Price Setting

Lit-X AI- & data-driven Price Setting addresses book publishers. It allows you to define a unique comparison group vs. any publisher/author/title combination, define a competitive initial price, adjust the life-cycle pricing based on a cohort comparison, and analyze your own or your competitor's price-change impact via a revenue estimation.

Benefits

  • Efficient

    Set strategic life-time prices faster and better informed for more titles

  • Quality

    Set data-driven prices, that directly optimize your bottom-line impact

  • Repeatable

    Repeat your individual process reliably for every title you acquire or sell

  • Robust

    Benefit long-term from initially well-set prices, for eBooks or print

  • Happy

    Focus on value-adding tasks that are fun, not manual research

  • Empowered

    Start working with AI and data and embrace this entirely new work era

Overview

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Details

Features

  • Define a unique peer group fitting your to-be-priced title, based on genre, publishing date, product variant, success and many more
  • Compare a transparent pricing distribution for your defined peer group and directly compare, e.g., with a competitive peer group 
  • Track price development over time in order to understand trajectories and adjust your pricing decision to anticipated future development
  • Differentiate your pricing for different product variants, publishing cohorts or other detail aspects 

Data Scope

We constantly extend our data scope. Depending on the data type, the scope may vary marginally. Currently, we cover the following data scope: 

  • Countries: Germany, United States
  • Titles: All titles generally available
  • Authors: All authors generally available
  • Genres: Crime, Thriller, Mystery, Children's (only story-telling sub-genres), Romance
  • Genres hierarchy: We provide a three-level genre hierarchy: 
    • Level 1, e.g., "Thrillers"
    • Level 2, e.g., "Thrillers - Supernatural"
    • Level 3, e.g., "Thrillers - Supernatural - Vampires"
  • Data types: Publisher, author, author gender, title, topic, various success metrics, ratings, reviews, price, product variants, popularity (custom use cases may include additional data types)
  • Sources: We collect data from dozens of sources including but not limited to major online shops, review communities, agent communities, individual publishers, distributors, agent and author pages, social media platforms, text aggregators, and industry associations. 
  • Updates: Data is updated once per month

    Data Quality

    Our data runs through an extensive quality control process. We capture all potential issues in an automated and reliable way. Issues addressed are constantly being updated, since we continuously increase our data quality further, dive deeper into the data and explore more use cases.

    Common issues include misspellings (e.g., Stefen King), different ways of writing names (e.g., H. P. Lovecraft vs. HP Lovecraft), data gaps in our input sources (e.g., no price available), wrong data in our input sources (e.g., miss categorized: "The Gift" in "Gift books" instead of "Thriller"), and many more.  

        Updates

        • Updates are generally done on a monthly basis
        • Updates imply a data pull from all available sources
        • Updated data doesn't overwrite previous data but is appended to it, building a transparent timeline and adding value to the data

            Success Definition

            We define "success" as a multi-layered metric that is user-centric and consists of two main aspects:
            • It includes a reader perception component that measures how well a book is received by the readership based on ratings and reviews
            • It includes an approximation of actual sales based on price, number and value of ratings, reviews, bestseller list entries, and more

                  Preview

                  Demo

                  Try out our fully functional Trend Scouting demo. It portrays all major features and the tool's look & feel using anonymous data. It's similarly representative of the Price Setting use case.

                  Try demo

                  Take-Home PDF Intro

                  Book an Intro

                  We are happy to walk you through our Trend Scouting use case, provide you with detailed explanations and share best practices on how to start working in an AI- and data-driven way.

                  Book an Intro Call

                  Purchasing Options

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                  Price Setting

                  Price Setting

                  €750.00
                  €1,000.00 €750.00
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                  After your order

                  • Firstly, you will receive a confirmation e-mail confirming we received your order.
                  • We then process your order and grant you access to your Dashboard.
                  • As soon as we have processed your order a new link "Your Success Analytics" will appear in the top navigation for you. Here, you can access your purchased product.
                  • Please allow any pop-ups for our page, to have an optimal single-sign-on (SSO) experience.
                  • When you purchased a standard use case product, you can immediately access your dashboard.
                  • When you purchased a customized product, we'll reach out to you to schedule a call to discuss your individual customization requirements. After the customization, you'll be able to access your product through the same "Your Success Analytics" link in the top navigation.
                  • You can check whether or not your order has already been processed in your customer account under "Order details".

                   

                      Purchasing conditions

                      • All Lit-X Success Analytics products are subscription models 
                      • Depending on your chosen subscription plan your payments are due monthly or annually
                      • Regardless of your chosen subscription plan, you can cancel your subscription in your customer profile
                      • All subscriptions renew themselves automatically after the last payment period, if not canceled in time 
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