This lesson covers using AI during the Opportunity to Quote stage within SAP Customer Experience solutions, in particular SAP Sales Cloud and SAP Commerce Cloud.
Using AI during the Opportunity to Quote stage includes:
- predicting opportunity conversion
- personalizing quotes
- optimizing pricing
- providing real-time support through chatbots, and
- automating proposal generation
This helps improve efficiency, accuracy, and effectiveness, leading to better conversion rates and increased revenue.
Let’s explore the various ways in which AI can be used:
- Predictive opportunity scoring: AI can analyze historical data to predict the likelihood of an opportunity converting for a customer. This helps sales teams prioritize their efforts and focus on opportunities with the highest potential to close a deal.
- Personalized quoting: AI can analyze customer data and preferences to create personalized quotes that are tailored to each individual lead. This can improve the chances of converting leads into customers by presenting them with quotes that are more relevant to their needs.
- Forecasting and pricing optimization: AI can analyze market trends, competitor data, and historical sales data to optimize pricing strategies and forecast potential revenue from different quoting scenarios. This helps sales teams make more informed decisions when creating quotes and negotiating deals.
- Intelligent chatbots: AI-powered chatbots can engage with leads in real-time, answer their questions, and provide them with relevant information during the quoting process. This can improve the overall customer experience and streamline the quoting process by providing instant support to leads.
- Automated proposal generation: AI can automatically generate and customize proposals based on the information provided by leads, saving time and effort for sales teams. This can help streamline the quoting process and ensure that leads receive proposals quickly and accurately.
Overall, AI can help improve the efficiency, accuracy, and effectiveness of the opportunity to quote stage within the Lead-to-Cash process, ultimately leading to better conversion rates and increased revenue for businesses.
The implementation of generative AI within Sales Cloud is designed to support sales professionals by offering concise and practical insights. This innovative AI functionality streamlines data analysis and enables personalized interactions to enhance relationship-building and sales effectiveness.
Features such as account summarization, contact summarization, and talking points, aim to automate the process of gathering and interpreting vital information about clients and contacts.
This advanced AI capability can provide sales representatives with instant access to comprehensive client summaries, including key contacts, recent news, and potential opportunities for upselling, thereby empowering them to make informed decisions and effectively engage with major clients.
Furthermore, the AI-generated contact summaries offer a snapshot of a new contact's background and their relevance to a salesperson's efforts, facilitating personalized and impactful interactions.
The integration of generative AI in Sales Cloud not only simplifies data analysis but also enables sales professionals to focus on core selling activities by providing quick and valuable insights.
Using AI during Opportunity to Quote Examples
Let’s see some samples:
Account Summarization Sample: Imagine you're a salesperson about to engage with a major client. Our AI tool can instantly analyze a wealth of data, condensing it into a brief, informative summary.
For example, when you open an account, you might see a summary like this: "XYZ Corporation - Industry Leader in Tech. Key Contacts: John Smith (CEO), Sarah Johnson (CFO). Recent News: Acquired ABC Inc. Big Opportunity: Upsell software solutions to optimize their new acquisition's operations".
Contact Summarization Sample: When you're about to reach out to a new contact, our AI provides you with a snapshot of who they are and their relevance to your sales efforts. Imagine you're contacting a potential client.
The AI-generated contact summary might look like this: "John Smith - CEO of XYZ Corporation. Key Interests: Cloud Solutions, Cost Reduction. Recent Activity: Attended our webinar. Personal Connection: Graduated from the same university as you".
Let’s look at an image with current SAP Sales Cloud AI capabilities:
Using AI during Opportunity to Quote Stage
Using of predictive AI in Commerce Cloud to enable real-time personalization, recommendations, and merchandising aimed at driving conversions.
It includes Intelligent Selling Services that use AI to anticipate and automate product recommendations to deliver personalized shopping experiences. The AI-driven product recommendations analyze purchasing patterns and trending products to suggest related items. The system can provide specific product recommendations tailored to the customer's preferences and also display related products to offer more choices.
Also, the AI can identify buying patterns from customer data and proactively recommend "buy it again" products based on those patterns. This functionality not only provides convenience to the customer but also enhances repeat sales.
These are some samples of AI usage for Commerce:
- AI-Driven Product Recommendations: AI analyzes a wealth of data, including purchasing patterns, trending products, and related items.
For instance, consider a customer who has previously bought a camera. Our AI can suggest relevant accessories such as lenses, tripods, and camera bags based on the purchasing history and what's currently trending among other customers.
- Upfront Specific Product Recommendations: Imagine a scenario where a customer is browsing your online store. Our system can immediately recommend specific products tailored to their preferences.
For instance, if a customer has a history of purchasing athletic shoes and is currently searching for running shoes, the system can suggest the latest models from their preferred brand or even cross-sell with related products like moisture-wicking socks or fitness trackers.
- Display of Related Products: Go beyond just one-to-one recommendations. AI also displays related products to offer customers more choices. Think about someone looking for a smartphone. Our system can not only recommend the smartphone they initially clicked on but also present complementary accessories like screen protectors, cases, and wireless chargers.
- Identifying Buying Patterns and Timely Recommendations: AI excels at identifying buying patterns from customer data.
For instance, if a customer regularly purchases printer ink every two months, our system recognizes this pattern. As a result, we can proactively recommend "buy it again" products when the customer is likely due for another purchase, ensuring they never run out of essential items. This not only provides convenience to the customer but also boosts your repeat sales.
The following image summarizes current SAP Commerce Cloud AI capabilities:
Summary
In this lesson, we have examined the sample use cases for AI during the Opportunity to Quote and how SAP Sales Cloud and SAP Commerce Cloud can use AI to improve them.