◆ Google Looker

Apply Looker Conversational Analytics best practices

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 summary of last week's sales performance for the 'Electronics' category, breaking it…+
Generate a summary of last week's sales performance for the 'Electronics' category, breaking it down by region.
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 acceptBefore the product team meeting, analyze the user engagement data for the new 'Feature X'.…+
Before the product team meeting, analyze the user engagement data for the new 'Feature X'. Focus on identifying any unexpected drops in usage or areas where users might be struggling, and present it in a way that highlights actionable insights.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe head of marketing just asked for 'the biggest drivers of recent customer churn,' but her…+
The head of marketing just asked for 'the biggest drivers of recent customer churn' but didn't specify a timeframe or segment.
The head of marketing just asked for 'the biggest drivers of recent customer churn,' but her request is so open-ended I don't know where to start. If I give her too much, she'll be overwhelmed; too little, and I'll miss something critical. I'm afraid of delivering an irrelevant answer. What's the best way to interpret such a broad request to deliver the most impactful insights without needing a follow-up clarification?
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 find myself guessing what business users really mean by their broad questions,…+
I often struggle to translate open-ended business questions into specific, actionable data queries.
I frequently find myself guessing what business users really mean by their broad questions, leading to analyses that don't quite hit the mark. This wastes time and frustrates everyone. What habit should I change to better understand and translate ambiguous business questions into precise, valuable data insights every time?
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.