Up to 40 percent more conversions, stronger business relationships, and customer experiences that directly drive revenue – the AI Sales Agent not only boosts speed and quality in sales processes but also unlocks significant business potential. In this third part of our blog series, you’ll learn how this value translates into measurable results and how to successfully enter the world of AI agents with quick wins. CX and AI strategist Sarina Hermann shares how AI-powered lead management can become your competitive edge.
All information on getting started with the AI Sales Agent
Get detailed information on implementing the AI Sales Agent with our presentation – including the process, project scope, and your investment. Simply tick the box in the contact form.
Efficient lead management – an underrated revenue lever
Why do so many companies fail to turn leads into opportunities and ultimately into customers?
What needs to be considered from the very first touchpoint: Lead processing and business development are always about people and human reactions. Many companies underestimate the impact lead handling has on future business relationships and customer experience (CX). An unanswered inquiry, a delayed callback, or an impersonal message can create bad vibes that last – and damage the relationship before it even begins. Sometimes, a prospect chooses a competitor simply because they responded faster, more accurately, or in a more personalized way.
Being late has consequences: Missed opportunities for conversion
Why is efficient lead qualification not just the starting point for a value‑adding CX, but also an underestimated revenue lever?
Studies show that up to 30 % of all leads are lost simply because they aren’t followed up on in time. This is especially common after events and trade shows, where a large number of leads flood in over a very short period. Every day without a response reduces the chances of turning promising leads into opportunities and, ultimately, customers. The bottom line: if you follow up on high‑potential leads too late – or not at all – you hand revenue potential to your competitors.
How data‑driven lead handling with AI pays off
How can AI help improve CX from the very first touchpoint and seize new opportunities?
Our AI agent provides a data‑driven, objective basis for prioritizing leads, accelerating follow‑up, and targeting outreach more precisely. This added speed and quality in lead handling can make the crucial difference in converting prospects into customers – delivering more conversions and closings. While the AI Sales Agent primarily streamlines marketing and sales processes, its downstream impact on customer relationships – and overall business value – is enormous and fully measurable.
Introducing: valantic AI Sales Agent
What exactly is the AI Sales Agent? In Part 1, find out how the AI agent makes lead qualification up to 97 percent more efficient – and which sales tasks it can automate.
From benefit to business value: Measurable head start with the AI Sales Agent
How does the business value of the AI Sales Agent translate into numbers?
In our first use case – AI-supported lead scoring – we hypothesize that it’s possible to increase the conversion rate by up to 40 percent, meaning a 40 percent better chance of turning leads into opportunities. Over the course of a year, this translates into a 1.6 percent increase in overall conversion rate.
Which industries, organizations, or teams benefit most from using the AI Sales Agent?
The application areas and advantages of the AI Agent are not limited to any particular industry, company size, or business model. In general, this AI system is a powerful asset for any organization looking to streamline sales processes and tap into digital potential in lead handling to gain a competitive edge. It’s particularly valuable in B2B contexts, where sales teams often juggle large volumes of leads and face the ongoing challenge of following up efficiently and with precision.
AI Sales Agent in practice
How well does the new AI agent support daily work in marketing and sales? In Part 2, our Head of Market Engagement shares aha moments and key learnings from the first hands-on experience.
How to start: Getting into AI with quick wins
How can companies implement the AI Sales Agent in their organization?
We now offer the framework of our AI agent to clients – customized and tailored to their specific needs. The AI Sales Agent is a fast and low-barrier entry solution that allows organizations to take their first step into the world of AI agents. To ensure a smooth start, we guide stakeholders through a structured development and implementation process, ensuring in multiple phases that the framework meets the individual requirements of the organization.
Step by step to your own AI Sales Agent
What does the implementation process look like, and how is the AI Sales Agent ultimately integrated?
We start with scoping and specification, where we define clear objectives and determine the value AI is expected to generate. Based on that, we form hypotheses, define KPIs for validation, and outline the technical requirements for the AI system. At the end of this phase, we define the scope of the Minimum Viable Product (MVP) and derive a solution architecture that delivers results quickly.
In the second phase, we develop and implement the AI Sales Agent: The framework is configured to meet the defined requirements and connected to relevant systems, such as CRM platforms, databases, or other systems, so the AI can retrieve and deliver data.
To validate the hypotheses, we test the system under real conditions with actual leads and analyze its performance to assess whether it delivers the expected value. We then present the results, discuss optimization potential, and jointly determine the next steps to continuously improve the solution and maximize value.
Details on implementing the AI Sales Agent
Find everything you need to know about the process, project scope, and investment in our presentation. Simply tick the box in the contact form.
From kickoff to first use case: Automated lead processing
How long does it take to start using your first AI application with the AI Sales Agent?
From kickoff workshop to results presentation, we typically plan about four weeks. By the end of the process, we’ll have developed at least one AI application: automated lead scoring. This allows companies to begin with a tested use case, experiment, and then expand based on their needs. The result is not a final, set-in-stone solution, but rather a flexible base setup that can be further customized and developed.
More than AI-powered lead management: Start small, scale fast
What could the further development of the AI Sales Agent look like?
Once implemented, the framework can be adapted and expanded in virtually any direction: new features, additional system integrations, or more AI agents taking over different tasks. For example, personalized briefings could be generated to support sales calls, or automated email campaigns could be launched. The iterative approach opens up a wide range of possibilities and use cases that go far beyond basic lead qualification and processing.
Mindset trumps digital maturity: What you need to get started
What are the minimal or technical requirements to start using the AI Sales Agent?
The digital maturity of your system landscape doesn’t matter at the beginning. You don’t need a fully digitized infrastructure. Technically, you just need two things: A central data source for incoming leads, and a platform where the AI can aggregate and output its results. This could even be a simple Excel spreadsheet at first if no compatible CRM system is in place. Companies with more mature systems can connect the AI Sales Agent to existing infrastructure for deeper integration.
The guiding principle is: Start simple, experiment, then optimize step by step. More important than technical conditions are the right mindset and an open, iterative approach –gaining experience and continuously improving the process. Any additional technical needs will be worked out together during the development and implementation phases.
AI in CX isn’t an end in itself – it’s a tool and a puzzle piece in a larger strategy. We’ll soon show you how to create holistic, value-driven customer experiences with our comprehensive CX portfolio.
Written by
Sarina Hermann
Lead Consultant CX
valantic
As Lead Consultant for CX with AI expertise, Sarina is responsible for developing customer-centric CX strategies that align technology, people, and company vision. Always with a sharp eye on business impact, she sees AI not just as a tool, but as a key to rethinking CX and smartly applying automation across all customer journey touchpoints. Her mission: challenge systems, think solutions one step ahead, and build bridges for a meaningful ‘AI x Human Experience’.
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