Customer Relationship Management (CRM) Software

According to a report by Pactera Technologies and Nimdzi Insights, in 2018, 53% of enterprises leveraged some form of AI in their CRM systems. Below are the top four ways of relying on AI technologies to transform CRM:

• Predictive lead scoring: Customer sales data can be used to determine a customers’ buying readiness. Companies can analyze won versus lost deals to detect trends that can inform predictive lead scoring methods. You can read more about this in our research on the topic.
• Data cleaning: Advanced analytics approaches can detect irregularities, anomalies, duplicates, and other errors in the data and clean them to improve decision making quality.
• Virtual assistant: Automated virtual assistants can help employees to manage calendars, schedule meetings, make phone calls, take notes, do follow-ups, and assist them in routine manual tasks within a CRM system. A virtual assistant can also group CRM data, support companies with customer segmentation, and interpret natural language queries to handle customer calls or support customer service agents as they answer customer questions.
• Recommendation system: CRMs are data repositories. Using data collected in CRM, next steps can be identified to progress customers along the sales funnel. For example, personalized sales and marketing material can delivered at specified times to improve sales performance. Customized product recommendations can also be identified for cross-sell based on CRM data.

A CRM (Customer Relationship Management) system tracks a company’s sales-related interactions with customers. It aims to increase sales efficiency and improve business relationships by maintaining customer relationships, facilitating processes, and improving profitability.

Wikipedia defines CRM as:"Customer relationship management (CRM) is an approach to manage a company's interaction with current and potential customers "

CRM data can be used to understand customers better and discover their needs or styles to personalize the customer communication or the products offered to the customer. Sales history, customers' online interactions and requirements of similar customers can be used in recommendations

Product recommendations are personalized in most advanced companies. As a real-life example, Microsoft has integrated Azure ML into Dynamics 365. The model computes relationships between customers and the products they purchase. The CRM system can show suggested products to sell. Users can rate these suggestions to improve recommendation performance. Salesforce, another vendor, states that personalization can improve sales by 10%.

Communication with customers is harder to personalize automatically. However, there is already multiple companies striving to support sales personnel with customer specific communication suggestions

According to research by Dun & Bradstreet, 91% of data in CRM systems is incomplete, 18% is duplicated, and 70% is rendered stale each year.

• Errors can occur while entering new sales data. These errors include duplicate entries, incomplete information, or mistaken values. If companies don't clean erroneous data, their analysis can misguide them and cause wrong decisions. Feel free to read our detailed guide about data cleaning.
• CRM data grows stale as customer employees change jobs, customers go out of business or change their area of focus.

Advanced analytics models can identify potential issues, clean duplicate data, look for incomplete data in other systems or suggest actions to update potentially stale data in the CRM system. It can also detect the anomalies in the CRM data and notify the users to correct the errors.

Virtual assistants are application programs that understand natural language commands and complete tasks for users. They access employee calendars, notes, and information, which provides them enough information to schedule new meetings, send reminders, and assist specific tasks that can be automated.

Besides employee support, call routing can be optimized using CRM data. Customer data can be used to cluster customers with similar behaviors. Natural language processing can be used to direct customers to agents who are more likely to have a positive interaction with that customer.

A CRM system collects all data related to existing and potential customers. It allows sales personnel to set themselves reminders, prioritize accounts and track their progress. Advanced CRM software also analyze customers’ interaction histories and their sales data. From these insights, CRM systems identify the needed services and products for customers. Overall, CRM helps companies understand their customers better. This leads to improved customer relationships and increased sales efficiency.

A CRM system can:

• Store customer data including their interactions with sales
• Track sales leads as they progress on the pipeline
• Prioritize sales leads
• Enable sales personnel to set reminders regarding clients
• Integrate with other essential business systems involved in sales such as email
• Allow other systems real-time access to automate/optimize the sales processes

Sales in the past was viewed as something of an art, a skill that best sales people possesed. Something a bit magical. Metric collection was made at a high level and customer interactions were not recorded. This made sense until 2000s as most meetings were either face-to-face or on a phone and the technology to record and analyze such verbal exchanges was not available. However, today's sales relies on emails, in most companies, inside sales teams make up the majority of the sales personnel. Since their interactions can be recorded and analyzed at limited cost, CRM systems have become increasingly useful, bringing science to the sales process.

Gartner forecasts that by 2021, CRM will be the single largest revenue area of spending on enterprise software. From SMEs to large banks to consultancies, most companies use a CRM system to track their sales.

Salesforce, one of the leading vendors, states that companies can improve their revenue by 25% and sales productivity by up to 35% with a CRM. A CRM system helps to focus on company relationships, including customers, suppliers, and employees. Companies use this solution to find new customers, provide support services, and increase sales efficiency.

The difficulty of learning CRM software depends on 

• the specific software functions
• the user's familiarity with technology (e.g., coding skills might be useful)
• the complexity of the business processes being managed. 

Modern CRM systems are user-friendly, with easy interfaces and useful features such as drag-and-drop capabilities, customized dashboards, and guided onboarding. However, some CRM systems may have a steep learning curve, particularly for non-technical users or enterprises with complicated requirements. Proper training and assistance may help users understand and use CRM software efficiently, therefore it is important to check out the possible customer support options of vendors.

CRM (Customer Relationship Management) and ERP (Enterprise Resource Planning) are both software systems to manage different aspects of their business operations, but they differ in their focus area and functionalities.

CRM: Focuses on managing customer relationships, including sales, marketing, and customer support. It helps businesses understand and engage with their customers, track leads and sales, and provide better customer service.

ERP: Focuses on managing internal business processes, such as finance, human resources, inventory, and supply chain management. It helps businesses streamline and automate their operations, improve efficiency, and reduce costs.