[Guide for IR Teams] Don’t Miss Insights Next Earnings Season: 5 Ways to Optimize Your Time

Why We Wrote This Guide

During earnings season, Investor Relations professionals are drowning in data. The tens or even hundreds of peers and analysts they track produce hundreds of pieces of data, documents, and news every week that could inform a change in earnings calls strategy and language or a response to management and stakeholder requests.

Getting through the deluge of information that becomes available each day can seem like an impossible task.

How can investor relations professionals get through earnings season documents and extract relevant insights quickly?

We’ve identified 5 best practices that you (and your team) can apply to optimize your time during earnings. Get the full guide here.

Get to the most relevant peer and analyst information in minutes to improve confidence in your strategy and drive changes in external messaging and earnings call narratives.

 

 

 

How well are your peers actually doing?

The documents that they’ve filed with the SEC are a gold mine of information. Before and during earnings season, you’ll want to stay on top of peer news and announcements, as well as related analyst commentary and sentiment.

Earnings call transcripts help you understand how peer management is positioning their company and how analysts are reacting. A company’s annual 10-K filing, specifically within the “Outlook” or “Use of Proceeds” sections, shows if they’ve used capital to expand or grow, to repay debt, or to support general operations. Can you see specific plans for this capital?

Annual reports (among many other document types) can also give good insight into product research and development (R&D), which can include everything from initial product design to compliance testing, to new market deployment. Track exactly how much your competitors are spending ?on innovation, and where they are reducing investment.

How To Do It

Use a tool that allows you to search across all document types, and even within specific document sections.

Get alerted when new competitor documents are released, whether they be an earnings call transcript, a press release, a 10-Q covering the company’s quarterly performance, an 8-K for material events (acquisitions, changes in corporate management, or updated fiscal year end-date), or an S-1 for an IPO.

Get alerted on specific company and keyword searches like “NVDA > R&D > automation,” so you’re always in the know about your competitor’s roadmap and benchmark language.

Sentieo Document Search and Alerts

Key catalysts to track include earnings announcements, product launches, and transactions. Use a calendar tool that automatically feeds in from your company watchlists.

For example, below we used our watchlist “Big Tech” to auto-populate our Sentieo earnings calendar for easy tracking.

Sentieo Earnings Calendar

 

During earnings season, you want a tool that allows you to get instant insights as soon as a transcript is released. Answering the questions below will help you make more strategic decisions in the future:

• What are consumers, analysts, and management teams saying about your peers?

• What is the sentiment towards your own company?

• What is the sentiment of your peers on earnings calls?

• Are your peers positive around certain topics? Or negative and deflecting?

How It Works

Try using a tool that tracks and manages sentiment in an efficient and meaningful way.

For example, Sentieo’s Smart Summary™ categorizes an earnings call transcript’s sentences for easy insight (i.e. by “Guidance,” “Financials,” or “Deflection”). It also color-codes sentences according to whether their sentiment is positive or negative — for easy, at-a-glance analysis.
Sentieo allows you to automate the receipt of transcript analysis reports to your email inbox, which can save you lots of time during earnings season!

Sentieo Smart Summary Transcript Analysis

To learn the other 2 ways to avoid missing insights during earnings season, download the full guide here.

To try Sentieo, request a trial or custom demo with us!

Taking a Data-Driven Approach to Alpha Generation: Part 2

Over the last few years, we have seen the not-so-gradual evolution of investment marketing, from the rise of indexing and quantitative strategies to the explosion of alternative data and fee compression. The need to “research different” to maintain your edge is greater today than ever before. But despite the changes, there remains one major thing all successful investors do: correctly identify trends. 

Over the coming weeks, we will cover three different strategies to overcome overreliance on hunches, intuition, or biased views and start quantifying and visualizing investable trends, to ultimately generate alpha faster. You can skip ahead and read the full report here.

