After significant research and speaking with many literary agents, we derived the following numbers:

  • unsolicited queries per day, seven days per week: 20 - 100 (typically agents receive 10,000+ per year, or 27 per day)
  • agents, as professional readers, spend 3 to 8 hours reading a full manuscript, on average about 40 hours per month spent reading manuscripts originating from the slush pile
  • average number of full manuscripts requested from slush queries per month =  1.8
  • number of hours spent reviewing manuscripts per month  = 4 weeks * 1.8 manuscripts * 5.5 hours = 39.6
  • average number of minutes spent reviewing queries = 2 minutes
  • average number of queries per month = 720 (most agencies get 20 to 30 queries a day, 7 days a week)
  • average number of hours spent reviewing queries per month (720 queries * 2 minutes ) = 24 hours
  • average hourly salary cost of a literary agent (from $55k salary) = $30
  • monthly spend on reading queries and submissions (39.6 hours + 24 hours) = 63.6 hours * $30 = $1908
  • average number of new clients acquired by an agent each year =  3
  • 0 to 0.05% of all queries result in a new client being signed by an agent
  • average resource spend to acquire new client with book deal, per month = ($1908 * 12months / 2 clients) = $11,448
  • average agent success rate (with shopping new client manuscripts to publishers) = 50%
  • % of manuscripts published from the slush pile = 0.05% get signed by agent
  • success rate of query submissions to book deal (0.05% * 0.50%) = 0.025%  (1 in 4000) 

Publishers lose money on 70% of the titles they publish.

Slush Filter

Slush Filter, helps literary agents filter through the mass of unsolicited manuscripts they receive on a daily basis, a process that is currently manual. It provides agents with generated metadata about the work, and a rating of its potential commercial value.

Slush Filter assists agents by:

  • reducing the man hours dedicated to manuscript review
  • increasing the accuracy of manuscript filtering (less high market potential manuscripts will be overlooked)
  • bringing a higher level of certainty to the clients/manuscripts agents invest in, backed by data

Slush Filter uses natural language processing and statistical analysis to identify manuscripts of high quality, and also to derive other important metadata, such as the industry standard BISAC classification.

Slush Filter does not aim to replace the manual selection and review process, but to augment it by providing more insight and information on a prospective manuscript, suggesting it be manually reviewed further.

The first version of Slush Filter will cover fiction titles only.