Clever Cars

clever cars 2

What can your driving habits tell us? A lot is the answer. In fact, where people drive can reveal a lot more than Google searches and this is what advertisers, startups, and car-makers are quickly realising.

For years car companies have been installing software and sensors that collect driving behaviour and location data from our cars. This is invaluable to advertisers & car companies alike.

 

Car companies argue this data will enhance the driving experience CX.  It could help to predict flat tires, find parking spaces or charging spots, alert authorities to dangerous crossings & even track criminals fleeing from crime-scenes.

Advertisers are even more excited. Israeli startup, Otonomo, cleans up and organises data for carmakers. They let drivers select the information they’re willing to share with companies in exchange for rewards & discounts – imagine leaving work late and a £5 Dominos discount coming up on your display 🍕

This is only the start. Ford estimates that by 2020 their vehicles will have 100m lines of code and Gartner estimates 98% of new cars in the US & Europe will have an embedded cyber connection.

clever cars

What about BIG data?

The real interesting part is when all this data is aggregated. With all this data, companies can see trends that are linked to other events. For instance:

  1. Hedge funds could use boot sensor data to see how much people bought when they went shopping which would show consumer spending
  2. Banks could see how many people had stopped driving to work, thus suggesting they’ve lost their jobs, and if this number began to rise they could anticipate an economic downturn
  3. 3rd parties could track trips to the police station, domestic violence shelters, STI/HIV testing centres and infer sensitive information about drivers’ health and relationships.

Autonomous cars won’t stop us… 

One of the most important big-picture outcomes here is that car manufacturers are not only hardware companies now, they’re also software companies. It’s often been suggested that traditional companies will die off with the coming of autonomous cars, but this shows they’re using tech themselves to find new sources of revenue.

People need to be aware of the level of privacy they’ll be giving away. Soon your car could know more about you than your family…

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Loose Lips cost Lives

strava military

I use Strava to map my runs & cycle rides but a recent article caught my attention on the importance of keeping your data private vs public.

Last November, Strava released a global user-activity heat map showing the running and cycling routes of people wearing fitness trackers. Some of those people work for the military & intelligence agencies.

Their data, which they neglected to opt out of sharing, reveals their daily routines and the contours of previously secret bases for anyone with a Strava account who might be looking. “A modern equivalent of the World War II-era warning that ‘loose lips sink ships,’ writes Jeremy Hsu, “May be ‘FFS don’t share your Fitbit data on duty.’”

So far, the breach hasn’t hurt anyone, and militaries and intelligence services will update their facilities (and personnel training policies) to render this particular vulnerability moot. But the unexpected risks of modern geolocation technology remain. “These digital footprints that echo the real-life steps underscore a greater challenge to governments and ordinary citizens alike,” Hsu writes. “Each person’s connection to online services and personal devices makes it increasingly difficult to keep secrets.”

Read the full article here

https://www.wired.com/story/strava-heat-map-military-bases-fitness-trackers-privacy/

7-11 crawl walk run

7-11 digital transformation using agile crawl- walk-run methodology to develop relevant data driven CX

Data Pulse #711

7-11 seized an opportunity to use the existing technology that most of its shoppers already had in their hands as they entered the store, and it did it from a standing start using AGILE methodology like a baby learning to CRAWL, WALK, RUN

 7-11 can now push real-time, rules-driven offers to customers through the 7-11 app.

The decision was made to launch a mobile app in efforts to deliver what the customer wants, when they want it, where they want it. Offers take account of rich data about the customer, both live and historic:

Real-time transactional: current basket, comms received, channel, geofencing

Real-time contextual: location, location temperature, time of day.

Historic modelling: transaction data, profile data, modelling scores.

Insights gained from feedback to offers over time is incorporated into business rules in a process of continuous refinement.

So, for example, on a cold morning, 7-Eleven might push hot drinks offers. At midday, some customers might receive offers for packaged lunches while others receive promotions on fresh foods. In the evening, lifestyle insights might be used to determine that some customers might be tempted by pizza and a DVD rental.

7-11 2

Dunkin Donuts Data Perks

dunkin donuts coffee and donut

Dunkin Donuts are just beginning to establish themselves in UK but in USA are the largest coffee retailer, and have applied data driven analytics and technology effectively to improve the customer journey.

A coffee and a Donut is one of the most popular calls, and is the mainstay of this convenience foodservice retailer.

Dunkin Donuts recognised the key to convenience retailing lay in the palm of their customers hands and build a customer journey revolving around the smart phone. They created an app based journey where customers could pre-order, collect and pay for their Dunkin Donut. It started with a minimum credible product, simple sign-up and sign-in and has developed into one of the most recognised programmes in USA.

