Agentic AI: A Sales Use Case
Our previous blog post Agentic AI: Shaping the Future of Business discussed the characteristics of Agentic AI, its relationship to Generative AI as a complementary AI technology, its benefits, and overcoming challenges in implementation. In this post we will focus on a real-world Agentic AI use case, discuss how the agent accomplishes its objective, and the business impact it is designed to deliver.
Customer-focused use cases are particularly intriguing because of their “high-risk, high-reward” nature. Done well they can improve prospect and customer interaction and positively impact revenue and goodwill. Done poorly they can have the opposite effect. In this post we’ll focus on prospect interaction with the Agentic AI’s objective being to schedule well-qualified first prospect meetings.
In this real estate example, the virtual agent will accomplish its objective by answering the prospect’s questions, converse in such a way that it facilitates the qualification process ultimately scheduling an appointment for the realtor. Unlike rules-based chatbots you’ll see the inherent value of the dynamic nature of the interaction.
Here is the interface as presented on a licensed realtor’s web page:
The “Welcome!” message and prompt are meant to initiate questions or conversation. In this example the prospect who is looking for new office space started by asking if the realtor focuses on commercial or residential properties. From this point on we’ll focus on the interaction between the virtual agent and the prospect.
The virtual agent answered their initial question then prompted for additional information to engage the prospect and qualify their needs. The prospect responds with a question looking for advice on square footage, the virtual agent analyzes their question and provides a well-considered answer, prompting the prospect to share more information and another question. Dialogue is happening and the qualification process is proceeding well!
The virtual agent responds by confirming they are aware of the location and its potential, even locating a specific property that may work well given the stated needs. It then goes on to answer the prospect’s question about budget and initiates more interaction leading to the prospect asking to proceed to a meeting.
The virtual agent has successfully conversed with the prospect, captured important qualifying information, and is now able to schedule the appointment based on the real estate agent’s available schedule.
Being a trained Agentic AI solution designed to work autonomously and conversationally the solution is constructed with LLM capabilities supplemented with NLP models for sentiment and intent detection to analyze the prospect’s side of the conversation and provide guidance to Generative AI providing answers and guiding the conversation. It integrates with scheduling applications to initiate the sales meeting at an appropriate point in the conversation so it can occur at a time convenient for the real estate agent and the prospect. As part of the scheduling process the dialogue is captured and additional information from the prospect is captured to confirm their stated objective for this first meeting with the licensed realtor. Also from an integration standpoint, the solution accesses a comprehensive listing service allowing it to conversationally support prospects who want to ask about property options, what properties may fit specific needs in specific locations and at specific price points. All conversationally and without the need to log into listing services and filter for properties.
There is a lot of subtly important activity happening here that drives successful lead qualification in a very prospect-friendly way. The prospect is able to converse and receive well-considered, fact-based answers immediately on very specific questions. The realtor is being represented very professionally delivering answers and guidance on topics that in some cases are more immediate and accurate than if they were answering the questions themselves. Unlike staffing options, this virtual agent is trained to be accurate and immediately responsive on day one, operates 24/7, and through machine learning becomes more effective at answering questions as it experiences more interactions.
How Qualetics Data Machines Can Help
For businesses looking to harness the power of Agentic AI, Qualetics Data Machines provides a no-code AI platform designed to help companies more effectively build, test, deploy and monitor AI solutions tailored to their specific needs. The Agentic AI solution demonstrated in this blog post is available as a “Data Machine” template in Qualetics’ AI platform. Combining our platform with our library of over 30 analytics and AI models, Qualetics enables organizations to leverage Agentic AI securely and effectively. By partnering with Qualetics Data Machines, businesses can confidently integrate Agentic AI into their operations, driving growth and innovation while addressing the unique challenges that come with AI autonomy.