Chapter 12 CRM software and Dashboard Design

Firms are increasingly applying Big Data Analytics to the areas of web analytics, search analytics, search engine optimization, customer analytics, and pay-per-click management to obtain automated and customized knowledge. The initial point is usually about obtaining data that are critical (Vreeman, 2014): 1) Lists of sites (competitors, blogs, suppliers, retailers, etc.) 2) Product and user information from those sites; and 3) Analytic data about those sites. Vreeman (2014) also lists some free Big Data Analytics tools that may help business with budget constraints to better manage NPD. With the power of synergistically combining expertise in both Traditional Marketing Analytics and Big Data Analytics, customized knowledge comes into play when firms can create idiosyncratic value for their customers (Hakanen & Jaakkola, 2012; Tudorache, Nyulas, Noy, & Musen, 2013).

The literature in different areas mainly uses Knowledge Fusion and Information Fusion alternatively (Jeong, 2012; Korres, & Tsami, 2010; Liu, Xu, & Zhan, 2014). In different sections, the study may use either Knowledge Fusion or Information Fusion. By following recent advances in engineering and decision-making studies (Liu et al., 2016; Yang & Deng, 2010, Smirnov et al., 2012, p.287), this study adopts “Knowledge and Information Fusion” as the main construct to represent a multi-level decision-making strategy of combining heterogeneous knowledge and information from different sources, and exploiting them to the fullest extent. This level of synergistic combination represents the highest level of knowledge extraction and generation.

12.1 Designing dashboards from a Knowledge Fusion Perspective

Specifically, Knowledge Fusion is a process by which heterogeneous information from multiple structured, semi-structured, and unstructured sources is merged to create knowledge that is more complete, less uncertain and less conflicting than the input (Hunter, 2006; IGI Global, p.106). A typical scenario applying the principle of Knowledge Fusion is when a driver is looking for a gas station and a good restaurant, a system, for example, GPS can incorporate gas station information and restaurant information with crowd-sourced and instantaneous feedback from consumers. In this kind of service interaction, GPS sensors, location services, ratings, online ad clicks, purchase histories, and public records are integrated together for the purpose of knowledge and information fusion, with the following types of knowledge helping decision-making: automated knowledge, heuristic knowledge and customized knowledge. In particular, GPS devices can track consumers’ behaviors — and tell app makers, or anyone who buys the product, where other consumers have been, and what customers say about the place.


Figure 12.1: dashboard

12.2 Designing Supply Chain Apps & Solutions - a Technical Perspective

The distribution process of a single product usually involves a four-stage supply chain: reailer, wholesaler, distributor, and factory. Marketing decision-making offers channel partners the updated marketplace knowledge to align supply and demand. The goal of an supply chain app or solution is to manage the flow of products, data, and resources in a seamless manner.

R is a good option for those who would like to develop apps for real-time supply chain solutions. For instance, you can use R and Shiny to create a interactive App for the Capacitated Vehicle Routing Problem.

Shiny Apps for Capacitated Vehicle Routing Problem

Figure 12.2: Shiny Apps for Capacitated Vehicle Routing Problem

Shiny Apps for Supply Chain Management

Figure 12.3: Shiny Apps for Supply Chain Management

With real-time dashboard designed using open-source technicala platforms like R and Python, companies could simply their supply chain process and offer customized solutions to their partners, channel members, and customers.

For instance, Plotly ( is a machine learning company that is built with the R, Python, and Julia programming environment. In Jan 2020, Scale AI awards $1.7M to Plotly to “speed innovation in supply chain AI technology.”

Designing Supply Chain Apps & Solutions using Plotly

Figure 12.4: Designing Supply Chain Apps & Solutions using Plotly


12.4 Exercise

Design an AdWords campaign dashboard for your project client