Segmentation is a tool to grow customer numbers

netfix house of cardsdata pulse #37

Delivering the most relevant, inspirational messaging and experiences through advanced segmentation and targeting is a key advanced use of data. Segmentation itself is relatively straight forward, we all do it all the time. The skill for CMO lies in bridging the technical teams and the business imperatives to develop segmentation that delivers on commercial objectives

Netflix is an organisation that uses data in three of the advanced states. Netflix micro-tagging of vast content archives allowed creation of nearly 77,000 film segments, rich data, views, searches , times, pauses and more is used to build behavioural profiles and predictive algorithms give uniquely targeted recommendations.

The segmentation techniques are not dissimilar to the segmentations that Tesco, Sainsbury’s , Coop  and Asda built for segmenting customers. Both cluster users based on attributing product features to films / products and then clustering film watched/ products bought using analytics.

The difference is the Volume, Velocity and Veracity of data used.

Coop Food apply 7 segments to members annually,

Netflix create 77,000 segments on daily basis, continually refining which segment members are in so better able to predict your best next film.

More complex isn’t always better, as organisations need to WALK before they can RUN, and align people and processes before they build more complexity. Asda is now using customer segmentations and tools and processes for building ranges and promotional plans, and continually building and refining, as well as segmenting customer communication to improve the Customer Experience

Customer focus, data-driven to deliver commercial imperatives.

Building more sophisticated segmentations will develop but add value if they are aligned to deliver commercial objectives, so creating strategic and operational capabilities

 

 

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.

Data is Magic for Disney

disney Magic band

“advanced technology is indistinguishable from magic”

Data Pulse #7

My god-daughter Rose Bolcato has just visited Disneyland Paris for her Birthday weekend over Easter. she loves the magic that is Disney. Disney  is the place to take your kids ( both small and grown up ones like me). The Disney brand is all about “Magic” and it’s critical to tell that story consistently.

Disney has invested heavily in its new ‘MagicBand’ technology that delivers an enhanced, data-driven experience for guests at Disney World.

The MagicBand, containing an RFID chip and a radio, connects visitors to a network of sensors around the park. The band allows guests to open hotel doors without a key, enter theme parks, use FastPasses for rides, and make purchases without a card.

The only information stored in the band is an identifier – all other data is stored remotely in the cloud. The MagicBands, sensors and supporting systems generate a rich stream of live data: who is visiting which parks, which routes they use, which rides they are visit, when they visit, queue lengths, food purchased, meal times, shows attended, gifts bought, bathroom stops, time spent in hotel rooms and more. This information allows Disney’s analytics team to make data-driven decisions to optimise the park experience so that visitors have a longer, more enjoyable stay – and spend more while they are there.

 

how to make a c-store more Convenient

 

 7-11

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

To build this capability, 7-Eleven is implementing a Crawl, Walk, Run process:  essentially an AGILE approach to building a customer and data-led convenience store customer experience

  1. Crawl: build the customer database, launch mobile app, introduce offers.
  2. Walk: integrate self-reported data into profiles, feed segmentation and modeling into communication strategies, increase volume of membership, transactions and offers.
  3. Run: launch programmatic loyalty (moving from offers to earned rewards), incorporate unstructured social/web data, advanced analytics, customer engagement.

7-11 3

The app also features an Idea Hub, where engaged customers can offer suggestions for ways 7-Eleven might improve stores, the app, or any other part of its offer.

 

Segmentation is easy

 

netfix house of cards

 data pulse #37

Delivering the most relevant, inspirational messaging and experiences through advanced segmentation and targeting is a key advanced use of data. Segmentation itself is relatively straight forward, we all do it all the time. The skill for CMO lies in bridging the technical teams and the business imperatives to develop segmentation that delivers on commercial objectives

Netflix is an organisation that uses data in three of the advanced states. Netflix micro-tagging of vast content archives allowed creation of nearly 77,000 film segments, rich data, views, searches , times, pauses and more is used to build behavioural profiles and predictive algorithms give uniquely targeted recommendations.

The segmentation techniques are not dissimilar to the segmentations that Tesco, Sainsbury’s and Coop Food built for segmenting members. Both cluster users based on attributing product features to films / products and then clustering film watched/ products bought using analytics.

The difference is the Volume, Velocity and Veracity of data used.

Coop Food apply 7 segments to members annually,

Netflix create 77,000 segments on daily basis, continually refining which segment members are in so better able to predict your best next film.

More complex isn’t always better, as organisations need to WALK before they can RUN, and align people and processes before they build more complexity. Coop is now using customer segmentations and tools and processes for building ranges and promotional plans, and continually building and refining.

Customer focus, data-driven to deliver commercial imperatives.

Building more sophisticated segmentations will develop but add value if they are aligned to deliver commercial objectives, so creating strategic and operational capabilities

 

 

Creating C.I. from B.I. for Customers

 

British Gas

Data-Pulse #69

Using data- driven analytics and technology to create new services that improve the Customer Experience by creating CI (customer version of BI) has emerged recently:

British Gas and Southern California Electric:

The development of SMART meters has revolutionised the available data from Energy. British Gas connect multiple sources of data to display personal energy use in simple terms: not just kW usage per day/ hour but cost per day/hour, with comparisons to average houses in the area, all presented in easy to use tables and graphs.

British Gas Hive 2

It provides clear practical information that delivers “Informed Energy”. It tells me last week it cost £3 a day to heat my home, and if i turned the thermostat down by 2 degrees i would save £1 a day……. giving me control

California Electric have used variable and peak demand pricing in California to manage energy use in area where there are energy restrictions.

