In our third post on the four part series on how machine learning works I’m going to explain two types of models that we use for our customers; decision trees and random forests. Random forests are more advanced learning models that are capable of creating more complex decision boundaries than logistic regression (covered in our last post). The “forest” part of the name means that it is made up of multiple decision trees.…
Predictive lead scoring has grown into a hot topic in the past 18 months. SiriusDecisions reports that there are nearly 14 times more B2B organizations using predictive lead scoring today than in 2011. With any new technology the questions arise of “what does this technology do?” and “how can it help me accomplish my goals?”
If you’re like most companies, you’re constantly on the hunt for ways to improve lead conversion rates and build higher quality pipeline.…
When evaluating a predictive lead scoring vendor, potential customers tend to prefer a black-box style of evaluation, in a legitimate imitation of the blind testing procedure in medical research. The purpose of these tests is to evaluate whether an analytics product will perform well in deployment, rather than simply on the initial evaluation data. However, sometimes the blinded nature of the test can defeat your true goal.…
Hot on the heels of a partnership with Dun & Bradstreet, the announcement of the Datalogix acquisition marks an aggressive move on Oracle’s part — an attempt to prove to the market that it’s getting serious about data-driven marketing. Salesforce added Datalogix to its marketing cloud back in April 2014. This Oracle acquisition will probably be making some Salesforce folks feel like they got a lump of coal in their stocking this year.…
In this blog post I’m going to cover logistic regression and how it applies to building predictive lead scoring models. This is the second in a four part machine learning overview series. Logistic regression is one of the simplest machine learning model types. It involves fitting a logistic function to a set of data. In one dimension, the logistic function looks like this:
What we are seeing here is that this function ranges between 0 (as we move left), to 1 (as we move right).…
The data science team here at Fliptop uses machine learning methods to create models that predict which leads will convert into an opportunity and customer for your business. In this blog I’ll talk a bit about how machine learning actually works. Specifically, I’ll discuss about a problem called “classification,” which means classifying data into different classes. At Fliptop, classification is important because we want to classify leads based on whether or not they will convert (in reality we make a more complicated prediction of how far the lead will make it in your sales pipeline, but we’ll keep it simple here).…
20 Can’t-Miss Marketing Events in H1 2015
With the new year just around the corner, it’s time to take stock—and secure a spot at—of some of the can’t-miss marketing events of the coming year. These events are not only a great opportunity to “press flesh,” but to learn about new trends in data-driven marketing from some of the foremost experts on the subject.…
Besides a new pair of boots, a nice jacket, and heck, a puppy, Predictive Lead Scoring would be on my Christmas List.
As anyone in sales knows, chasing prospects is hard. It takes creative emails, follow up, persistence, and lots of phone calls. What’s harder is going through a list of hundreds of prospects to call without really knowing anything about them, or if they are even qualified.…
At Fliptop we are fortunate enough to work with some of the leading tech companies in the world. On Sunday November 23rd we took a group of them to watch the 49ers play the Redskins in the new Levi’s Stadium. As a company we are a fan of predictions and it looked like the 49ers would win according to Microsoft’s prediction engine.…
If you’re like most companies, you’re constantly on the hunt for ways to create better alignment between sales and marketing. When sales are disappointing, marketing blames sales for poor execution on the valuable leads they sourced. Sales, in turn, argues that marketing is spending too much of the budget on activities that generate weak leads. Sales needs more, better qualified leads and it’s marketing’s job to deliver the goods.…
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