How to Summarize Your Metrics and Spot Patterns with AI
Turn raw numbers into clear insights, reflection questions, and next steps
Metrics matter — but they can also be overwhelming. You’ve got dashboards, spreadsheets, open rates, follower counts, downloads, and watch times. The numbers pile up quickly, and instead of feeling informed, you end up drowning in data.
At Anchor Change, I track performance across my newsletter, podcast, and social platforms. But here’s the truth: metrics alone don’t tell me what to do next. They only become useful when I can connect them to patterns, decisions, and strategy. That’s where AI comes in. With a few simple prompts, I can turn spreadsheets into plain English, ask smarter questions about what’s really happening, and uncover opportunities I might have missed.
Here’s how you can do it too.
Step 1: Gather Your Data
Export your metrics into a format you can drop into AI. This might be:
Newsletter open/click rates,
Podcast downloads,
Social media analytics,
Website traffic.
Anchor Change example: I recently exported my Substack analytics — open rates, click rates, subscriber growth — from the last quarter.
Step 2: Ask for a Plain-Language Summary
Instead of staring at rows of numbers, get AI to translate them into a narrative.
Prompt template:
“Here are my newsletter metrics for the past 3 months. Please summarize the key patterns in plain English — what’s improving, what’s declining, and what stands out.”
This is where you move from raw numbers to quick clarity. AI might tell you:
Opens are steady but clicks dipped 10% in June.
Subscriber growth spiked during a particular week.
Certain subject lines drove higher engagement.
Step 3: Go Deeper with Reflection Questions
The real value comes from asking AI to push you — not just describe what happened.
Follow-up prompt:
“Based on these metrics, ask me 3–4 reflection questions that could help me think about my content strategy.”
For my newsletter, AI asked:
Why might readers open emails but not click through — is the value contained in the email itself?
What was unique about the week subscriber growth spiked? Can you replicate it?
Do your subject lines reflect your voice, or are they leaning too generic?
These questions helped me focus not just on what was happening but on what I could change.
Step 4: Compare Across Channels
AI is especially helpful at connecting dots across different platforms.
Prompt template:
“Here are my newsletter and podcast metrics. Please compare them and identify overlaps, differences, or opportunities.”
When I did this, AI flagged that weeks with higher newsletter engagement also saw podcast spikes. That told me I should experiment with cross-promotion more intentionally.
Step 5: Spot Longer-Term Patterns
Metrics aren’t just about the last month — they reveal bigger arcs over time.
Prompt template:
“Here are my quarterly metrics for the past year. Please identify recurring trends or patterns, and suggest what they might mean for the next quarter.”
I discovered that my open rates dip every August (summer slowdown) but rebound in September. Knowing that lets me plan lighter content for August and bigger launches for September.
Step 6: Turn Insight Into Action
Finally, translate analysis into next steps.
Prompt template:
“Based on these insights, suggest 3 practical experiments I can run in the next month to improve results.”
For me, AI suggested:
Test subject lines that lean into storytelling.
Pair a podcast drop with a newsletter teaser.
Re-share a popular post on social with a fresh angle.
Why This Works for Professionals
Political operatives: Spot which messages resonate with voters, not just which ads get impressions.
Trust & safety professionals: Track policy rollouts or training impact over time.
Corporate leaders: Turn quarterly reports into plain-English takeaways for teams.
The key is not to let metrics live in isolation. With AI, you can connect the dots between numbers, strategy, and action.
Try This Today
Export one set of metrics (newsletter, social, podcast, or website).
Ask AI to summarize in plain English.
Push it for reflection questions.
Compare across channels if you have them.
Translate insights into 2–3 concrete experiments.
✅ Anchor Change takeaway: Data tells you what happened. Intuition tells you why it matters. AI bridges the gap by helping you name patterns, ask better questions, and move from information to strategy.