain process. The
transparent spatial CRM value chain ensures optimal business decision-making.
The paradox of three case studies on customer transparency, from ecosystem
boundaries to neighborhood partnerships, reviews customers' needs and the
domains of a CRM ecosystem using spatial data. Transparent activities in
customer domains enhance reliability in service delivery.
Implementation
of the first case study
The customer service
team can select SQL statements in the CRM ecosystem. Algorithms allocate
specific customer profiles on the MapInfo desktop application. SQL statements
can assign several customers who want to purchase the Q-500.
Implementation
of analogical mapping in the first case study
The geographic
analysis patterns in the first case study lead to seven analogical mappings.
Buffering around polygon features shows attractive attributes in customer
neighborhoods. Similar characteristics require assessment in part of the
geographical data. An analogical mapping implies further investigation of similarities
and customer contacts.
A spatial approach
in the first case scenario, based on filtering customer locations, affected product
purchases. The customer service team can analyze geographic variations, new
product feature models, and customer product strategies. Spatial data
identifies key factors beyond marketing automation platforms, which lead to
profitability for all transaction partners.
Implementation of the second case study
The latter case
study focuses on logistical performance and distances between customer and
dealership locations.
Company M_100 can
manufacture innovative security products. They send items by air, sea, and
truck to customer enterprises. Company M_100 discovers a better way of
transporting products to customers. Logistics activities can reduce transport
costs by leveraging MapInfo in alignment with the CRM ecosystem.
Company P_200 is a
transportation firm that works as a supplier. They
can recommend the most suitable freight rate structure for Company M_100.
A business model
describes the transportation of products within specific regions and distances.
The freight rate structure is cost-effective for enhancing activities and
business within Company M_100's logistics operations. Company P_200 offers
special discount freight rates to customer enterprises in the north-central
region of Phoenix.
Implementation
of the third case study
The third case study
focuses on marketing performance in the CRM ecosystem.
Company T_700 is
located in Florida. The product design manager in the production factory in
California would like to do marketing research. One of the select stores in the
CRM ecosystem is located in Sweden. The product design manager wonders how many
men between 20 and 40 live within 10 km of a store.
The
outlook of the current CRM market
Successful CRM
implementations among enterprises are paving the way for an increasingly
crowded CRM market. CRM critical customer success expands with popularity across
broad industries such as securities, telecommunications, medicine, consulting,
insurance, network technology, manufacturing, and banking. Over 100 CRM
technologies are available in customer service delivery platforms.
The customer-centric
point of view is the primary goal of CRM strategy and customer service
platforms. However, the CRM frameworks most prevalent in the market lack
geographic context analysis and spatial interoperability. Encapsulated CRM
software with context modeling for geographic applications is built by
different vendors today. Still, their system applications are only compatible
with existing CRM software (Yet combining GIS function models from
other disciplines). Google Earth can be used as an alternative by enterprises
that adapt CRM portals with template coordinate systems in a customer database.
The Google Earth applications visualize CRM customer metadata and spatial
phenomena; however, structural functions for spatial analysis apply only to the
constraints used. CRM implementation software requires significant capital
investment for technology and employee education programs; therefore, small and
medium-sized enterprises prefer to retain their present CRM frameworks. Large
enterprises can target an encapsulated CRM and GIS framework in the IT
market.
MapInfo software can support the visualization of spatial data for small and medium-sized enterprises without interoperability issues. MapInfo Framework can streamline the CRM value chain process while reducing maintenance costs in tight-budget environments.
