# Prompt library 26 ready-to-use prompts for asking an AI assistant about your marketing attribution data, grouped by use case. Source: https://sourceloop.ai/help/mcp/prompts/ --- ## Five habits that change the answers - **Name the window.** "Last month" resolves in your workspace's timezone. "Recently" does not resolve at all, and the assistant will pick something. - **Ask for the caveat.** Adding "and tell me how confident you are given the volume" turns a confident wrong answer into a useful uncertain one. - **Say which number you mean.** Leads, conversions and closed revenue tell different stories. An unqualified "performance" leaves the choice to the model. - **Chain the checks.** "Check data health first, then …" costs one extra tool call and removes the most common cause of a wrong conclusion. - **Ask for the definition.** "State what each number counts" makes the assistant quote our definitions rather than assume ROAS is profit. ## The weekly review What to ask on a Monday, in the order that makes the answers trustworthy. Start with whether the data is sound, then read the numbers. > Check SourceLoop's data health, then give me last week versus the week before: conversions, revenue, spend and cost per lead, split by channel. > What changed most between last week and the four-week average? Only mention things that moved more than 15%, and say whether the change is big enough to be real given the volume. > Summarise last week for a non-marketing audience in five bullets. No jargon, and state what each number counts. > Which campaigns produced leads last week that already have deals attached, and which produced leads with nothing behind them? ## Diagnosing a drop The sequence that gets to a cause rather than a restatement of the symptom. > Our cost per lead went up last week. Work out why: break spend and conversions down by channel, then by campaign inside whichever channel moved most, and tell me whether it was a spend increase or a conversion decrease. > Conversions fell on Tuesday. Before blaming marketing, check attribution coverage and data health for that day and tell me if the drop is real or a tracking gap. > Compare this month's traffic mix with last month's by source and device. Has the mix shifted in a way that would explain a lower conversion rate on its own? > Show me the funnel from first touch to closed won for this quarter and last, and tell me which single step accounts for most of the difference. ## Budget decisions Questions that end in a decision. Ask for the caveat as well as the number, because a confident answer over thin data is worse than an uncertain one. > If I had 20% more budget next month, where would you put it? Use closed revenue rather than lead volume, and tell me how confident you are given the sample size. > Which campaigns have spent more than 2,000 this quarter and produced no closed revenue? Show the spend and the number of leads for each. > Compare cost per acquisition and lifetime value by channel, and tell me the payback period for each. Say which channels are profitable and which are only cheap. > What would our cost per lead look like if I cut the worst-performing 20% of campaigns by spend? Be explicit about what that estimate assumes. ## Pipeline and revenue Marketing questions answered in sales terms, which is the version a founder or a CFO will act on. > Which marketing sources produced the deals we closed this quarter? Use the deal value, not the lead count. > Show me the full journey behind our three largest closed deals this year. What did they have in common? > Which open deals over 10,000 came from paid channels, and what was the first touch for each? > What is our lead-to-close rate by channel this year, and how long does each take to close on average? ## Agencies and multiple sites One connection can cover every client website, so the loop happens in the assistant rather than in a script you maintain. > List every website I have access to, then give me last month's conversions, spend and cost per lead for each, as one table sorted by spend. > Across all my clients, which ones had a worse cost per lead last month than the month before? For each, name the channel most responsible. > Draft a short monthly update for Acme: what worked, what did not, what I am changing next month. Use their numbers and state the date range you used. > Which of my clients have attribution coverage below 80%? Those are the ones whose reports I should caveat. ## Data quality Worth running before anyone builds a decision on a number, and worth running after any change to your site. > Check data health and attribution coverage for the last 30 days. List anything that would make a report misleading, in order of how much revenue it affects. > How much of last month's revenue is attributed to a source, and for the part that is not, what are the reasons? > Are any of our forms or integrations sending fewer conversions than they did a month ago? ## Writing outcomes back These change your data, and in the case of deals your CRM. They need a connection with write permission, and it is worth asking the assistant to confirm before it acts. > The Acme lead closed at 12,000. Record that in SourceLoop, and tell me what it does to paid search's cost per acquisition. > Find contacts from last month's webinar campaign with no outcome recorded, list them, and ask me before changing anything. > Move the Acme deal to Negotiation and confirm the change reached the CRM. Tools reference: https://sourceloop.ai/help/mcp/tools.md