Data Driven Communications


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Data driven communications presented to RMIT University

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  • (C) 2008 ADMA Education Courses
  • (C) 2008 ADMA Education Courses
  • (C) 2008 ADMA Education Courses
  • So what is big data exactly?

    Big Data is data that is too big and complex for many organisations to handle. It’s not an Excel sheet. It’s far greater than that.

    The biggest problems we have with data include it’s sheer size, the speed at which we’re creating it and the diversity of the data being generated.

    Big Data isn’t just created by the Microsofts or IBMs of this world.

    We all contribute to Big Data – we as in consumers – with every click, every view, everything we do is a contributing piece of data that is collected world wide.

    Look at this simple image demonstrating the plethora of data sources.

    How many of these can you tick off personally as contributing to data sources and input?
  • Many businesses have little or no need to manipulate big data for their benefit. In saying that, there are plenty of great examples where businesses are using big data opportunities very successfully.

    Here’s an example of Big Data in action with a fast food manufacturer, unfortunately not disclosed. This company placing cameras on drive through lanes to determine what to display on the digital menu board. When the lines are longer, the menu features products that can be served quickly, whereas when the lines are shorter, the menu interface features higher-margin items that take longer to prepare.

  • People Like U is from U Bank, a brand created by NAB.

    PeopleLikeU pulls together anonymous transaction data to identify trends and allows visitors to compare their spending with that of their fellow Aussies.
    The PeopleLikeU site has been built with UBank and NAB customer information, such as balances, savings goals, and mortgage details; census data; and spending numbers sourced from analytics firm Quantium.  
    Site users can search by area, gender, age, income and living factors to identify trends and insights and compare their habits to those of peers, with, reportedly, more than 1bn numbers crunched.
    Users can check to see where people choose to spend their money and time in different cities, carry out financial health checks by comparing their circumstances to their peers, and predict their futures by adjusting age and income.
    The names and addresses in all the PeopleLikeU data has been stripped out and the information available is around what transaction occurred, when it occurred and how much it occurred for. Instead of unique identifiers such as names or account numbers, the age of the customer, where they live and such are mentioned.
    Why don’t you give it a go and see how unique you are? 
  • At the earliest stage of personalisation, marketers can use basic name, gender, email and customer status information.

    Over time, you will have collected data on their purchase behaviour, and can start targeting consumers based on this knowledge alone. Again, think of Amazon and their model of “customers who have bought this product also bought this product”

    As your tools become more sophisticated and you start to track your data, you can offer a 1 on 1 experience – offering the customer what they want, in the channel they interact and engage in, all based on their behaviour data. That’s the ultimate relationship, on a customers terms.
  • 12 months ago I would never have used Coles as an example of using data in a clever way. Coles and also Kraft in the US have made leaps and bounds in using the data they collect to really personalise the experience for customers.

    In the past, most newsletters have been generic in nature. Coles are now leading the way in using this information to provide me, as a customer, the most relevant and timely offers and information. All of these products in the email are something I have bought (or a cross-sell of) in the last month. My only brow-raising offer was for Balsamic Vinegar, as I’m at a loss as to how you’d use 250ml in a month!

    An example of Kraft in the US is the personalisation of cross selling products based on purchase history. For example, if the consumer has never purchased pork, the recipes that Kraft distribute in their communications won’t include pork as an ingredient.
  • Your web analytics can provide you a depth of information that isn’t visible on the surface. By delving into your data, you can start to uncover a bunch of valuable data points, that when pulled together, can give you a clear profile of your individual users. You can then layer this information with other variables. Looking at this information will allow you to segment your audiences and provide tailored communications to them, based on their behaviours, needs and wants.

    For example, from your site, you will be able to determine their behaviour with your current products and services. The first layer you could place on top of this are the environmental layers, followed by a referrer variable (which is the channel or communication method which engaged this particular user), plus the temporal variables. The example would then look something like this: A current customer, on the eastern seaboard of Australia, aged 35-45 years, who received and acted on your email activity, who has visited your site more than 5 times in the last month – can then be offered a new ACTION, as you know they are loyal customers who are active with you, you don’t need to waste your communications on you products because they know your products. However, you may be looking for a cross product sell opportunity. You can then match the exact offering to the individual.
  • My favourite case study when it comes to using data in a clever way. Amazon is amazing. If you’re not an Amazon customer, then you should become one simply to monitor the way they monitor you and how perfectly aligned & sophisticated their targeting is.

