Abstract
This project aims to provide a reliability
assessment for MapInfo software that is 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 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. CRM solutions can develop traceability for
customers' needs; therefore, they target data mining techniques to analyze
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 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 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 that 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 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. However, the CRM
frameworks that are the most present 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 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.
