All posts in “Big Data”


Connect With Customers by Leveraging Smartphone Sensors

We not only live in a world of billions of smartphones, but we now also live in a world of sensors, soon to number in the trillions. As smartphones start to really live up their name, new models are being outfitted with an increasing number of sophisticated sensors that can pick up cues from a user’s immediate environment. Samsung’s Galaxy S4, for instance, has nine sensors that provide a glimpse into someone’s physical world. Apart from embedded smartphone sensors, there are external sensors — from iBeacons to connected devices within the internet of things category. People are moving through their daily lives with a great variety of sensors on and around them — in their homes and cars and the stores they walk into. Marketers need to tap into the treasure trove of sensor data to inform their dialogue with customers and create highly relevant, personal and intimate interactions. At no other time in history have companies been able to learn so much about their consumers, the actions they take and circumstances they open, tweet, click, “like,” redeem, book or buy. Here are five ways companies can leverage smart sensors to create great customer experiences: 1. The traffic-jam experience. Many companies have started using location sensors for geotargeting, but as this tactic is used more frequently, marketers will need to push the creativity envelope further than simply accessing consumers’ whereabouts. A smartphone’s GPS sensor provides a window into what is happening around a person. Marketers can tap into third-party data streams like nearby traffic conditions, transit disruptions and other real-time situational factors to personalize and contextualize interactions. What’s more powerful? “Enjoy $1 off coffee today” or

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heavy delays due to an accident. Enjoy $1 off a coffee. It’s going to be a long ride.” 2. The highness experience. In office buildings, malls, airports and other multistory structures, altimeter sensors measuring elevation can let companies know not only that a person is on a block or near a building but also the floor they took the elevator to. As more companies try to drive foot traffic to brick-and-mortar stores through mobile devices, leveraging altitude as a trigger for campaigns will provide more accurate and intriguing messaging. (Look up. We’re right above you. Visit us and earn double loyalty points.”) 3. The emotionally distressed experience. If someone is having a bad day, his or her spouse may steer clear or try to bring cheer via a gift or a compliment. From Intel to Samsung, the biggest technology companies are developing tools that can infer emotions by assessing how hastily a person types and mistakes made as well as by using cameras to read the mood on a face. Marketers could develop interactions with customers to play on certain attitudes and try to turn moods around. If people received a free gift from a company when they were having a rough week, their brand loyalty might be boosted. Companies will also be able to anticipate consumers’ emotional state (like dreading the dentist or stressing over a board meeting) based on their attitude historically to certain weather or to types of calendar appointments. Analyzing the results of emotion-based campaigns will be critical on an individual level, though, since everyone responds differently to stress or angst. Some people might be annoyed by a company’s intervention effort, though, while others would welcome it. 4. The speed experience. Movement, speed and orientation data available through accelerometer and gyroscope sensors can provide interesting insights for triggering campaigns. A company wouldn’t want to distract consumers with a push alert as they drove a highway at 60 mph. This would promote bad driving and people are likely to ignore the message. Mobile interactions should occur when people can give proper attention, like when they window-shop or stop for lunch. Use of orientation data can also help keep marketing budgets in check. instead of targeting all individuals nearby, marketers can use sensors to send offers to people walking away from a store who’ve not come in and thereby increase the return on investment. 5. The hot and wet experience. Heat, humidity and pressure sensors provide precise

readings of environmental conditions related to a person’s exact location. Active-lifestyle marketers can tap into temperature and hygrometer sensors to suggest real-time modifications to someone’s workout based on past performance in specific situations. (“You may want to slow down. We are at 83 percent humidity.”) Retailers, consumer-packaged goods companies, travel and food and beverage firms can self-police how often they reach out to customers by using historical performance data; thus the companies can push messages only when they are hyperrelevant and likely to drive action. If a coffeehouse obtains better results from iced-coffee promotions when it’s hotter than 85 degrees, it should not target people in conditions below this threshold. Data from sensors is not enough, of course. The interactions that will have the biggest impact and drive the best results will be those that are highly personal, not just highly contextual. This evolving “system of engagement layer” of smart interaction lives on top of all existing tech systems from companies and is the future of customer relationships.


