Why outbound beats waiting for data to come to you

There are two ways to acquire company data. You can make it known that you are buying and wait for sellers to arrive, or you can decide what you need and go find it. Waiting is cheaper per conversation. Going out is how you end up with the dataset you actually wanted.

Inbound supply is shaped by who hears about the opportunity and who acts on it. That tends to favor certain kinds of companies: those with founders who follow AI news, those whose investors mention data licensing, those in sectors where the idea has already spread. It underrepresents everyone else.

For a lab, that skew shows up in the training mix. If most sellers are software startups from a few regions, the data teaches agents how software startups in those regions work. Agents meant for logistics, healthcare administration, professional services or manufacturing get less of what they need. We looked at this from the marketplace side in why inbound data marketplaces have coverage gaps. This post is about what to do instead.

The people who can license a company's data are directors, officers and finance leaders, and in wind-downs, liquidators and assignees. Most of them have never thought of chat logs and ticket histories as an asset. They are not searching for a buyer, because they do not know there is a market.

That matters most when data is most at risk. A company winding down has a short window before its systems are cancelled. Its officers are dealing with employees, creditors and contracts. They will not go looking for a data licence, but many will listen if someone explains, in a few minutes, that the records may be worth something and that the process takes about an hour of their time.

Outbound starts from the lab's requirements rather than from whatever supply happens to exist. That shifts several things in the lab's favor.

• Composition. A sourcing brief specifies sector, headcount, tool stack, years of history, regions, and operating or winding-down companies. The target list is built to match, so the resulting mix reflects a decision rather than an accident.
• Connection depth. Technographic data shows which companies ran on the combination of tools a lab wants, so outreach can focus on companies likely to have chat, email, tickets, code and CRM connected over several years.
• Timing. Intent signals point to companies approaching a wind-down, acquisition or tool migration, so they can be reached before their records disappear. See intent signals.
• Pace. Outreach can be scaled up or down to meet a delivery schedule, rather than depending on how many sellers arrive in a given month.
• Gaps. When a lab notices its data is thin in a sector or region, outbound can target that gap directly. Sector coverage describes how labs think about balance.

Outbound is not a mailing list. Done well, it is skilled work, and it is worth being honest about what it involves.

It takes a target list built from company and technographic data and refined to the brief. It takes reps who can explain an unfamiliar idea quickly and credibly to a busy founder or liquidator, answer the obvious questions about privacy and signing authority, and know when to step back. It takes several channels, because the person who ignores an email may answer a call, and the person who will not take a call may reply on LinkedIn. And it takes persistence, because most first attempts do not reach anyone.

This is work Martal Group has done for 17 years in B2B sales. We have more than 200 onshore sales reps across the US, Canada, the EU and LATAM, with experience prospecting 24 industries, using cold calling with a power dialer and signal-driven prospecting alongside email and LinkedIn. For data sourcing, that capability is pointed at one goal: reaching the people who can sign a data licence for a company that matches a lab's brief.

Outbound only matters if conversations become datasets. Once a seller is interested, the process is the same as for any seller: a 15-minute intro call, scope and exclusions set by the seller and annexed to the contract before any data moves, a read-only evaluation that takes under an hour of the seller's time, anonymization in house, and a review of an anonymized sample by the seller before delivery.

Every person, company, address, email, phone and account becomes a consistent token across every tool. Credentials, API keys, card numbers and government IDs are removed outright, and HR, payroll, medical and legally privileged folders are excluded by default. For the lab, datasets arrive on a rolling basis as each company completes the process, rather than in one batch at the end. The licence covers training and evaluation only, and buyers may never market to, profile, contact or re-identify anyone in the data.

Waiting for data to arrive is a reasonable way to start. It is a poor way to build a dataset with a deliberate shape. If your agents need particular sectors, company sizes, tool stacks or lengths of history, the reliable way to get them is to say so and go find the companies that have them.

To start an outbound sourcing campaign, send us a sourcing brief.