The creation of Hive by British Gas allows remote control of customers’ home central heating, again with an excellent customer experience, allows customers to run their home more efficiently. I can turn the heating on as I come home from work, or manage remotely my teenage daughter who has turned up the temperature before going out herself.

British Gas Hive

Hive will continue to develop as IoT connects more devices to create a House management system.  your Fridge will be connected via IoT to electricity supply and it will automatically switch itself off in periods of low use ( night time ) when no energy is needed to maintain temperature.

Hive have just launched new products in the Hive product family:

  1. Hive Active Plug to connect home electrical appliances via your phone. eg iron or hair straighteners or schedule lamps to turn on and off when on holiday
  2. Hive window or Door Sensor: you can find out if a door is opened or closed when you are away from the house , they’ll tell you by sending an alert to your phone.
  3. Hive Motions Sensor: extra peace of mind with small and sophisticated sensors sending alerts to your phone if movement spotted in your house. 

british gas hive 1

 

Starbucks data driven mobile approach

starbucks

Starbucks have adopted a data driven mobile first approach to making the customer journey simpler and easier in its coffee shops world-wide. 

Innovating and transforming the Customer experience by leveraging data-driven analytics and technology is critical for success in a 21st Century convenient foodservice retailer. 21% of Starbucks transactions are now completed via mobile … in store at the till using Apple Pay via app or using Starbucks Mobile Order and Pay . What’s more is Starbucks processes more than 6million Mobile Order and Pay transactions a month globally.

Mobile Order & Pay is available on iOS and Android . It’s a relatively new feature of the popular Starbucks mobile app that allows customers to place and pay for an order in advance of their visits and pick it up at a participating Starbucks location. Following successful launches in select US cities , mobile ordering is emerging as the fastest and easiest way for Starbucks customers to order ahead , then pay and pick up their purchases, providing on-the-go customers a simple and quick alternative to get their favourite coffee. Massive in USA and beginning to be trialled in UK,There’s a trial store on Tottenham Court Road.

The Mobile Order and Pay feature allows customers to choose a store from a (Google) map view , browse , select and customise drinks, view the estimated time the order will be ready and pre-pay the order. All within the Starbucks app, and integrated into the existing Starbucks app, and my-Starbucks Rewards loyalty programme. A simple easy way to sign up and earn Stars

Starbucks are leading the way as Tech leaders in convenience foodservice, using data and technology in a way that McDonald’s , Burger King and Dunkin’ Donuts will need to respond to rapidly if they want to respond to customer needs.

 

 

Taking data into communities

nike plus

Similar to Strava, Nike+ Running is a fitness tracking app which measures and records running and cycling activity.

nike 1

While the playback of exercise data to users is considerably less detailed than Strava, Nike+ has committed more energy to connecting real world communities with Nike+ Run Clubs and Training Clubs. Run Clubs are for all kinds of runners, with different types of run – Long Run, Speed Run, Track Night and more – designed to help runners achieve their personal goals. Separate to the Running app, Nike+ Training provides over 100 workout routines catering to different needs: Get Lean, Get Toned, Get Strong etc. at beginner, advanced and intermediate levels. Users can share their workouts, see how their friends are doing with their own training programmes and give and receive messages of encouragement.

nike 2

The Nike Training Club puts on free exercise classes in city locations (typically parks and shops) and also feature in some paid-membership gyms. These classes bring together people of all types, regardless of ability.

Nike also stage real world events so that the digital community can become a physical community.

Mike and I both Run Hyde Park and run around the same time.

Nike+ invite us to a NIKE event in Hyde Park,

Data Driven Donald Storms Ahead?

trump

data pulse #29

Donald Trump has been quietly building a data juggernaut like Barack Obama: defying sceptics he’s been putting tools in place to get out the vote and results from the states so far suggest he is pulling ahead as front-runner because he’s getting the vote out for his supporters.

In 2015 his campaign assembled an experienced data team to build sophisticated models to transform fervour into votes. The team is led by two low-profile former data strategists, Matt Braynard and Witold Chrabaszcz, and they are using the Republican Data Centre plus supercharging it.

The RNC Data Center 2016 is a powerful query and data management tool, providing an interface for over 20 years of voter contact data. This allows Republicans / Trump to read and write data to and from the platform, continuously serving up the latest information to Trump. If Trump wanted to find 10 people on a residential block that haven’t voted in the past 20 years, have strong views on conservative topics and don’t like the Affordable Care Act, they could do so in seconds.

The system is described as the ‘centrepiece of the RNC’s new data-driven political ground game.’ Voter scoring is employed to track each individual in for contact (by mail, door, phone) and whether they voted (by absentee or on Election Day). Advanced voter profiling even matches social data to voter data automatically

The data push is focused on integrating information Trump has collected, through his campaign website and at voter rallies, on nontraditional or unregistered supporters. It also includes commercial data obtained from the RNC and other sources, in an effort to mobilize voters in key early states.

A data driven Trump seems to be storming the Primaries (he won over 50% of vote in Connecticut, Delaware, Maryland, Pennsylvania, and Rhode Island  with record turnout ) and into the White House in November.

Check out other Blogs : Data Driven Rednecks, Obama in Subscription Business

Data driven Aussies

ARFU fans.jpg

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

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 .

sierra club 2

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.

siera club 1

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.

 

Obama- in the subscription business

obama

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?

customer data joke 5.jpg

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.

 

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.