Goodbye, Price Tags. Hello, Dynamic Pricing. — Transcript

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1. 0:00This is the story of a little piece of
2. 0:02technology
3. 0:04that you have been taking for granted.
4. 0:07Almost every time you've gone to the
5. 0:09store, this little guy has been fighting
6. 0:11for you.
7. 0:13It's called the price tag.
8. 0:17And over the past decade, companies have
9. 0:19been on a secret mission to kill it
10. 0:21without you noticing.
11. 0:23The scary part is they're actually
12. 0:25getting away with it. And that's because
13. 0:27a lot of us who grew up with the price
14. 0:28tag just never realized how radical it
15. 0:31really was.
16. 0:35Back in the 1800s, shopping was like a
17. 0:37game. The clerk would charge you based
18. 0:39on what they thought was important at
19. 0:40the time, like the length of the line,
20. 0:42the time of day, or how rich you looked.
21. 0:44If you didn't like the price he named,
22. 0:46>> 20,
23. 0:46>> you'd haggle.
24. 0:47>> 15 17. My last word. I won't take a
25. 0:50penny less or strike me dead. 15. Done.
26. 0:53>> The Quakers had a problem with this.
27. 0:55People were paying different prices for
28. 0:57the same product and that was unfair.
29. 1:01>> So they started posting prices. Other
30. 1:04stores followed suit and this one price
31. 1:06system completely changed how Americans
32. 1:08shopped. You could more easily compare
33. 1:10prices between stores and that pressured
34. 1:12stores to lower prices.
35. 1:15In the 1930s, Stan Avery invented what
36. 1:18he called come clean adhesives. [music]
37. 1:20The name didn't stick, but the product
38. 1:22sure did.
39. 1:24Soon enough, price tags were everywhere.
40. 1:27Each of these stickers was like a little
41. 1:28handshake. It represented an agreement.
42. 1:31One price for every customer.
43. 1:36But now that agreement is breaking
44. 1:40with AI and automated surveillance,
45. 1:42corporations are turning shopping back
46. 1:43into a game. Except this time, all of us
47. 1:48are going to get played.
48. 1:50>> Tonight, hidden threat to your wallet.
49. 1:52It's a practice called [music] dynamic
50. 1:54pricing.
51. 1:55>> The price of your groceries may soon
52. 1:57change right in front of your eyes.
53. 2:02>> You've probably heard about dynamic
54. 2:03pricing. It's the reason Uber prices
55. 2:05keep changing and flight costs jump up
56. 2:08and down.
57. 2:08>> Feels like we're constantly
58. 2:09[music and singing] being taken
59. 2:10advantage of.
60. 2:11>> It can send concert ticket prices
61. 2:13through the roof. Companies are using
62. 2:15algorithms to instantly change prices
63. 2:16based on demand, competition, and what
64. 2:19they know about their customers.
65. 2:21These algorithms are in a race to
66. 2:23identify the highest [music] price at
67. 2:24which a sale can still be made and
68. 2:27customers don't exactly love it.
69. 2:29>> Whoever invented dynamic pricing is
70. 2:30going to hell.
71. 2:31>> Dynamic pricing
72. 2:33>> Okay, let's chat about the ticket
73. 2:35prices, shall we? Oh my lord.
74. 2:37>> Let's be clear, price changes are the
75. 2:39language of capitalism. It's how we talk
76. 2:41to each other about supply and demand.
77. 2:44In some cases, having algorithms make
78. 2:46these changes can benefit both customers
79. 2:48and companies. But as dynamic pricing
80. 2:51proliferates, companies are also using
81. 2:53this technology to take advantage of
82. 2:54customers. And they're doing this in
83. 2:56three ways. The illegal way, the legal
84. 2:59way, and the definitely should be
85. 3:02illegal way. Let's start by breaking the
86. 3:05law.
87. 3:08Now, back in the price tag days,
88. 3:10collusion took a lot of effort. The
89. 3:12bosses had to sit around a table with
90. 3:14their competitors and smoke a cigarette
91. 3:16and agree to raise prices without
92. 3:17getting caught.
93. 3:21But today with pricing algorithms,
94. 3:23collusion is just a few clicks away.
95. 3:26When a bunch of individual companies
96. 3:28sign up for the same algorithm, they can
97. 3:30effectively collude without ever talking
98. 3:32to each other. Just look at what
99. 3:34happened with Real Page.
100. 3:35>> Software firm Real Page is accused of
101. 3:38scheming with landlords to keep rents
102. 3:39high.
103. 3:40>> Landlords subscribing to the service
104. 3:42would input data about their apartments,
105. 3:44including location, square footage, and
106. 3:46amenities. The algorithm would tell them
107. 3:49how much to charge for rent. But the
108. 3:52algorithm wasn't designed to determine
109. 3:53the market price. It was designed to
110. 3:55maximize landlord profits. So, it did
111. 3:57all the things that would have been done
112. 3:59in a backdoor deal with an ease that
113. 4:01old-fashioned colluders could only dream
114. 4:03of. It advised landlords to price their
115. 4:05apartments above the market rate. And if
116. 4:07demand was falling, it told landlords to
117. 4:09leave apartments empty rather than
118. 4:11reducing rents. The company boasted that
119. 4:13their algorithm raised revenue by 3 to
120. 4:157%. This scheme impacted over 3 million
121. 4:19apartments across the country
122. 4:21and as a result Americans were
123. 4:23overcharged by billions of dollars.
124. 4:26Now, the good news is that this model is
125. 4:28likely illegal. In fact, the Justice
126. 4:30Department sued Real Page.
127. 4:32>> That's classic [music] price fixing.