A couple weeks ago, we covered everyone’s favorite industry buzzword: alternative data. Today, we switch gears and focus on how to capitalize on your internal datasets for alpha generation.

When looking to “supercharge” research, it’s important to include internal proprietary data sets, such as search statistics on corporate documents, like earnings call transcripts. Unlike alternative data sets, which are widely available for purchase, document search statistics are your own internal proprietary data set. These can be a powerful source for trend identification and verification.

One example of this is the short-lived “gluten free” fad. A quick search of conference call transcripts that mention “gluten free” show that while gluten intolerance is in fact a real issue, it really only impacts a small percentage of the population. As a result, the corporate response clearly came and went

Another example is the opioid crisis. In this case, search statistics help quantify metrics for risk management purposes. For example, we can see that the number of 10-K filings with Risk Factors that mention “opioid” or “opioids” have increased substantially over the years

Search statistics for documents can also be combined with financial metrics to spot trends in an industry group as a whole. For example, combining restaurant industry transcript mentions of “wage inflation” against the average adjusted EBIT margin for a group of US casual dining chains shows that the margin peaked and started to decline shortly after document statistics pointed to increasing wage pressures

But these internal datasets can do more than just verify or quantify trends, they can also help you spot trending terms as well as “equivalents” to help you generate ideas and develop a thesis. For example, looking at all corporate documents for YUM! Brands (global parent of KFC, Pizza Hut, and Taco Bell), we can identify company-specific trending topics.  

This same concept can be applied to searches for document types: searching 10-K filings with the SEC for Vietnam and other Southeast Asian countries are trending in the mix.

Most importantly, search statistics for documents are entirely your own proprietary data set. Because they’re not available from the data vendors, they are your own competitive advantage and enable you to preserve your edge for longer.

Next week, we’ll cover how to create powerful visualizations over time using sector-level financial metrics. If you can’t wait that long, you can download the full report here.

LockerDome Cuts CI Research Time In Half With Sentieo

About the Customer

LockerDome (“an ad platform with a brain”) is a software designed specifically for performance-based advertising. LockerDome, headquartered in St. Louis, Missouri, is trusted by leading advertisers and publishers to drive revenue. Advertisers trust LockerDome’s ad platform to generate revenue from product sales, and publishers trust LockerDome to maximize revenue from their website, in-app, and email traffic.

Mark Lewis, CFO, is LockerDome’s head of finance and accounting. Mark also oversees competitive intelligence (CI) analysis for the company.

Challenge/Problem

LockerDome competes with public adtech companies such as Critteo, The Trade Desk, and Rubicon. As the CFO, Mark manages all of LockerDome’s admin, accounting, legal, and HR teams. This makes for a lot of responsibilities and limited time for CI research, especially at a rapidly growing, lean tech company.

Before using Sentieo, Mark was investing far too many hours searching through documents and manually tracking competitor activity. He was using Excel or Google spreadsheets to track comparable company metrics: funds raised, valuations (at private round, IPO, current, exit), revenue, net income, EBITDA, valuation multiples, acquisitions, board seats, and more.

Mark was spending hours on gathering, tracking, and updating these metrics — all manually. Unfortunately, this made it easy for him to miss insights and difficult for him to maintain updates and scale his work. He was also dealing with many different sources of information that he was unable to easily access.

All of these issues led him to try Sentieo.

Solution and Results

In 2018, Mark invested in Sentieo as his principle corporate research platform in order to accelerate his research process. The goals of this investment were to:

• Dramatically decrease the time he and his team spent
researching competitor news and public filings
• Reduce the risk of LockerDome missing a change in strategy
by a competitor that would have impacted their business
• Get visibility into competitor insights to drive the process of
adapting and growing their corporate strategy

Want to see how Sentieo solved LockerDome’s pain points? Read the full story here.

