Revolutionizing Collection Development
ESP harnesses the same Machine Learning methods that drive Apple’s Siri, Google’s Assistant and the recommendation engines at Netﬂix and Amazon to predict how current and forthcoming titles will perform in your library’s collection.Continue Reading »
Which titles? ESP’s Powerful Ranking engine examines evidence of author’s past performance, BISAC performance, title reviews and demand to recommend titles that will perform well in your collection.
How many copies and to which branches? ESP’s Distribution function suggests how many of each title to buy and how to share those titles across library branches based on local circulation evidence. ESP understands that every community is diﬀerent and so empowers you to create unique distribution goals to meet the needs of each branch.
"We’ve been using ESP for more than five months. Combined with our collectionHQ strategies we’re already seeing steady drops in our Dead on Arrival numbers month after month. We’ve also increased our turnover which is something we’re focusing on more as we try to right-size the collection based on usage and demand.”
- Dr. Gabriel Morley, Atlanta-Fulton Public Library System
" The reason we chose collectionHQ and ESP was for the level of transparency it offers our staff and stakeholders in collection planning. "
- Deanna Rabago Lechman, Contra Costa County Library
" We hit one million+ circulations last year for the ﬁrst time ever and I give credit to collectionHQ and ESP. We are using collectionHQ to develop our materials budget this year. We monitored our ESP purchases and found that after a few tweaks a very small percentage did not circulate in the ﬁrst 90 days. Oh, and our turnover rate is 3.2. I’m super pleased. "
- Corinne Hill, Chattanooga Public Library
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