◆ Google Looker

Create positive experiences for Looker users

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskGenerate a report showing customer lifetime value for all customers acquired in the last six…+
Generate a report showing customer lifetime value for all customers acquired in the last six months, segmented by acquisition channel.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptThe marketing team needs to see how their campaigns are performing. Make this dashboard…+
The marketing team needs to see how their campaigns are performing. Make this dashboard engaging and easy for them to grasp the impact of their spend. Focus on key metrics like conversion rate and ROI, and show month-over-month changes clearly.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentOur key client just called, unhappy with the latest campaign's reported performance, saying it…+
Our key client just called, unhappy with the latest campaign's reported performance, saying it doesn't match their internal numbers.
Our key client just called, unhappy with the latest campaign's reported performance, saying it doesn't match their internal numbers. I'm afraid this could jeopardize the contract, and I can't let my manager know I might have miscalculated. What's the most common reason for client-side data discrepancies, and how can I quickly identify if our report or their tracking is off?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI frequently get requests for custom reports that are just slight variations of existing ones,…+
I frequently get requests for custom reports that are just slight variations of existing ones.
I frequently get requests for custom reports that are just slight variations of existing ones, which wastes a lot of my time. It feels like I'm always reinventing the wheel for small tweaks. What habit should I change to empower users to answer these 'what if' questions themselves, so I can focus on deeper analysis?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Google Looker's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.