Predictive Sales Analytics is a game-changing technology in B2B sales. Any organisation trying to rein in erratic sales funnel, to improve the performance of their sales force or to avoid customers from churning, should have a clear understanding of predictive analytics.
Sales leaders need to grasp the applications, the benefits and the limitations of predictive analytics. They should be able to define the scope of a predictive analytics project and to calculate its return on investment (ROI). Sales executives do not need to become data scientists; they need to understand the possibilities and limitations of the data science methodology for predictive analytics.
Predictive analytics could mislead sales managers, depending on how they implement it. The most dangerous attitude is to remove predictive analytics from the radar due to a lack of basic understanding.
Machines using predictive analytics can only predict results sales managers have programmed them to do. Having this limited range of options means that they can jump to erroneous conclusions or miss critical information.
Any statistics student can tell that historical data does not inevitably determine a future outcome. That is why B2B sales leaders need more education in Predictive Sales Analytics. Here we present you with the best books to get you started with predictive sales analytics in B2B.
The Best Predictive Analytics Books for Sales in B2B
1. Data Science For Business: What You Need to Know About Data Mining & Data-Analytic Thinking, by F. Provost & T. Fawcett
Why is this book great for B2B sales leaders?
If a sales leader wants to get a good start with predictive analytics, she cannot do without some basics in data science. Data Science For Business is a great book for B2B sales leaders because it explains the basics of data mining and pattern recognition using B2B examples. It does not dwell much on data science and keeps the business cases always in focus.
This book expands on an MBA course that Provost taught at New York University for more than ten years. It introduces some fundamental principles of data science and shows the reader a “data-analytic thinking” necessary for extracting knowledge and business value from sales data. It also helps to understand today’s most modern data-mining techniques.
A sales manager can learn how to improve communication between data scientists and business stakeholders, and how to participate intelligently in her company’s data science projects. It provides several examples of real-world business problems to illustrate data mining principles.
An example of one great line of this predictive analytics book:
“To calculate the overall expected value of a model, the costs and benefits of decisions must be specified. If this is possible, the data scientist can calculate an expected cost per instance for each model and choose whichever model produces the lowest expected cost or greatest profit.”
2. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by E. Siegel
Why is this book great for B2B sales leaders?
If data science is a good start in predictive sales analytics, well, so is predictive analytics. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die is an excellent book for B2B sales leaders because it deals exclusively with predictive analytics. It also offers a special section with examples of predictive analytics for marketing and sales.
In this entertaining book, former Columbia University professor and Predictive Analytics World founder Eric Siegel argues about the power and threats of predictive analytics. Predicting human behaviour combats financial risk, overcomes spam, helps crime fighting, and, of course, improve sales.
Predictive analytics unleashes the power of sales data. With this technology, a machine learns from sales data on how to predict the future behaviour of customers. It’s not necessarily a sales book, but it is a great first approach to predictive analytics. The text is full of examples from companies such as Citibank, Facebook, Ford, Google, IBM, Pfizer, among others.
An example of one great line of this predictive analytics book:
“Whit prediction, risk becomes an opportunity.”
3. The Power of Sales Analytics by A. Zoltners, P. Sinha and S. Lorimer
Why is this book great for B2B sales leaders?
If data science is the mother of predictive sales analytics, sales analytics is the father. Although this book does not specifically discuss predictive analytics as a science, it is a significant push into the analytics mindset that a B2B sales leader nowadays must have.
Over 20 managers from ZS Associates, Inc., a global renowned sales and marketing consultancy, wrote The Power of Sales Analytics.
This book shares practical advice and illustrative case studies for using sales analytics to back sales force decisions and drive sales results. It is well structured and a great read.
The Power of Sales Analytics also offers advice on how to cost-effectively implement sales analytics capabilities by bringing together the right combination of internal and external resources. Zoltners is a professor emeritus of marketing at Northwestern University’s Kellogg School of Management, and Sinha is a former Kellogg faculty member.
An example of one great line of this predictive analytics book:
“Determining the necessary sales analytics capabilities starts with understanding what the sales force needs to be successful.”
4. Predictive Analytics, Data Mining and Big Data – Myths, Misconceptions and Methods by S. Finlay
Why is this book great for B2B sales leaders?
This is probably the only particular book in Predictive Analytics of our list. Therefore, for sales leaders with data science aspirations or data mining affinity, this book is a must-read. It offers several great examples of data analysis solutions and their benefits for B2B organisations.
This in-depth technical book is written in an accessible style and provides sales managers with a solid understanding of data science and data trends. It also presents the reader with examples of the opportunities that big data analytics can offer to their businesses, and the drawbacks of these technologies. Steven Finlay provides with “Predictive Analytics, Data Mining and Big Data” a contextual roadmap for developing solutions that effectively create value in B2B organisations.
Dr Finlay holds a PhD in predictive analytics, is an honorary research fellow at Lancaster University in the UK and is currently Head of Analytics at HML, the UK’s largest provider of mortgage administration services. He brings more than 20 years’ experience in developing practical value-added solutions in big data environments and has published several practically focused management books about predictive analytics.
An example of one great line of this predictive analytics book:
“Predictive Analytics is all about understanding the relationships between the predictor data and the behavioural (outcome) data. You can’t do predictive analytics if one of these types of data is missing.”
5. Predictable Revenue: Turn Your Business Into a Sales Machine with the $100 Million Best Practices of Salesforce.com by A. Ross and M. Tyler
Why is this book great for B2B sales leaders?
Any sales leaders aiming to grow an organisation using predictive sales analytics should read this book. Although it is a bit of free advertisement for Salesforce and A. Ross, it offers great detailed advice on building sales processes that will encourage a predictable outcome.
Predictable Revenue is a book about building a predictable sales process, not specifically about predictive analytics. It will help you to understand the active link between clearly defined sales processes and predicting revenue forecast.
Predictable Revenue describes in detail (maybe excessively) the outbound sales process underpinning almost $100 million in recurring revenue to Salesforce.com.
This book offers a robust analytical approach to undertaking a classic prediction problem: revenue planning and growth. It also compares its co-author, Aaron Ross, with Thomas Alva Edison.
Not every example provided might be of interest to a B2B sales leader, but altogether it is a fascinating read. If predicting revenue growth is the primary challenge that your B2B organisation is facing, then read it.
An example of one great line of this predictive analytics book:
“If you sell to sales executives, change your fiscal year to January 31 or February 28. Why make life unnecessarily harder for yourself by trying to close deals with the very people that are trying to close their deals at the same time? ”
Do you know any other predictive analytics book to recommend? Do you have questions? Write to us!
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