Impulse
We’re getting angsty about what reopening means for business. Maybe we should just take a breath.
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In the two-week run-up to Zoom’s earnings release Monday, its stock fell 16% on fears of what’s going to happen when we “return to normal.”
The company synonymous with video conferencing and our “year of WFH” surprised investors, though, beating Wall Street expectations and offering strong guidance for the year ahead. So much so that the stock popped more than 10% Monday.
Everyone is a little angsty about what our future holds.
Maybe that’s because we seem to be inching closer to it: Texas is fully reopened, deodorant sales are picking back up.
As this continues, we’ll impulsively search for more data points to suggest we’re “back.” It sounds promising, perhaps even reassuring, to look for these signals.
If only it were that easy.
According to consumer sentiment study by Numerator, more than half of consumers aren’t jumping at the idea of returning to normal. More than 30% said they’ll likely be the last to resume to “normal,” and nearly 25% say they’ll follow the lead of others they know.
Whatever “back” ends up being may take a while to get here, then. And that makes reading the tea leaves more challenging than normal.
This weekend’s email started swirling in our head when we caught a tweet about the shift to digital hurting “impulse and unplanned purchases.” It may be true, but we met the absolutism of the tweet with skepticism—mostly because the same datasets that suggest those types of purchases are down also suggest that those types of purchases are up.
Example: Gum sales are down, and so are single-can sales of Coke. But Hershey’s had stronger year-over-year growth in 2020 than it did in 2019, and Coke has said its at-home business (which excludes sales generated from places like restaurants and event venues) has grown the last two quarters.
Which begs a series of questions: Are impulse buys down? Are they up? Is what we’re impulsive about changing?
The problem with responding impulsively to global data sets is they’re unhelpful in answering those questions. What can be helpful, though, is thinking more critically and finding data that is more signal than noise. Perhaps, a historical look at a category’s repeat rate—and how those accompanying repeat intervals are moving across quartiles—would be more helpful in answering such questions?
For DTC brands, this type of data is easier to get. It can also be a strategic advantage in understanding a customers’ relationships with products—and whether it’s growing or decreasing over time.
It may not be a leading indicator of when we’re “back,” but it likely is for where a brand is going.