    All the opportunities for targeting are highlighted in yellow.
  • Here are a few applications where quantified self is at the forefront of the technology:

    Sleeptime App – measures sleep patterns
    monitors and analyzes your sleep cycles – to wake you up in the lightest sleep phase (e.g. within 30min range), allowing you to wake up better relaxed and refreshed
    Also keeps historical track of your sleep cycle to help improve better sleep patterns for deeper sleep and better rest
    uses smartphone motion technology to sense subtle movements throughout the night and graphs your sleep cycles
    uses proven sleep science and has worked with Stanford University to create a best-in-class, proprietary algorithm to analyse

    Runkeeper – measures run times distance and routes
    GPS fitness tracking application – track their run, walks or hikes using the GPS already installed in their phones – measures time, distance, and pace
    thus allowing mobile phones to replace tracking methods traditionally monitored by an athletic trainer
    integrates with the built-in music function of the phone
    integrates with social networks (eg Facebook, Twitter and Foursquare) and has an online social network of users that share progress, goals, training programs and mapped routes

    QUENTIQ - German wearable qualified self sport sensors
    all round wearable sensors to track and benchmark your health, fitness & lifestyle.
    define goals, Achieve health scores, share activities with friends/support groups, and win challenges – all towards living fit and healthy.
    their platform tracks over 95 fitness activities (indoors and outdoors)

  • As technology starts to match against needs, wants and desires, we’re seeing an influx of cool stuff in market, like this – the Prep Pad.

    The Prep Pad is a digital scale that calculates nutritional information in real-time/ Designed for health-conscious home cooks, and riding the wave of the quantified self movement, it provides users with nutritional information about their meals – calories, protein, carbohydrates, and fat content – similar to the information you’d find on the nutritional label of any packaged good.
  • When we refer to social networks, remember there are other networks outside of Facebook and Twitter. What about Pinterest and Instagram for inspiration and aspiration.
  • One of the best apps in the market is the Woolworths Everyday Rewards app. This app has a huge amount of utility, and it’s users a loyalist as their finest.

    1.7m downloads in it’s first 3 months, this app just keeps getting better and better as they optimise and improve the functionality.

    In a major update, Woolworths has integrated with app with its online shopping service - enabling customers to browse the supermarket aisles, order and pay on their mobile phone. They will also be able to scan items to build their shopping list and then convert it to an online order. The addition of mobile shopping was "a significant project" according to Woolies. This development began shortly after the release of the original app as it was one of the most common requests from customers.

    This is such a great example of listening to customer feedback and the data and then implementing that feedback. Well done Woolies.

    Initial release Aug 10, 2011
    Current version (5.0.11) Oct 25, 2012

    Android 336084 downloads @ 13/02/2013
    Iphone ios

    Woolworths adds online shopping to mobile app (reported 15 February 2012)
    Last August, Woolworths launched an in-store shopping app for iPhone that organised a shopping list in aisle order for any particular store. Other features included recipes, weekly specials, barcode scanning, and integration with the Everyday Rewards scheme.
    That was followed in September by an Android version, and a number of minor updates have been released since then. The Woolworths app has been downloaded 1.5 million times, and according to Has Fakira, innovation program manager at Woolworths Supermarkets, the number of updates downloaded indicates the app is actually being used. "We are over the moon" about the way shoppers have taken to the program, he told iTWire.

  • Looking forward to future trends in mobile, we can expect to see the rise of super applications – where 2 or more applications come together to provide the ultimate utility for consumers. Think RunKeeper and Calorie King in partnership, or perhaps the blood sugar glucose monitor plus FoodSwap and Everyday Rewards from Woolworths. Consumers can monitor what they eat through FoodSwitch, order the right food through Woolworths and monitor their sugar levels in all the one place. That’s ultimate consumer health management.
  • Data Driven Communications

