Strategic Challenge
Bland is a conversational AI platform that lets enterprises build voice, SMS, chat, and email agents on a self-hosted stack. In less than a year, the company went from seed to Series B and raised $65M, which translated directly into waves of inbound interest every time a product launch or announcement hit social media.
Each viral spike produced more leads than the team could safely triage, and there was no reliable way to separate serious buyers from noise before those meetings landed on AE calendars. The team had the classic inbound stack: a form, routing, and scheduling tool stitched together. When big campaigns spiked traffic, AEs risked seeing too many low-value meetings, while high-intent visitors who dropped off at the scheduler had no safety net. There was no consistent way to decide which leads should get straight to an AE, which needed more qualification, and which should go into sequences for later.
On top of that, Bland ran a strong PLG motion: prospects could “get started for free today” on self-serve. Enterprise companies would sign up, start playing with the product, and never get channeled into a sales conversation. The team knew there was “GTM alpha” hidden in these signups, but no process to quickly enrich, qualify, and route to the appropriate rep.
As the company grew, spinning up new motions added even more complexity. The team launched a marketing phone line where visitors could get a live call from “Blandy,” their AI agent—but for months, nothing happened with that call data after the demo ended. In parallel, an outbound SDR program was booking meetings, but handoffs to AEs were inconsistent and vulnerable to “cherry-picking”—selecting whoever would most easily accept a meeting as qualified.
All of this created real business risk. Inbound leads were unevenly prioritized, self-serve activity wasn’t consistently surfaced to sales, marketing line callers weren’t being followed up with systematically, and SDR-booked meetings weren’t being distributed fairly across AEs. The team could feel the drag: too much manual triage, too many “ghost” leads that no one owned, and no single place to see how all these flows worked together.
{{testimonial-1}}
Default Layer
Bland brought in Default first to stabilize inbound. Over time, that decision turned Default into “a really core pillar in our go-to-market tech stack,” spanning inbound, PLG, and the marketing line. Instead of three disconnected workflows, everything now runs on a single control layer.
For inbound, the contact sales form on Bland’s website is now powered end-to-end by Default. When someone fills it out, Default enriches the record using waterfall enrichment. Conditional if/else checks then decide whether the lead is qualified, which segment it belongs to, and whether it should land on an AE’s calendar, go to a different path, or be nurtured.
“Default is powering this end to end for us from the contact sales form on our website to the scheduler, to the really important conditional logic that ultimately is what keeps the unqualified or maybe more questionable meetings from landing directly on AEs’ calendars.” said Mack Caruso, Director of Revenue Operations.
Crucially, the same logic doesn’t have to be rebuilt in ten places. Self-serve signups now use a Default-powered form as well. Every signup flows into Default, is enriched, and is evaluated using shared conditions. SDRs get Slack alerts for the highest-value signups so they can “pick up the phone within a few minutes” and ask, “Hey, I saw that you just signed up for Bland. What are you hoping to build?”
Default also became the orchestration layer for more creative workflows. Bland’s marketing line now pushes call variables from the AI agent into Default via webhook. Default enriches the caller, checks fit, and notifies sales to follow up directly after the AI demo.
In outbound, SDRs log calls in HubSpot and use a Default-powered scheduling link embedded directly on the contact record. A short form determines whether the meeting should go to enterprise or mid-market, and Default then distributes meetings equitably across AEs based on shared rules, rather than letting individuals route to their “favorite” rep.
Underneath, the team now has a single place where definitions, logic, and safeguards live. In Mack’s words, “the platform is incredibly flexible. It's allowed us to solve a number of challenges in the business as we've grown or as we've realized opportunities,” from inbound handoffs to PLG to the marketing line. Default coexists with HubSpot, Salesforce, and other tools, but it’s the layer that keeps behavior consistent—one system they can reason about and change without worrying that a tweak in one channel will unpredictably break another.
{{testimonial-2}}
GTM Advantage
For Bland, Default started as a way to survive “massive waves of inbound demand” with a small team. It’s now the connective layer that runs inbound, PLG, and the marketing line—and the first place they look when they see a new GTM opportunity. As Mack puts it, “[Default] is incredibly flexible. It's allowed us to solve a number of challenges in the business as we've grown.”
Operational Wins
- Cleaner, safer routing across three motions. Default’s shared conditions now filter out “unqualified and maybe not the best use of time type of opportunities” before they hit AE calendars, while Slack alerts for scheduler drop-offs give SDRs a structured safety net for high-intent visitors who didn’t click “book.”
- Fewer manual fixes and less tool-sprawl overhead. Instead of “stitching together multiple tools… and then even more to try and understand the data picture,” Bland runs inbound, PLG, and the marketing line on one control layer. That consolidation reduces the number of brittle handoffs RevOps has to monitor and fix.
- A system they can actually reason about. Because routing, enrichment, and qualification live in Default, changes feel safer: the team can toggle conditions “in real time” as they see new patterns in demand, without wondering which hidden flow will break.
Revenue Wins
- Bland attributes net-new pipeline directly to the combination of Blandy + Default. They state, “we have pipeline that exists now that would otherwise not have existed,” and note that self-serve conversion to enterprise has “gone up” thanks to steering high-value signups into sales conversations.
- Revenue lift from focusing reps on the right opportunities. By cutting time on unqualified leads and turning new lead sources into structured, enriched leads, “revenue has gone up… [Default is] helping us generate pipeline… and creating that efficiency within the team.”
Strategic Wins
- A foundation for better attribution and forecasting. Default’s AI prompts now normalize messy UTM parameters and stamp them into HubSpot, giving Bland “end-to-end” visibility from Google Analytics through to their CRM and setting the stage for more reliable attribution over time.
- One platform to extend before buying the next tool. Internally, the mantra has become: “before you go and buy another tool, ask yourself, can I build it on Default? Because the answer for us most commonly has been yes.” That mindset turns Default from a point solution into a strategic layer they can keep compounding on.
{{testimonial-3}}
Looking ahead
The next chapter is less about adding more tools and more about deepening this foundation: tightening attribution, layering in richer analytics on top of Default’s cleaned data, and continuing to ask “can we build this on Default?” whenever a new motion appears. With a single system to capture signals from web forms, product usage, and marketing calls, Bland is set up to turn today’s operational control into tomorrow’s compounding GTM intelligence.