How can you use AI to route leads effectively?
Lead routing is the process of assigning leads to the right sales reps based on various criteria, such as location, industry, product interest, or lead score. It is a crucial step in optimizing your sales funnel and increasing your conversion rates. However, manual lead routing can be time-consuming, error-prone, and inconsistent, especially when you have a large and diverse sales team. That's why many businesses are turning to artificial intelligence (AI) to automate and improve their lead routing strategies. In this article, you will learn how you can use AI to route leads effectively and boost your sales performance.
AI lead routing is the use of advanced algorithms and machine learning to analyze your leads' data and behavior, and match them with the most suitable sales reps. AI lead routing can also take into account your reps' availability, skills, preferences, and performance, and distribute leads evenly and fairly among them. AI lead routing can help you avoid lead leakage, reduce response time, increase rep engagement, and enhance customer satisfaction.
-
Nate Roybal 🤖
Partnerships and Sales @ Syncari || Clean and Accurate Data, Everywhere || Dyslexia & ADHD are my superpowers
AI lead routing could mean something as simple as a decision tree in your CRM or as complex as a stand alone scoring and routing platform. For most, the complexity of needs should be balanced with the complexity of owning and maintaining a process around it. Listed from simple to implement & maintain to complex and probably expensive. - Regional and territory rules - Demographic based - Enriched - LTAM - Intent based - Automatically booked - Behavior scored - Personality matched to reps - Completely autonomous
4
AI lead routing works by collecting and processing data from various sources, such as your CRM, website, email, social media, or chatbot. It then applies rules, models, or patterns to identify and score your leads based on their fit, interest, and readiness to buy. It also evaluates your reps' profiles, schedules, and results to determine their capacity and suitability to handle each lead. It then assigns leads to reps automatically or provides recommendations for manual assignment. AI lead routing can also monitor and optimize the lead routing process over time, by learning from feedback, outcomes, and changes in your data.
-
José Braccini
Innovation Advisor | Startup Mentor | Business Development | Board Member
IA lead routing makes it possible to identify customer sentiment by monitoring conversations and provide information about the quality of the conducted call. The lead attribution can be done in three ways: • Rotational attribution: leads are allocated one by one to each team member. This process is restarted as soon as the sequence is completed. • Attribution based on the availability of the sales team OR the available hours of the sales executive. • Location or territory-based attribution. For example, a salesperson based in London may handle UK clients, speaking the language with the typical accent, understanding the market and regional culture. This creates greater proximity to the customer, positively impacting lead conversion.
AI lead routing can bring many benefits to your sales organization, such as saving time and resources, improving lead quality and conversion, and enhancing sales performance and alignment. It can eliminate the need for manual intervention, human errors, and delays in lead assignment. AI lead routing can also reduce the workload and stress of your sales managers, who can focus on coaching and mentoring their reps instead of managing lead distribution. Moreover, it ensures that leads are matched with the reps who have the best chance of closing them, based on their expertise, experience, and rapport. Additionally, it helps prioritize and follow up with the most qualified leads and avoid wasting time on low-quality or unresponsive leads. Finally, AI lead routing increases reps' productivity, motivation, and retention by giving them more relevant and valuable leads. It also creates a transparent system of lead allocation and fosters a culture of accountability.
-
José Braccini
Innovation Advisor | Startup Mentor | Business Development | Board Member
It is known that response time directly influences the increase in sales conversions. Therefore, the longer it takes to respond to a lead once they make contact, the lower the chances of closing a deal. The lead router with AI can optimize the entire distribution process, reducing response time. With fair and balanced distribution, it ensures that leads are distributed fairly and evenly, preventing any salesperson from being neglected or the sales team from being overwhelmed. As a result, there are gains in better utilization of resources invested in marketing and the sales team, leading to a consequent increase in performance and customer satisfaction with the service.
AI lead routing can be implemented in various ways, depending on your goals, budget, and existing tools. For instance, you can use a third-party solution such as Lead Assign, LeanData, or Conversica which can integrate with your CRM and other systems. If you have the resources and expertise, you can also build your own AI lead routing solution using tools and frameworks such as Python, TensorFlow, or Amazon SageMaker to customize and fine-tune the solution to your specific needs. Alternatively, you could start with a hybrid solution where AI is used to assist and augment manual lead routing. AI can also be used to provide suggestions, alerts or reports to sales managers who can make the final decision on lead assignment. Furthermore, AI can monitor and evaluate lead routing performance and identify areas for improvement.
AI lead routing can be a powerful tool to enhance your sales efficiency and effectiveness, but it also requires some planning and preparation to ensure its success. To begin with, you should define your goals and criteria in accordance with your sales strategy, processes, and culture. Additionally, you must clean and enrich your data to ensure its accuracy, completeness, and up-to-date status. It is also important to secure the data and make sure it is in compliance with relevant regulations and policies. Lastly, you should test and optimize your solution regularly by using A/B testing, split testing, or multivariate testing. Furthermore, it is beneficial to collect feedback from reps and customers to improve the solution.
Rate this article
More relevant reading
-
Sales OperationsHow can AI improve lead scoring accuracy?
-
Marketing AnalyticsHow can you use predictive lead scoring to align your sales and marketing teams?
-
SalesWhat are the most effective lead scoring models for sales?
-
Solution SellingHow do you keep up with the latest trends and innovations in AI and automation for solution selling?