A number of CRM applications have come to prominence and will continue to grow in 2019. Marketers now see marketing analytics as a key business requirement. It delivers a competitive edge for them.
AI has risen in importance across all four CRM functional areas. Mobile also stays in top 10 among customer service, sales and marketing. But the area wherein AI is receiving highest investments is customer service. Real use cases have come to prominence, over experimentation and proof of concept (POC’s).
Machine learning and Deep Neural Networks (DNN) technology is taking rapid strides across areas such as customer service and sales. The facts are as and according with Gartner’s study – What’s Hot in CRM Applications in 2018. Gartner comes up with the results after closely analyzing the areas in which their clients have expressed maximum interest in. It gives the industry an indicator into the technology solutions that are in maximum demand.
For marketing, the hottest CRM applications priorities include marketing analytics, multichannel marketing hubs, customer data platforms and journey analytics. Similarly for sales, the most important trending technologies include sales predictive analytics, price optimization and management, and digital content management.
Among the recent most important customer service technologies are AI/Chatbots/VCA, integration of channels and case management/problem resolution. Similarly for digital commerce, the most in demand technologies include personalization, API-oriented architecture and AI.
The most preferred cross-CRM technologies include master data management, customer analytics, customer engagement hub, and voice of customer.
Interest in marketing analytics is soaring
CMOs of different enterprises are nowadays on a lookout to get measurable returns, in terms of revenue, pipeline growth and lead generation. In such a situation, the interest in marketing analytics is particularly high. Analytics and data driven results bring about a change in the process of decision making and give direction to marketing strategies. They nowadays are seen as quintessential requirements for a business’s success.
The metrics that an enterprise chooses to go ahead with essentially has a strong bearing over their future.
Importance of AI and ML
Artificial Intelligence (AI) and machine learning (ML) have bought around a revolution in way of selling.
Salesforce Einstein and intelligent agents that are comparable bring value to the sales cycle. This brings us closer to the era of futuristic AI enabled selling.
Salesforce Einstein is loaded with the capacity to scale across all phases of customer relationships. Even while price optimization and management is a decades old core technology, AI and ML algorithms have given it a boost that was much called for. These algorithms have enabled the technologies to bounce back to prominence and have rendered a significant effect over their popularity.
Sales teams come across guidance over the products that are most profitable to sell in real time. This is enabled by Salesforce Einstein and AI-powered apps that are comparable. Marketers also get a fair idea regarding optimal prices that must be changed and the deal terms that boost the odds of closing deals.
Over a global scale, CPQ (Configure, Price, and Quote) is now viewed strategically, as an integration of CAD, PLM, CRM and ERP, along with price optimization systems. When integration is planned and carried out strategically, enterprises grow faster as compared to their competitors. CPQ helps delivers the next generation of products, which are smart and connected.
Streamlining customer service
We nowadays come across a number of instances wherein organizations launch and implement pilot AI projects. They work towards streamlining customer service in a number of ways.
This is a kind of contextual intelligence. Customers are recommended suggestions based upon their service histories.
ChatBots is another prime AI technology that has deep implications over online customer service. It adds to the Net Promoter Scores (NPS).
Senior marketing teams of various enterprises have the opinion that predictive analytics and AI technologies such as ChatBots help unleash the true value of NPS. NPS then reflects over a number of metrics of customer profitability, including Customer Lifetime Value (CLV).
