Why Competitive Data is Crap | eCommerce Matters Ep. 003
Listen Now
In this episode of "eCommerce Matters" Philip Huthwaite, Founder & CEO of BlackCurve, and Dr Rob Horton, Product Director and in-house eCommerce Data Scientist at BlackCurve, tackle the elephant in the room - why competitive data is crap.
Rob and Philip detail the nuances of competitive data, why cleansing is important to avoiding bad pricing decisions and how to not worry about what your competitors are doing when it comes to pricing.
Hosts: Philip Huthwaite (CEO & Founder of BlackCurve) and Rob Horton (Product Director at BlackCurve).
🎧 Available to listen to now on all major podcasting platforms.
🎧 Available to listen to now on Apple.
🎧 Available to listen to now on Spotify.
Watch Now
Full Episode
Podcast Summary
Introduction
The participants discuss the challenges faced when working with competitor data in the e-commerce industry. They specifically mention the issue of gaps in competitor data where information suddenly disappears, leading to incomplete datasets. This can occur when third-party suppliers fail to understand the nuances of collecting data from online marketplaces, resulting in missing or inaccurate information.
Understanding the Nuances of Online Marketplaces
Understanding the nuances of online marketplaces, such as Google and other major platforms, is crucial for collecting accurate competitor data. The participants highlight the need to navigate obstacles like blocking, distinguishing between paid and unpaid listings, and using the right IP addresses to obtain a representative sample. They stress the importance of having processes and technologies in place to handle these challenges effectively.
Data Hygiene for Reliable and Usable Data
Data hygiene is essential for ensuring the reliability and usability of competitor data. The participants emphasize the need for proper curation and cleansing of the data to make it suitable for use. They provide examples of data hygiene issues, such as distinguishing between secondhand and new products, flagging significant price changes or anomalies, and avoiding pricing decisions based on incorrect or outdated information.
Challenges Faced by E-commerce Merchants
The conversation acknowledges the challenges faced by e-commerce merchants, particularly when competing against large corporations. While building in-house capabilities for data processing at scale may be challenging, the participants suggest focusing on checking the quality of the data obtained. This involves verifying that the data meets the necessary standards for its intended use, even if it is obtained from external sources.
Revenue Implications of Better-Quality Data
The participants highlight the revenue implications of having better-quality competitor data. They explain that optimizing the data set can have a direct impact on profitability. By leveraging advanced techniques like image processing and machine learning, merchants can improve the quality of the data and make more informed pricing decisions, ultimately increasing their revenue.
Importance of Competitor Data in E-commerce
In conclusion, the participants emphasize the significance of competitor data in the e-commerce industry. They stress the need to understand the nuances of online marketplaces, maintain data hygiene, and utilize reliable data sources. By doing so, e-commerce businesses can make more effective pricing decisions and stay competitive in the market.