Taking a Data-Driven Approach to Alpha Generation: Part 1

Over the last few years, we have watched the not-so-gradual evolution of investment marketing, from the rise of indexing and quantitative strategies to an explosion of alternative data and fee compression. The need to “research different” to maintain your edge is greater today than ever before. But despite the changes, there remains one major activity that all successful investors do: correctly identify trends. 

Over the coming weeks, we will cover three different strategies to help you surpass your overreliance on hunches, intuition, or biased views — and start quantifying and visualizing investable trends (so you can ultimately generate alpha faster). You can skip ahead and read the full guided report here.

Today we’re covering everyone’s favorite industry buzzword: alternative data.

“Alternative data,” a broad term that refers to newer data sources, has become increasingly popular over the last few years. From credit card data to search trends, app rankings, and even Twitter mentions, alternative data has become a buzzword as well as a useful tool for research. 

Alternative data can be powerful. But to identify alpha-generating trends, we need more than just one data source, and we need to combine data sources. For example, let’s take a look at clear aligners (the clear plastic trays used for teeth alignment). You might be familiar with the leader in the space, Align Technologies (makers of Invisalign), but there are a good number of recent entrants in the space. These include SmileDirectClub, a DTC (direct to consumer) clear aligner company that recently completed an initial public offering. 

Starting with a very basic alternative dataset, search trends, we can gauge both the direction and the seasonality of the topic. An important point to make here is the distinction between search term (the exact term) versus the broader search topic (which bundles a number of related search terms together). 

Plotting the search interest, we can see that interest in clear aligners has been growing very steadily for the last few years, with peak levels (indexed to 100) happening in 2019. We can also see distinctive seasonality: a drop off into the December holidays, followed by a spike to new highs in January, consistent with self-improvement trends post-New Year.  

Interactive chart http://snt.io/KEF8ejHb8

But search is just a part of the picture. 

Using Alexa web traffic data, we can combine the search interest with web traffic data for the major players in the clear aligner space. While there are “web traffic share” gains and losses, we can see that, as a whole, traffic is increasing across all players: Align, Smile Direct, Snap Correct, Candid Co and Smile Love. 

Interactive chart: http://snt.io/MfF8emuTG

As the final step here, we can overlay the financial and valuation metrics for Align Technologies as the public company in the group with the longest trading history. For clarity, we are “hiding” the non-ALGN traffic metrics. We can see that the search trends correspond very nicely to quarterly revenues (2-year correlation is 0.8), while valuation (EV/Sales here) seems to move based on web traffic direction on shorter time frames. 

Interactive chart http://snt.io/BSF8epB5B

You don’t have to focus on individual securities to use trends in alternative data—it can also be used to detect changes in macroeconomic trends. 

For example, using Twitter as a “repository” for live conversations, we can see that tweets containing “new job” (30-day moving average for smoothing) foreshadowed the increase in the non-farm quits rate by months around 2012-2013. 

Interactive chart http://snt.io/NcF8et44S

Effortlessly combining traditional and alternative data sets in compelling visualization lets you not only see more but speed up your idea velocity in the pursuit of alpha. In the case of clear aligners we can see that there is a very strong, and growing, underlying demand for more convenient, “tech first” cosmetic dental care.

Next week we’ll cover how to capitalize on your internal datasets for alpha generation. If you can’t wait that long, you can download the full report here.

Save More Time with Sentieo’s New Category Search

About Sentieo Document Search

Clients love Sentieo’s industry-leading Document Search for its depth, precision, and workflow integration. Users save hours with the ability to search across all companies, watchlists, individual entities, or by excluding tickers from searches.

Easy document specification with our IN: function covers the most common document types. (For example, search just 10-Ks or just transcripts). Our in-section search lets you search within a specific document section (in:10k MD&A or in:transcript), or by speaker (statements by CFO, by analysts, etc). You can also search PPT presentations, or get very granular document-level controls like “8-K Credit Agreements.” Filter down your search by industry classifications, geographies, market caps, and timeframes. 

