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One of your reps has a bad week. Their closing score drops 12 points. Do you coach it?
Probably not, or at least I wouldn't. Sales data is noisy. Customers differ, leads differ, and people sometimes just have a crap week. Reacting to every number that moves is a good way to spend your whole life reacting to numbers that move. It's also a good way to drive your sales team mad.
There is a question hiding in there, though. How long are you supposed to ignore it? "Let's see if it happens again" is sensible management advice, but it's also vague. Does again mean tomorrow, next week, next month? When does a bad week stop being a bad week and become how someone actually performs?
We now have enough data to have a go at answering that. The answer looks like about seven days.
Give it seven days
We looked at more than 30,000 pairs of weekly scores across four sales behaviours and many companies and industries. These aren't weekly scores built from the two calls somebody happened to review for QA. They're based on all the calls we analysed for that rep.
The first thing to know is that weekly scores move around a lot, even with that coverage. About one in ten moved by eight points or more. A decent-sized sales team will see this often. That matters, because you don't want a manager jumping on every large move as though something important has just happened.
We then took the larger moves and followed what happened next. A typical large rise was about 12 points. After a week, roughly 60% of that improvement remained. Four weeks later, it was still roughly 60%. Large declines followed almost exactly the same pattern.
What fades from a big weekly move fades in the first seven days
Average score after a big weekly move, in points from where the rep was the week before, for rises and for falls.
That's the whole reason I'm writing this post. I first thought the interesting finding was that roughly half of a big weekly move is still there a month later. That's true. But the more interesting part is what happens between week one and week four: almost nothing.
In other words, most of the movement that is going to disappear has gone after a week. What remains is, on average, what you will still be looking at a month later.
If someone's score falls 12 points this week, I'd leave it alone. A big part of that drop may disappear without anyone doing anything. Coaching somebody on a dip that was about to fix itself mostly wastes everyone's time. But I'd look again next week. If they're still six or seven points down then, I wouldn't keep telling myself they had a rough week. The data gives me very little reason to expect weeks three and four to bring them back.
There's an important limit here. This doesn't tell us the rep changed. Maybe their lead mix changed, they moved to a different queue, the product changed, or something else happened around them. We can see that the score moved and stayed moved. We can't tell from this analysis what caused it. If I'm managing that team, that's fine. I now have a good reason to go and find out.
Up is apparently the same as down
When a rep suddenly gets worse, we're good at inventing reasons not to believe the number. Tough leads, bad luck, hard customers, odd week, let's see what happens next. When the same rep jumps 12 points after our coaching session on Tuesday, we seem to lose that healthy scepticism. Look, the coaching worked!
Unfortunately, the data doesn't share our optimism. The rises and falls are almost mirror images. Both lose a big part of the initial move during the first week, then mostly stay where they are. So perhaps the rule isn't "don't overreact to a bad week". It's this: don't believe a big move until you've seen next week, whether you like the result or not.
This also changes how I think about weekly coaching. I've argued before that managers should look at performance weekly rather than monthly, mostly because monthly averages hide too much variation. But perhaps the better reason is that weekly data gives you time to not react. You see the drop, do nothing on purpose for a week, and let the noise clear itself. When you look again seven days later, the problem has either gone or it hasn't. If it hasn't, you can dig in while the rep still remembers what changed.
With a monthly average, you don't see the move and then see what survived. You only see the result after everything has been mashed together. With quarterly QA it's worse again. A change early in the quarter can spend months quietly becoming normal before anyone asks what happened.
That's an important difference. Measuring more often doesn't have to mean reacting more often. It can mean getting much better at deciding what not to react to.
On Monday
So I wouldn't build an elaborate process around any of this. I'd look at the behaviours I care about each week. I'd flag the unusually large moves in either direction and wait seven days. If they've bounced back, forget about them. If they haven't, get curious and look at the calls.
Maybe that's one of the underrated benefits of having lots of data. You can afford to be calmer about what it tells you. Sometimes the most useful thing your data can say is to do nothing and check again next week.
CallCoach is how we score every call, which is what makes the seven-day test cheap to run on every rep rather than on the two calls somebody sampled. Try it on your own calls and see which of last month's bad weeks were still there a week later.
All CallCoach data in this post is aggregated, anonymised performance data from hundreds of thousands of calls across a variety of industries. We report the trends we spot; full statistical analysis is beyond the scope of a blog post.