Alignment of the MapInfo Technology in the CRM Ecosystem

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 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 a map 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 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 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. 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 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 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 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 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 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 live 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 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 their 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.