Add another layer with our large library of Boolean operators, like “OR” for parallel searches and “BEFORE/NEAR/FAR” for proximity and order control. In the background, we have three levels of synonym control for the thousands of synonym/acronym groups. For example, sales and revenue will “pick up” each other, so you don’t need to know the exact term that the company uses in order to find what you’re looking for.

Machine learning-based Document Search will dynamically suggest synonyms based on your specific query, in addition to autofilling text in your query based on your document set. And if you do not have a query, Sentieo will suggest trending terms based on the searched ticker.

We have extensive Document Search statistics that let you see real trends, and you can drill down quickly with one or two clicks. Imagine seeing all companies that mention China within 25 words of Vietnam, clicking on Consumer Discretionary, and then seeing the top companies that mention your query most frequently. You can also do a “search within a search.” 

On the workflow side, you can save all positive hits as a watchlist for future work (for example, all Industrial companies with a market cap over $1 bn that mention Mexico in their 19-K Risk Factors). You can even automate your workflow with saved searches. All of our searches can be saved and turned into email and/or desktop alerts at the frequencies of your choice.

Highlight and label text as you read, and these annotations will be all stored and automatically ticker-tagged in your Notebook. You can even call out your team members with comments: “are you ready to take a look at this note on [x]?” Take screenshots from presentations and use the web clipper to bookmark webpages. All of your internal documents including uploads, emails, notes, and built-out theses are searchable, too. 

So What’s This New Category Search?

We’ve had in-table search functionality for years, enabling users to find numbers that are broken out in tables. For example, find mentions of EMEA Revenue only in tables, rather than everywhere in the doc. In our latest release, we’ve taken locating numbers to the next level. 

With the newly-released v3.9, users can search for specific types of numbers based on our very extensive categorization system. A Category is a set of keywords which are not synonyms but have similar meanings or constructs.

Category search allows you to search for an entire class using one search term. You can now look specifically for categorized numbers, such as currency, percentages, duration, length, area, temperature, volume, and a lot more. So now finding the “sales growth percentage” or “production volumes” takes a second. 

Moving forward, we will show a few examples of what is now possible in Sentieo’s Document Search.

In this query below, we are searching transcripts for revenue growth within 10 words of a percentage. You can also see how “revenue” picked up “sales” as a part of the synonym search. 

Swapping out the percentage from the query above with the currency categorization, we can look for currency amounts, like dollars or euros. 

Staying on top of KPIs is also easy with our new numbers categories. You can search for specific information like oil/gas production volumes or leasable area in real estate. 

You can search 8-K Credit Agreements for leverage ratios using the Ratio classification:

Need to call up a company? Search all filings (in:CF) for the headquarter phone number listed on the front page. 

The numbers we classified do not even need to be numeric. As a part of this update, we have fractions, time periods and more. 

These are just a few of our new Document Search use cases. Sentieo offers many more categories that help you find exactly what you need, faster.

To find out more about our new Category Search, or any part of Sentieo’s research workflow solution, please get in touch.

[Videos] How to Use Sentieo’s Table Explorer To Extract Data and Save Hours

In this “how to” post, we will review how to use our Table Explorer table chaining function in SEC documents, as well as the major updates we integrated with our recent v3.9 release. 

Broadly speaking, you can do a LOT with tables in Sentieo. 

  1. Export one or all document tables into Excel 
  2. Search only within table (s) using our popular “in:table” shortcut 
  3. See side-by-side historical tables (very useful for annual filings like proxy statements)
  4. Export PPT/PDF tables to Excel 

But none of these functionalities come close to what Table Explorer can do. Table Explorer uses a machine learning model to identify, chain, and visualize reported data. This is done in an auditable, transparent fashion, with added one-click flexibility for elements such as YoY and QoQ changes, common size statement conversion, and more. Analysts save countless hours with this ability to quickly chain tables, as well as visualize data and trends.

