Watch a new consumer segment change month by month

The task

The audiences of new categories or products tend to shift fairly early on. The early adopters of anything (electric cars, buy-now-pay-later, weight-loss drugs) look different two years later. Not understanding how a category is shifting can land you in trouble, especially when you’re trying to grow a brand. Imagine trying to convert an audience with creative, pricing and distribution all planned around an early adopter demographic that’s shifted dramatically.

Our AI Connector lets you keep tabs on those transitions. Because Morning Consult interviews tens of thousands of people a day and asks about behaviors as they emerge, a segment defined by a behavior (“currently taking a GLP-1 medication”) can be profiled every month and compared with itself over time. Ask for the profile month over month, and the answer is a set of trend lines: who the users were when you started watching, who they are now, and which dimensions are moving fastest.

Prompt

Using Morning Consult data, show me a chart of how the demographic profile of current GLP-1 users has changed month over month from August 2025 to July 2026.

The result

The AI tool defines the segment from the tracker’s own usage question, profiles it for every month in the range, and returns the trend across dimensions such as gender, generation, income, education, community type and household composition, with the monthly sample noted. For GLP-1 users, twelve months of data show a category mainstreaming in a hurry.

Finding the inflection

Trend lines show direction. An even more useful question for planning is when the shift happened and whether it’s still happening. You can ask a simple follow-up to see that view:

Prompt

Which month did the profile change the most, and has the pace of change slowed since?

The AI tool ranks the month-over-month moves and points to the step: between December 2025 and January 2026, the female share of users jumped five points in a single month, the college-educated share dropped three, and the suburban share rose two, after which the profile stabilized at the new mix for the rest of the period. Natural next questions from here:

• “What else changed about GLP-1 users in January? Compare their economic sentiment and spending priorities before and after.”

• “Profile the people who say they’re considering a GLP-1 medication but aren’t taking one yet. Is the next wave different again?”

• “How do current users index against the general population on the brands and retailers I care about?”

Keep in mind

Define the segment by a behavior the survey actually asks about. “GLP-1 users” is a clear segment because there’s a question with that answer. Segments defined by inference (“people who probably use…”) don’t exist in our data; segments defined by a response do, and the tool will tell you the exact wording it used.

Ask for the trend, then ask for the step. A monthly profile shows direction; asking which month moved most shows whether change is gradual or sudden.

Watch the sample as the segment grows. An emerging category’s user base is small early and larger later, so early months are noisier. Ask for the monthly sample alongside the profile, and treat a move that appears in one small month as a hypothesis until it holds.