How Taft Love drives higher lead conversion rates

When Taft Love audits a new client’s CRM and revenue operations, he often sees the same root problem: confusing systems and misalignment between teams.

The result is predictable: Leads slip through the cracks, conversion rate suffers, and no one can pinpoint why.

As the Founder of Iceberg RevOps, Taft helps growing companies align their sales and marketing systems so teams can move faster and make smarter decisions as they scale, ultimately enabling them to improve conversion rates and drive revenue.

His approach focuses on building simple systems that enforce accountability, creating feedback loops that improve lead quality, and aligning teams around shared metrics.

Here's how he does it:

1. Build credibility before making changes

Before you can fix broken systems, you need the authority to make sales and marketing teams change how they work. Taft's approach: be biased to action.

When he sees a problem, he writes down exactly how to fix it, backs it up with data, and socializes the solution openly. He doesn't worry about who gets credit or whether someone else implements it.

"If you open source all of your ideas and you just speak openly about how you think things should be...that has worked really well for me," Taft says.

When writing proposals, he starts with what decision makers care about and ties solutions directly to their outcomes. No buried leads, just clear headlines backed by data.

The result: leaders start trusting him with more authority.

"If you look around you, you're not gonna see a lot of people who just go get shit done," Taft says. "If you can be that person, there's kind of no limit to what people will give you."

This approach is what has allowed Taft to implement the systems that actually fix leakage.

2. Enforce consistent behavior with a simple lead system

One of the first problems Taft addresses at orgs he works with is “cherry-picking.”

"90% of the time reps cherry pick because they don't trust the quality of what they're receiving from marketing," Taft says. "They know that this type of lead virtually always converts well, and all these other ones are kind of garbage." In other words, sales reps work the leads they’re most confident about and let the rest sit.

His solution: force uniform behavior. Whether a rep thinks a lead is gold or garbage, they need to treat it the same way. Here’s how he implements this:

Create non-negotiable SLAs

Taft sets two rules.

1. All leads must be followed up with immediately.

2. All leads must be dispositioned within three business days. After a set number of days with no response, leads automatically move to unqualified and drop off the rep's plate.

By ensuring reps work every lead, the data shows what actually converts and helps tighten up the MQL definition upstream.

Build a clear status system

Holding reps accountable for working every lead only works if they know exactly what's expected. But Taft often finds the opposite: 30+ confusing lead statuses with names like "Jim follow up - 15" and "Sarah, bucket for February."

"They're all gonna be confusing and they're not gonna be mutually exclusive," Taft says.

When statuses overlap and no one agrees on what each one means, accountability becomes impossible. His fix: five mutually exclusive statuses.

• New – You have work to do immediately

• Attempting to Contact – First activity sent (automated)

• In Contact – Buyer responded (automated)

• Qualified – Lead converts to contact

• Unqualified – Terminal status with required reason code

How to set it up

Taft creates a "Follow-Up Status" field that lives on both leads and contacts. He uses a single shared list of values so the two can never get out of sync. He also maps these same statuses to the sales engagement platform.

Most status changes happen automatically. When the first email or call goes out, the system moves the lead to "Attempting to Contact." When the buyer responds, it moves to "In Contact." After a set number of days with no response, it moves to "Unqualified."

The CRM becomes the single source of truth. "Never again is 'I didn't get the lead alert' an excuse for not following up immediately," Taft says.

Taft also builds better alerts for reps. Each alert includes context about the lead and links to documentation. He puts unique information in the subject line so every alert starts a new email thread. That way, unread alerts always equal unworked leads.

"Once you have this simple system, it's really, really powerful. No leads get lost," Taft says.

The teams that held reps accountable to this system performed better over time. But the system did more than prevent leakage. It created the data needed to improve lead quality.

3. Use feedback loops to tighten MQL definition over time

The five-status system prevents leakage, but Taft builds something more valuable: a system that improves itself. The mechanism is simple. Reps can't mark a lead unqualified without choosing a reason why.

Taft separates feedback into two categories:

Business reasons:

• Bad timing

• Wrong fit

• Not in the ICP

• Chose a competitor

Technical reasons:

• Bad data

• Email bounce

• Fake form fills

This distinction matters because each category requires a different fix. Technical issues go to the data team. Business issues go to marketing to tighten the MQL definition.

"Once we sort of created this small window during which sales is responsible for talking to leads, we made it so that they always have to follow up with every lead they get," Taft says. "And then created a feedback loop."

Marketing can now see exactly why leads aren't converting. They fix data quality issues immediately and adjust the MQL criteria based on what actually converts.

The virtuous cycle

When the feedback loop works, lead quality improves, sales trusts leads more and responds faster, and conversion increases.

"Have the smallest subset of all these leads actually rise to the level of marketing qualified lead and get them in front of a hungry sales team," Taft says. "You've got something that's gonna snowball."

At Dropbox, Taft took this further by using AI-driven lead scoring that learned from the feedback loop instead of relying on manual point assignment.

The AI watched disposition data and constantly iterated. The result: higher response rates, higher conversion rates, better opportunity quality, and higher win rates because qualification was happening upstream.

4. Align incentives around revenue, not lead volume

When you improve the systems and conversion still doesn't improve, Taft believes the root cause is almost always misaligned incentives.

Marketing is compensated on lead volume. Sales is compensated on pipeline. The solution: align both teams on revenue.

"[If] marketing and sales get paid for the same outcome, you'll start to see them work together more closely," Taft says.

This doesn't mean abandoning upstream metrics. Marketing should still measure engagement, MQLs, and conversion rates. But the North Star metric must be revenue.

"Don't make any part of your business choose between what's best for them and what's best for the company. What's best for the company is revenue," Taft says.

When both teams win or lose together, the dysfunction disappears. Marketing stops gaming volume metrics and sales stops dismissing leads without working them. Both focus on quality.

Final takeaway

Taft's framework for improving conversion rates eliminates the gaps where leads traditionally leak: cherry-picking, confusing systems, poor feedback loops, and misaligned incentives.

At Dropbox, his approach more than doubled MQL to pipeline conversion rates.

The system Taft built manually is what Spara delivers automatically. Instant engagement when leads arrive, automatic context gathering, intelligent routing, and built-in feedback loops that eliminate leakage.

Modern revenue operations aren't about making reps work harder. It's about building systems that make the right actions automatic and conversion inevitable.