August 1, 2022
3 mins read
Data Science and Demandbase – Yeah, We Do That
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We recently highlighted the numerous modeling data attributes available from Demandbase. This blog will address how and where this data is used in the model building process.
There are many paradigms that can be used to represent the model building process in different levels of detail – a long popular example is CRISP-DM. For this exercise, we’ll use the fairly simple example shown below.
Demandbase can help with the model building process in two key ways. First, the more traditional way that we’ve supported Data Scientists(DSs) is in the Data Gathering and Data Pre-Processing Steps as shown below. Second, Demandbase recently launched D2 Labs – a group of data scientists, data analysts, and solutions engineers that can assist in the entire model building process, developing customized models and predictions for our customers. We’ll cover those more recent capabilities later in this post.
1. Data Gathering/Sourcing
When predicting the probability to convert, DS’s may have some ideas on which set of data attributes will be most helpful based on domain and industry knowledge. But, there are attributes/variables/features that are predictive that they may not be aware of. That’s why DSs want “all of the data!” – they don’t know what they don’t know. Today, DSs can input tens or even hundreds of variables into their algorithms. That allows them to determine which of all of those potential features help better predict lead-to-pipeline conversions.
2. Data Pre-Processing
Demandbase can play a couple of roles here.
Demandbase’s recent launch of D2 Labs offers a significant advantage for customers that don’t possess the prerequisite knowledge to build their own models – as well as for customers that want to leverage Demandbase’s vast data repositories and take advantage of an Analytics team that works day-to-day with this data in conjunction with 1st-party data.
Our D2 Labs scientists wield custom data sets (1st and 3rd-party) to unearth new opportunities using proprietary propensity models. Customers can now engage with Demandbase’s data experts and data scientists directly to turn their incomplete, inactionable data into revenue-generating insights.
D2 Labs has worked with enterprise customers such as Microsoft Azure, Adobe, DocuSign, and more.
To learn more, contact your CSM or account manager. If new to Demandbase you can reach us here!
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