Research\/Full Copy<\/b><\/h2>\n\n- 5:30am: The internet-connected thermostat automatically adjusts the temperature of the house to ensure the most comfortable temperature for the Consumer when they wake up.\n
\n- It compensates for the humidity and cloud cover outside to run more efficiently.<\/li>\n<\/ul>\n<\/li>\n
- 6:13am: The Consumer\u2019s smart alarm clock wakes them up at just the right time for their sleep cycle.\n
\n- They selected a time range of when they wanted to wake up (6:00-6:20am).<\/li>\n
- The device recorded the Consumer\u2019s movements and sounds to track their sleep cycle.<\/li>\n
- The alarm wakes the Consumer up during their lightest sleep phase in the range they selected.<\/li>\n<\/ul>\n<\/li>\n
- 6:25am: The Consumer calls out to their AI assistant to ask about the weather forecast.<\/li>\n
- 6:45am: As the Consumer eats breakfast, they check the price of a new TV on a major retailer\u2019s website from their phone.<\/li>\n
- 6:50am: They send a link through Facebook Messenger to a friend to get their opinion on one TV set.<\/li>\n
- 8:00am: Once they arrive at work, the Consumer uses their car\u2019s built-in parking assistance to help them parallel park.<\/li>\n
- 10:00am: During a work break, the Consumer checks Facebook and sees an ad for the TV they were looking at.\n
\n- The ad features a coupon for 15% off if the Consumer buys from the retailer they were checking before.<\/li>\n
- The retailer used Facebook Pixel to reach back out to the Consumer.<\/li>\n<\/ul>\n<\/li>\n
- 11:43am: The Consumer gets a text message from their bank asking about a potentially fraudulent charge to their debit card.\n
\n- When the bank\u2019s AI-enabled management system caught a charge that didn\u2019t fit the Consumer\u2019s pattern of behaviour, it immediately declined the charge and texted the Consumer.<\/li>\n<\/ul>\n<\/li>\n
- 12:15pm: Over their lunch break, the Consumer listens to music from a playlist generated by AI.\n
\n- It\u2019s based on their personal playlists, what they\u2019ve listened to recently, and playlists created by similar users.<\/li>\n<\/ul>\n<\/li>\n
- 12:22pm: Curious about the deal on the TV set they saw on Facebook earlier, the Consumer checks the retailer\u2019s website again from their laptop.\n
\n- They use the chat bot that pops up on the TV\u2019s product page to ask about other deals.<\/li>\n
- After a few basic questions about the Consumer\u2019s lifestyle, the chat bot recommends a different TV.<\/li>\n
- Instead of taking notes, the Consumer enters their email address and has the chat log sent to their inbox.<\/li>\n<\/ul>\n<\/li>\n
- 12:45pm: The Consumer checks their email from their phone and finds a new coupon from the retailer for the TV the chat bot recommended.<\/li>\n
- 12:46pm: Clicking the phone number in the email, the Consumer calls the retailer to learn more about the TV.\n
\n- The phone number is for the store closest to the Consumer\u2019s current location.<\/li>\n
- After talking to the Salesperson, the Consumer decides to complete the purchase online and pick the TV up after work.<\/li>\n<\/ul>\n<\/li>\n
- 12:55pm: The Consumer goes back to the emailed coupon and clicks on it to go to the retailer\u2019s mobile site.\n
\n- The landing page is for the TV set the Consumer wants, and the discount is automatically applied when they add it to their online cart.<\/li>\n<\/ul>\n<\/li>\n
- 1:00pm: Excited about their new TV, the Consumer checks Google Maps to find out how long it will take to drive to the store.\n
\n- They decide to go at 5:30pm, which is listed as a less busy time for the store by Google\u2019s AI.Then, to find out what time they need to leave the office, the Consumer uses the map feature that predicts drive time. It says to leave at 5:05pm to account for rush-hour traffic.<\/li>\n<\/ul>\n<\/li>\n