Giving Up on Mobile? You’re Not Alone: What Brands Can Learn from Uber

Mobile apps for brands have failed. This is the quite jarring — but not unsurprising — sentiment at many agencies and brands. Despite investments in the development and promotion of branded apps, very few, if any, can be considered a success. Download numbers are dismal and for the consumers who have taken the download bait, their attention span is comparable to that of a goldfish. I get it. The ROI that marketers are seeing is very discouraging. EX200 From a consumer’s point of view, there are a few reasons why I’m not engaging – or even using – branded apps. There is no efficiency increase, no real system of engagement and no true mobility add-ons. So how do brands move from unsuccessful mobile initiatives to results that are worth the investment? As one of the most successful

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mobile stories of the year, examining the five key characteristics of Uber is a great place to start:

  • Mobility: Uber was designed for the mobile-first world. It’s not just a ported version of an existing Web solution. Too often, brands simply replicate other digital solutions, offering no mobile add-ons. The apps that keep users engaged over the long-term will be built for the form factor, taking into account the small screen and leveraging all of the available sensors to provide a true mobile experience.
  • Integration: Uber connects with a network of systems and data sources to provide a comprehensive, seamless user experience throughout the entire customer journey – from discovery to payment to reviews. Apps cannot live in silos; they need to simplify the user experience as much as possible. For instance, a retailer app should allow for in-store contactless payments, connect with CRM systems and transaction records to allow for personalized deals.
  • Automation: Previously done manually, Uber automates the demand matching workflow for the taxicab industry. The nature of the “always-on” consumer requires automation technology to power marketing efforts. Marketers need to automatically trigger campaigns based on a variety of situational and behavioral factors for millions of individuals. To intervene in consumers’ lives at the right moment, mobile marketing campaigns must be agile, launching when it is relevant for the individual – not the brand.
  • Data: Uber figured out how to act on data in real-time. By analyzing the integrated data streams and anticipating customer demand, the company has introduced surge pricing to maintain optimal ratios. Marketers need to adopt predictive and prescriptive analytics to not only anticipate customer

    behavior but also make this information actionable. For example, a clothing brand could predict which items from the new spring line a customer would be interested in and know that a Free Shipping offer sent Friday afternoon is more likely to motivate a sale.

  • Community: Uber has created its own community; users are empowered to rate drivers and drivers can rate consumers. By allowing people to participate and connect with other users, they have a sense of ownership. Brands should find ways to let their users connect with each other, contribute content (in the forms of reviews, photos, etc.) and participate in decision-making, like voting on new app functions or products, such as a new seasonal holiday drink at a coffeehouse.

The customer journey no longer fits into the “funnel” that has guided marketing

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for decades. The complex new reality mobile has created is one of always-addressable consumers who

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are increasingly unforgiving of less than ideal experiences. As marketers reinvest in the development of native branded apps in 2014, they should keep Uber in mind – and not just for a ride around town – but as

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a mobility model

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Predicting is the new black: The latest trend in marketing

How powerful would it be for marketers to know what their customers are going to do before they actually do it? To predict how they would react to certain messages and offers, or to intervene just before a customer loses loyalty and switches brands? The medical community has been doing this for years — predicting the best course of action, based on family history and genetics. Wall Street too has used sophisticated algorithms to predict future market trends that guide high-risk trading decisions. Even some prison systems use the power of prediction to determine which prisoners should be paroled and which should serve out their full term. And no one can forget the use of predictive analytics in baseball, as shown by Brad Pitt in the movie Moneyball. Everywhere we look, the concept of “predictive analytics” is taking hold and is now becoming the most powerful tool in marketers’ increasingly sophisticated toolboxes. While the idea of predicting customers’ behavior may seem like something out of the Jetsons-era, it is very much a reality today and is dramatically shaping the way marketers engage with their customers. This can be seen in something as seemingly ordinary as Netflix predicting which movies I may like based on what I have watched, or as advanced as Target

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predicting which of its customers are likely to be pregnant. It’s no secret that brands have been collecting heaps of data on their customers in order to create robust profiles and personalized customer experiences. User profiles allow marketers to segment their audience on the simplest level by: geography, basic demographics and purchase history. Apart from actual sales and general profile data though, marketers – and their data scientists — are now analyzing things like social behavior, the stickiness of certain emails and promotional campaigns,

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and website activity to build living profiles. Each piece of customer data allows for advanced customer segmentation and goes into the statistical equation that predicts how likely action or inaction is. By using sophisticated algorithms based on the results of historical and real-time campaigns, marketers can now predict with a high percentage accuracy things like:

  • Who will purchase?
  • How much are they willing to spend?
  • What is the predicted lifetime value (LTV) of new customers?
  • What is a customer’s propensity to buy?
  • What is a customer’s propensity to engage?
  • Who will become a brand advocate and share about their experience on social media channels?
  • Who is likely to abandon for a competitor?
  • Which offer will resonate most with certain audience segments?

