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When the market is challenging and the flow of fresh leads slows down, many sales directors shift their attention to both careful planning and clear communication with leadership to ensure sales remain as successful as possible.
Although your sales team isn’t bombarded with new leads right now, you likely have a pool of leads that haven’t been quite ready to commit to a sale.
These aged leads are more valuable when there aren’t as many new leads flowing. Use the time and resources you have now to maximize aged leads with improved AI lead nurturing.
Accessible applications of AI help sales teams prioritize each aged lead to guide data-backed sales activities and offer predictive analytics for optimized sales outcomes.
Overcome the common lead nurturing challenges of working aged leads
In the past, lead nurturing might’ve taken a backseat as your sales team focused on new leads flowing in. If a lead didn’t respond positively during initial outreach, you could’ve dismissed or lost track of them.
Now, as inflation rises, sales slow, and consumers hesitate, you’ll benefit from shifting your sales strategy to meet aged leads where they are and focus on guiding them to conversions.
Common lead nurturing challenges sales teams face
Aged leads are more valuable now, but the original obstacles of working them remain.
The bad news? You probably relate to these common lead nurturing challenges:
- Unsure how to prioritize aged leads
- Not knowing whether leads will convert or if you’re wasting time and resources
- Difficulty keeping lead data up-to-date and maintaining context for each relationship
- Facing ongoing competition if leads aren’t exclusive
- Not having time or resources to manage lead nurturing campaigns
So what’s the good news? You don’t have to struggle with or avoid working aged leads anymore. Many of these obstacles are now simple to overcome with advancing AI technologies.
The role of AI lead nurturing in maximizing aged leads
Now that AI has essentially become mainstream, more software is available that integrates with common lead management systems to benefit sales operations.
These affordable, production-ready applications of AI help sales directors navigate challenging market conditions by revolutionizing lead nurturing to increase the likelihood of conversions — among both fresh and aged leads.
Let’s dive into the top ways AI lead nurturing helps sales teams convert and maximize aged leads while dissolving previous lead management challenges.
With AI lead nurturing, sales teams prioritize high-potential leads effortlessly with ongoing, automated data and behavior tracking.
AI applications for sales operations use machine learning models to measure several complex dimensions for each lead, including their demographics and ongoing behaviors. The models then use this information, and your historical lead data, to predict which aged leads are qualified and most likely to close a sale.
This informs lead scoring and lead distribution with capabilities for ongoing lead tracking and automated sales team alerts. And the machine learning models continuously learn on their own to make predictions more and more accurate over time.
- Guide to Predictive Lead Scoring and Why Most Lead Scoring Models are NOT Predictive
- Why AI Lead Scoring is Essential for Raising Conversion Rates
Advanced analytics and data management
AI’s use of machine learning models can also be applied to several other data points within the sales and lead nurturing process. Through advanced, predictive analytics, your entire team has access to information that reveals opportunities that were previously hidden in your data.
Use your lead and sales data to gain insights into sales forecasting and consumer trends and patterns. Anticipate market shifts and intelligently adjust sales tactics with predictive decision support that provides insights beyond what has ever been possible with manual data management.
Improved customer experience
Consumers now expect a personalized experience when making a purchase decision. AI provides advanced personalization combined with automated segmentation to better sort, target, and engage a wide range of leads, simplifying many steps of the lead nurturing process.
As leads flow into your system and their behaviors change over time, AI can help you sort them intelligently and automatically into targeted segments. Throughout their extended decision process, AI helps you personalize communications and steps to meet leads exactly where they are currently while helping to guide them to a sale.
With an improved customer experience, you’ll see better lead engagement that outdoes your competitors.
Other AI applications like chatbots, virtual assistants, and automations are now available to streamline interactions with leads. These tools use sentiment analysis and Natural Language Processing (NLP) to interpret lead communications intelligently, collect lead data, and even push leads through to the next phase of the sales funnel.
They provide instant responses to lead questions and concerns, while also measuring how qualified each lead might be. They can help you automatically schedule meetings between aged leads and the sales team, alert the team of changes in prioritization, or trigger automated communications that are relevant to the interactions had with leads.
These reduce repetitive tasks salespeople have had to previously manage manually, which also lessens the human errors that go along with it. And they make it possible to provide quick, relevant information to leads for improved engagement.
5 practical steps to implement AI lead nurturing
The many benefits of AI may motivate you to add the goal of improving lead nurturing to your ongoing sales plans as you navigate the current market.
Make the most of your sales operations by investing in and implementing technology that is crucial to overcoming lead nurturing challenges. These are the 5 steps you need to implement AI and start converting aged leads:
- Look at your current setup: Assess current lead nurturing processes and software to know what’s working, what your pain points are, and what needs you have to improve working aged leads.
- Research new options: Once you’ve established what you need, research and demo AI software to find the right fit that will help you overcome lead nurturing challenges efficiently.
- Communicate needs and benefits: Get buy-in from leadership by painting a clear picture of how investing in AI will streamline lead management, increase conversion rates, and improve ROI.
- Integrate AI tools into your process: Choose AI software that integrates into your current processes. Ensure all team members that will use it are trained to maximize its effectiveness.
- Measure and fine-tune: As you begin to use AI in various parts of your sales process, assess how it’s going and dedicate time to adjust where needed to establish a smooth transition into using AI lead nurturing.
Are you ready to maximize the value of your aged leads?
If you know that data-backed prioritization, advanced analytics, improved customer experience, and a streamlined AI lead nurturing process could improve your sales then it’s time to adopt AI technologies that have become widely accessible.
By finding AI applications that integrate with your current lead nurturing and lead management system, you’ll not only optimize aged leads and close more deals, but you’ll also get ahead of your competitors that are facing the same challenges you’re experiencing in this market.
Our established machine learning models can guide your sales team to prioritize the best leads, sending them to the right salespeople, at the right times for maximized likelihood of conversion. We can also develop custom models to meet the specific complex needs of your business. Schedule a demo to discuss your lead management needs with us.