Jun 11, 2024
Jun 11, 2024
by
by
Aditya Khargonekar
Aditya Khargonekar
Analyzing an earnings call transcript with ChatGPT
Account Research
Account Research
Introduction
This post is the third in a series on how AI can help with various aspects of researching an account, one of the core parts of the job of a sales rep. As a sales rep, it’s important to deeply understand your customers: their business, their goals, and their priorities. The more you understand, the better you’ll be able to help them and in turn, earn their trust because your approach is authentic to their specific needs — they’ll feel like you’re part of the team, not just another vendor.
Part one: Basic account research with Perplexity.ai
Part two: Analyzing a 10-K with ChatGPT
Part three: Analyzing an earnings call transcript with ChatGPT
In our previous articles, we walked through using Perplexity AI to get the basics about a company and GPT to analyze a 10-K. Here, we’ll dig into a useful follow-on to a 10-K analysis: how to analyze an earnings call transcript.
Earnings call transcripts are particularly interesting sources of information on publicly traded companies. While required filings are invaluable to understanding a company, they can often be weighted toward broad statements and disclosures that are difficult to craft specific motions around. However, following their quarterly filings, companies also host a conference call with analysts from major institutions where they are pressed for more specificity. During this Q&A, the company’s leadership provides visibility into strategy and priorities that can’t easily be gleaned from news releases or financial statements. Extracting insights at this level can better serve your outreach to leaders at your accounts.
Quick tips on earnings calls
When using AI to analyze earnings call transcripts, there are a few general things AI is uniquely good at helping you parse: sentiment, analyst concerns, and strategic initiatives.
There are many excellent guides about what to look for in earnings calls, please consult them to learn more!
Analyzing the earnings call transcript with ChatGPT
Here, we again use ChatGPT because it is excellent at taking and analyzing a specific file or dataset. In this case, we want to give ChatGPT the transcript of the earnings call and ask it to go to town.
Getting a transcript into the tool
In continuation from our previous articles, we’re a sales rep at Endgame learning about Zscaler, a new prospect in our book. Here, we focus on Zscaler’s Q2 2024 earnings call. To get the transcript, you can typically go to the Investor Relations section of a company’s website and download it in PDF format.
Then, open up a fresh ChatGPT window, and use the “attach” button to upload the PDF, send it, and you’re ready to go!
Digging in
Let’s take a shot at the items above — sentiment, analyst perspective, and initiatives.
Sentiment
Was company leadership confident? Mixed? Defensive? Tone can tell you a lot about how the company might be perceived, regardless of the raw numbers in the filings.
That tracks with what we learned in our basic research efforts previously—the company seems to be doing well, and its management team is quite bullish on its future. Depending on your perspective, there’s a bunch of stuff here to dig into; as a rep at Endgame, I’d want to learn more about their shift to an ABM-centric approach along with vertical sales.
That said, let’s make sure we get some specifics on performance just in case there’s any area they’re missing.
Analyst perspective
Analysts are motivated to deeply understand the levers that impact future share prices going forward, so following their lines of questioning can be a great proxy for what the market cares about, which, to no surprise, often aligns with what the company cares about in the near to medium term. It is a great way to find clues about where or how you might be able to provide value.
Tons of good stuff here. From an Endgame perspective, we’d want to dig into concerns about the org changes and new strategy in Sales, but each of these might be interesting to different vendors — for example, vendors that focus on enabling government sales and services might want to investigate how Zscaler is trying to position for that environment, or a marketing agency might want to learn if they can help Zscaler work through messaging against competition.
Let’s continue by learning a little more about strategic initiatives.
Strategic initiatives
Often, these calls discuss vital new initiatives or adjustments to existing ones. These may be in the form of leadership hiring or investment areas (technology, go-to-market, geographic expansion, etc.)., amongst others. This might give you insight into where new budgets may be available or which executives have a mandate to change things up, often a great opportunity for vendors.
In the Sentiment section, ChatGPT highlighted Zscaler's CFO discussing their “disciplined investment in strategic areas.” This is ultimately where we can learn a lot as sales reps: where they’re investing, there’s potential opportunity for vendors to help.
This is great intel. We’ve already noted their investment in GTM, but there are some great additional insights here for reps in a variety of industries:
A deep investment in R&D for new products. This could merit help from a variety of angles: dev shops, marketing agencies, market research come to mind.
Global expansion, both in terms of customer acquisition and support. There are many offerings that could benefit Zscaler in this effort.
For Endgame, since we’re oriented towards helping companies better understand and sell their accounts, we’ll want to dig in there. Let’s see what we can get:
We now know who’s in charge (Mike Rich, new CRO), and he came from ServiceNow, so there are a few new angles to play with as you think about finding connections with the company. Who were ServiceNow’s preferred vendors? Has anyone else from ServiceNow’s sales organization moved over to Zscaler recently? Is there more information about who was involved in the pilot program? There are some clues to follow up on on LinkedIn, the company blog, the news, and other sources. This is also a clear signal to vendors in ABM, customer analytics, CRM, and more to reach out with a specific offer to help Zscaler accomplish an obvious strategic priority.
Assumption check
As a brief aside, you might be thinking: Which company isn’t going to have its executives be bullish and optimistic when meeting with analysts and investors? Here’s an example of sentiment analysis showing it’s not always rosy—executives admitting challenges in the path forward, analysts probing into long-term competitiveness. The important thing here is that this is still a great way to figure out where your company might help the customer.
Conclusion
It’s remarkable how quickly you can get really deep strategic insight into a public company by analyzing its 10-Ks and earnings calls and doing solid public news and web research. In future posts, we’ll provide suggestions on how to effectively research private companies that don’t always have so much information freely available.
