Customer Relationship Management (CRM) has always been one of the most important and most popular enterprise software applications. CRM technology enables businesses to manage their entire customer portfolio in an integrated way. They provide a 360o view of the customer based on the consolidation of customer information from multiple sources, while at the same using these data to automate a wide range of sales and marketing processes. Moreover, they help enterprises to communicate and collaborate with internal stakeholders, such as other departments in their organization, in a more streamlined way, thus improving overall productivity.
Once upon a time, CRM software packages consisted of a bunch of simple analytics and visualization tools over a database. Over the years, CRM systems have advanced in-line with the evolution of digital technologies. In recent years, CRM systems are profoundly affected by emerging technologies such as artificial intelligence (AI), machine learning (ML), and advanced natural language processing (NLP). These technologies will allow firms to gain insights from massive amounts of data in new, unobvious ways. At the same time, they open new horizons in customer service and support. For instance, many enterprises are changing their call centers in directions that automate processes based on Automated Virtual Assistants (AVAs). Virtual assistants record voice snippets of each call and then play them back when customers want supervisors or managers instead of waiting on hold. Hence, AVA technologies allow employees to perform non-customer facing activities while freeing them up to focus on important tasks that require faster responses or high-level decision making.
The technological evolution of CRM systems and software is therefore impacting the functionalities of CRM systems, as well as the ways in which modern enterprises evaluate and select their CRM software solutions.
Understanding CRM functionalities is a key to evaluating different CRM packages. One of the most common classifications of CRM functionalities is between analytical and operational CRM systems. Analytical systems employ advanced analytics (e.g., data mining and machine learning) over customer datasets to extract knowledge about sales and marketing processes. For instance, analytical CRM functionalities are used to segment the customer database in order to develop targeted marketing campaigns that maximize the customers’ response rate. On the other hand, operational CRM systems support transactional processes like sales order reception and handling of customer requests.
Another taxonomy of CRM functionalities classifies them into sales, marketing, and support. Most large-scale CRM packages support all three types of functionalities, yet there are also smaller scale systems that focus on one of them (e.g., customer service). This classification is orthogonal to the previous one. For example, marketing functionalities are based on both analytical and operational modules.
From a technological perspective, a CRM system is categorized as on-premise and cloud-based system. Legacy CRM systems used to be hosted the users’ premises. Modern CRM systems are cloud based, which obviates the need for enterprises to purchase and maintain IT infrastructures for their CRM systems. Furthermore, modern CRM systems come with functionalities for mobile users, which has given rise to mobile first functionalities and Mobile CRM packages. Similarly, there are also Social CRM modules which leverage social media channels to acquire customer information and to interact with the customers.
Modern CRMs are also differentiated from legacy ones based on the level of automation that they provide. There are CRMs that provide basic machine learning functionalities and others that employ advanced Artificial Intelligence systems such as chatbots for the front office, NLP for marketing campaigns and deep learning for customer segmentation and leads management. Therefore, enterprises need to understand their desired level of automation and the CRM functional areas where they would like to see this automation being applied.
The first step to selecting a CRM package is to determine the scale and scope of the desired CRM functionalities. This will enable an enterprise to focus on the vendors and the products that meet a great deal of their requirements. In principle, the selected CRM package must fulfill a minimum of 70% of the desired functionalities without any customization. This provides a sound basis for running a proper consulting and customization project that will cover the gap between the desired functionalities and what is readily available. In most cases, many CRM vendors will offer support for the desired functionalities, which means that additional criteria should be considered in the selection process. These criteria include:
The various selection criteria can serve as a basis for establishing a scoring formula. The latter can be used to weight the different factors, assign a score to alternative solutions, and ultimately rank the available options. Short listed CRM vendors can be invited to an interview or asked to offer a trial version of the product.
Overall, when selecting a CRM system, businesses need to review their needs, budget and available resources. CRM selection criteria include the CRM Product functionality, design, functionality and performance. Factors like user training set up costs, the service or supportability of the system during operation and reports generation capabilities are very important, yet often neglected in the selection process. It is also important to compare prices and discuss contract terms as well as system scalability, integration capability and support options before making a final decision. Recall that selecting a CRM software product is a critical decision that may affect your organization’s performance for years. Although selecting a CRM based on the above-listed guidelines can be a time-consuming process, understanding the features and benefits of each system can help you avoid costly mistakes.
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