The MQL is Dead: How AI is revolutionizing sales and marketing

If you're on LinkedIn for any length of time, you're bound to run into a think piece about how "X foundational piece of B2B marketing is dead."

And let's be honest. Most of them are reaching.

But our Founder & CEO, Kraig Swensrud , and our CMO Maura Rivera , outlined why MQLs are actually dead and how AI is transforming how B2B marketers are generating, qualifying, and converting leads instantaneously and without human oversight.

What does the traditional MQL process look like?

For years, the MQL has been a cornerstone of marketing and sales alignment. It’s a metric that defines whether a lead is ready to be handed off from marketing to sales development representatives (SDRs) for further qualification and nurturing.

The traditional process involves three phases: 

1. Lead generation: Marketers generate leads through various offers, such as demo requests, webinar sign-ups, and content downloads.
2. Lead qualification: These leads are then scored based on predefined criteria to determine if they are sales-ready.
3. Lead follow-up: Marketing Qualified Leads (MQLs) are passed to SDRs, who follow up and attempt to convert them into opportunities.

However, this process is fraught with inefficiencies.

Leads often get stuck in queues, and the follow-up times can be painfully slow, causing potential buyers to lose interest and move on to other options. We know that 78% of the time, buyers choose the first vendor that gets back to them when they're ready to invest, so speed to lead is critical in deal success.

Why isn't the traditional MQL model working any longer?

The MQL model, though effective in the past, wasn't built for today's buyers. The three biggest issues are a result of not being able to scale human SDR teams in efficient ways.

1. Slow response times: Despite the well-known 5-minute rule—which states that leads responded to within five minutes are 20 times more likely to convert—most companies take far longer. The best companies can manage follow-up within 90 minutes, but the industry average hovers around five hours, with some companies taking up to six days. This delay is a major lost opportunity.
2. Human-dependent workflows: The current process relies heavily on human SDRs who must manually assess and respond to leads. Given the volume of leads and the complexity of personalization, this approach is neither scalable nor efficient.
3. Lost leads: Leads that don’t meet the MQL criteria often fall into a black hole, being relegated to automated nurture programs that are impersonal and ineffective. These leads might still have potential, but they are often ignored due to resource constraints.

How does AI transform the MQL process?

As AI Workers enter the market, AI SDRs are quickly conquering the MQL model and scaling marketing qualified leads in ways human SDR teams simply can't. Tools like Piper the AI SDR are transforming how companies handle leads by automating the follow-up process and ensuring no lead is left behind.

Here’s how AI is changing the game:

1. Instantaneous response: AI SDRs like Piper can engage leads immediately, beating the five-minute rule without fail. Whether it's 10 or 1,000 leads, Piper can handle them all simultaneously, ensuring no delay in follow-up, and no additional headcount.
2. Scalable personalization: AI can access and analyze vast amounts of data to personalize interactions at scale. By pulling in information from various sources, AI can craft tailored messages that resonate with each lead, far beyond what a human SDR could achieve in the same timeframe.
3. Efficient lead management: AI doesn’t just work the hottest leads; it can also intelligently engage those middle-of-the-funnel and top-of-the-funnel leads that were previously neglected. This ensures a more comprehensive and efficient approach to pipeline generation.