A relevant audience includes people for whom the offer, the message or the relationship with the brand has real use. Not all of them will buy right away. Some are discovering the category, others are comparing, some recommend, and others take part in a decision made as a team.
Evaluating the audience means telling these roles apart, so that the next communication makes sense to the people who receive it.
The right audience starts with a situation
A maintenance service for retail spaces is not defined well enough by “people between 30 and 55.” What matters is the type of space, the person’s responsibility, the problem to be solved, the area served and when the decision is made.
In B2B, the person watching the demonstration may be the user, while someone else approves the budget. In a family purchase, the person who discovers the product may pass the information on to the person who completes the order. If we evaluate only the immediate buyer, we can overlook real contributions.
These roles are working hypotheses, checked through conversations and data that are legitimately available. We do not infer purchase intent, financial situation or other personal traits just from a profile or a reaction.
Exposure beyond your followers is only the start of the explanation
A high share of views from people who do not follow the account shows that distribution has expanded. It does not prove that those people belong to the target market or that they received the piece through a friend’s recommendation.
Meta describes Trial Reels, for example, as a way to show content first to people who do not follow the creator. It is a concrete example that a new audience can also come through the platform’s own mechanism. The feature’s availability and conditions of use are checked in the account. Source: Meta, Trial Reels.
So we have an additional question: what did people do and ask after seeing it? Aggregated distribution data and questions people ask voluntarily can help. Neither should be treated as a complete description of every visitor.
How relevance shows in reactions
Some reactions show interest in the piece. Others show closeness to a need the brand can solve. We can track the difference without turning every conversation into sales pressure.
| Signal observed | Possible interpretation | Question to check |
|---|---|---|
| Questions about compatibility or use | The person is trying to assess fit | Is the information missing from the product presentation? |
| Requests from outside the area served | There is new geographic interest | Can we serve that area, or does coverage need clarifying? |
| Shares among professionals | The piece may support a recommendation | Are relevant conversations starting, or only reactions between colleagues? |
| Many requests that cannot be taken on | The message may create the wrong expectations | Are the conditions, indicative price and limits of the service clear? |
These are interpretations to check. A precise question is not automatically a qualified lead, and the absence of a question does not prove a lack of interest.
An example where exposure says too little
A fictional example. A workshop that installs furniture in a single region publishes a visually satisfying video about its process. The piece circulates internationally. Another video, about the measurements needed before a quote, gets much less exposure but sparks local conversations about projects that can actually be done.
The first piece may have value for awareness, recruiting, partnerships or showing the quality of the work. The second may be closer to the current commercial objective. The decision depends on the workshop’s priority and resources, not on an obligation for every post to produce inquiries.
A suitable follow-up could explain the area served and the types of projects taken on, while keeping the interest in the process. We do not need to abandon the visual idea; we can give it a clearer connection to the offer.
The message can steer the conversation better
Relevance does not depend only on targeting settings. The situations shown, the vocabulary, the examples, the terms of collaboration and the destination after the click help people work out whether the offer is right for them.
“Software for efficiency” is very broad. An example about centralizing the requests a field service team receives makes the need easier to recognize. Clarity can reduce poor-fit inquiries and bring more applied questions, but the effect is checked, not promised.
There is also the opposite situation: a message that is too narrow can exclude relevant people who describe their problem differently. That is why we talk about checking and adjusting the message, not about finding the perfect wording on the first try.
From reactions to results that can be tracked
Over a period suited to the buying cycle, we can compare where inquiries come from, how relevant they are, which conversations start and which results are confirmed. We use shared definitions: what counts as a relevant inquiry, who evaluates it and when the status is updated.
A small number of inquiries can produce percentages that swing sharply from one week to the next. Incomplete data, duplicate contacts and delayed conversions call for caution. If we cannot reliably trace a link to the post, we describe it as a signal, without attributing all of the period’s sales to it.
For paid campaigns, the comparison includes the cost of getting the relevant result. For organic content, we include the time spent on production and on handling conversations. A large audience can also create a heavy workload for support, and that resource has to be planned for.
How we turn understanding into useful work
NOT MORE. can clarify audiences and messages, produce the materials, adapt the pages people are sent to and connect measurement with how inquiries are handled. We can do this directly or together with the internal team and the partners already involved.
The client validates the delivery area, the commercial terms and the capacity to respond. Responsibilities for content, distribution and sales conversations are set explicitly. That way, we can tell more accurately whether a problem lies in the communication or in how inquiries are handled.
The natural next reads are “The post did well. Compared with what?”, for choosing reference points, and “A post took off. What do you do next?”, for building the next step.