Using Twitter & AI to understand why The Cheesecake Factory tanked after its latest (Q2FY18) earnings release

What’s the story?

Everybody wants the takeaway — the big picture insight. That story is typically hidden in plain sight. It’s embedded in the context of text information like articles, blogs, comments, the transcript, the filing. It takes time to read, process, and put things into perspective. Most folks don’t have the time or the resources. This is where A.I. can help.

It’s in the context behind the number

Over the past weeks, streams of public companies have released their earnings. Keeping up with the rationale behind share price action of these companies is not an easy task. For example, Cheesecake Factory (trading on the NASDAQ as CAKE) released its financial results for the second quarter of fiscal 2018, which ended on July 3, 2018. On the surface, revenue was up, from $569.9 million a year ago, to $593.2 million and comparable restaurant sales increased 1.4% in the second quarter. Yet, the stock tanked after the earnings release.

Let AI read the Internet for you

Last week I introduced the ALM Social Edge — our “social network analyzer” that uses Symbolic AI to learn what’s relevant and why by reading Twitter messages and drilling into the content of links people share using deductive rationale. Today, paid tools (Sprinklr, Brandwatch) and a plethora of free options analyze social media but are limited to surface insights — counts of hashtags, likes, and mentions — that lack context. The difference is simple. With Artificial Intelligence, the ALM Social Edge understands context, intent, and articulates the rationale — all by itself.

The importance of context

Let’s look at an example. MarketWatch, a popular finance blog, published an article “Cheesecake Factory stock falls on earnings miss” which gives us numbers, but no context.

“The company reported second-quarter net income of $28.4 million, or 61 cents a share, compared with $38.2 million, or 78 cents a share, in the year-ago period. Adjusted earnings were 65 cents a share. Revenue rose to $593.2 million from $569.9 million in the year-ago period. Analysts surveyed by FactSet had estimated 81 cents a share on revenue of $592.7 million.”

Finding context with the ALM Social Edge

We connected an ALM to a Twitter account that follows business and financial accounts. The ALM automatically publishes a report every hour of key relationships and supporting excerpts. After The Cheesecake Factory published its earnings, our AI picked up the following.

• EARNINGS -> CAPITAL -> HEALTH
• See BUSINESS -> PERFORMANCE -> GROWTH -> HEALTH

We can read the excerpts one by one or use Meta-Vision, an ALM reporting tool, to re-organize the AI findings by sentiment and trace the following excerpt to the company’s “Safe Harbor Statement”:

“ … ability to: deliver comparable sales growth; provide a differentiated experience to guests; outperform the casual dining industry and increase its market share; leverage sales increases and manage flow through; manage through cost pressures, including increasing wage rates, group medical insurance costs and legal expenses, and stabilize margins; grow earnings; remain relevant to consumers; attract and retain qualified management and other staff; manage risks associated with the magnitude and complexity of regulations in the states and municipalities where the Company’s restaurants are located; increase…”

The AI also linked this excerpt from a retweeted press release.

“Comparable sales at The Cheesecake Factory and core restaurant operating performance were in line with our expectations during the second quarter, said David Overton, Chairman and Chief Executive Officer. However, $4.6 million in higher group medical insurance costs year-over-year and $4.5 million in increased legal expenses impacted our bottom line results this quarter.”

In just a few seconds, the ALM gave us the missing puzzle pieces that help explain why The Cheesecake Factory tanked after earnings came out.

Connecting the Dots

Every day, business teams — from sales to PR to marketing and client services — let 99% of Twitter insights go unused. Surface insights from quantitative analysis are like getting the file size and views of a picture without knowing what’s inside.

In contrast, the ALM’s symbolic AI finds the dots and connects them to help you see the big picture and deep insights you need to help de-risk decision-making and capture more opportunity.

The best part: The ALM Social Edge is available today — as many users, as many Twitter streamers, as much data, as many reports as you want — for just $100/mo. Learn more here at our website: www.sitefocus.com/almedge

Questions? Just reach out or follow us on Twitter!

Note: this article was originally published on the SiteFocus Blog.