We will start with a simple example: the income statement. Table Explorer chains either 8-Ks, or 10-Qs/10-Ks. Since Q4s are not always reported, we create “synthetic” Q4 statements with one click. We use Adobe’s income statement as an example. Watch the video to find out more. 

In this second video, we cover the balance sheet. Similar to the income statement video above, we have an easy adjustment for Q4 balances. We go over the Netflix balance sheet, starting with their most recent filing. 

In this next video, we cover the cash flow statement. Cash flow statements are often presented in a cumulative fashion: 3-month in Q1, 6-month in Q2, 9-month in Q3, and 12-month in Q4. In this specific example, we use Mondelez International, the global snacking giant. We convert to quarterly with just one click. (We even came up with a new word for this function: “to quarterize”).

Table X does not stop here. You can export your chained data to Excel and to our data visualization tool, Plotter, for further work. You can save the data into your Sentieo Notebook to add to a full thesis.

The video below reviews these steps. We extract and chain Adobe’s income statement, convert it to “common size,” then visualize and export the percentage split of service vs. product revenues for the company. We then export to our main data visualization tool Plotter, where we overlay two of the thousands of data sets included in Sentieo, and finally, we save the chart in our Notebook for use in our full-blown thesis on the company.  

Table X works on other tables too. For example, you can extract your own KPIs or any other table-based data. While some KPIs might be available from the standardized data providers, not all are, and extracting your own means greater confidence in your data through our on-screen auditing function. In this fifth video, we show you how. We extract and chain Chipotle’s KPI tables, and we quickly visualize the trends in average unit volumes and comparable store sales. 

After Table X was released to rave reviews earlier this year, the number one request was handling line item renaming. With the latest product release, we created a Row Merge/Demerge capability to address this workflow. We show you how in this video. In the example here, Crocs, a footwear company with a wholesale and a retail business, reports a quarterly store count by geographic region. However, the company changed its line item name from “Europe” to “EMEA” recently, creating a discontinuity in this specific data set. We show how to merge the two rows and how to check that the mapping is correct. 

In the final, and most technical, video we show you how Table X handles a specific type of table called a “roll-forward” table. A standard use case for this is a company reporting a change in balance over the quarter, where we have the starting balance on top of the table, any changes below that, and then we have the ending balance at the bottom. In this specific example, we chain Chipotle’s unit openings/closings table from their 10-Qs and 10-Ks, and then make a few quick adjustments to add a Q4 column with the correct starting/ending balance, and intra-quarter additions. We also demonstrate the importance of visualizations. Unit openings are clustered in Q4, and this plays a role in forecasting the annual revenues due to the backend loading. 

To find out more about Sentieo’s Table Explorer, or any of the other features in our complete workflow research platform, please get in touch with us. 

 

[Guide] Don’t Miss Insights Next Earnings Season: 5 Ways to Optimize Your Time

Why We Wrote This Guide

With companies releasing a multitude of documents every hour of the day during earnings season, getting insights quickly can feel like an impossible task.

The hundreds of companies that analysts track each produce hundreds of data points, documents, and news — any of which could inform a change in corporate strategy or competitive response.

During earnings season, competitive intelligence professionals are often drowning in data, and can miss important insights as a result.

 

 

 

We came up with 5 ways that you (and your team) can optimize your time during earnings. Download the full whitepaper here.

You can easily gain a competitive edge by staying ahead of emerging global or industry trends, including:

• consumer/customer preferences
• trends that are favorable/unfavorable to you or your competitors
• new or disruptive ideas and products

Ask yourself and your team:

What are the macro, global market, and consumer trends happening right now that are impacting my business and my peers?

How To Do It

Alternative datasets can give you great insight into market trends. Try a tool that includes datasets like:

• Twitter mentions – Observe globally trending topics, your competitor’s brand mentions, and their number of followers. Are they spending advertising money on Twitter?

• Alexa website visits – Are your competitor’s website visits going up or down? How come?

