natural language processing Finding frequently asked questions in Google with Natural Language Processing It's pretty clear that Google searches are a key way people find businesses. 35% of referral traffic comes from search, versus 26% from social, a difference that appears to be growing.
models Talks on probabilistic modelling from tech @ ThriveHive In the past month or so we've been giving talks and workshops on one of our projects to predict customer spend on different digital marketing services. Briefly, the project aimed to use
models Interpreting machine learning models: Picking low-hanging business insights, Part 3: Getting results In the previous blog posts we talked about interpretability in machine learning and how to set up your machine learning question. We also discussed a bit about the application to ThriveHive's data.
models Interpreting machine learning models: Picking low-hanging business insights, Part 2: Asking questions Interpreting machine learning models: Picking low-hanging business insights Part 2: Asking questions In the previous blog post we examined the importance of interpretability in machine learning models and how to interpret the parameters
models Interpreting machine learning models: Picking low-hanging business insights, Part 1: Linear thinking ThriveHive has been putting out a couple of exciting infographics based on some of our work here on the Data Science team. I thought it might be worthwhile to dig into the
natural language processing Identifying product mix, part 2: Implementation In the previous post, we outlined one of the major challenges facing analytics here at ThriveHive; segmenting a business population that may not fall neatly into existing classification systems. We came up
natural language processing Identifying product mix: A bottom-up approach to segmenting a small business population Part 1: Set up Typically methods for segmenting businesses have relied on standardized industry classification systems (e.g. NAICS). However, the limitation of a top-down industry classification system is that it does
natural language processing How the Words Used in Email Subject Lines Relate to Open Rates Previously, we found that the association between subject line length and email open rate varies by industry. In this blog post, I will use the same generalized linear model (GLM) to examine
email What Impact Do Email Subject Lines Length Have on Open Rates? Previously, we found that ThriveHive customers' email campaigns achieve open rates significantly higher than the industry standard. This difference, however, varies by industry. For example, Computers & Electronics and Entertainment & Events