Hear from our CEO, Carl Wartzack, on a variety of topics from the state of data acquisition to the role technology plays in shaping e-commerce.
Learn the challenges of competitive data analytics, techniques that make data acquisition difficult, and investments QL2 is making to collect better data while maintaining anonymization.
In this series, our Data Scientist explores and analyzes a QL2 used car dataset to understand and provide actionable market insights.
As we shared in the first blog post in this series, the continued investment in the anti-bot and anti-scraping space makes it continually harder for automated processes to access data on these protected sites. For the most part, there are three different strategies that sites may take in order to limit the efficacy of automated … Continue reading The Challenges We Face When Acquiring Competitive Pricing Data (Part 2)
Data continues to be one of the most valuable and sought-after commodities on the planet. Billions of dollars are being invested into figuring out how to acquire and process large sums of data. From travel to retail to government to media to healthcare, competitive data, in particular, plays a vital role in shaping the course … Continue reading The Challenges We Face When Acquiring Competitive Pricing Data
With travel season at its peak and Amazon’s Prime Day just behind us, now seems like the perfect time to blog about seasonality in competitive data. Back in June, QL2’s VP of Analytics, Joe Gagnon presented a webinar on summer travel demand and pricing. You should spend 40 minutes watching the webinar, but the summary … Continue reading How to Take Advantage of Seasonality in Competitive Data
In Part 1 of this blog series, we defined the business questions that we were going to answer, prepared the data for the analysis, created the necessary features, and decided on the data grain to perform the analysis on. Exploratory Data Analysis (EDA) In this blog, we are going to answer those business questions using … Continue reading Generating Insights from a QL2 Data Set: Used Car Example (Part 2)
So, how do you go about generating insights from a dataset? A big part of being a data scientist at QL2 is understanding and supporting the business by providing actionable market insights. To generate insights, a thorough study of the data—data cleaning, feature engineering, data sampling, statistical analysis, etc.—is necessary. Today, we will explore and … Continue reading Generating Insights from a QL2 Data Set: Used Car Example (Part 1)
As retailers roar down the e-commerce highway with omnichannel marketing becoming table stakes, the question that I’m hearing from most retailers is “How do I effectively compete in dynamic e-commerce marketplaces?” As most are discovering, technology is the answer. Some retailers have aggressively pursued technology strategies. Home Depot Ventures created a $150M fund to invest … Continue reading The Role Technology Plays in Shaping E-Commerce
When working with new customers, one of the questions that I often get is “How often should I be conducting searches, and what should I be searching for?” With regard to how often you should be searching, my base guidance is to search no more often than your ability to both analyze the data and … Continue reading Are You Optimizing Your Pricing Searches with QL2?