. They understood the customer journey not in part but fully and recognised they were a convenience foodservice retailer and making a coffee and a donut easy for customers would drive more customers to make more visits.

Dunkin Donuts wanted to reward loyal guests in a fast and convenient manner, and provide an overall superior customer experience. Very similar to the goals that Whole Foods had in mind when launching its own loyalty program.

Understanding the Commercial Goals: Dunkin Donuts used advanced analytics to understand the commercial imperatives, and what would best drive them. They recognised that there was a bigger upside from increasing visits and number of visits that slightly increasing the average basket. ( There are only so many coffees and donuts you can eat in one sitting , but it’s important to be the coffee house of choice when there is a choice of 2-3 on the street.

Design a Customer experience that delivers the commercial imperative: They were clearly focusing on driving additional visits from additional customers because they designed a DD Perks programme that rewarded frequency vs average basket.

The Points based reward Rewarded Frequency: Assuming people ordered a coffee and a donut they earned points which became a free coffee every 10-20 visits.  High value to the consumer and relatively low cost to Dunkin Donut.

They also made it easy and intuitive to sign up, and in addition to the basic points structure, Dunkin’ also included features to drive more sign-ups. Sign up on an app downloaded onto their phone,

Make it easy to get to the first reward Customers get a free reward when they join and on their birthday,. That emotional feeling of drinking a free coffee prompts more usage of Dunkin Donut

Make it more rewarding: once the first reward has been claimed targeted offers for incentives and bonus points based on consumer behaviour enable fast rewards accumulation

Make it Easy to Use / Pay Customers must pay with a registered DD payment card at participating locations, or more importantly customers can connect their DD cards to their phone, which enables mobile payments and gets more customers (hopefully) to download the Dunkin’ mobile app.

One last benefit of the program is that customers can share rewards with friends, which is high on many customers’ lists as a desirable loyalty program feature.

Technology developments to make it Easier :  with the onset of Apple Pay, Dunkin Donuts enable mobile ordering through its app. Customers on their way to Dunkin’ Donuts can get their order in quicker, and Dunkin’ can speed up its line. In addition, Dunkin’ also announced interest in Apple Pay as a way to make payments easier for consumers

 

Three key outtakes for success:

  1. Be Clear on the commercial imperative: frequency or average spend
  2. Make it simple, rewarding to use
  3. Integrate across the whole customer experience to make it easy for the customer

Dunkin-Donuts shop

Tech City Coffee

starbucks shop

Understanding customers better has always been critical. Identifying the heart of the commercial challenge and developing customer led solutions to solve them is critical.

Meeting customers needs and simplifying the customer experience using data and digital is a key skill of the new Chief Marketing Officer and delivering the most relevant, inspirational messaging and experiences through advanced segmentation and targeting is a skill every CMO must ensure is delivered.

Starbucks do that

Starbucks carries only 200SKUs but has managed to meet the needs of customers with relevant offers and communications whoever or wherever you are. 

How?

Starbucks Influencing Wheel

Starbucks created a segmentation for customers by day of week, time of day and purchasing details, creating the Starbuck’s Influencing Wheel: which helps frame the problem in terms of what they know about a customer.  Transaction data allows Starbucks to know what behaviours can be observed at purchase time. External f

  1. ENTERPRISE Influences / Transaction data allow Starbucks to know what behaviours can be observed at purchase time ( Food, Beverage, in-store experience etc.)
  2. EXTERNAL Influences ( Weather, Competitors, Events, Community) may impact the way customers behave so Starbucks collected data to simulate local conditions that may affect purchase behaviour.
  3. CUSTOMER Characteristics ( occupation, demographic, need state, day part, media channel preferences etc.)  Not all behaviours can be observed in a transaction so Starbucks deploy .a social listening strategy in order to capture some aspects of a customers lifestyle and how products& services may fit into that lifestyle

starbucks influencing wheel

Customer needs for coffee on way into work, is different to lunchtime or afternoon during the week, and again different to weekend morning coffee. This data is combined with open data to give highly tailored and timely communications with live triggers- offers in the right place at the right time. Arriving at Manchester Piccadilly rail station for early (5-55am)  train to London I get an alert on my phone to pick up a Starbucks coffee for the train. and it really does taste sweet that early in the morning…..

Starbucks also improved the customer experience by being one of the first retailers using a digital app that allows payment through Apple pay or creating a Starbucks wallet that is automatically topped up.

Starbucks are leading the way in delivering the power of value based customer delivery, leveraging data driven analytics and digital technology to drive L4L growth.

Uber focused on data

uber

Uber is a people logistics service that uses a matchmaking model to connect customers directly with drivers to reduce prices for customers by optimising load capacity for drivers. It is now available in 53 countries and more than 200 cities and is revolutionising logistics and service using data. .

