AIONOS Demo (L'Oréal ) — Transcript

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1. 0:03In this demo, we'll walk through a
2. 0:05single customer journey in the world of
3. 0:08L'Oreal. We'll meet two personas. John,
4. 0:11a chief sales officer who is running a
5. 0:13campaign targeting consumers planning a
6. 0:15trip to Europe this summer. And Sarah,
7. 0:18one of L'Oreal's target customers. She
8. 0:21receives an AI generated personalized
9. 0:23video, becomes interested in the offer,
10. 0:26and then calls the L'Oreal AI advisor to
11. 0:28learn more about what L'Oreal has to
12. 0:30offer. We'll then show you the other
13. 0:32side of the journey, how that customer
14. 0:34interaction feeds back into the system,
15. 0:36and how L'Oreal's corporate team gains
16. 0:38visibility into whether the campaign is
17. 0:40delivering meaningful business outcomes.
18. 0:42Sarah has been identified as someone who
19. 0:44is planning a trip to Europe this
20. 0:46summer. Based on that signal, L'Oreal's
21. 0:49system has automatically generated and
22. 0:51sent her a personalized video tailored
23. 0:54to her profile and interests. What
24. 0:56you'll see now is the video she received
25. 0:59on WhatsApp.
26. 1:03>> Hey Sarah, let's glam up your summer. We
27. 1:05saw your interest in that glowing summer
28. 1:07look with an intense matte lip. Smart
29. 1:09move. What you really want is bold color
30. 1:11that stays comfy in the heat. Try
31. 1:14L'Oreal Paris Color Riche Intense Volume
32. 1:16Matte Lipstick. It is soft, buildable,
33. 1:19and feels lightweight. Explore the
34. 1:21shades or pick one up this week. For any
35. 1:23more info, give a call on the number
36. 1:25given here. Cheers.
37. 1:29>> This is the campaign John set up, one
38. 1:32that has reached Sarah directly through
39. 1:33a personalized experience. After
40. 1:36watching the video, Sarah wants to learn
41. 1:38more. So, she decides to contact
42. 1:40L'Oreal.
43. 1:41What you'll see next is her conversation
44. 1:43with L'Oreal's AI advisor, conducted
45. 1:46seamlessly in both English and French.
46. 1:51>> Hello. How are you? I'm Lumi, your
47. 1:54L'Oreal beauty advisor. How can I help
48. 1:57you today?
49. 1:57>> Hey Lumi,
50. 1:58>> actually traveling to Italy for my
51. 1:59summer vacation and I need help choosing
52. 2:02the right shampoo. Can you help me with
53. 2:03that?
54. 2:04>> I'd love to help. What's your hair type
55. 2:07like? Is it fine, thick, curly, or
56. 2:10straight?
57. 2:11And are you looking for something
58. 2:13specific like volume, moisture, or color
59. 2:15protection for your Italy trip?
60. 2:18>> Uh so my hair tends to get dry and
61. 2:20frizzy, especially in warm weather.
62. 2:22>> That makes sense.
63. 2:24Warm weather can really bring out
64. 2:27is your hair fine or more on the thicker
65. 2:29side?
66. 2:29>> fine.
67. 2:31>> For fine hair that's dry and frizzy in
68. 2:33warm weather, I'd recommend our EverPure
69. 2:35sulfate-free moisturizing shampoo.
70. 2:38It's gentle but really hydrating without
71. 2:41weighing your hair down.
72. 2:42The formula has rosemary and mint to
73. 2:45keep your scalp fresh in the Italian
74. 2:47heat.
75. 2:48Would you like me to send the details to
76. 2:49WhatsApp?
77. 2:50>> Yeah, sure. That'd be great.
78. 2:52And also my friend will be joining me
79. 2:54from France.
80. 2:56Uh can you help help him with some
81. 2:58queries as well?
82. 2:59>> Of course. I'm happy to help your
83. 3:01friend, too.
84. 3:02What kind of beauty questions does he
85. 3:04have? Is it skin care, hair care,
86. 3:08>> So he's on the call with me, you can
87. 3:09talk to him directly.
88. 3:11>> Hello, it's great to meet you, too. What
89. 3:14can I help you with today? Are you
90. 3:16looking for skin care, hair care, or
91. 3:18something specific for your trip to
92. 3:20Italy?
93. 3:21>> Salut Lumi, je recommande
94. 3:23>> Bonjour, je vous recommande notre
95. 3:25L'Oreal after-sun hydrating cream.
96. 3:28Elle contient de l'aloe vera et de la
97. 3:29vitamine E pour apaiser et hydrater la
98. 3:32peau après l'exposition au soleil. C'est
99. 3:34parfait pour votre voyage en Italie.
100. 3:36Souhaitez-vous que je vous envoie les
101. 3:37détails sur WhatsApp?
102. 3:39>> Je veux bien. Est-ce que ce produit est
103. 3:41adapté à ma peau grasse?
104. 3:42>> L'excellent hydrating cream est formulé
105. 3:44pour être douce et apaisante. Mais pour
106. 3:46les peaux grasses, je vous
107. 3:48recommanderais plutôt notre after-sun
108. 3:49gel légère.
109. 3:51Elle est non grasse, s'absorbe
110. 3:52rapidement et hydrate sans laisser de
111. 4:16>> What you just experienced was the
112. 4:18journey from Sarah's perspective. How
113. 4:21L'Oreal can engage customers like her
114. 4:23entirely through AI-powered experiences.
115. 4:27Now, let's switch to the operational
116. 4:29side and see what L'Oreal's team
117. 4:31experiences behind the scenes.