128. 4:34>> Earlier this week, Real Page settled the
129. 4:36case, agreeing to change its business
130. 4:38practices.
131. 4:40But even if this model of sharing the
132. 4:42same algorithm is illegal, this model
133. 4:45where each company uses its own
134. 4:46algorithm is legal.
135. 4:49New research suggests that even when
136. 4:51companies are using different
137. 4:52algorithms, prices still go up.
138. 4:56Let's say you run a gas station and your
139. 4:58biggest rival is over here on the other
140. 5:00side of town. Throughout the day, you're
141. 5:02constantly afraid that your rival is
142. 5:04stealing business by offering lower
143. 5:05prices. and you're constantly trying to
144. 5:08steal business from them by cutting your
145. 5:10own prices. This competition is painful
146. 5:12for you and your rival. But guess who
147. 5:15benefits? The drivers.
148. 5:19Fast forward to 2025, and you and your
149. 5:21competitor are both using dynamic
150. 5:23pricing algorithms. They're different
151. 5:25systems, but they both do the same
152. 5:27thing. They constantly monitor the other
153. 5:29stations prices and immediately match
154. 5:31any price cuts. The result is a
155. 5:33stalemate. You both stop trying to
156. 5:35undercut each other on price because you
157. 5:38know that the other station would
158. 5:39immediately respond. So prices stay high
159. 5:42and both of you make more money. But
160. 5:44guess who loses? The drivers. They end
161. 5:47up paying more for gas. A study of gas
162. 5:50stations in Germany found that stations
163. 5:52that adopted algorithms were able to
164. 5:54charge prices 15% higher than before the
165. 5:56computers took over. And researchers are
166. 5:59finding similar patterns in a growing
167. 6:01number of markets.
168. 6:03This would help explain why companies
169. 6:05are so eager to ramp up dynamic pricing.
170. 6:08Digital price tags that allow retailers
171. 6:10to update their prices instantly are
172. 6:11already in use.
173. 6:14And even small stores can play the big
174. 6:16data game. Shop owners can rent pricing
175. 6:18algorithms for as low as $79 per month.
176. 6:22And that brings us to the definitely
177. 6:24should be a legal way that algorithms
178. 6:26are used to take advantage of customers.
179. 6:29These algorithms aren't just studying
180. 6:31competitors. They're also studying you.
181. 6:35Companies want to know how much you
182. 6:36make, how you make decisions, your
183. 6:38emotional triggers, and when and where
184. 6:40you're willing to spend. So, they're
185. 6:42tricking you into handing over this
186. 6:44information by offering you
187. 6:45>> My [music] McDonald's rewards gets you
188. 6:47breakfast before work.
189. 6:48>> We're rewarding you with dollars off
190. 6:50your next purchase.
191. 6:52>> These programs do offer loyalty
192. 6:54discounts, but make no mistake, you are
193. 6:57the reward. Loyalty programs have become
194. 7:00massive data harvesting operations. Sign
195. 7:03up for My McDonald's and with one small
196. 7:05check mark, you've given the company
197. 7:06permission to track your geoloc,
198. 7:08internet history, and social media.
199. 7:11The grocery store chain Kroger has
200. 7:13stated they have over 60 million
201. 7:15household profiles. And unlike
202. 7:18McDonald's, they're not just using this
203. 7:19data themselves, they're selling it to
204. 7:21other companies.
205. 7:23So what's the harm? Well, companies have
206. 7:26already been caught quoting higher
207. 7:27prices to people logged in on fancier
208. 7:29devices and offering higherpriced
209. 7:31products based on browser history. It's
210. 7:34easy to envision how things could get
211. 7:36worse. Imagine a drugstore chain
212. 7:38increasing the price of your medication
213. 7:40by hundreds of dollars because they know
214. 7:42you need it.
215. 7:44Or that a rental site knows that you
216. 7:45need housing immediately because your
217. 7:47new job starts in 2 weeks, so it ups the
218. 7:49rental prices that you see.
219. 7:52Imagine
220. 7:54that your city faces a boil water
221. 7:55advisory.
222. 7:56>> Boil water advisory is
223. 7:58>> and so an algorithm raises the price of
224. 8:00bottled water.
225. 8:01Imagine that your smart speaker
226. 8:03overhears a conversation in which you
227. 8:04mention that you're out of paper towels.
228. 8:07And so knowing you're about to make this
229. 8:08purchase, it ups [music] the price.
230. 8:11This is the future of the price tag. a
231. 8:14series of algorithms that study you,
232. 8:16that stalk you, that do everything in
233. 8:19their power to squeeze every possible
234. 8:21scent from your pocket.
235. 8:26Governments are starting to take these
236. 8:27problems seriously. Regulators have
237. 8:30pursued companies that use algorithms to
238. 8:32collude, but we still need stronger
239. 8:34laws. Legislators should regulate when
240. 8:37companies can change their prices. They
241. 8:39could even set a single time for price
242. 8:41changes, like 6:00 a.m. That would
243. 8:43restore the need to compete on price.
244. 8:46Governments also need to limit the use
245. 8:48of personal data by both rewards
246. 8:50programs and [music] pricing algorithms.
247. 8:55Buying has always been a sort of game.
248. 8:58As algorithms take over, the future
249. 9:00[laughter] with its personalized prices
250. 9:02may at times resemble the past.
251. 9:04>> They won't take a penny less or strike
252. 9:06me dead.
253. 9:08But unless lawmakers step up, you'll be
254. 9:10up against something humanity has never
255. 9:12faced before.
256. 9:14The constant dread of wrestling with an
257. 9:17algorithm that just won't lose.