data driven Volvos

 volvo 3

The problem at V.W. caused by the scandal of emissions testing shows just how far car manufacturers have changed from being mechanical and electrical engineering companies to being software companies. A modern car is now a moving computer emitting data like a Boeing 747.  V.W. leadership are all great mechanical and electrical engineers but they just didn’t quite understand software and data, and hadn’t made the transition in organisational culture , systems processes. Hence the problem that crept in through the corporate governance.

Car companies will need to retell their brand stories to customers and become part of customers’ own stories.

One company that has started to tell its “brand story of safety” consistently to customers using data and technology is Volvo.

‘Volvo on Call’ allows Volvo owners to control their car through their phone. The app allows the driver to perform a range of checks and commands without having to be near the car, such as: check the cars maintenance levels, create and track a personal driving journal which can be transferred into an excel format as data, identify the car’s location, lock/unlock the car, call an operator for roadside assistance using your GPS location.

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Volvo are also using data to improve road safety for drivers, introducing a new system that warns drivers of potentially hazardous road conditions ahead. This is achieved through pulling data from wheel sensors to detect the presence of black ice. When this happens, the car transmits a GPS location to the Volvo Cloud platform, which sends the data to other vehicles nearby that are equipped with the system. These cars then see an icon on their dashboard warning them of the risk. Similarly, sensors are attached to Volvo cars’ hazard lights to detect when they are activated. At that time an alert is sent to nearby cars, warning them of a hazard ahead.

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Icy road data gathered during the pilot was shared with road authorities so they can improve road safety through gritting or public announcements. Using data and technology as an integral part of the brand story and customer journey / customer experience is a critical skill organisations will need to build. The implications for Insurance companies will be significant, as the risk factors will significantly change from who I am, where I live , and what i buy to more how and where I drive….. one to watch.

3 Single Men and a Wedding

wedpics founders

data pulse #71

First problem: They were guys. Second problem: They were all single. None of them had ever been married, and they were based in Raleigh, North Carolina, which was not a place that anyone had ever built a large consumer app company. Lastly they were entering a crowded market.

How did WedPics defy conventional wisdom?

Identify a small niche market and build a highly targeted product to fit that market’s need. After conquering that niche market, expand out to other niches until you get some real momentum.

Wedpics decided to target brides as their customer niche. Brides can’t get enough pictures and videos, not just from their wedding photographer but also from everyone else with a cell phone.

If this mantra sounds familiar, it should. Think Airbnb, Strava

When you look at WedPic’s success, there are two overriding lessons that stand out:

1.The product is simple. The UI is intuitive, and regardless of whether you are 12 or 62, if you have a phone you can snap pictures and videos and instantly share them with the rest of the wedding party. In fact, the founders claim that there are no features.

2.They understand their buyer (the bride). Out of the gates, they offered instant support regardless of the time of day. The boys each took turns on call and averaged 20 minutes to turn around any question or concern. I mean, we are talking brides here preparing for the biggest day of their life. It didn’t matter that Koren, Heymann, or Miller received calls in the middle of the night. Yes, I said calls. Not email. Not chat (though that would have been cheaper and easier). The brand said, The company is here for you; we know we only get one shot to do this right.

What I love about the success of WedPics is how Koren, Heymann, and Miller  focused on finding customers. My favourite image is that of a six-foot-four tattooed guy (Miller) standing behind the company table at a wedding conference. Today, WedPics stands at 29 people and has raised more than $7.5 million from investors across the country.

Oh, all three founders are still single

Data driven Aussies

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Players always say that when it counts the most, fans and supporters can represent the force of an extra player in the team. the “Unfair Advantage”

Competing against three other football codes in one of the most crowded sporting markets in the world, the Australian Rugby Union (ARU) has used data to harness that Unfair Advantage.

Data has become a crucial battleground at Rugby’s top level with every aspect of a match and a player’s performance analysed over and over to find that competitive edge. The Australian Rugby Union also use data to create a community at grass roots playing and grass roots supporters. They learnt from the 2012 Olympics in London and went back home and built a bottom up connected supporter community.  

As Bill Pulver, ARU CEO, states:   “The fundamentals of running a sport are pretty similar to running a business, the difference being you have this thick layer of passion over the top. “

Unlocking Fan Force with Rugby Link

Rugby Link is the platform through which the ARU engages every member of its community – “from the age of 5 right through to the age of 75”.

According to Bill, the Australian Rugby Union have a digital platform for omnichannel one-on-one communication on  that is relevant to a fan or player’s historical engagement with the game; as well as enabling a customised future with the game as well.  