118. 4:33What you'll see next is the analysis of
119. 4:36the call that took place along with how
120. 4:38quality assurance can be automated using
121. 4:40AI. Unweave is more than just
122. 4:43conversational AI. It's an execution
123. 4:46layer that not only handles
124. 4:47conversations, but also completes tasks
125. 4:50and automates workflows. On top of that,
126. 4:52it provides analytics, call
127. 4:54intelligence, and AI-powered QA
128. 4:57automation, creating a continuous
129. 4:59feedback loop that helps improve future
130. 5:01customer interactions and business
131. 5:02outcomes.
132. 5:07The call has ended and the system has
133. 5:09already processed it.
134. 5:11The operations team can view a detailed
135. 5:14breakdown of the interaction.
136. 5:16Each conversation is logged and
137. 5:17searchable.
138. 5:19They can see the customer's number and
139. 5:21the time they called.
140. 5:23Search by duration, intense, outcome,
141. 5:26completion rate, sentiment, and call
142. 5:28status.
143. 5:30Instantly accessible details help the
144. 5:32team find information immediately, not
145. 5:35later.
146. 5:36Double-click any interaction for details
147. 5:38like call duration,
148. 5:40the number of turns taken by the voice
149. 5:42AI, and completion rate.
150. 5:45Replay the conversation. Each
151. 5:47interaction is logged with available
152. 5:48transcripts and intents, allowing you to
153. 5:51replay the conversation.
154. 5:53Zoom out to view the holistic dashboard.
155. 5:56This shows all channel interactions,
156. 5:58overall outcomes, average handle times,
157. 6:01and more.
158. 6:02>> So, everything you just saw, the
159. 6:03campaign, the conversations, all of it,
160. 6:05that was AI making real decisions on
161. 6:07behalf of L'Oreal's business in real
162. 6:08time at scale or hospital to the channel
163. 6:10final opinion of Lee. And that's where
164. 6:11it get interesting for a leadership
165. 6:13team. Because the moment the AI start
166. 6:14making real decisions, you need to
167. 6:16answer some very basic questions. Is it
168. 6:18doing what we told it to do? Is it
169. 6:19performing well? What is it actually
170. 6:21costing us? And if something goes well,
171. 6:23how do we find out? And how do we
172. 6:24explain it? Right now, most companies
173. 6:26cannot answer those questions. Their AI
174. 6:28is running across different systems,
175. 6:29different teams, different tools, and
176. 6:31nobody have a single view at any of it.
177. 6:33They get insights from analyst reports
178. 6:34that come in weeks later on stale data.
179. 6:38What you're looking at is the answer to
180. 6:40that problem.
181. 6:41Every AI agent L'Oreal have deployed
182. 6:43across every department, regardless of
183. 6:45which system it runs on or which team
184. 6:47built it, visible here with the same
185. 6:49level of accountability applied to every
186. 6:51single one of them.
187. 6:52One control tower.
188. 6:54Let me show you what that means in
189. 6:55practice. Let us go into the consumer
190. 6:57experience department, where we have
191. 6:59Lumi, who had our post-purchase
192. 7:01conversation today.
193. 7:02The campaign went live this morning, and
194. 7:04we leave volume doubled almost
195. 7:06immediately. Then what you're seeing
196. 7:08over here is exactly how the platform
197. 7:10responded. Ike detected, surge mode
198. 7:12activated, guardrail tightened, op fleet
199. 7:15notified.
200. 7:17All of it automatic. All of it before
201. 7:19anyone on the team had to make a single
202. 7:20call. And every one of both moments
203. 7:22logged, timestamped exactly as it
204. 7:24happened, not reconstructed after the
205. 7:26fact, not apologied.
206. 7:28Exactly as it happened.
207. 7:30And if you want a deep dive into a
208. 7:31specific interaction, like the one Lumi
209. 7:33had with Sa, you can go all the way in.
210. 7:36Every data point the AI used, every rule
211. 7:38it checked, every step it took to reach
212. 7:40the outcome.
213. 7:42No human in the loop. If a revenue
214. 7:44waiter walks in tomorrow and asks how
215. 7:45that recommendation was made, this is
216. 7:47the answer in one click.
217. 7:49Now, the question I always get at this
218. 7:51point is, "Okay, but how good is the AI
219. 7:54actually? Not just is it running, but is
220. 7:56it performing?"
221. 7:57And this is what you get the honest
222. 7:58answer. Benchmarked against industry
223. 8:00peers on Morial's own data. Not our
224. 8:03claim, a platform's number. This is
225. 8:05something that becomes really important
226. 8:07as the AI landscape keeps developing.
227. 8:09New models come out constantly, and the
228. 8:11question is always,
229. 8:13"Are we on the right one for our
230. 8:14business?"
231. 8:15This gives Morial the ability to compare
232. 8:17models against their own workload, their
233. 8:19own data, their own use cases, and make
234. 8:22that call themselves based on evidence
235. 8:24and not on functions. And this, this is
236. 8:27the one that tends to get people's
237. 8:28attention.
238. 8:29Every single day the platform calculates
239. 8:31what the AI costs versus what a human
240. 8:33team would have cost to for the exact
241. 8:35same volume.
242. 8:37Not a projection, not a slide someone
243. 8:39put together.
244. 8:40The real number built from every
245. 8:42interaction that ran, updated
246. 8:43automatically.
247. 8:45When the CFO asks what the business case
248. 8:47is, all they hear
249. 8:49is the campaign tool built the campaign.
250. 8:52The customer experience agent ran the
251. 8:53experience. And this platform gives the
252. 8:55business complete visibility over every
253. 8:57decision made today. Traceable,
254. 8:59benchmarked, with a cost attached.
255. 9:02There's a big difference between running
256. 9:04AI and being in control of it. This is
257. 9:06what being in control looks like.