The sales lead black hole: On sales reps' follow-up of marketing leads

The sales lead black hole-the 70% of leads generated by marketing departments that sales representatives do not pursue-may result from competing demands on sales reps' time. Using the motivation-opportunity-ability framework, the authors consider factors that influence sales reps' pursuit (or lack thereof) of marketing and selfgenerated leads. The proportion of time that sales reps devote to marketing leads depends on organizational lead prequalification and managerial tracking processes (extrinsic motivation), as well as marketing lead volume (opportunity), and sales rep experience and performance (ability). Consistent with a person-situation framework, individual sales rep factors should also moderate the influence of organizational processes on lead follow-up. Data from 461 sales reps employed by four firms confirm that as sales reps' experience increases, their responses to managerial tracking of lead follow-up and marketing lead volume decrease; responses to the quality of the lead prequalification process increase. As sales reps' performance improves, their response to the volume of marketing leads increases, but their response to managerial tracking decreases. The interplay of individual sales reps' abilities and organizational marketing and sales processes explains differences in sales reps' follow-up of marketing leads.' © 2013, American Marketing Association

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research