AI for Marketing and Product Innovation

INDEX

A

• Absolute value function, 48, 196
• Accenture, 209
• Acura, 175
• Adjacency expansion, 129
• Advertising costs:
  • rationalizing of, 24–25
  • and time compression, 178–181
• Advocacy, consumer, 142–143
• Agreeableness (personality trait), 167–168
• Ahrendts, Angela, on consumer data, 26
• AI, see Artificial Intelligence
• “AI-complete” problem, 61
• Algebra, 78
• Algorithms, xxiii
  • forecasting/prediction, 54–61
  • for future creative/research agencies, 203–204, 221–223
  • genetic, 87–92
  • for identifying product contexts, 125–126
  • NLP, 61–70
  • for promotions, 139–140
  • tasks executed by, 3–5
• Algorithmic Pricing, 131
• Alpha-beta search (game AI), 42
• AlphaGo, 39
• AlphaZero, 2, 39–40, 49
• Altman, Sam, on AI, xxv
• Amazon, 22, 111, 196, 211, 219–220
• Ambiguity score, 186
• Anomalies, detecting, 116–117
• Apple, 220
• Ariely, Dan, on Big Data, 181
• Armstrong, Stuart, on difficulty of programming, 153
• Artificial Intelligence (AI):
  • defined, xxii
  • latest capabilities of, xxv
  • partnerships with, 195–196
• Artificial selection, 88
• Association, 103
• ATM fees, 136
• Attitude, 21
• Auto-completion, 62, 65
• Automatic rule inference, 10
• Automatic translation, 69
• Average values, 19
• Awareness, consumer, 141

B

• B2B (business-to-business), 189–190
• Backus, John, 93
• Backward chaining, 10
• Bait and switch price, 137
• Barksdale, Jim, 141
• Barron’s, 110
• Baseball, 82–83
• BASIC, 94
• Bayesian algorithms, 104
• Bayesian classifiers, 53–54
• Bayes’ theorem, 53
• BCG, 194
• Behavioral data, 155
• Bell Labs, 93, 95
• Berriman, Richard, 185
• Best Buy, 174
• Big 5 personality ...