Emerging Business Models and Data-Driven Decision Making (PART TWO)

Course Objective

Understanding how using data and analytics can inform publishing decisions, including where and how to find the most useful data for your publishing plan. The importance of using dynamic pricing, strategic marketing, and data marketing

Segment 1: The Importance of Data in Converting Interest to Sales

• Case Study: How Data Can Generate Sales
• Book Content
• Acquisition and Development
• Ulysses Press: Unofficial Hocus Pocus Cookbook
• How our team researched the market
• Google Trends
• Facebook Insights
• Supporting Sales Data
• Why we researched
• Cost of producing this type of book
• Limited list means every book’s success is critical
• The Results
• USA Today bestseller
• $500,000 in net revenue in first 30 days
• Callisto: My First Learn to Write Workbook
• Assessing the Market - Demographic Data
• Retail Data / Comp Titles
• Amazon Search Terms
• Tiller: The Sugar Skull Tarot Deck and Guidebook
• Assessing the Market - Audience Insights
• Retail Data and Comp Titles
• Amazon Search Terms
• Product packaging - Creating a barrier to entry in a competitive market
• Where to Find your Data
• Keepa and Online Datasets
• Competitor Websites
• Book Fair Trends
• Bestseller Lists

Segment 2:

• Pricing
• Understanding price elasticity in book publishing
• The traditional value stack of a book
• The 10x Rule
• Doing your due diligence - analyzing the market and competitor packaging and pricing

Segment 3: Marketing Data and How to Harness it

• Harnessing social media data
• Building a smarter website
• Google Analytics
• Facebook Pixel and Cookies
• Email Newsletters
• A/B Testing and Campaign Optimization
• Testing before you Decide
• Using surveys and Customer Feedback
• Research Data
• Google Trends
• Moz and Alexa
• Social Analytics and Social Listening
• The Value of Sales Data in Decision Making

Segment 4: Data Modeling for Decision Making

• The Value of a good dataset - Compiling your data and data hygiene 
• Forecasting for optimal inventory
• Using time-series datasets to optimize publication dates
• Comp Titles
• Google Trends
• Amazon Search Terms
• Crafting and reviewing P&Ls
• Tools for Data Visualization (low cost and free trials)

Download Exercise 1

Download Exercise 2

Google Analytics

CMS: Content Management System (a backend system used to edit and publish content on a corporate website). 

Unique User: An individual browsing a website from an IP address that is fresh to the site. 

Pageviews: The sum of website pages visited by Users during a set period of time. Users may visit multiple pages during a session on the CMS. 

Session: A user’s (IP address) active period on the site (sessions reset after the IP address has not been active on the site for 30 minutes). 

Bounce Rate: The percentage of visitors who arrived on a page and then exited without taking any action (clicking a link, button, etc.). Target bounce rate: below 70%.

Events: Specific actions on the website tied to preset KPIs (such as newsletter signups or clicks on “buy” buttons).

Device Category: Reporting on the devices a visitor is using to access web content: a desktop/laptop, mobile phone, or tablet. (Knowing this is critical for optimizing page layout and design).

Organic Visitor: A user who has arrived on the CMS through a search engine keyword search.

Referral Source: A third-party website, social media platform, or service directing traffic to the CMS (i.e. NYT, TheNovl.com, Twitter).

Other Source: When Google Analytics doesn’t know how to classify a source, it falls into “Other.” This often happens if you are not tagging your digital marketing campaigns.

Direct Source: Traffic originating through a typed URL, bookmarked page, email link click, blocked site, or deemed “undefined” by Google Analytics.