    1. 1. Data Driven Communications Presented to RMIT, 12 August 2014 © 2014 Zuni | All Rights Reserved | Confidential
    2. 2. Hi, I’m Valentina Co-owner & Client Relationship Director of specialist digital agency Zuni Current clients include Michael Hill, NRMA, TAFE, Macquarie University, Lend Lease, Suncorp, Westfield, Roche 20 years agency-side experience © 2014 Zuni | All Rights Reserved | Confidential
    3. 3. DATA’s VERY important © 2014 Zuni | All Rights Reserved | Confidential
    4. 4. Digital Strategy Process Document the business objectives and the expectation of digital’s role in achieving them, as well as current asset performance Understand key target audiences, their online behaviour and determine how they use digital as part of the customer journey to purchase / engage with the product / service Review the broader market and competitive environment Develop an overarching framework that outlines how the various elements of digital work in harmony to achieve the objectives Develop specific executional plans that can be implemented © 2014 Zuni | All Rights Reserved | Confidential
    5. 5. UNDERSTAND THE TARGET AUDIENCE Map out how the target audience uses digital channels to engage with the problem area / solution options and brands, focusing on understanding their digital behaviour and requirements. Key areas of focus : • What does the customer journey for the product / service look like • How is digital used as part of that process • What users want – functionality, channel and content • Differences between target audiences • Frequency of visits
    6. 6. UNDERSTAND THE TARGET AUDIENCE-METHODS • Review all current information on target audience • Market knowledge of the product and audience • Online surveys – On own website – Via email • One-on-one interviews • Qual vs Quant – depends on what you’ve already got
    7. 7. Data Trends in Marketing © 2014 Zuni | All Rights Reserved | Confidential
    8. 8. © 2014 Zuni | All Rights Reserved | Confidential
    9. 9. What is Big Data? • Not an Excel Sheet • Lots of data that can’t be easily managed or manipulated • Layers of data that if mined for the insights are extremely valuable • Know more about the customer and their habits © 2014 Zuni | All Rights Reserved | Confidential
    10. 10. • Realistically, most businesses have little or no use for big data • Large organisations will benefit the most Long drive through queue Short drive through queue © 2014 Zuni | All Rights Reserved | Confidential Electronic menu board displays quick to prepare items Electronic menu board displays higher-margin, longer to prepare items Should I be concerned?
    11. 11. Data Sources • NAB customer data • Census data • Spending data from Quantium Case Study
    12. 12. Data Enabling Personalisation Basic email sending Basic reporting © 2014 Zuni | All Rights Reserved | Confidential PERSONALISED CONTENT: Segmented based on purchase behaviour 1:1 CUSTOMER EXPERIENCE: When the customer wants, in the channel they want, based on behaviour in multiple channels TOOLSET & INTEGRATION TIME & DATA CAPTURE
    13. 13. Case Study Personalisation Localisation Purchase history makes up my weekly offers Creating Relationships Other retail examples:
    14. 14. Data you can leverage for personalisation Site Behaviour Variables • Customer v Prospect • New v Return visitor • Previous Visit Patterns • Previous Product Interests • Search • Previous online purchase • Previous campaign exposure • Previous campaign response © 2014 Zuni | All Rights Reserved | Confidential Environmental Variables • IP address • Country of Origin • Time Zone • Operating System • Browser Type • Screen Resolution • Demographic Layer (income, age) Referrer Variables • Referring domain • Campaign ID • Affiliate • PPC • Natural Search • Direct / bookmark Temporal Variables • Time of Day • Day of Week • Recency Offline Variables • Frequency
    15. 15. Case Study © 2014 Zuni | All Rights Reserved | Confidential
    16. 16. Quantified Self Sleep Time (Azumio) app Runkeeper app Sources,, © 2014 Zuni | All Rights Reserved | Confidential QUENTIQ platform – wearable sensors and app
    17. 17. Quantified Self © 2014 Zuni | All Rights Reserved | Confidential
    18. 18. Know your customer journey Discovery/ Awareness •General internet usage • Paid Media – including traditional media like pamphlets • Search / Google • Social networks •Word of Mouth: Forums, Reviews, Blog sites Consideration • SEM: Search terms around location, open times, offers and deals; alternatives to gym location (ie independent group exercise) • Social media spaces: View experiences & recommendations of others in network •Word of Mouth: your go-to person (someone you know, in the know), water-cooler chat • Your Product: free trial / offers, try before you buy PT offer © 2014 Zuni | All Rights Reserved | Confidential Final purchase decision • SEM: Search terms around location best options and flexibility • Ongoing Support: Meeting and surpassing your fitness goals; nutritional support, plan reviews • Social Aspect: onboarding process, team introductions, support network creation • Your Product: free trial / offers, try before you buy PT offer; investigate range of membership offers and onboarding offers; member-get-member offers Experience & advocate • Your Product: Content engagement through VALUE for the customer (recipes, meal plans, at home solutions) • App integration: wearable technology information & success – understanding of personal achievements and assessment • Social media spaces: Recommend & share, part of a community
    19. 19. © 2014 Zuni | All Rights Reserved | Confidential
    20. 20. Comms Data Decisions © 2014 Zuni | All Rights Reserved | Confidential
    21. 21. © 2014 Zuni | All Rights Reserved | Confidential
    22. 22. Data, Data, Data © 2014 Zuni | All Rights Reserved | Confidential Results • 1.7million app downloads in first 3 months (iPhone & Android) • Customers who shop both in-store & online spend 70% more than customers who shop solely in store Emails – exclusive member discounts Mobile app with in-store shopping – Shopping lists ordered by aisle of local store – Bar code scan products to add to shopping list – Track fuel vouchers & savings – My specials – offers designed around things customers buy most – Health & wellbeing content – Recipes – add ingredients directly to shopping list See more here
    23. 23. Super Applications © 2014 Zuni | All Rights Reserved | Confidential + + +
    24. 24. © 2014 Zuni | All Rights Reserved | Confidential
    25. 25. © 2014 Zuni | All Rights Reserved | Confidential
    26. 26. ? Questions Valentina Borbone Client Relationship Director e: w: p: 02 9516 5480 t: valentina1975 l: © 2014 Zuni | All Rights Reserved | Confidential