I’m calling it now. The next battleground for analytics adoption among business users will be the productivity suite. Let’s unpack that statement by considering these two examples: Traditional BI has always forced you down a one-way street for answers—drop what you are doing, login to the BI tool, and pray to the data deities that you can find the answer you’re looking for.

I recently watched the movie Air. I absolutely loved it. Note: if you don’t want spoilers, you may want to skip the next two paragraphs. Air is a story chronicling how Nike, the underdog in those days, steals Michael Jordan away from Adidas and Converse. With the cards stacked against Nike—they had a much smaller budget than their big-brand competitor, Adidas—it was conventionally assumed that Michael was better off signing with a more established brand.

In the past, it was commonly believed that only administrators or designated support contacts benefited from live product support. But that shortsighted view fails to acknowledge the reality that every user—be you an occasional business user, tenured analyst, or in-the-weeds IT administrator—can encounter roadblocks and require assistance. That's why our new In-App Support is available to all users worldwide, regardless of their role.

Here’s what customer loyalty looks like to us at Wellthy and the data-driven tactics we rely on to keep our customers coming back for more.

Picture it: You are the owner of a growing digital purveyor of premium baked goods. You see that your chocolate chip, macadamia nut cookies with a hint of coconut are going gangbusters whereas sales for peanut butter cookies are declining. This is bad for margins because the peanut butter cookies cost less to produce than the chocolate chip, macadamia nut, coconut cookies. You decide to offer a special coupon for your loyalty customers to grow the peanut butter cookie sales.

Organizations across all industries are racing to understand large language models (LLMs) and how to incorporate the generative artificial intelligence (AI) capabilities provided by LLMs into their business activities. Thanks to LLMs’ broad utility in classifying, editing, summarizing, answering questions, and drafting new content, among other tasks they are being embedded into existing processes and used to create new applications and services.

It’s no surprise that cloud spending is rapidly increasing, so it’s also no surprise that controlling those rapidly increasing cloud costs is a top priority for business, technology, and data leaders. According to Gartner, the use of public cloud computing has increased IT spending for most organizations (54%) over the last three years, with only 29% reporting that the cloud decreased IT spending.

Today we're excited to officially launch AI Explain on ThoughtSpot for Sheets, the ultimate cheat code for data literacy and exploration. AI Explain integrates Google's PaLM 2 LLM, specifically leveraging the Bison model to automatically generate the top data stories for any visualization created with our Sheets extension.

At ThoughtSpot, we believe making data accessible to every knowledge worker requires human-centered technology—an analytics experience that bridges the “language” barrier between technology and people. AI is the perfect compliment to search because it empowers organizations to analyze, understand, and act on data.

Active listening is an admired and sought after skill in both the professional and personal sphere. After all, who doesn’t love to be heard? But what happens when we apply that mindset to the way our organizations solicit feedback and interact with our customers? We don’t have to make any assumptions to answer this question, because we have the data.