NTT DATA Business Solutions
Julie Hannerz | september 20, 2023 | 5 min

15 AI capabilities of SAP Sales and Service Cloud

Today many organizations are eager to harness the vast reservoir of data within their CX solutions. By leveraging AI they are able to uncover patterns, generate insights and effectively turn their CX solutions into proactive sales- and service assistants.

In this blog, CX Senior Expert Julie Hannerz provides an overview of 15 AI capabilities available or planned within SAP Sales and Service Cloud.

Presentation of AI features and capabilities of SAP Sales- and Service Cloud
Data points of working with CX solutions

Leverage AI in your SAP Sales and Service Cloud Solution

It is safe to say that AI should be on everyone’s agenda these days – especially after the launch of ChatGPT last year.

Many companies are looking into how the vast amount of data collected in CX solutions can be leveraged and how AI can help uncover hidden patterns with the aim of transforming CX solutions into proactive sales- and service assistants rather than just systems of record.

In the realm of SAP, some AI functionalities are already available or planned in enterprise applications such as SAP Sales and Service Cloud. Please note that some AI capabilities might require additional licenses in order to be used in SAP Sales- and Service Cloud, whereas the AI capabilities are included in the license for SAP Sales and Service Cloud V2.

Visualisation of AI capabilities of SAP Sales and Service Cloud

AI capabilities of SAP Sales Cloud

Elevate your sales endeavors through intelligence – by leveraging the AI-driven capabilities of SAP Sales Cloud:

  • Lead Intelligence: Lead scoring, where a machine learning algorithm identifies leads with a high potential of conversion into opportunity and/or account, thereby helping the sales reps to better prioritize their time and efforts.
  • Deal Intelligence: Or in more familiar terms – Opportunity Scoring. Here a machine learning algorithm can predict the likelihood of closing an opportunity based on past sales data. This in turn helps the sales team better prioritize their time more productively.
  • Business Text Intelligence: Leverages Natural Language Understanding (NLU) to get actionable insights such as activities from text analysis.
  • Product Recommendation (Planned): Provides machine learning based product recommendation(s).
  • Relationship intelligence: Leverages a connection to the Office 365 email server to map out who knows who in your organization and to calculate relationship strength using Hugrank (Hugrank is a relationship score between employees within an organization and an account contact person). Hugrank can be calculated for accounts, contacts, employees and relationships, and is based on the recency and frequency of email and calendar exchanges with the respective stakeholders).
  • Customer Insights: Categorizes and recommends accounts to the sales team based on configurable scores and embedded AI. Configurable scores include:
    • Customer Relationship Index (scores most important accounts by including opportunities for business growth)
    • Customer Health Index (scores accounts and uncovers potential challenges from sales perspective)
    • Signal Index (scores most important signals)
  • Opportunity Close Data Prediction (Planned): Uses machine learning to predict the expected close date of an opportunity.
  • Sentiment Analysis: Leverage sentiment analysis of survey responses to gain a deeper understanding of them.

Read more about SAP Sales Cloud

Woman looking at mobile edition of AI SAP Sales and Service Cloud

AI capabilities of SAP Service Cloud

With the AI capabilities of SAP Service Cloud you can ease the workload of your service agents and increase efficiency through:

  • Ticket categorization and priority prediction: Automates categorization and prioritization processes using text analysis. When a ticket is created either manually or based on channels like e-mail or social media, the Service Categories and Priority are automatically populated.  This will reduce the time your service agents have to spend on completing these tasks manually while also speeding up the routing of tickets to the relevant teams or agents.
  • Similar Ticket Recommendation: Based on text analysis a top 3 of similar tickets are presented to the service agent. The agent can check these tickets for possible solutions to re-apply, thereby reducing the processing time of the ticket.
  • Ticket NLP classification: Uses Natural Language Processing (NLP) to identify ticket language and sentiment. An emoji next to the incoming e-mail shows if the email is considered Positive, Negative or Neutral. Furthermore, NLP is also used to extract information from the incoming e-mail and automatically populate fields like Product ID, Serial ID and Customer ID.
  • Ticket Time to Completion: Predicts the time range it takes to complete a ticket based on the time it took to complete past tickets. Can be leveraged to optimize resource allocation and prioritization of tickets.  Also provides the possibility to communicate an estimated time to completion to the customer at an early stage of the ticket processing.
  • E-mail Template Recommendation: Recommends a top 3 of the most fitting response templates for a ticket. Instead of manually searching through all the different templates, the service agent can save time by selecting from an already filtered list.
  • Machine Translation: Translates the text of a ticket based on a pretrained machine learning model. This can help agents in global service centers to fully understand the ticket even though the customer communicates in their local language.
  • Text Summarization: Uses NLP to summarize all ticket interactions. The summary contains all relevant information from the e-mail correspondence as well as the subject. A manager or service agent assisting in the resolution of the ticket will have to spend less time getting familiar with the issue by reading the summary instead of going through (an often lengthy) e-mail correspondence.

Read more about SAP Service Cloud

Presentation of AI features and capabilities of SAP Sales and Service Cloud

Last but not least

As stated above, quite a bit of AI functionality is already available in the SAP Sales and Service Cloud and hopefully a lot more to come.

Finally, it is also important to keep in mind that AI heavily depends on data, which means that there are prerequisites related to both the amount and quality of data in your systems in order to successfully train AI models and to benefit from the AI capabilities the systems have to offer.

Read more about SAP Sales & Service Cloud from SAP 

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