Who replies? The first or last author? Analysis of email marketing performance vs author position

In Email Marketing by Xu CuiLeave a Comment

When you are sending a cold email to a lab introducing your awesome products or service, you might wonder who is the best person to reach out, the boss (PI), or the students or postdocs who do the actual experiments?

We can argue either way. The boss (PI) might be too busy to care cold emails. He might not even care about the materials (e.g. reagents) used in the experiments. But they are the final decision maker, and maybe they will forward interesting emails to his lab. Students or postdocs are real users of the products, but it does not mean they are interested in trying new products. They most likely do not control the money.

To address this question, we run an analysis on the email marketing data collected by a biotech company over two years (2017-2019). The company provides wet lab services to biologists. In these two years, the company acquired ~1,200 hot leads (who requested a quote or asked a technical question) by email marketing to over 200,000 scientists.

We infer the lead’s status in the lab (PI or students/postdocs) by the position in the scientific publications. The last author (corresponding author) is usually the PI, and the first author is usually the students/postdocs who did the main experiment, and the rest authors also contributed to the publication. To find who is the best to contact, we calculate the distribution of all scientists in the company’s email list over author position and compare to the distribution of hot leads. Here is the result:

Table 1. Percentage of scientists in each author position

Fom the table and chart above, we can see that out of the ~200,000 scientists, about 37% are last authors, and 18% are first authors. The rest 45% are middle authors. While the last authors constitute 37% of the scientists, they contribute to 59% of the “hot leads” who replied the cold marketing emails. This means the last authors, or the PIs, should be the top priority to contact.

If we calculate “efficiency”, which is defined as the ratio of the percentage of hot leads and the percentage of all scientists (the ratio between column 3 and column 2 in Table 1), we find the last author has efficiency of 1.6, followed by the first author, 0.7, and then followed by middle authors.

This data clearly show that the PI is the best person to contact, and other people in the lab, including students and postdocs, are also good to reach out. There are a few reasons why this happens. First, many labs are small and the PIs, while busy, still managing “small things” in the lab including what equipments and reagents to purchase. Second, a PI often forward interesting emails to his team for futher information.

Lesson learned:

  1. PI is the best person to contact.
  2. Other people in the lab, including students, postdocs, and technicians, are also good to contact.
  3. Generally, we should include all scientists and do not exclude any particular type in our email marketing activities.
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