Every week, you get an overview of recommendations. Some hit the mark, others are so general they could have applied to any brand in your sector. Anyone working in marketing knows the feeling: the advice isn't wrong, but it isn't about your customer. The cause is often simple. The overview doesn't know who you are making it for. In GripIQ, you solve that with personas, because the weekly Insights take them into account. They also remember what you indicated about earlier Insights. These are two little-known features, but together they make the difference between an overview you click away and one you actually act on.

What personas are in GripIQ

A persona is a profile of a type of customer or decision-maker for whom your project is monitored. In GripIQ, a persona has a name, a description, an intent and demographic characteristics: age group, gender, marital status, education level, employment situation, social class and life stage. For each persona, you also see how many Prompts are linked to it.

You find your personas under Personas, in the same menu group as Brands, Tags and Settings. Click a persona, and the full profile opens. That page is read-only, because your personas are managed by GripIQ. Want a persona adjusted or added? Contact your account manager, who is listed at the bottom of the page.

What the weekly Insights do with them

The weekly Insights receive your project's personas as context: name, description, intent and whatever demographics have been filled in. That way, the recommendations can match your target audience. If a project has no personas, the Insights don't change and work as they always have.

In practice, this means: the more precisely a persona is described, the more the Insights can do with it. A persona with just a name gives little to go on. A persona with a clear description and an intent, for example a buyer comparing suppliers, does give the recommendations something to hold on to. We can't promise a fixed improvement: the persona is passed on as context, but that doesn't guarantee different advice.

What a good persona contains

Because your account manager fills in the personas, you help shape the content by sharing what you know. For each target group, you can answer these questions:

  • Name: choose a name your team recognises, for example the buyer's job title.
  • Description: who is this, what kind of organisation do they work in and what keeps them up at night?
  • Intent: what does this person want to achieve when they look for a supplier or ask an AI assistant something?
  • Demographics: the characteristics you do know, such as age group or employment situation.

Only pass on what you really know, and don't make anything up. A persona full of guesses steers the recommendations in the wrong direction. A short persona that is accurate gets you more than a long one you can't back up.

Insights that remember what has already been said

The weekly Insights also look back. Before writing a new overview, they look at the Insights of the past four weeks, with the status those received. The recommendations you rejected, postponed or scheduled over the past six months are taken into account too, together with the explanation you added. As a result:

  • the overview doesn't repeat itself;
  • a recommendation you have already applied or scheduled doesn't come back as a new proposal;
  • a recommendation you rejected or postponed only comes back when the reason at the time no longer applies, and then with a note on what has changed;
  • a problem that keeps showing up in the data and was never addressed is not quietly dropped, but brought back to your attention with a higher priority.

The lesson for your team: what you do with an Insight has consequences. If you reject a recommendation, you give a reason and can add an explanation. That reason helps decide what you see next week. If you postpone a recommendation, you deliberately put it aside for a while, and that reason is passed on too. If you schedule a recommendation with a date, the overview takes that into account. If you never review anything, the overview doesn't know what you do and don't want.

An example

Say you are the marketing manager at a business software supplier. Your project has two personas: a buyer comparing suppliers, and a managing director who wants a quick summary. Monday's weekly Insights take both into account.

One of the recommendations suggests publishing a comparison page. You reject it and note that the page is already planned for the third quarter. A week later, the same recommendation doesn't come in again as if it were new, because the Insights know what you decided earlier. If the situation changes, for example because the page is dropped from the planning, the recommendation can come back, with a note on what has changed.

Where to start

You don't need to install anything for this. It all starts with personas that are accurate. You get a good persona from a target audience analysis; how to approach one is explained in What is a target audience analysis? Model and example. And if you want to know how to show up in AI answers, read Generative engine optimization: what it is and where to start.

What you can do now

  • Open Personas in your project and check whether every persona has a description and an intent. If something is missing, pass it on to your account manager.
  • Review this week's Insights, including the recommendations you won't act on, so the overview doesn't repeat them next week.
  • When rejecting or postponing, briefly note why, so the Insights and your colleagues can later see the reason behind it.

Open GripIQ and go to Personas to view your target groups.