• Google Trends – How are people searching for your competitors on the web?

Understanding macro trends can also help you focus your efforts during earnings season. A tool that allows you to plot both financial and document data can expedite this step in your workflow.

In the example below, we plotted document mentions of “wage inflation” (green bars) against EBIT Margins for Cheesecake Factory and Texas Roadhouse (purple & orange lines). We see that as wage inflation has risen, there has been a substantial decline in the margins for the two chains. With visualization tools, CI analysts are able to see the factors that drive trends, and stay ahead of competititors.

Key catalysts to track include earnings announcements, product launches, and transactions. Use a calendar tool that automatically feeds in from your company watchlists.

For example, below we used our watchlist “Big Tech” to auto-populate our Sentieo earnings calendar for easy tracking.

 

Want to learn the 3 other ways that you (and your team) can optimize your time during earnings? Download the full whitepaper here.

Facebook (FB) Transcript Smart Summary™ — Legal Discussions Get Longer and Instagram Innovates

In this final installment of our earnings season blog posts (informed by Sentieo’s transcript Smart Summary™), we’re covering Facebook (FB).

We kicked the week off by “getting to the meat” of Beyond Meat’s call on Monday night. While growth and margin expansion were strong, our keyword surfacing highlighted McDonald’s as a key topic.

We then looked at Tuesday’s transcript from Merck. While its VIP drug Keytruda is growing nicely, the Smart Summary™ highlighted pricing pressure concerns.

YUM! Brands, the parent of KFC, Pizza Hut and Taco Bell, reported on Wednesday morning. Smart Summary™ was useful to check on the many moving parts of this global, multi-brand QSR chain — from regional comp sales across brands to unit growth. Our sentiment scoring noted a particular analyst question about system-wide margin pressures. (Because it was deep in the transcript, a human reader could have missed this). Our blog posts above also feature short videos, with our Head of Research Nick Mazing reviewing how transcript push notifications work in Sentieo, and what he chooses to hone in on for each ticker.

For Facebook, since it is a well-covered company, we will focus on a smaller set of topics: 2020 guidance, regulatory discussions, and product innovation. 

On the guidance side, we see 2020 revenue growth deceleration, but this is widely expected, as Facebook is already large. We also see concrete expense numbers; there have been questions regarding Facebook’s investment in combating fake news and other undesirable content. 

There is a very lengthy regulatory discussion on this call. We see various entities/regulations mentioned on this call. Investors pay close attention to the regulatory environment. Heavy regulation tends to benefit the incumbent players, and Facebook is poised to lock out threats, similar to what happened in the US with the cigarette companies and the “Master Settlement Agreement.”

Contrast this Q3 2019 regulatory discussion versus Q3 2018. We can see below that the category in the Smart Summary™ was blank. 

We can also see the spike in Facebook’s 10-K/10-Q mentions of FTC. They went from single mentions to 27-30 more recently. 

We can also see the financial impacts. The FTC levied a fine in the billions of dollars, which we can see when we chain together the breakout table in the latest 10-Q with the same table in prior filings. 

The last highlight from this call is product, specifically Facebook’s innovation around Instagram. Our NLP-based keyword surfacing picked up the conversation there as the top keyword on that call. 

 

Check out our quick video walkthrough on Facebook.

Smart Summary™ is just a part of Sentieo’s research platform. To find out more about us, please get in touch

YUM! Brands’ Q3 Transcript Smart Summary™ — Extracting the Essentials From a Call With Many Moving Parts

This week, we continue to use Sentieo’s transcript Smart Summary™ to highlight selected reporting companies. We apply machine learning and natural language processing to create a more efficient and a more repeatable process. On Tuesday, we highlighted Beyond Meat (Nasdaq:BYND), and on Wednesday, we looked at Merck. (While Keytruda continues to power through, we picked up pricing pressure warnings for 2020.)

