Following the release of a whitepaper on email newsletters, accompanied by a series of Jupyter Notebooks, which allows organizations to analyse their own data— the Shorenstein Center team have started working on an Email Newsletter Benchmarking tool. This article exposes the process of the invention, its use, and what every news agency should expect from the new tool.
At Shorenstein Center, the tech team focuses on examining and creating a tech model that helps newsrooms work toward reliable business models.
Note: An email benchmarking tool offers reports that can be used to improve the efficiency and engagement newsroom’s email products.
Will Hakim explained how the positive feedback and complaints from their initial users helped improve the product. While speaking on the availability of their product to the public, he said “Any newsroom can apply to use the tool, enter a MailChimp API key, and receive a “report card” with a few email metrics benchmarked against peers.”
Differences between email benchmarking tool and Jupyter Notebooks
Considering the similarities between series of Jupyter Notebooks and email benchmarking tool, one would conclude that the benchmarking tool is a modified version of Jupyter notebooks. The motivation behind the creation of email benchmarking tool is founded on the complaints lodged by the users of Jupyter Notebooks — inconvenience, bulky analysis, incomprehensible data and clarity issues.
The new email benchmarking tool has these qualities;
- Down-to-earth interface
- Simple and clear results
- Relevant statistics based on users permission
Behind every awesome digital invention, there’s a technology behind it. With Python backend, the tool is supported Flask, RabbitsMQ, Celery, and Postgres operating on AWS.
At trail, most products go through the process of partnered reviewing and this tool is not an exception. Email benchmarking tool has gotten a lot of positive reviews from its initial users.
The process each feature goes through before implementation is a thorough one. After proposal, the team would discuss pending features, start feature development using git-flow model. Within the stipulated time, the new feature is ready. Then, in order to filter out residual bugs, the team would run QA on a development server.
Having read the product use, reviews, process of creation and new features, one would realize email benchmarking tool is a fortune waiting to be explored. What’s your take on this new tool?
Let us know your view in the comment section. Thanks.