Special thanks to Parm Uppal from Benchling, Tyler Stetson from Drata, and Chris Burgess from Maze for reviewing this post!
Introduction
This post is the third in a series on how AI can help with various aspects of researching an account, one of the core parts of the job of a sales rep. As a sales rep, it’s important to deeply understand your customers: their business, their goals, and their priorities. The more you understand, the better you’ll be able to help them and in turn, earn their trust because your approach is authentic to their specific needs — they’ll feel like you’re part of the team, not just another vendor.
Part one: Basic account research with Perplexity.ai
Part two: Analyzing a 10-K with ChatGPT
Part three: Analyzing an earnings call transcript with ChatGPT
In our previous articles, we walked through using Perplexity AI to get the basics about a company and GPT to analyze a 10-K. Here, we’ll dig into a useful follow-on to a 10-K analysis: how to analyze an earnings call transcript.
Earnings call transcripts are particularly interesting sources of information on publicly traded companies. While required filings are invaluable to understanding a company, they can often be weighted toward broad statements and disclosures that are difficult to craft specific motions around. However, following their quarterly filings, companies also host a conference call with analysts from major institutions where they are pressed for more specificity. During this Q&A, the company’s leadership provides visibility into strategy and priorities that can’t easily be gleaned from news releases or financial statements. Extracting insights at this level can better serve your outreach to leaders at your accounts.
Quick tips on earnings calls
When using AI to analyze earnings call transcripts, there are a few general things AI is uniquely good at helping you parse: sentiment, analyst concerns, and strategic initiatives.
There are many excellent guides about what to look for in earnings calls, please consult them to learn more!
Analyzing the earnings call transcript with ChatGPT
Here, we again use ChatGPT because it is excellent at taking and analyzing a specific file or dataset. In this case, we want to give ChatGPT the transcript of the earnings call and ask it to go to town.
Getting a transcript into the tool
In continuation from our previous articles, we’re a sales rep at Endgame learning about Zscaler, a new prospect in our book. Here, we focus on Zscaler’s Q2 2024 earnings call. To get the transcript, you can typically go to the Investor Relations section of a company’s website and download it in PDF format.
Then, open up a fresh ChatGPT window, and use the “attach” button to upload the PDF, send it, and you’re ready to go!
Digging in
Let’s take a shot at the items above — sentiment, analyst perspective, and initiatives.
Sentiment
Was company leadership confident? Mixed? Defensive? Tone can tell you a lot about how the company might be perceived, regardless of the raw numbers in the filings.
That tracks with what we learned in our basic research efforts previously—the company seems to be doing well, and its management team is quite bullish on its future. Depending on your perspective, there’s a bunch of stuff here to dig into; as a rep at Endgame, I’d want to learn more about their shift to an ABM-centric approach along with vertical sales.
That said, let’s make sure we get some specifics on performance just in case there’s any area they’re missing.
Analyst perspective
Analysts are motivated to deeply understand the levers that impact future share prices going forward, so following their lines of questioning can be a great proxy for what the market cares about, which, to no surprise, often aligns with what the company cares about in the near to medium term. It is a great way to find clues about where or how you might be able to provide value.
Tons of good stuff here. From an Endgame perspective, we’d want to dig into concerns about the org changes and new strategy in Sales, but each of these might be interesting to different vendors — for example, vendors that focus on enabling government sales and services might want to investigate how Zscaler is trying to position for that environment, or a marketing agency might want to learn if they can help Zscaler work through messaging against competition.
Let’s continue by learning a little more about strategic initiatives.
Strategic initiatives
Often, these calls discuss vital new initiatives or adjustments to existing ones. These may be in the form of leadership hiring or investment areas (technology, go-to-market, geographic expansion, etc.)., amongst others. This might give you insight into where new budgets may be available or which executives have a mandate to change things up, often a great opportunity for vendors.
In the Sentiment section, ChatGPT highlighted Zscaler's CFO discussing their “disciplined investment in strategic areas.” This is ultimately where we can learn a lot as sales reps: where they’re investing, there’s potential opportunity for vendors to help.
This is great intel. We’ve already noted their investment in GTM, but there are some great additional insights here for reps in a variety of industries:
A deep investment in R&D for new products. This could merit help from a variety of angles: dev shops, marketing agencies, market research come to mind.
Global expansion, both in terms of customer acquisition and support. There are many offerings that could benefit Zscaler in this effort.
For Endgame, since we’re oriented towards helping companies better understand and sell their accounts, we’ll want to dig in there. Let’s see what we can get:
We now know who’s in charge (Mike Rich, new CRO), and he came from ServiceNow, so there are a few new angles to play with as you think about finding connections with the company. Who were ServiceNow’s preferred vendors? Has anyone else from ServiceNow’s sales organization moved over to Zscaler recently? Is there more information about who was involved in the pilot program? There are some clues to follow up on on LinkedIn, the company blog, the news, and other sources. This is also a clear signal to vendors in ABM, customer analytics, CRM, and more to reach out with a specific offer to help Zscaler accomplish an obvious strategic priority.
Assumption check
As a brief aside, you might be thinking: Which company isn’t going to have its executives be bullish and optimistic when meeting with analysts and investors? Here’s an example of sentiment analysis showing it’s not always rosy—executives admitting challenges in the path forward, analysts probing into long-term competitiveness. The important thing here is that this is still a great way to figure out where your company might help the customer.
Conclusion
It’s remarkable how quickly you can get really deep strategic insight into a public company by analyzing its 10-Ks and earnings calls and doing solid public news and web research. In future posts, we’ll provide suggestions on how to effectively research private companies that don’t always have so much information freely available.
Special thanks to Parm Uppal from Benchling, Tyler Stetson from Drata, and Chris Burgess from Maze for reviewing this post!