- 4:55pm: The Consumer\u2019s phone buzzes with a notification that their route to the store will take longer because of construction on the highway. The AI-powered app has already calculated a faster route, but still recommends leaving in 5 minutes in order to arrive at 5:30pm.<\/li>\n
- 5:30pm: When the Consumer walks into the store, they ask to see the Salesperson who helped them earlier.\n
\n- The Salesperson greets the Consumer at the entrance and has the TV for the Consumer.<\/li>\n
- Because the retailer\u2019s AI-enabled CRM found a pattern among TV purchases, the Salesperson also hands the Consumer a package of new batteries for the remote, free of charge.<\/li>\n
- Then the Salesperson gives the Consumer a set-up guide, created in-store, as multiple customer reviews on the website mention that the manufacturer\u2019s instructions are difficult to follow.<\/li>\n<\/ul>\n<\/li>\n
- 7:00pm: The Consumer is home, watching their favorite show on their new TV.\n
\n- Their phone buzzes with a text from the retailer asking the Consumer to score their shopping experience.<\/li>\n
- After the Consumer responds, the reply from the retailer asks them to save their customer service phone number in case they have any questions or concerns in the future.<\/li>\n<\/ul>\n<\/li>\n
- 7:40pm: An email from the retailer lands in the Consumer\u2019s inbox.\n
\n- It thanks them for their purchase.<\/li>\n
- It presents a coupon for a complementary product.<\/li>\n
- And it has the manufacturer\u2019s warranty and instructions attached in case the Consumer misplaces the paper copies that came in the box.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
Conclusion<\/b><\/h2>\n
Artificial intelligence has become a part of our daily lives. In order to keep up with connected, informed, and demanding customers, companies have to use powerful technology the right way to anticipate, assist, and attract them.<\/p>\n
![](\"https:\/\/www.salesforce.com\/ca\/blog\/wp-content\/uploads\/sites\/12\/2023\/10\/how-companies-use-ai-to-improve-consumers-lives.png?strip=all&quality=95\")
<\/img><\/p>\n<\/p>\n
Share “Sunup to Sundown, How Companies Use AI to Improve Consumers\u2019 Lives” On Your Site<\/h3>\n
- \n
- It compensates for the humidity and cloud cover outside to run more efficiently.<\/li>\n<\/ul>\n<\/li>\n
- 6:13am: The Consumer\u2019s smart alarm clock wakes them up at just the right time for their sleep cycle.\n
- \n
- They selected a time range of when they wanted to wake up (6:00-6:20am).<\/li>\n
- The device recorded the Consumer\u2019s movements and sounds to track their sleep cycle.<\/li>\n
- The alarm wakes the Consumer up during their lightest sleep phase in the range they selected.<\/li>\n<\/ul>\n<\/li>\n
- 6:25am: The Consumer calls out to their AI assistant to ask about the weather forecast.<\/li>\n
- 6:45am: As the Consumer eats breakfast, they check the price of a new TV on a major retailer\u2019s website from their phone.<\/li>\n
- 6:50am: They send a link through Facebook Messenger to a friend to get their opinion on one TV set.<\/li>\n
- 8:00am: Once they arrive at work, the Consumer uses their car\u2019s built-in parking assistance to help them parallel park.<\/li>\n
- 10:00am: During a work break, the Consumer checks Facebook and sees an ad for the TV they were looking at.\n
- \n
- The ad features a coupon for 15% off if the Consumer buys from the retailer they were checking before.<\/li>\n
- The retailer used Facebook Pixel to reach back out to the Consumer.<\/li>\n<\/ul>\n<\/li>\n
- 11:43am: The Consumer gets a text message from their bank asking about a potentially fraudulent charge to their debit card.\n
- \n
- When the bank\u2019s AI-enabled management system caught a charge that didn\u2019t fit the Consumer\u2019s pattern of behaviour, it immediately declined the charge and texted the Consumer.<\/li>\n<\/ul>\n<\/li>\n
- 12:15pm: Over their lunch break, the Consumer listens to music from a playlist generated by AI.\n
- \n
