Find the person.
Understand the account.
Emailcontact@example.com
Phone+41 •• ••• •• ••
LinkedInDecision-maker identified
A practical way to distinguish research assistance, verified evidence and human responsibility in an outbound campaign.
Emailcontact@example.com
Phone+41 •• ••• •• ••
LinkedInDecision-maker identified
Research can involve a large amount of repetitive reading and classification. AI can help organise company information, summarise context and prepare draft hypotheses. A fluent summary is not evidence by itself. Important facts need a source and a verification step before they influence targeting or appear in outreach.
A company announcing a new office is an observable fact. Assuming it needs your product is an inference. Both may be useful, but they should not be confused. The research brief should preserve that distinction so the message does not turn a plausible hypothesis into an unsupported claim about the prospect.
AI can help prepare variations for different personas or sectors. The underlying proposition, proof and proposed next step still need to be approved. Human review should check that the message is relevant, accurate and natural, and that personalisation is based on information that genuinely matters to the business conversation.
A reply changes the account context. It may identify another contact, clarify timing or explain why the offer is unsuitable. Treating every response as a trigger for the same next message loses that information. The operating model needs someone accountable for understanding the reply and choosing an appropriate action.
The useful test is whether research is more reliable, decisions are clearer and follow-up is more coherent. Tool volume is not a commercial result. LGS’s AI-assisted research service is scoped around those tasks while keeping targeting and outreach responsibility with people.
Let’s find the right companies, start the right conversations and build your Swiss pipeline.