CRM and Artificial Intelligence

CRM vendors are increasing their investments in AI technology and making it available in their CRM platforms to support decision making and to trigger actions.

AI encompasses machine learning and deep learning as well data science methods. It is closely linked to the field of data analytics.

AI is about thinking machines. Data is ingested and patterns are detected using statistical models. These patterns can be used to predict behaviour and a host of other outcomes.

These benefits include predictive scoring (lead scoring), forecasting (predict future revenue), recommendations (for cross sell purposes) and early warning systems (for retention). In other words, AI will eclipse what generic algorithms offer, will enhance salespersons’ intuition and will intelligently monitor customer activities.

Other benefits include chatbots, virtual customer assistants, intelligent social media monitoring and automatically logging customer interactions.

Having made the investments the software marketing machines are kicking into high gear so there is an element of hype. However, the benefits for successful early adopters could be significant so be on the look-out for opportunities to experiment with the ever-expanding and quickly maturing AI toolset.

Finally, as always, as with all things CRM the quality of the data will make the difference between a mediocre outcome and a great outcome.

CRM (Artificial Intelligence) AI vendors and tools include:

  • Conversica – automated sales assistants
  • Introhive – data automation and sales acceleration
  • Salesforce.com Einstein – AI built into Cloud products
  • DigitalGenius – automate customer service
  • Microsoft Cortana – marketing, sales and service analytics solutions

Zaheer Ismail

CRM and the Cloud

CRM in the Cloud or Cloud services refers to CRM software applications which are hosted on the Web and made available through a Web Browser.

In this way there is no need to manage hardware and software on premise.

CRM and Big Data

Big data, in the context of CRM, relates to large volumes of data used for (mostly predictive) analytics.
Data can be collected from various sources including customer channels, transactions and other customer activities such as product usage.

By applying analytics to these large volumes of data customer patterns, associations and trends can be identified. This can then be used to predict behaviours and outcomes.

Benefits can include better decision making, predictive modeling, and benchmarking.

This means that, for example, Marketing, Sales or Service reps can be equipped with insights to identify hot leads, close sales faster, predict when service issues can blow up.

Marketing functionality

CRM Marketing refers to tools or features which automate or help manage marketing processes.
This could include:

  • Campaign management
  • Lead management
  • Web and social media management
  • Multi-channel customer journey management

CRM software applications

A multitude of software solutions have been developed to manage customer relationships.

While there are differences between these applications there are a number of common features which provide functionality to manage key aspects of the customer lifecycle.

  • Marketing
  • Sales
  • Service

Social, mobile and analytics (including big data) are new generation features.

These solutions address the key customer management processes: targeting, acquisition, retention and collaboration. Underlying these pillars and core to the success of the organisation and the CRM application is understanding the customer and managing the experience.

Getting the most out of your CRM implementation

Key areas to focus on when implementing or improving a CRM system.

  • What CRM-related problem are you trying to solve? Focus on these rather than all available features
  • How will you incent employees to use the CRM system, you need to answer the ‘What’s in it for me?’ question
  • Who will sponsor and continue to back and promote the project?
  • Is the application easy to use? especially compared to what is currently being used?
  • Is there an adequate training and refresher program in place?
  • How will you ensure that the data will be kept current?
  • What other systems and tools can be integrated with to make it more useful? Email and calendar tools, ERP/accounting, human resources, social media, management information, etc
  • Is the CRM application accessible via a mobile device?
  • Think about how would you analyse the data in the application using Analytics tools to improve customer satisfaction, pipeline conversion, customer engagement, etc

Zaheer Ismail

Business objectives

When implementing a CRM application focus of the business objectives to be achieved.

In the beginning it makes good sense and aids adoption to only focus on achieving a few key objectives.

The choice of these objectives depends on the most critical needs of the business relating to customer relationship management.

Executive oversight should provide input to set a vision for customer relationships, prioritize the right relationships and assign metrics that measure relationship activity not just sales activity.

Managing change

When embarking on a CRM programme consider the following:

  • Are the business needs driving the change or is the technology driving the change?
  • Have the people, process and cultural dimensions been accounted for?
  • Is there a change management plan in place to drive the implementation?

The change management plan should include dealing with resistance to change, executive support, messaging to end users and other interested parties, and defining metrics to measure adoption and success.