The app automatically detects the user’s position using GPS – so ‘riders’ can book a taxi with a single press of a button. Users can get an estimate of their fare by entering their destination. This is calculated by algorithms which consider the distance, prices of similar journeys, and the current Uber price rate.

uber app

Uber uses an algorithmic approach to account for differences in supply and demand in different areas. when supply out-strips demand prices are low, when demand increases the algorithm drives up pricing to encourage more drivers out and optimise revenue. This is called ‘surge pricing’. When demand outstrips supply in a certain area, surge pricing is applied and the usual fare rate will be multiplied appropriately. Users will be notified of surge pricing on booking, and can cancel the trip if they do not want to pay the increased fare.

When a the taxi is booked, a temporary bridge is created between customer and driver data allowing them to make contact and see each other’s location. Once the journey is over and the transaction complete, the exchange of data ends.

Uber scaled rapidly through partnership, using the best experts in any one area ( eg Google Maps, or best checkout system, or best driver id check ) and focused their development on the unique pricing model that optimises pricing to reduce prices for customers, increase occupancy rate for drivers, and drive customer growth and frequency for UBER.

UBER is changing the model for transport in cities around the world, with loyal customers, drivers clamouring to become an UBER driver, and a system determined to continually drive down pricing and increase service levels.

UBER has already changed the way transport works in London, picking up an UBER for shorter and well as longer journeys. replacing the need for a car at all. The future looks good.

 

Blow Up Bedrooms….

lifestyleairbnb

Data Pulse #23

When a few programmers and bloggers bought some air-beds , built a website and offered an air-bed with a coffee on their floor during a particularly busy conference season in San Francisco, they didn’t think they’d be creating a dis intermediation business to rival Marriott or Intercontinental Hotels.

Airbnb is a lodging rental platform with headquarters in San Francisco, California.

airbnb has grown staggeringly quickly over the past half-dozen years. The mind-boggling numbers show its incredible popularity; 1.5million listings in 33,000 cities in 191 countries around the world have attracted 65million guests – and counting.

 

Last June the company was priced at $25.5billion (above hotel giant Marriott’s $20.90bn), and ranked the third most valuable start-up business in the world, behind transportation network company Uber ($51billion), and Xiaomi, the world’s fourth-largest smartphone maker ($46bn).

airbnb has used data to deliver against the brand purpose, tell the brand story and build the customer experience . “Experience the world like a local” 

 

airbnb describes itself as a ‘community marketplace where guests can book spaces from hosts, connecting people who have space to spare with those who are looking for a place to stay.’ A super brand that is community led.

The hosts are business partners, and airbnb is led by what the business partners say, continually getting their opinion and gauging reaction to business challenges and opportunities. It quickly builds a sense of openness, trust and meaningful interacton to form a strong community.

Every year, some 5,000 hosts from more than 100 countries are invited to the company’s airbnb Open (the 2015 edition was held in Paris) and encouraged to talk about the nature of their work. It is a great opportunity to both connect with the hosts and understand how airbnb can help serve them better. It is also a good way to feel part of that broader global community and the local area.

airbnb ran an innovative campaign to engage not only hosts but visitors in the airbnb community. The One Less Stranger campaign – where 100,000 hosts woke up on New Year’s Day, 2015, to an email from airbnb’s founder Brian Chesky saying he had paid $10 into their bank account – was an instance when “full editorial control” was taken away from Airbnb. Brian wrote that we would like the hosts to do something to help someone else, and to meet someone new with that money, It was a $1million marketing campaign where we gave full editorial control to the hosts. Some people just pocketed the money, but the idea here is that you can allow people who are your biggest advocates to be your spokespersons, and do your marketing for you, on social media and word of mouth.

It all builds up to the goal that your brand is driven by community rather than people in a marketing department.

 ‘It’s far better to have 100 people love you than 100,000 people sort of like you.’

airbnb also use data to make a ever growing core of people love them . The platform has disrupted the traditional hotels industry by eliminating the middle man and connecting travellers directly with people who have space to offer. airbnb collects detailed data relating to how customers are using the platform and attributes much of its success to an ability to analyse and understand how to improve the service.

airbnb employs extensive A/B testing to score multiple configurations or designs of its website and apps. Different users will also be exposed to different ranking and recommendation algorithms – the variation they experience is then linked to their next actions – viewing patterns, bookings and ultimately reviews of their stay.

airbnb uses natural language processing to decipher users’ true feelings about their stay, finding this to be more accurate than simple star rankings (which, they hypothesise, are overinflated due to the personal contact between guest and host).

Must admit i was a little nervous using airbnb for the first time ,. Found a little room in deepest Shoreditch, better than the local Premier Inn and cheaper… but now i’m a convert