- It\u2019s based on their personal playlists, what they\u2019ve listened to recently, and playlists created by similar users.<\/li>\n<\/ul>\n<\/li>\n
- 12:22pm: Curious about the deal on the TV set they saw on Facebook earlier, the Consumer checks the retailer\u2019s website again from their laptop.\n
- \n
- They use the chat bot that pops up on the TV\u2019s product page to ask about other deals.<\/li>\n
- After a few basic questions about the Consumer\u2019s lifestyle, the chat bot recommends a different TV.<\/li>\n
- Instead of taking notes, the Consumer enters their email address and has the chat log sent to their inbox.<\/li>\n<\/ul>\n<\/li>\n
- 12:45pm: The Consumer checks their email from their phone and finds a new coupon from the retailer for the TV the chat bot recommended.<\/li>\n
- 12:46pm: Clicking the phone number in the email, the Consumer calls the retailer to learn more about the TV.\n
- \n
- The phone number is for the store closest to the Consumer\u2019s current location.<\/li>\n
- After talking to the Salesperson, the Consumer decides to complete the purchase online and pick the TV up after work.<\/li>\n<\/ul>\n<\/li>\n
- 12:55pm: The Consumer goes back to the emailed coupon and clicks on it to go to the retailer\u2019s mobile site.\n
- \n
- The landing page is for the TV set the Consumer wants, and the discount is automatically applied when they add it to their online cart.<\/li>\n<\/ul>\n<\/li>\n
- 1:00pm: Excited about their new TV, the Consumer checks Google Maps to find out how long it will take to drive to the store.\n
- \n
- They decide to go at 5:30pm, which is listed as a less busy time for the store by Google\u2019s AI.Then, to find out what time they need to leave the office, the Consumer uses the map feature that predicts drive time. It says to leave at 5:05pm to account for rush-hour traffic.<\/li>\n<\/ul>\n<\/li>\n
- 4:55pm: The Consumer\u2019s phone buzzes with a notification that their route to the store will take longer because of construction on the highway. The AI-powered app has already calculated a faster route, but still recommends leaving in 5 minutes in order to arrive at 5:30pm.<\/li>\n
- 5:30pm: When the Consumer walks into the store, they ask to see the Salesperson who helped them earlier.\n
- \n
- The Salesperson greets the Consumer at the entrance and has the TV for the Consumer.<\/li>\n
- Because the retailer\u2019s AI-enabled CRM found a pattern among TV purchases, the Salesperson also hands the Consumer a package of new batteries for the remote, free of charge.<\/li>\n
- Then the Salesperson gives the Consumer a set-up guide, created in-store, as multiple customer reviews on the website mention that the manufacturer\u2019s instructions are difficult to follow.<\/li>\n<\/ul>\n<\/li>\n
- 7:00pm: The Consumer is home, watching their favorite show on their new TV.\n
- \n
- Their phone buzzes with a text from the retailer asking the Consumer to score their shopping experience.<\/li>\n
- After the Consumer responds, the reply from the retailer asks them to save their customer service phone number in case they have any questions or concerns in the future.<\/li>\n<\/ul>\n<\/li>\n
- 7:40pm: An email from the retailer lands in the Consumer\u2019s inbox.\n
- \n
- It thanks them for their purchase.<\/li>\n
- It presents a coupon for a complementary product.<\/li>\n
- And it has the manufacturer\u2019s warranty and instructions attached in case the Consumer misplaces the paper copies that came in the box.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
Conclusion<\/b><\/h2>\n
Artificial intelligence has become a part of our daily lives. In order to keep up with connected, informed, and demanding customers, companies have to use powerful technology the right way to anticipate, assist, and attract them.<\/p>\n
<\/img><\/p>\n<\/p>\nShare “Sunup to Sundown, How Companies Use AI to Improve Consumers\u2019 Lives” On Your Site<\/h3>\n