A good example that Jade McAuslan, CRM Manager, describes is how the platform allows the ARU to understand when fans and players renew their seasonal membership, and as a result, time and personalise their outreach accordingly. The way that the data and metrics inform that personalised connection is critical to keeping people more engaged than with any of the other codes.

In the modern, professional era of Rugby Union, teamwork and communication are fundamental to success on the field. But also increasingly it is the cohesion and strength  of the entire organisation behind that team, all the way down to the 5 year old touch rugby player, that provides that edge to keep the national teams winning again and again. With Rugby Link,  the ARU has secured an Unfair Advantage in that international contest.

It can help them get to the final… but didn’t stop them against the mighty All Blacks

Predictive analytics running shops

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Energy usage accounts for 60% of the operational carbon costs in running shops. In with its 2020 vision for sustainability, Sainsbury’s set in motion a series of CSR strategies. A revamped refrigeration strategy prioritised carbon reductions, although not necessarily reduced costs.

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Fridges and freezers were all fitted with devices to monitor performance (primarily energy usage and temperature). This information, pushed every 15 seconds, provided an alarm strategy so that any unit that strays from its optimal temperature can be identified immediately. This systematic approach ensures that all food types are kept at the right temperature for as long as possible, so that customers always receive the freshest goods.

Sainsbury’s then transitioned from active management to predictive management. With the data being produced by refrigeration units, it was possible to identify which types of cabinet performed best, which refrigerants are most efficient, and to predict which units would need to be serviced and/or have parts replaced. In this way, Sainsbury’s could stay ahead of the curve and react before technical failures caused serious losses.

Data and digital technology is being used to deliver solutions to business problems making it Better for customers ( more environmentally friendly and always available fridge and freezers) Simpler for colleagues in store ( central predictive control means fridges are never down and have to be emptied and repaired) and Cheaper for the organisation ( less energy, better refrigeration contracts less stock wasted)

a reputation that preceeds you

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It’s 6pm, still thirty minutes to go before Bubbledogs opens its doors for dinner. The line snakes down the street and around the corner. A few people have bookings for tables of six or more, but not many, most are walk-ins who know that if you’re not dining with a bigger group and have no reservation (house rules), then you need to get there early. Bubbledogs reputation precedes it.

There is clearly no time for the management to worry about what the dozen other restaurants within walking distance are doing and no urgency to allocate resources to traditional marketing campaigns.

Like the Bubbledogs team every one of us has a choice. We can spend the majority of our time either managing our reputation or keeping pace with our competitors or we can deliberately create the reputation that precedes us.

What’s the story you want customers to tell about your brand?

[Take time to write it down].

How will you make that happen?

cutting the corners using data

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data pulse #22

UPS generates rich data through devices, vehicles, tracking materials and sensors throughout its operations. Using advanced data analytics it aims to ‘turn that complex universe of data into business intelligence’.

Route optimisation delivers immense value for UPS – a reduction of one mile per driver per day results in up to $50 million each year. Telematics sensors in UPS vehicles monitor speed, direction, braking, RPM, oil pressure, shifting, idle time, seatbelt use, and hundreds of other data points, including geographic and map data. The analytics team now runs advanced algorithms to crunch all of this information, factoring in delivery routes, customer information, business rules and employee work rules. These algorithms can determine the vehicle’s performance and condition, and can even recommend driving adjustments.

Through these analytics, UPS reduced total miles driven per year by 85 million. Idle engine time was also reduced by 10 million minutes. The information UPS receives allows fully informed decisions about vehicle replacement, and helps determine best driving practice so that drivers get the best possible training.

“We don’t look at initiatives as ‘analytics projects,’ we look at them as business projects. Our goal is to make business processes methods, procedures and analytics all one and the same.” – UPS Senior Director of Process Management.

 

how to connect customers lives?

#data pulse 17

Times have changed significantly since we built the first unified view of customers in Tesco in 2005 working with Clive Humby and the team at dunnhumby. We were cutting edge at the time and had to build all the systems and processes from scratch. Technology has improved with the likes of IBM Infosphere providing MDM systems , and new agile , start-up mentality ways of working changing delivery timetables.

Gone are the days of 12-24 month development programmes, with waterfall methodology and timescales that mean the business imperatives have moved on before they can be addressed.

Hello to technology and ways of thinking about data problems for the 21st Century where leaders can focus on the business problems and organisational process changes required to solve the problems for customers.

