One of the hottest topics in information technology today is using artificial intelligence (AI) and analytics tools to help you identify patterns which can guide you in digital transformation efforts.
To make these efforts fruitful, your first hurdle is to identify data worth mining. For many organizations, your CRM system is a great place to start. If you have used CRM such as Microsoft Dynamics 365 (formerly Dynamics CRM), Salesforce, Oracle, Adobe, SAP or Siebel for several years, you are likely to have built up a repository of data which reflects your organization's customers, vendors, and stakeholders as well as your interactions with them through customer service, sales and marketing efforts.
The leading CRM vendors are in a race to add AI and machine learning to their products. Microsoft claims that over 682,000 developers are using their Azure Cognitive Services. AI features in CRM include automated responses to customer inquiries, alerts to sales staff, and segmentation of customers and leads based on algorithms. Most of my CRM customers have already implemented similar features using workflows and business rules, but without the benefit of machine learning and sophisticated algorithms.
What can you expect AI to yield from your CRM data. Here are some potential benefits:
These scenarios may be the least interesting because they are more obvious than what AI and machine learning can uncover, if optimistic projections come true. I will illustrate these examples in more detail in future blog posts, using widely available AI and analytics tools.
To make these efforts fruitful, your first hurdle is to identify data worth mining. For many organizations, your CRM system is a great place to start. If you have used CRM such as Microsoft Dynamics 365 (formerly Dynamics CRM), Salesforce, Oracle, Adobe, SAP or Siebel for several years, you are likely to have built up a repository of data which reflects your organization's customers, vendors, and stakeholders as well as your interactions with them through customer service, sales and marketing efforts.
The leading CRM vendors are in a race to add AI and machine learning to their products. Microsoft claims that over 682,000 developers are using their Azure Cognitive Services. AI features in CRM include automated responses to customer inquiries, alerts to sales staff, and segmentation of customers and leads based on algorithms. Most of my CRM customers have already implemented similar features using workflows and business rules, but without the benefit of machine learning and sophisticated algorithms.
What can you expect AI to yield from your CRM data. Here are some potential benefits:
- Chatbots allow you to provide 24 hour customer service without staffing around the clock. Putting a chatbot in front of your Contact Us or Create Case form may help someone solve their problem or answer their question more quickly.
- Machine learning can make your knowledge base more useful than ever. Most CRM products already sort knowledge base articles by popularity and rating, but AI could help you understand your knowledge base better and create new articles to fill gaps or consolidate redundant articles.
- Email marketing and outreach could be made more efficient through algorithms that drop people from marketing list based on attributes and behavior tracking. I know that I receive many wasted marketing emails every day. Some marketing automation products charge based on the number of emails sent or the size of your customer database, so this can result in cost savings as well.
- Machine learning could uncover unknown patterns in your sales data. Your CRM may contain records of every phone call and email between you and prospects. These patterns may be different depending on the industry and your business model.
These scenarios may be the least interesting because they are more obvious than what AI and machine learning can uncover, if optimistic projections come true. I will illustrate these examples in more detail in future blog posts, using widely available AI and analytics tools.