By understanding this, marketers can better allocate resources to target specific groups and, with the most compelling message, drive the most profitable relationship. By harnessing predictive analytics, brands can also understand which customers are worth pursuing and “courting,” and which will not pay off in the long run. As marketing budgets continue to be stretched, this power of prediction will be incredibly essential. Mobile has changed the ‘digital touchpoint’ landscape. Predictive analytics solutions would not have been as powerful pre-mobile, as

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the always-addressable customer did not exist. Now, brands need to discover the winning

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combinations of who to target, when to do it, with what type of message, on what channel – and how to react quickly if the outcome is not as predicted.


How ‘Little Data’ Will Unleash an Army of Jason Bournes

We all, of course, live in a physical world — our homes, offices, cars, places

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we frequent, and people with whom viagra gnc we associate. However, the world that is dramatically changing the way we live our lives and our daily experiences is a mass ocean of data, invisible to everyone but us. These physical and digital worlds are becoming increasingly interconnected by millions of sensors that make up the Internet of Things. Our data is superimposed over the physical world, accessible through smartphones, car dashboards, tablets, biosensors — and eventually through a Google Glass headset interface or the next-gen equivalent. 70-463 Grounded in ever-sophisticated predictive analytics, this data-world is quickly evolving and will soon automatically take action on our behalf, interacting with our physical world, offering options and opportunities you want, foreseeing what you don’t even know you want, all without having to ask. You are the center of both worlds because mobile devices have shrunk big data and made it about you. They have acquired,

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filtered and reconfigured themselves for your personal needs and wants. Some might call this a “James Bond future” because it’s about hi-tech, futuristic toys and living on the cutting edge of cool. But we don’t need — or want — to be James Bond. Digerati will quickly evolve from Bond (reacting to his environment) to Jason Bourne (always anticipating traffic, weather, the bad guys — intuitively exploiting every opportunity). We’ll realize a Jason Bourne future where our physical world magically cooperates with us. Consider these facts:

  • Automakers are integrating disparate data, blending everything from incoming phone calls to physical road conditions, gas prices, traffic, weather, and opportunities (fuel dropping below 20 percent — stop at next station).
  • Intelligent houses monitor and adjust temperature, energy expenditure, call your security company if an alarm is triggered, and send refrigerator alerts if you’re low on milk.
  • Fitbit is one of the wearable computing devices that feature biosensors and biometrics. Soon, an athlete with a heart condition will get a life-saving automated cialis malaysia price text and call indicating his pulse is rising with a recommendation that could help him avert a heart attack.

So what is driving this (r)evolution? Six primary trends:

  1. Smartphones are getting smarter. Smartphone apps will use more sensors (GPS, camera, microphone) to drive relevance, using location as a cue for situational awareness and action triggers. Imagine your phone checks your train status in the background as you walk towards the station without you asking for it, and

    adjusts your thermostat as you drive home,

    without triggering it.

  2. Every device and location is becoming a node in the network. Cars, homes, utilities, the office, and stores will be intelligent nodes; your smartphone will be the intelligent glue, delivering the beginning of a user-centric model.
  3. Shared data is also becoming a norm. Data will be shared phone-to-phone, vehicle-to-vehicle and via any real-time, peer-to-peer communication link. Rapid-data authentication and ID protection make it private and secure.
  4. Cloud nine will be your home address. The cloud will store your tastes and preferences, feeding them to the services you use. Imagine you’re driving toward a smart, linked, next-gen ATM that has been “told” you’re arriving by your smartphone. The ATM already knows (based viagra china on secure, encrypted data you stored in the cloud) that on the third Friday canadian pharmacy of each month you like to transfer $1,000 to your wife’s account, while simultaneously paying your mortgage and withdrawing cash.
  5. Predictive Analytics: As more of your data is collected and analyzed, tech will anticipate what you need or want before you even realize it. My favorite store, for instance, will predict what products I like and send me a relevant offer.
  6. You will be the “master orchestrator.” Tomorrow’s tech will empower users to blend data streams with on-demand information from the cloud to help smartphones “think” and suggest ways to make lives easier. Connected services also enable the user to trigger an action; big data analysis, personalization and machine learning will be key elements of the “orchestrator” toolset.

The cutting edge of cool means rejecting the unattainable Bond fantasy for the increasingly available Bourne reality. The cialis and nasal congestion Internet of Things is ushering in a new lifestyle with seamless orchestration of information services and the corresponding real-world entities. Every setting we encounter will be ready to interact for fast, easy, smooth, smart and automatic collaboration. 700-501 Who needs James Bond’s buy viagra in mexico “license to kill” when the new urban mobile lifestyle can give you Jason Bourne’s “license to thrill”?