In today’s highlight, we are looking YUM! Brands (NYSE:YUM), the parent of global restaurant chains KFC, Taco Bell, and Pizza Hut. The company reports many metrics about its business: domestic (US) and international unit growth, comparable store (“like for like”) sales growth, and “systemwide” sales growth (reflective of the health of the franchisee system). 

Additionally, the company has a minority investment in order aggregator/delivery company Grubhub, which further complicates the financial reporting, as YUM reports mark-to-market adjustments on top of the operating earnings. 

In this post, we will share our highlights from the Smart Summary™ PDF that we received in our email inbox a few minutes after the original transcript came through. (The Sentieo platform is much larger and more interactive that what you see in this post, so we encourage you to check it out.)

With Smart Summary™, the transcripts are parsed by a ML tool which classifies and scores sentences based on broad classifications, such as Guidance or Legal. (See below). Smart Summary™ runs a layer of NLP processing on top of that, classifying sentiment (positive/negative/neutral), looking for “deflection” statements, and surfacing keywords. 

Looking at the YUM Q3 call Guidance section, we immediately spot the big delta between the GAAP and non-GAAP earnings. We also see the red (negative) outlook for Pizza Hut US, a unit that has been weak for a while. 

As we mentioned earlier, the transcript (as well as the press release) are very KPI-heavy. The convenient sentence extraction and classification helps you get the full picture faster.

We also note a number of negative sentiment questions from the analysts on the call, with the most “negative” analyst question being about system-wide margin pressures. 

The keyword surfacing logically picked up Same Store Sales, Net New Units, and System Sales.  We are highlighting just one of these here; unit growth keeps up, so the sentiment overlay is green. 

Watch our short video walk-through:

To find out more about the Smart Summary™ and all of Sentieo’s other AI-powered features, please get in touch

 

Merck Q3 Transcript Smart Summary™ – Keytruda Growth Continues, But Pricing Pressure Looms

As a part of our earnings season coverage, we’re continuing to use Sentieo’s transcript Smart Summary™ to highlight selected reporting companies. Smart Summary™ applies machine learning and natural language processing to create a more efficient and a more repeatable process for transcript analysis. Yesterday, we highlighted Beyond Meat (Nasdaq:BYND), where we definitely went beyond the meat of the matter and into the details.

In this piece, we will take a quick look at pharmaceutical giant Merck. We are using the newly-released email push notification functionality for the Smart Summary™ transcript, which provides users with both the summary and the full transcript in a single PDF. We’ll go through parts of the Smart Summary™ PDF for Merck, but you can view the full report here.

The key headline from the MRK release was that the company increased its 2019 non-GAAP EPS guidance. We can see this clearly in the Guidance section of the summary. 

In the KPI section, we see several interesting tidbits: tax rate, Animal Health division data, plus comments on Keytruda, an important drug. 


The pricing pressure comment that was ranked high in Guidance was also notably ranked high in the Products/Markets section as well.

On the Legal/Regulatory front, we see comments around drug approvals. 

In addition to the ML-based classification, we also apply NLP (Natural Language Processing) in three dimensions: sentiment (positive/negative), deflection (language associated with “deflection”), as well as keyword surfacing. 

In Merck’s transcript, we see a lot of highly-scored positive sentences (100 out of 100). 

On the negative side, we see the pricing pressures in 2020 comments (already picked up and classified by the ML layer) marked as mostly negative.

We can also see that pricing is the most negative analyst question as well!

The top keyword based on our algorithmic keyword surfacing is Keytruda, a relatively new but popular drug.

The second and third keywords are also product related. Below we see an active discussion around Gardasil capacity.

And the focus on Keytruda and Gardasil is justified. Using Sentieo’s Table Explorer table chaining tool on the 8-K filing, we can see that both drugs continue to grow, with Keytruda now approaching 30% of revenues. 

Watch the video below to see it in action:

View the full report on Merck here, and try using Smart Summary™ for yourself by signing up for access for Sentieo.