This week, I'm going to demonstrate an earnings call alt data analysis technique that many pod shops like Citadel use.
What these investors do is try to infer whether a company will beat or miss earnings based on how packed their investor relations or corporate events calendar looks.
The logic for how this brings predictive power is this:
- If a company beats earnings, they want to beat their chest and make sure investors know. ESPECIALLY sell-side Wall Street coverage who could hopefully raise price targets. Therefore, the 'marketing calendar' will be full in the following 4-6 weeks post earnings.
- Conversely, if the company does poorly for that quarter, they want to make sure there isn't as much coverage around it (and hence the 'marketing calendar' will be light)
I want to note that this isn't a foolproof 100% hit rate for predicting earnings, but it's another angle to conduct earnings analysis and as investors we will take as many data points as possible that can give us any edge.
I'm going to show you how to use AI to conduct this analysis with Adobe $ADBE upcoming 3Q25 earnings in September.
Here's the plan for how our prompt will work:
- Scrape marketing calendar from official sources for the 4-6 weeks after the upcoming earnings
- Compare this vs the marketing calendar vs the last quarter
- Scan sell-side buy/sell consensus to determine potential for upgrades or downgrades on the stock
The Prompt
Prompt: I like to use ChatGPT Thinking Mode for this!
Role
You are my market communications and analyst relations strategist.
Task
For <<Adobe $ADBE>>, analyze the post-earnings marketing schedule for the upcoming 3Q25 earnings in September and assess sell-side upgrade/downgrade potential, including implications for stock price movement. I also want you to compare vs the last quarter to infer if there are more or less items on the marketing calendar after earnings in same window for 3Q25.
Input
Primary sources: SEC filings, investor presentations, company event calendars, conference schedules, earnings call transcripts, investor relations press releases.
Secondary sources: Analyst ratings and target price data from FactSet, Bloomberg, Capital IQ, Visible Alpha — clearly labeled if secondary.
Gather:
Recent and upcoming investor conferences, roadshows, or non-deal marketing events post-earnings.
Current analyst ratings distribution (Buy/Hold/Sell counts, average target price, high/low target).
Historical market reaction patterns to upgrades/downgrades for this stock.
Tone
Analytical, concise, neutral.
Output
Provide:
Post-Earnings Marketing Assessment – List scheduled investor events and marketing activities in the 4–6 weeks following earnings, and assess whether timing suggests proactive damage control, momentum building, or neutral communications.
Upgrade/Downgrade Setup – Based on current ratings distribution and average price target vs. spot price, assess:
How “upgradeable” the stock is (room for upward revisions).
How “downgradeable” it is (risk of negative revisions).
Conviction vs. Price Target – Highlight how analyst conviction levels (e.g., “top pick” vs. “neutral”) may carry more weight than rating labels alone, especially when paired with implied upside/downside from their target prices.
Conceptual Market Impact – Describe how the combination of the marketing schedule and ratings setup could influence near-term stock performance.
Rules
Cite all data inline.
If event schedules or rating data are unavailable, state “Not disclosed.”
Use USD for price targets and % for implied upside/downside.
Avoid em dashes.
The Result:
Full output here: Link
Here are a few key snippets we are looking for in the output.
- "Relative to Q2, the near-term IR calendar looks light right now, which leans neutral on post-earnings messaging."
- "Q2 had 2 IR events within 2 weeks and 3 within 6 weeks post-earnings. Q3 currently shows 0 disclosed in the same window."
- "The stock has shown sensitivity to Sell calls. Example: Redburn (Rothschild & Co) cut to Sell with a $280 PT in July, shares fell about 4 percent that day. This highlights a persistent downside-revisions risk if AI adoption or pricing durability disappoints."
- "PT bumps without rating changes have had limited immediate impact in 2025, given broader skepticism on AI monetization and recurring post-earnings volatility."
The overall interpretation of this analysis is that because (1) the marketing calendar is light after the 3Q25 window and (2) the stock is susceptible to downgrades, the company might disappoint on its upcoming earnings.
If we were to look at the 2Q25 earnings, Adobe beat with record revenue and raised 2025 revenue & EPS targets. Hence makes sense why they had several investor relations events scheduled immediately proceeding the earnings report.
Thanks to AI we can equip ourselves with this new technique to blaze through this analysis without manual site scrubbing!
Posts from Me:
I published my full short thesis on $BLSH ~1.5 weeks ago and it's a position I've been riding to hedge out long exposure on high growth tech in my portfolio.
I used several AI research techniques to blaze through this diligence, including no code statistical modeling, ChatGPT forensic accounting, and management diligence with deep research.
Feel free to hit the reply button if you have any questions on any specific techniques I used to put together my investment thesis there.