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The MetLife Wall is a good example in financial services of creating a unified view. It joins all linked customer information in a single place, with one screen that gives all of the information needed to serve customers quickly and effectively. The Wall provides a simple 360 view of each customer across MetLife’s businesses. The interface shows interactions across all touch points (e.g. call centre, in-person interactions with agents, claims, policy updates), connecting more than 70 legacy systems. The application allows customer service agents to reach the information they need with far fewer clicks, and makes it much easier to effectively cross-sell.

The first prototype of the system took just 2 weeks to build. The entire development process, from conception to final product, took just 3 months.

The lessons to learn from Met Life are

  1. a clear focus on what problem you want to solve with the Unified View of Customers.
  2. an agile, start-up mentality where you build minimum credible product and then continually improve.
  3. unified view of customers is a start point to solve business problems not an end point,

AddUp data in Grass roots activation

 sierra club

data pulse#21

Sierra Club is the USA’s largest grassroots environmental organisation, operating at national and chapter level, with more than 2 million members.

AddUp is Sierra Club’s digital platform, combining grassroots campaigning with the power of big data, predictive recommendations and integrated social sharing to encourage activism and demonstrate collective impact. It is a tool to move members through the defined ‘’engagement ladder’ to deliver the organisational commercial imperatives .

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The AddUp homepage shows petitions to sign, social media actions to take, events to attend and ways to recruit friends. With AddUp it is easy to see the difference that each action makes over time. Through real-time updates, campaigners can see how their involvement is driving the cause forward incrementally, and the chain reaction that follows.

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E.g. Thanks for engaging to support Dolphins in Florida. 155,000 people supported the petition (2550 in your state) and we forced the governor to change his mind about introducing a new law on fishing that would have destroyed Dolphin environment. Thank you. Would you now like to support this cause: stop introduction of pesticides that will kill Bees.

A predictive recommendation engine suggests campaigns to each user based on what is trending, location, personal interests and, most importantly, previous actions. By integrating across platforms, Sierra Club can track online and offline donations, petition signatures, membership, household groupings, account management, and participation in Sierra Club outings, pulling all of this data together to build a complete view of each member – allowing the user to see their cumulative impact, and Sierra Club to deliver more relevant, targeted comms.

 

Telling a story with data

 Telling a story is hard

Telling a story with data is easier

data pulse #19

Don’t let anyone kid you. Telling your story, or the story of your business is hard and most people struggle with it on some level

But there’s a trick to tapping into the heart of your story.

Start where the story ends.
Write down the words you want people to share about you tomorrow.

  1. What did they love about your product?
  2. What made them care about your service?
  3. How did you blow them away?
  4. What difference did you make?

And now that you’ve figured out what you want people to say, go and do all the things that will make them say it.

Here’s the clever piece

The clever piece is rather than shouting loudly to everyone think a little.

Use data to understand who would listen to your story and appreciate it more.

Use data to understand how to best get them to tell your story to all their friends.

Use data to change their behaviour and become more engaged up the engagement ladder.

Use data to get other people to sell your story

You are not the only one who is telling your story

Obama- in the subscription business

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data Pulse #27

The Obama presidential campaign 2008/2012 created a step change in how data was used in political campaigning. Obama campaign mobilised  a team of experts to give him an unfair advantage against the other candidates. It could be seen as very sophisticated but in reality they were just applying all the simple skills that data-driven Direct Marketers have been using for decades, but doing it with discipline, at scale, and speed.

Obama’s team focused on making sure that Democrats voters would come out to vote on election day, and built a machine that enabled people to be involved and donate their money, time and energy to the cause.

Obama campaign was in “the subscription business”

Obama had clear purpose, but also ran a political campaign in a professional business like manner. he had clear data-driven targets, reviewed daily. Obama built an excellent customer experience that micro-listened so they could target with precision to maximise the impact of communications. They built an engagement ladder to move through in a monitored way from aware, to supporting to donating or actively volunteering.

All messaging was A/B tested to maximise the effectiveness of targeting for different groups. They know that an email from Michelle Obama would appeal more to one group, or from a local Oklahoma name in Oklahoma would work better for a different group.

This enable mass fund raising and mass engagement of grass-roots supporters, and blew away the Republican Party candidates twice.

The rest is history…. until 2016.

will customers trust you with their data?

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data pulse #17

It’s tempting to think of customer data as the new oil.

Combined with advanced analytics, it offers the promise of marketing nirvana. By perfectly profiling an individual customer, marketing can be truly personalized, improving a customer’s experience, and eliminating waste.

