The situation

Levara ran a 200-person B2B operation selling fundraising infrastructure to nonprofits and enterprise organizations. Their Salesforce had 45,000+ records and a sales team of 22 reps covering inbound and outbound. The Head of Sales had noticed that pipeline was healthy on paper but conversion to closed-won had been declining for two quarters. Activity metrics looked fine. Win rates were down.

The initial hypothesis was product-market fit drift: the market was getting more competitive and the value proposition needed work. Before investing in a rebrand, they wanted the data to confirm whether the problem was positioning or process.

What we found

The positioning hypothesis was wrong. When we traced deals through the full pipeline, the pattern that emerged was more specific: deals where the first rep contact happened within 4 hours of lead creation converted at 3x the rate of deals where first contact happened after 24 hours. The product wasn't the problem. Response time was.

The average response time in their data was 18 hours. But the average hid a distribution problem: 40% of leads were being contacted within 2 hours, and 35% weren't being contacted for more than 48 hours. The fast responders were producing most of the revenue. The slow responders were generating activity data that looked normal on a dashboard but was destroying conversion in practice.

The routing logic was the structural cause. Leads from two high-volume sources were being routed to a shared queue rather than assigned directly, creating a pickup race that defaulted to whoever happened to check the queue first. Time-zone coverage gaps meant that leads coming in after 4pm EST sat overnight before being worked.

The second finding: channel attribution was wrong in ways that were misallocating budget. The highest-converting lead source was being underreported because UTM parameters weren't being passed correctly through the main content form. It showed up as Direct in 60% of cases. The channel was performing significantly better than the data showed.

What changed

Routing was rebuilt to eliminate the shared queue for the two affected sources, assigning directly to reps based on territory and availability. A coverage policy was added for after-hours leads to ensure same-day contact the following morning. Average response time dropped from 18 hours to 6 hours within 30 days.

The UTM fix corrected attribution going forward and provided a corrected baseline for the previous 12 months. Budget was reallocated toward the underreported channel. MQL volume from that source increased 40% in the first quarter after the fix.

MQL-to-SQL conversion went from 24% to 48% over six months, driven primarily by the response time improvement. Revenue increased 28% in that same window, with the attribution fix enabling a budget reallocation that contributed roughly a third of that growth.