If you work in sales, you know leads are like having gas in a car. Without them, the engine can’t run. When they get too low, you don’t go as far. But when there’s enough in the “tank,” your ability to drive seems endless.
However, drumming up prospects doesn’t look the same as it did three to five years ago. Similar to other core business functions, lead generation is being transformed by artificial intelligence. Whether it’s handling after-hours follow-up tasks or identifying consumer intent, AI is expanding sales teams’ ability to target, nurture, and convert. Let’s look at four industries where technology is changing how teams generate leads.
1. Automotive
In the automotive industry, the problem usually isn’t with the number of leads. It’s how many sales reps can get to in time to turn initial interest into a sale. The pipeline is there, but those prospects may lose interest if someone doesn’t reach out fast enough or at the right time.
AI tools are helping teams convert more car sales leads by increasing appointment-set rates by 25% and closing rates by 26%. These solutions integrate with customer relationship management databases, schedulers, and dealer management systems. The technology knows what vehicles are on the sales floor, what financing options are available, and the prospect’s service history with the dealership. It can even figure out a trade-in deal using the lead’s current vehicle.
Since AI can operate 24/7, it bridges the gap between tech and human abilities. It doesn’t replace a face-to-face conversation with an actual rep. But it does optimize human-to-human interactions. AI books appointments when a rep’s gone home for the day, confirms a specific vehicle is available, and lets a rep pick up where AI left off. In short, AI lowers the chances of a lead going cold or dropping out of the pipeline.
2. Real Estate
Technology has been reshaping the real estate landscape for a while now. It used to be that you had to contact an agent first to know what properties were on the market and get the specs. A real estate office was also your go-to source for local market data. They alone could tell you what average list prices were and whether it was a seller’s or buyer’s market.
Real estate apps shifted this dynamic. Pull up one of the more popular apps, and you can browse through properties online, take virtual tours, and calendar in open houses to attend. You can see how your local market is performing, get an overview of comps, and get estimates on what your home could sell for.
While these platforms are using AI, the technology is also transforming how agents get their leads. Before, they waited for the calls to come in and expanded their networks through existing relationships. Those tactics still exist, but AI in real estate has started to analyze public and behavioral data to pinpoint which homeowners are most likely to sell.
This identification happens before prospects pick up the phone. It occurs before they send an email or fill out a contact form. Real estate agents and brokers can be selectively proactive instead of using a broad-based approach.
3. Financial Services
When money’s involved, the risk of fraud increases. Sales teams working in the financial services industry probably know this better than anyone. Insurance also falls under the umbrella of financial services, particularly when carriers are writing policies for annuities and other investment products.
One of the issues reps run into is the ability to determine which leads are fraudulent or unqualified. These individuals may not be who they say they are and may misrepresent their backgrounds. An applicant for a mortgage might look qualified based on their application. They make the right amount of income, and the monthly payment checks the affordability boxes.
But further investigation uncovers a debt-to-income ratio that shows the mortgage would be too much of a strain. Plus, that income hasn’t been steady for long enough and comes from unverifiable sources. Furthermore, their history of paying creditors is spotty at best.
AI is able to assemble and analyze this disparate data more quickly when generating a customer lifetime value score. Sales teams can improve the speed and accuracy of their business decisions, so they don’t waste time or expose the company to unnecessary risk.
4. B2B Software
In the B2B software arena, AI is changing how leads get identified and ranked. Like the real estate sector, predictive analytics comes into play. AI-backed tools can analyze online behaviors to pinpoint which businesses might be looking for SaaS solutions. These tools can also forecast with greater accuracy which companies in existing pipelines are most likely to convert.
Predictive analytics examines how successful deals have moved forward, identifying certain behaviors and triggers that resulted in conversions. Instead of humans relying on memory, intuition, and pattern recognition, technology puts the puzzle pieces together faster. Missed opportunities are less likely to happen.
Simultaneously, AI that is integrated into sales pipelines can help personalize and manage outreach. Touchpoints go out to the correct contacts at ideal milestones. These communications aren’t generic, either. AI puts various details together, such as the correct contact information for top leads, to make each outreach relevant and highly personal. It’s not an email or direct mailer using the spray-and-pray approach.
AI’s Role in Transforming Lead Generation
Connecting marketing performance to business outcomes is a struggle for 85% of B2B marketers. The volume of prospects doesn’t necessarily translate to revenue on the books. While not all sales teams operate in a B2B market, this statistic underscores how it’s really about the quality rather than number of leads that come in.
AI is directing sales teams’ efforts toward leads most qualified and likely to convert. Instead of spinning their wheels, reps gain the traction that influences the bottom line.
