Natural Language Processing (NLP) in computing started over 40 years ago with a series of hard if-then rules that defined how text should be interpreted. Traditionally, NLP is thought of as analyzing large volumes of text to achieve a goal. Some of these include but are not limited to:
Natural Language Search (NLS) was introduced through search engines (anyone else an AltaVista lover?) and perfected by Google. Today, you can type the same phrases in Google and Bing and get very similar results.
We work with organizations around the world every day who are looking for a tool that helps business users get the answers they need. These organizations for all of eternity have wanted to know — what happened, why did it happen, how to react? This model has been applied to making decisions around who to target, products to develop, areas to explore, business models to deploy, setting prices, negotiations and beyond.
Analytical tools were slowly developed to address different pieces of this decision making process. As technology advanced, each progressive part of this process was addressed.
It’s a tale as old as time — why am I losing clients? The maniacal focus on losing clients is really driven by the client cost of acquisition (CAC), the dreaded cost of landing new customers. Churn analysis is more important than ever, as the cost to retain existing customers is almost always exponentially lower than the cost of acquiring new ones.
According to Hubspot, cost of acquisition is increasing because:
1. Consumer trust in business is eroding
2. Marketing costs are rising
3. Increased competition (at the source — from marketers themselves like Google with competing offerings)
Analytics transformation within organizations starts with data — collecting, organizing and storing data that might be of some value to you. Temperatures from sensors, clickstream from your website, demographic data, cash flows, job performance of your employees, on and on and on.
Rob Thomas, who lead IBM cloud when I was there, co-authored a book on the “AI ladder” — a concept that IBM sales reps spent 2018–19 fruitlessly trying to interpret and regurgitate to customers. I agree with the sentiment around data collection — every company should collect as much data as possible. …
I leave the oven on quite a bit. It’s an issue that my significant other takes great umbrage at, and for good reason — it’s a waste of resources! It doesn’t seem like a lot, but it adds up to the tune of about $0.30 per hour. This is a great example of waste at the scale of an individual, at it probably costs me 5 scolds and maybe $1.50 per year.
All over the world, people are leaving the oven on. In this case, it is a metaphorical oven with an even greater cost — that metaphorical oven is…
We view content not only as lead generation, but also as a requirement for any modern company. An ecosystem of content, both product-focused and not, is an important part of our ecosystem. From educating prospects pre-sales, to creating competitive differentiation, to converting individuals within prospective or current clients into sponsors on behalf of Tellius — content is critical for us.
So how do we put out…
More than ever, CIOs are chartered with unlocking insights into their data at scale. To support this mission, thousands of organizations are making the move to Snowflake — the cloud data platform. Technology leaders understand that rapidly expanding data volumes combined with the growth of user-driven analytics requires a scalable, flexible data foundation on the cloud like Snowflake.
We’re partners with Snowflake because they provide a great platform that unifies data and provides the world’s easiest access to that data, all while being cost effective for their customers. …
If you were even remotely aware of your surroundings in 2007, you almost certainly remember this seminal moment: Steve Jobs revealing the iPhone. Check out this clip where the crowd goes nuts when Jobs demonstrates touch scrolling. The dominant smartphone maker at the time (RIM) was reportedly incredulous and thought Apple was lying about the capabilities they showed off.
Why was the crowd so excited? They saw the potential of an integrated device. People for years used cameras for photos, TomToms for GPS, computers or terrible PDAs to send email and phones to make calls/send texts.
The 2007 iPhone had…
How I Learned to Stop Digging Through Dashboards and Love Insights
Data has been collected since ancient history. The Inca people used knotted, colored fiber strings called quipus for collecting data and keeping records — from tax obligations to census records and calendrical information.
Applying Moneyball to the NBA using Tellius
In 2003 Michael Lewis came out with a book called Moneyball: The Art of Winning an Unfair Game. This book talked about the story of Billy Beane and the Oakland Athletics — an organization that refused to spend as much money as other baseball clubs on players. Billy Beane and the A’s of 2002 applied analytics and salary adjusted sabermetrics to the player market to build competitive teams on a payroll 1/3 of the size of some of their competitors. In that same year, they won 103 games on a $41M payroll. …