Use cases

A signal that nothing follows from is an entry in a list. The value only arises through the chain behind it: an event is detected, mapped to a company, checked against the ideal customer profile, prioritised, handed to a responsible person – and that person then does something specific. Break one link in that chain and the whole effort was wasted.

This page describes the use cases that have proven themselves in practice, and the organisational part that is usually underestimated. The terminology is under fundamentals.

Sales prioritisation

The simplest and most effective way in. Sales has a list of possible contacts that is longer than the time available. Intent signals do not change who gets approached, but in what order.

In practice it looks like this: from the accesses of the last few days, a list is generated of the companies that were there repeatedly or unusually deep. That list is reconciled with the CRM – existing customers, open deals and already-worked accounts drop out. What remains goes to sales as a daily list.

The appeal is that no new tool is needed in the sales routine. The order of an existing list changes, nothing else. That is also why this use case fails at rollout least often.

Account-based marketing

ABM aims marketing at a fixed list of target companies rather than at a segment. Intent signals supply the timing: the list exists anyway, the question is which accounts are currently moving.

Four things have to come together. The accounts have to fit the offering, which is a decision that precedes any data analysis. The timing comes from the signal. The message has to match what was researched – someone looking into interfaces does not need a brochure about market leadership. And the channel has to actually reach the people involved, which depending on the industry can be ads, email, telephone or a conference talk.

The most common mistake: the target account list is generated from the signals rather than the other way round. Then you end up prioritising companies that happen to be very active online.

Targeting ads – and excluding

On platforms with company-level targeting, audiences can be built from company lists. A list of currently active accounts is a usable basis for that, as long as it is refreshed regularly.

The reverse direction is underrated. Exclusion lists often save more than an additional audience brings in: existing customers who do not need a new-customer ad, open deals, competitors, agencies, job applicants. Every one of those clicks costs budget and delivers nothing.

Content and website

When it is known which industry an access comes from and which topic is currently being read, content can be tuned to it: matching references first, an example from the same industry, a datasheet instead of an overview.

Two caveats belong with that. First, personalisation only works when there is enough material – three references cannot sensibly be spread across twelve industries. Second, it is a change to the site like any other and should be tested accordingly. A personalised page that performs worse than the general one is no rarity.

For the landing pages behind campaigns the usual rule applies: they have to deliver on the expectation raised beforehand.

Existing customers and churn

The least used case, although it is often the most valuable. Signals do not only come from prospects. When an existing customer suddenly opens your pricing page, your cancellation terms or a competitor’s pages, that is a hint. Likewise when a customer reads up on a product they do not yet have.

Both lead to a call that sells nothing but asks whether something is not right.

The outreach

This is where most projects come apart, and not on the technology. “I saw you were on our pricing page three times yesterday” is a sentence that ends a conversation before it begins. Even where the processing is lawful, it comes across as intrusive in that moment.

What works is using the signal as a selection criterion, not as conversational content. The signal determines whom you approach and about what – not that you were watching. So instead of “you were on our site”, an opening that fits the topic researched: a specific question, a pointer to a similar case, an invitation to something relevant.

The rule behind it is simple: if the sentence would be uncomfortable to say in the conversation, do not use it.

Prioritising on two axes

For day-to-day work, a grid of two dimensions is enough: fit with the ideal customer profile, and strength of the current signal.

High fit and a strong signal belong in the hands of sales immediately. High fit, weak signal is a case for marketing – stay known until something moves. Low fit, strong signal is observed but not worked; this is where most wasted effort comes from. Low fit and weak signal drops off the list.

This grid is deliberately coarse. It only gets finer once enough closed deals exist to check which signals actually correlate with wins.

Setting up a pilot

A project that begins with a platform rollout often ends with a platform and no result. A narrow trial makes more sense:

• One use case. Sales prioritisation suits best, because the result is immediately visible.
• One fixed segment. One industry, one size band, one region.
• A fixed duration. Long enough for meaningful volumes, short enough to reach a decision.
• A metric defined in advance. What should change, and how will you measure it?
• A named person who works the list. Without ownership, nothing happens.

What matters is the expectation about timing: with long procurement cycles, the effect on closed deals only shows after months. A four-week pilot can therefore only test intermediate measures – reachability, conversation rate, quality of the list.

What gets measured

The meaningful comparison is between worked signal accounts and the previous way of working:

• Share of contacted accounts that turn into a conversation
• Share of conversations that turn into a qualified opportunity
• Time from first approach to close
• Average order value in comparison
• Share of the list that turns out to be unusable

The last figure is the most honest. If sales hands back half the list as unsuitable, the model is wrong, no matter how high the scores look.

Common mistakes

Evaluating too many signals at once before one is understood. Setting up alerts nobody reads because they come too often. Handing the list to sales without explaining where it comes from – then it does not get worked. And attributing results to a method although three other things were changed in the same period.

The B2B intent signals entry page describes the scope of the topic. If you want to set up a pilot and are wondering where to start, drop us a line – you can also book a slot directly there.