But customer data isn’t a natural resource. It’s generated by people. And as our connectivity increases, so does our awareness of the data being collected and the erosion of our privacy.

With customers increasingly seeking more control over the data they share and with whom, access to customer data will become increasingly valuable, a source of competitive advantage, and a privilege to be earned. Brands will need to demonstrate to customers that they can be trusted with their data.

There are a number of practical steps that should be taken now:

  1. Make sure you are using the data you already have to improve the customer experience, so it’s clear to customers what value they are receiving in return. This may seem obvious, yet I’m still struck by how infrequently the data I’ve shared is used to improve my experience. My inbox, for example, is still full of mass rather than personalized emails. Why not let customers feel the benefit of their data?
    1. Sainsbury’s email programme highlights which of their promotions and which manufacturer coupons a customer might be interested in, based on their purchase history.
    2. Coop emails are linked to promotions in your favourite store on things we think you would like to buy based on previous shopping.
    3. Starbucks use location data to prompt offers on the phone when you are near a starbucks
  2. Give your customers more control over their data. Let them opt-in, for example, rather than have to opt-out, and be very clear what they are opting into. Be upfront about your cookie policy, and its implications. And give customers options over such questions as frequency and method of contact.  Why not work with customers to figure out ways that you can turn data they could generate into something of value to them? Nike has done this to great effect, helping customers generate data to help with their own fitness, and in the process deepening their connection with the brand.
  3. Only collect the data that’s essential to deliver the benefit to customers, rather than everything you can. And be clear about what data you need to collect, the reason why you need it, and what benefit they will get in return.

While data security is certainly a complex technical and legal challenge, it’s underpinned by a question of brand mind set.

If customer data is viewed internally as a commodity, then it’s something to be extracted from customers and traded…and customers will be wary, as behaviours will give the brand away.

But if access to customer data is viewed internally as a privilege, where we don’t own a customers data it’s their data we are only curating it and looking after it to improve our customers experience then it’s something precious that has to be protected…and the resulting behaviours will inspire more trust among customers.

 

a very female community

data pulse #43

Now I’m not one into female fashion ( just ask my wife) , nor do I hang around the shops but I do love how Tamara Hill-Norton has used data to create a passionate community with Sweaty Betty since she set up the first boutique in Notting Hill in 1998 . Initially targeting “yummy Mummies” but now broadened out to connect fitness and fashion.

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Sweaty Betty is a British retailer specialising in active wear for women, featuring in 30 UK stores and 2 new ones in New York and selling significantly digitally. Sweaty Betty aims to ‘inspire women to find empowerment through fitness’.

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Sweaty Betty distinguish themselves from the competition by moving beyond traditional retail practices to focus on building an active community. This is achieved through regular Sweaty Betty fitness classes that are actively promoted to its customers. These classes range from yoga, run clubs and boot camps right through to Pilates, and are held in Sweaty Betty stores around the world. For those who can’t attend in person, there are also online fitness classes.

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Sweaty Betty was very clear on their purpose and had a very clear story that was developed starting inside the organisation, and building out into their community. A data driven approach to brand building and creating community, loyalty and interaction meant people starting telling the Sweaty Betty story themselves.

Sweaty Betty leverages a broad range of data-driven social tools – Twitter, YouTube, Instagram, Facebook and Pinterest are all used. They also created ‘brand ambassadors’ and allowed customers to have a conversation, helping to underline the sense that Sweaty Betty is a ‘fitness community rather than just a sportswear retailer

 

Don’t be frightened of data

data pulse # 33

We should not be frightened to use data: People have been recording data and creating information for thousands of years.

Data use is older than the written word and has been used through history to provide information:

75,000BC the Blombos Ocher Plaque is thought to be the first recorded piece of data.

Blombos Ocher

In 850AD Al-Kindi examined the frequency of letters in text to systematically create and crack coded messages.

Al-Kindi

In 1662 John Gaunt analysed mortality figure (in an early excel spreadsheet) as a means to predict the onset and spread of bubonic plague.

John Graunt excel

In 1855 Florence Nightingale used advanced visualisation techniques to make her data more persuasive for the generals and convince them that more soldiers were dying in the hospitals of the Crimea than on the battlefield, and so allow her to use her lamp.

Florence Nightingale

In the 21st Century there is more data and even more being created every day but the same simple principles apply.

Be clear on your outcome and then decide what data you need to tell the story you want to tell.

Anyone can use data, not just the analysts and data scientists. You just need to give them the confidence , skills and tools to do so.