Reddit mentions: The best total quality management books

I'd probably start with a combination of Boyd's Convex Optimization and Nocedal's Numerical Optimization.

Convex optimization optimizes convex functions over convex sets, and thus provably finds global optima efficiently. Nocedal's book on the other hand first covers unconstrained and then later constrained methods for the optimization of non-linear functions which may or may not be convex. Thus these methods will only provably converge to local optima.

Convex optimization has a rather structured almost algebraic feel to it, when compared to the more free-form and heuristic feel of general nonlinear optimization.

For Boyd's book you can supplement it with his online course EE364a as well as a set of excellent supplemental problems found here.

For Nocedal's book you can supplement it with some notes by Blomgren found here.

After this you could move on to more advanced convex optimization with Boyd's follow-up course on advanced convex optimization EE364b. Or you could look into heuristic/global optimization which relaxes guarantees on convergence in an attempt to find the global optima of non-convex functions.

There is also integer programming/combinatorial optimization. For this in my opinion the best introduction for a mathematically mature student is Wosley's Integer Programming.

Integer programming generally proceeds via relaxations to convex optimization problems, followed by rounding the results to integer values, and tends to incorporate more probabilistic methods than do either convex or nonlinear optimization. Integer programming is also inextricably linked to complexity theory, so you'll get to learn about the various complexity classes and how they relate to various families of integer programming problems.

This should be enough to get you started.

• Start with pretty much anything Seth Godin has written. Especially Purple Cow.
  
  
• I'm a big fan of understanding cognitive issues, so Thinking Fast and Slow can help you understand how minds work.
  
  
• to understand what CRM was really intended to be, read The One to One Future
  
  
• Given your interest in digital check out these books on lean methodology: The Lean Startup and Ash Maurya's brilliant compliment, Running Lean
  
  In general, when it comes to things like SEO, SEM, etc you are better off sticking with blogs and content sites like SEOMoz, Marketing Sherpa, and Danny Sullivan/Search Engine World. By the time a book is written it's usually out of date in these fields.

If you want theoretical / mathematical I would suggest reading a few math, stats or engineering books.

Dover is a great place to find some cheaper reading material. They republish old scientific and math texts that were popular in their time in a smaller sized paperback. They're a nice size to bring around with you and they don't cost much.

Math and stats findings of today build on this knowledge, and much of it is still used in state-of-the-art applications. Or, that math/stats is used as part of some state-of-the-art algorithm. Lots of the newest ML algorithms are blending math from a variety of areas.

Statistical analysis of experimental data

Principals of Statistics

Information Theory

Statistics Manual

Some theory of sampling

Numerical Methods for Scientists and Engineers (Hamming)

Mathematical Handbook for Scientists Engineers

Handbook of Mathematical Functions: with Formulas, Graphs, and Mathematical Tables

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There is also the Data-Science Humble Bundle for more technical / practical skill building.

Best $17.60 you'll ever spend

To be fair...he wrote A book. And it wasn't particularly ground breaking, his first book was basically the TL;DR version of "The One to One Future" by Peppers and Rodgers:

http://www.amazon.com/One-Future-Don-Peppers/dp/0385485662/ref=sr_1_1?s=books&ie=UTF8&qid=1414407616&sr=1-1&keywords=the+one+to+one+future

http://www.amazon.com/Crush-Time-Cash-Your-Passion/dp/0061914177/ref=sr_1_3?s=books&ie=UTF8&qid=1414407524&sr=1-3&keywords=Gary+Vaynerchuk