Does waiting longer between ChatGPT questions make the named brand less stable?

A natural guess about brand-naming instability in ChatGPT answers is that it should get worse the longer you wait between asks. More time means more opportunity for news, reviews, product launches, and search results to shift, so a brand named first today might plausibly fall out of favor weeks later. This study tested that guess directly, and the guess mostly does not hold.

The underlying measurement: pairs of ChatGPT answers to the same buyer question, one earlier and one later, checked for whether the same brand was named first both times. Across 172,624 total pairs, the brand named first changed in 74.6% of cases overall. To see whether this rate depends on timing, the study split pairs into three segments based on the gap between the two answers: within a week, one to four weeks, and over four weeks.

The results, segment by segment:

Within a week, out of 23,072 pairs, the named brand changed in 76.1% of cases, versus 23.9% where it stayed the same.

From one to four weeks, out of 15,733 pairs, the named brand changed in 77% of cases, versus 23% staying the same.

Over four weeks, out of 133,819 pairs, which makes this the largest of the three segments by far, the named brand changed in 74.1% of cases, versus 25.9% staying the same.

Line these three numbers up and the pattern is not a steady climb. The one-to-four-week segment actually shows the highest instability rate of the three, 77%, slightly above both the within-a-week figure of 76.1% and the over-four-week figure of 74.1%. The differences between all three segments are small, a few percentage points at most, not the widening gap you would expect if instability accumulated steadily with elapsed time.

What does this mean? The most direct reading is that most of the instability in which brand gets named first is not a slow drift that builds up over weeks. It looks more like noise that is already present within days, essentially as soon as you ask the same question a second time at all. If instability were driven mainly by slow-moving factors, like a brand's reputation genuinely improving or declining over a month, you would expect the over-four-week segment to show visibly higher instability than the within-a-week segment. It does not, within-a-week instability is already close to three in four.

This points toward the retrieval mechanism discussed elsewhere in this study: ChatGPT's answer to an open buyer question likely depends on whatever sources it pulls at the moment of the ask, and that pool of sources can vary meaningfully even within the same day, let alone the same week. If that is right, waiting longer between checks does not meaningfully protect a brand's first-mention status, because the volatility is already baked in at short intervals.

One caution: the over-four-week segment is both the largest by count (133,819 pairs, compared to 23,072 within a week and 15,733 for one to four weeks) and necessarily mixes together pairs with gaps of very different lengths, anywhere from just past four weeks to much longer. A company deciding how often to re-check its own standing should treat the three-segment split here as a rough map, not a guarantee that checking monthly versus checking weekly reveals meaningfully different risk. The weekly-or-sooner instability rate is already high enough that frequent checking buys mostly reassurance, not meaningfully better odds, that your brand stays on top.