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- 1. David Wright Innovation Specialist David.Wright@kantar.com IOT AND THE CUSTOMER OF ONE
- 2. “Does your home have any of these connected home technologies(generally they will allow control via a mobile app)?” Is gaming/entertainment the way into the connected home?
- 3. Fitbit Which wearable device do you use on a regular basis? The Rest The way the device behaves doesn't change as I change my behaviour. I become healthier or bored, either way the notifications don't change.
- 4. Highly Personalized Service The data of one! Generic Service Sweet Spot AmountDataShared
- 5. A deeper and more personal view Innovative Methods for Data Gathering May, 2015 Survey DataSocial media and lifestyle data Sensor Data Qual & Quant Datasets
- 6. Health Research – now and future Innovative Methods for Data Gathering May, 2015
- 7. People care about their data! – a caregiver perspective John Costik. Diabetes Dad to Evan Enamored with accuracy of Evan’s Dexcom data and wanted unlimited access despite no FDA solution. Innovative Methods for Data Gathering May, 2015
- 8. “The Feed” Innovative Methods for Data Gathering May, 2015 Epic EHR – 15 million patient records
- 9. Proximity Beacons – Use Case China 312 BEACONS
- 10. Beacon Hotspots – China SE Asia WeChat “Shake Nearby” WeChat’s Wallet
- 11. Combining proximity with biometric Contactless reader not working
- 12. How ONZO helped Kantar ONZO used analytics to detect when appliances were being used within the home from the overall energy use without the need for individual appliances to be chipped. Detection of when appliances were used was 13% more accurate than diaries. Detection of appliance use was 80% more accurate than survey data. Kantar compared the accuracy of ONZO’s automatic detection of appliance use, to that from diaries and surveys.
- 13. The Utility Industry - Future Time of Washing Machine use in a single household (24 hour clock) ONZO analytics can detect the time and patterns of use for how homes use appliances. When combined with e-commerce platforms, campaigns and products can be targeted based on the lifestyle’s of the homes. Spot the days when homes’ cook Know how many times a washing machine has been run
- 14. Is Artificial Intelligence going to sort this data out for us? Usage of SIRI on our US Panel is low 2% use it in a given month*
- 15. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1/1/2015 2/1/2015 3/1/2015 4/1/2015 5/1/2015 6/1/2015 7/1/2015 8/1/2015 9/1/2015 Embedded Intelligence Product Pages Views from Recommendation Engine Product Pages Views from Search
- 16. AI: Recommendations versus Decisions No you can’t open the fridge!
- 17. 55% of online shoppers use the same shopping list from one purchase to the next Removing Friction – the “no click” future
- 19. Trust! Highly Personalized ServiceGeneric Service AmountDataShared
Notas do Editor
- However, now the ability to gather data from wearable sensors, devices and apps as well as mobile-enabled market research PLUS data on patient social media activity, which can be a great indicator of lifestyle, can enable us to get a deeper view of patients than was ever possible before.
- However, now the ability to gather data from wearable sensors, devices and apps as well as mobile-enabled market research PLUS data on patient social media activity, which can be a great indicator of lifestyle, can enable us to get a deeper view of patients than was ever possible before.
- Meet John Costik, self-proclaimed diabetes Dad to Evan. Obviously, once Evan was diagnosed with T1 diabetes John’s life priorities changed and he, like any diabetes dad, wanted to be sure he could monitor his son’s blood glucose any time day or night wherever he might be. He loved the accuracy of Evan’s DEXOM Continuous Glucose Monitor and wanted to be able to access it remotely from his smartphone. But there was no FDA-approved device that did that
- IOT can help to differentiate between consumer vs shopper. Think about Echo(natural language voice recognition) – it can differentiate between the parents vs the children, boys vs girls – both could be a huge impact on the recommendations provided by the CRM. This is the realm of the Digital Agent - running slick AI software, making predictions and recommendations that makes your life better and more efficient. A brilliant example of digital agent is X.AI – which manages your calendar appointments. So send the invite – cc AMY – and AMY manages all the back and forward required to lock in the meeting. Similar digital agents might be used to manage the shopping list. For instance – most more than 50% e-commerce shopping lists are set to repeat (double check with Kantar World Panel e-commerce study “Our data shows that 55% of online shoppers use the same shopping list from one purchase to the next, giving first movers a big advantage.”) – a digital agent might be aware that you are holding a dinner party and make appropriate suggestions to add X Y Z to the list. HOWEVER THIS IS EMERGING NOW AND WE ARE TALKING ABOUT THE FUTURE Phase 2, to us, could feel weird. This is when AI moves from Recommending to Making Decisions. For instance - your TELSA drives itself off for a service at 1 AM. All of a sudden your juicy thick steaks are replaced in your shopping delivery- with watercress – because you withings scales told on you. Perhaps brands in future – are going to have to associate products with multiple occasions – if they want to be recommended by list AI! – i.e. Master Data.. look at Spotify for examples of this! [Creative] Creative around the futurescape – the idea of the AI shopping list. Idea that brands in future might need to focus on context and associate with different occasions. Like how Spotify – has “life style” themed music packs.... at the Party, Workout, Pop, Mood, Focus, Dinner Chill
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