Data Analytics Methods
Practical Time Series Forecasting – Data Science Taxonomy
“Big data is not about the data.*” ― Gary King, Harvard University (*It’s about the analytics.) Machine Learning. Deep Learning. Data Science. Artificial Intelligence. Big Data. Not a day goes by that one or all of these buzzwords stream past in our business news feeds. Data analytics has become mainstream. And you better jump on…
Read MorePractical Time Series Forecasting – Potentially Useful Models
“All models are wrong, but some are useful.” ― attributed to statistician George Box This quote pretty well sums up time series forecasting models. Any given model is unlikely to be spot on. And some can be wildly off. But through a careful methodical process, we can whittle the pool of candidate models down to…
Read MorePractical Time Series Forecasting – Some Basics
“The long run is a misleading guide to current affairs. In the long run we are all dead.” ― John Maynard Keynes, A Tract on Monetary Reform Forecasting the future is an exercise in uncertainty. And the further out one looks, the more uncertain the forecast becomes. Most businesses are keenly focused on the next…
Read MorePractical Time Series Forecasting – Introduction
“The only thing I cannot predict is the future.” ― Amit Trivedi, Riding The Roller Coaster: Lessons from financial market cycles we repeatedly forget It goes without saying that every business is keenly interested in knowing what the future will bring. Will sales grow next year? By how much? Will suppliers increase their prices? How…
Read MoreFinding B2B “Look-Alikes” in Latin America
One of the uses of any B2B database is to find prospective customers that look like current customers (aka “look-alikes”). With more developed and complete data, like what exists for the US, this can often be done using statistical predictive models. These models can yield “prospect scores” appended to individual business locations as to their…
Read MorePractical Time Series Forecasting – To Difference or Not to Difference
“It is sometimes very difficult to decide whether trend is best modeled as deterministic or stochastic, and the decision is an important part of the science – and art – of building forecasting models.” ― Diebold, Elements of Forecasting, 1998 A times series can have a very strong trend. Visually, we often can see it.…
Read MoreEnhanced B2B Data Can Markedly Improve Prospect Scores
Data availability can limit the quality of B2B prospect scores. We are not talking about sample size, which is important. But about the characteristics of the businesses the prospect score is meant to rank. A client’s customer was using an “off the shelf” application for prospect scoring. This application used a very limited set of…
Read MoreB2B Prospect Scores – Improving Marketing ROI in the Information Technology Vertical
We build a lot of B2B prospect scores for one of our clients. One customer of this client recently tested a prospect score we built on their behalf. Their goal was to determine how much “lift” the prospect score provided to their outreach campaign for their information technology networking solution. That is, they wanted to…
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