Abstract
This project aims to provide a reliability assessment for MapInfo
software aligned with the CRM ecosystem. MapInfo uses a range of desktop GIS
functions for extending and visualizing spatial data structures in the CRM
ecosystem and Value Chain Model through geographic analysis patterns. Over one
hundred CRM Systems exist in the business markets with and without GIS
technology. Individual Business Enterprises align a CRM framework with a
Geographic Coordinate System, which identifies customer data in a specific
region or location. The CRM solution can develop traceability for customers'
needs; therefore, it targets data mining techniques for analyzing customers'
data models.
The CRM ecosystem collaboration is the software architecture System that automates customer desire data through ERP systems and Supply Chain
Management software applications within the Enterprise.
A geographic information
system is a conceptualized framework for storing, mapping and
analyzing spatial and geographic data. GIS
applications can regulate query execution in a database and show metadata in
maps format to 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 and focuses
on adding value to Products and Services in the CRM ecosystem through map
visualization. CRM Value Chain identifies critical steps in developing products
in the CRM ecosystem. It determines how 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 tests the reliability of MapInfo alignment in the CRM
ecosystem, exploring 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 for capturing 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 test the reliability of
MapInfo in alignment with 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 an optimal business decision-making
model. The paradox of three case studies on customer transparency from
ecosystem boundaries to neighborhood partnerships reviews customers' needs and
domains of a CRM ecosystem by 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. Desire algorithms allocate specific customer profiles on the MapInfo
desktop application. SQL statements can assign several customers who want to
purchase product Q-500.
Implementation
of analogical mapping in the first case study
The outcome of geographic analysis patterns in the first case study
leads to seven analogical mappings. Buffering around polygon features shows
attractive attributes in customer neighborhoods. Similar characteristics
require assessment in part of 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 the purchasing of products. The customer service
team can scrutinize geographical variations, new product feature models, and
customer product strategy. Spatial data identifies key factors beyond marketing
automation platforms, which leads 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 aircraft, ships, and trucks to customer enterprises. Company M_100
discovers a better way of transporting products to customers. The logistics
activities can save transport costs by exploring MapInfo in alignment with the CRM
ecosystem.
Company P_200 is a transportation firm and works as a Supplier. They can
suggest the best-suited 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 logistics for Company M_100.
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 selective stores of the CRM ecosystem is situated in Sweden. The product
design manager wonders how many men between 20 and 40 reside 10 KM from a
store.
The
outlook of the current CRM market
Successful CRM implementations among enterprises pave the way for CRM
applications to become a densely populated market. CRM critical customer
success expands with popularity in broad industries like securities,
telecommunication, medicine, consultation, insurance, network technology,
manufacturing, and banking. Over one hundred sorts of CRM technologies exist in
customer service delivery platforms.
The customer-centric point of view is the primary goal of CRM strategy
and customer service platforms—the most present CRM frameworks in the market
miss 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 present CRM frameworks. Large
enterprises can target an encapsulated CRM and GIS framework in the IT
market.
MapInfo software can support visualizing spatial data for small and
medium-sized enterprises without interoperability issues. MapInfo Framework can
promote the CRM value chain process with lower maintenance costs for tight
budget environments.
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