Ronan Vander Elst, Partner and Digital Co-Leader at Deloitte Luxembourg

From the 80s standalone mainframe databases storing basic customer information to the incorporation of business-wide interactions into an integrated platform, Customer Relationship Management (CRM) systems have come a long way.

For the last decade, the ease of access to information and the boom of social media have granted an increasing power to customers, making companies shift from a product-centric to a customer-centric model. CRM has become a must-have component across different customer touchpoints, with the CRM market representing US$56 billion in 2019*.

After a rather slow evolution, CRM capabilities have recently expanded with the development of cloud-based configurable software, such as API technologies, Big Data and the emergence of Artificial Intelligence. These technologies have changed the way organizations deal with sales, service and marketing.

* “Source: Smarter with Gartner –Cloud to represent 75 of total spend on CRM in 2019”

Yet many organizations face difficulties to leverage on their CRM capabilities to a full extent and do not experience the performance boost initially expected. Three main challenges often limit their performance:

• Low adoption and/or misuse due to complex interfaces and processes, leading to the relegation of the CRM to a time consuming customer information tracking tool
• Difficulties to integrate the CRM with other business applications across the organization
• A strong data dependency requiring an accurate and systematic capture of data to properly fuel most advanced CRM functionalities

To overcome these challenges, recent CRM solutions have committed to deliver a user-friendly experience facilitating adoption. Solutions have also become extensively configurable by design to fit specific processes while offering low-value task automation capabilities, saving significant time and allowing agents to focus on what matters most.

By combining cloud computing and API oriented architecture, top CRM solutions have become the center of integrated ecosystems, placing interoperability at the core of their strategy. In addition, SaaS CRM leaders realized early on that their platforms could be further leveraged by establishing open market places such as AppExchange or AppSource. These offer the possibility to build ready-to-install solutions to any third-party partners, allowing the ability to extend core CRM functionalities and scale fast.

Ajda Alev, Senior Manager at Deloitte Luxembourg.

Lastly, data has become a vital enterprise asset. Their increasing volume and variety require companies to be able to properly collect, manage, and analyse them to take the full advantage of signals customers provide. Given their data-craving nature, leading CRM solutions are now integrating advanced machine learning, predictive analytics, natural language processing and smart data discovery capabilities, bringing AI to the mass market. Deloitte Global forecasts that this year, 70 percent of companies that adopt AI technology will obtain AI capabilities through cloud-based software.

The CRM of the future will not integrate AI as a fancy additional feature but as a transversal layer embedded across the whole CRM core capabilities.

CRM must be able to adapt to companies’ needs and processes, to learn and get smarter from every interaction and additional piece of data. Einstein, Salesforce’s AI layer, is a set of best-in-class services integrating advanced AI capabilities into the very core of the platform. Einstein acts as the agent’s personal data scientist, automatically discovering relevant insights, predicting future behavior, proactively recommending the next best actions and automating complex tasks leveraging both internal and external data.

Although AI powered CRM may present itself as the missing puzzle piece you have always been looking for, its implementation is still far from being a smooth journey. To fully benefit from CRM in the future, companies must overcome a complex set of technology, regulation, process and behavioral challenges:

• AI needs historical data to be trained and requires legacy information to be cleaned to avoid the well-known “garbage in, garbage out” scenario
• Data privacy and regulatory constraints demand maturity from the organization to assess the sensitivity of the personal data processed and the purposes of such processing
• Change is never easy, especially with new and disruptive technologies. Business acceptance and customer understanding must be supported by a concrete adoption strategy along with a complete reorganization of internal processes

A time when CRM was a simple customer database and a sales reporting tool is definitely behind us. Today, AI powered CRM aims to serve everyone—customers, sales, services, marketing and management—becoming a powerful customer Intelligence tool. It will enable companies to define sales, services, and marketing strategies with greater precision and ensure the operation efficiency to deliver the differentiating experience customers expect.