Why targets backfire

Location CX targets on Google rating or review counts push managers towards what moves the number fastest: asking only happy customers, offering incentives, or pressuring customers in store. Google's policy prohibits all three, and the profile can be restricted.

What to target instead

  • A specific issue's rate at the store, such as billing-wait complaints, against its peer range.
  • Reply time and coverage for negative reviews.
  • An operational driver linked to a top issue, such as peak-hour staffing.
  • Completion of agreed actions by their dates.

Setting them

  • Start from the store's top issue.
  • Use the peer group's typical range as the reference.
  • Set a direction and a review date rather than a precise number for small stores.
  • Agree it with the store manager, with the reviews in front of you.

Reviewing

Check targets monthly with the evidence: the issue's rate, the count behind it and new reviews. Close targets when the issue is back in range for a few months.

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An example

Instead of "reach 4.5 stars", a store's target becomes "bring billing-wait complaints from 18% of reviews to the peer range of 8% to 12% by March, with a second counter on weekend evenings". The manager controls it, it cannot be gamed by selective asking, and it fixes something customers care about.

Common mistakes

  • Rating targets.
  • Review-count targets.
  • Targets based on the best store.
  • Targets without evidence.

Common questions

Can we target the rating at all?

As a network ambition, perhaps; not as a store manager's target.

What about small stores?

Use directions and longer windows rather than precise numbers.

Should targets affect pay?

Only for things managers control and cannot game.

How many targets per store?

One or two, tied to the top issues.

Checklist

  • No rating or review-count targets for stores.
  • Issue-rate targets against peer ranges.
  • Reply targets.
  • Evidence and review dates.

In short

Set store targets on specific issue rates, reply measures and drivers managers control, against peer ranges, and avoid rating and review-count targets that invite gaming.

A worked example of a target set

For a store whose top issue is billing waits: target the billing-wait complaint rate to fall into the peer range by a set month; target negative reviews to be answered within one working day; target the agreed action, a second weekend counter, to be in place within two weeks. Three targets, all within the manager's control, none of which can be met by asking only happy customers for reviews.

Explaining targets to managers

Show the manager the reviews behind the issue before discussing the target. Targets that come with evidence are accepted as fair; targets that arrive as numbers from head office are argued with. Agree the action together, and review progress with new reviews each month.

Network-level ambitions

Leadership may still want a network ambition such as a better average rating. Keep it at network level, explain that it comes from fixing the issues behind complaints and asking every customer for reviews, and track it alongside the store-level issue targets that drive it.

Doing this with Falcon

Falcon shows negative share by topic, location and month on one heatmap, flags locations with too few reviews to compare, and lets you compare any period with the one before or the same weeks last year, so a location's problem can be told apart from a network-wide one. Every number opens the reviews behind it, in customers' own words, so a comparison can always be checked.