A buying signal is any observable event or piece of behavior that suggests a company, or a specific person inside it, has an increased likelihood of being open to a purchase in the near term. It is not proof that someone wants to buy from you. It is evidence that something changed in a way that raises the odds a conversation would be timely.

The idea is not new. Good salespeople have always paid attention to context: a company that just announced a new office, a contact who just got promoted, a competitor who just lost a client. What has changed is scale. There is now enough public data, funding announcements, job postings, LinkedIn activity, technology adoption records, that software can watch for these events across thousands of companies at once instead of a person noticing them one at a time.

Not every signal carries the same weight, and the right ones to track depend on what you sell. That said, a few categories show up again and again as strong indicators worth building a process around.

• Funding rounds. A company that just raised capital has budget it did not have before and pressure to deploy it toward growth. This is one of the clearest signals in B2B, especially for tools tied to headcount, sales, or infrastructure growth.
• Hiring surges. A sudden jump in open roles on a specific team tells you where a company is investing right now. A wave of sales hires suggests a go to market push. A wave of engineering hires suggests a product build out.
• Executive moves. New leaders often re evaluate the tools and vendors already in place within their first few months. A new VP of sales or a new CFO is a natural moment for a relevant vendor to introduce themselves.
• Tech stack changes. Adding or dropping a specific tool tells you something about a company’s direction and often creates a gap that adjacent tools can fill.
• LinkedIn activity. A founder or executive posting about a specific problem, a company sharing a launch, or a spike in employee engagement around a topic can point directly at a current priority.
• Contract renewal windows. Companies re evaluate vendors around renewal time. If you can identify when a prospect’s contract with a competitor or an adjacent tool is likely to come up, that window is a natural point to reach out.
• Review site activity. A company researching or comparing tools on a review platform is showing active intent, even if they have not spoken to any vendor yet.
• Event participation. Attending a relevant conference, webinar, or industry event suggests a person is actively thinking about the problem your product solves.

Any single signal on its own is a hint, not a guarantee. A company hiring one new salesperson does not necessarily mean much. But when multiple signals show up on the same account around the same time, the picture gets much clearer.

This is called signal stacking, and it is one of the most useful concepts in signal based selling. Take an account that just closed a funding round, is actively hiring across sales and marketing, and has a newly appointed VP of revenue who just started posting on LinkedIn about scaling go to market motion. Individually, each of those is a reasonable data point. Together, they describe a company that is very likely to be evaluating new tools right now, and that combination is far more predictive than any one signal alone.

Teams that build scoring models around signal stacking, rather than any single trigger, consistently see better qualified pipeline, because the accounts that clear a higher stacked threshold are genuinely further along in a change that makes them receptive to outreach.

A signal has a shelf life. The value of knowing a company just raised funding or just hired a new VP fades quickly as more vendors notice the same public information and reach out. Speed is not a nice to have here, it is the entire point of tracking signals in the first place.

This is the practical argument for automating signal monitoring rather than relying on a person to check manually. A rep checking news and LinkedIn once a week will always be behind a system that watches continuously and flags a change the day it happens.

The clearest way to see why signals matter is to compare reply rates. Cold outreach, a message sent to a company with no particular reason for timing, typically converts poorly because the prospect has no context for why they are hearing from you right now. Industry benchmarks commonly put average cold email reply rates around 5.1 percent.

Signal based outreach, a message that references a specific recent event and explains why it is relevant, performs meaningfully better. Reply rates around 13.4 percent are commonly reported for outreach tied to a real trigger, more than double the cold baseline. The difference comes down to relevance: a message that says “congratulations on the Series B, teams at this stage usually run into X” reads as informed rather than random, and prospects respond to that difference.

1. Identify the signal, the event that just happened.
2. Connect it to a specific, honest reason your product is relevant right now, not a generic pitch.
3. Reach out quickly, ideally within a day or two of the signal appearing.

None of this requires guessing. The pattern is consistent enough that building a repeatable process around it, watch for signals, stack them for confidence, act fast, tends to outperform larger but less targeted outbound campaigns.

Shaku AI is built around this exact idea. It monitors 20 signal types across your target accounts, funding, hiring, executive moves, tech stack changes, LinkedIn activity, contract windows, review site research, and event participation among them, and combines them so an account with multiple stacked signals rises to the top of your list automatically. Every lead comes with the specific signal that surfaced it and a note on why the timing matters, so outreach can go out while the moment is still fresh rather than after the window has closed.

If you want to see how signal stacking looks on your own target accounts, Shaku AI offers a free trial with full access and no credit card required.