Understanding the basics of buying Ripple on your phone

When you’re dipping your toes into the world of mobile crypto trading, it can feel like navigating through uncharted waters. The convenience of purchasing digital currencies like Ripple on your phone is unparalleled, but it does come with a learning curve. Thankfully, most mobile platforms offer intuitive interfaces that help simplify the process. The key lies in finding an app that provides clear instructions and streamlines the steps required to make your first purchase, turning what might seem like a complex transaction into a few taps on your device.

Before venturing into mobile cryptocurrency trading, it’s essential to grasp the basics of your chosen trading app, whether it’s Ripple or another digital currency. Begin by learning how to set up and secure your wallet, verify personal information, and transfer funds. These fundamental steps act as your anchor, providing a solid foundation for a successful trading journey in the vast crypto world.

The perks of using mobile platforms for real-time trading

The magic of mobile trading platforms is in their immediacy. The financial world doesn’t wait, and with a mobile app, neither do you. Real-time updates mean you’re always in the know, and the ability to act on a market movement as it happens couldn’t be more critical when dealing with cryptocurrencies’ volatile nature. Where once traders were tethered to their desks, a mobile platform gives you the freedom to manage your digital assets whether you’re lounging at the beach or commuting to work. This accessibility is revolutionizing how we think about and engage with trading.

The vital role of user interface design in mobile trading apps

An app’s user interface is the captain of your mobile trading experience. It’s essential for steering through the often complex world of crypto trading, and a well-designed interface can make or break your journey. A clutter-free and responsive design holds the key to a smooth sailing. It allows quick access to essential features like your crypto wallet, market analysis, and buy/sell functionalities. This attention to user experience ensures that both newcomers and seasoned traders can navigate the app confidently and effectively.

Unpacking the essentials of crypto trading for mobile users

Moving from traditional trading to mobile platforms might feel overwhelming, but it’s actually making trading more user-friendly. In the mobile-first era, apps simplify complex processes into manageable steps. They guide you in setting up your wallet, explain terms, and even let you practice trades. This makes the learning process smoother and opens up crypto trading to a wider audience, encouraging more people to explore the possibilities of digital assets.

Fortifying your digital assets in the mobile realm

Security is a top priority when it comes to handling your digital assets via mobile. Mobile trading platforms are continuously enhancing their security protocols to ensure that your investments are protected from any virtual storms that may come your way. Encryption, two-factor authentication, and secure login processes form the bedrock of a trustworthy mobile trading app. It’s also up to individual users to follow best practices, such as using strong passwords and avoiding public Wi-Fi when trading, to maintain a tight ship for their digital treasures.

How mobile applications are changing the game for traders

With the world of crypto trading in your pocket, the control is quite literally at your fingertips. The user-centric designs of these apps mean that you get a personalized experience tailored to your trading style. Features like customizable dashboards and the ability to set up push notifications for price alerts allow you to remain agile and informed. Furthermore, the integration with other financial services means you can oversee all your investments from a single point of contact, simplifying your financial management even while you’re on the move.

Navigating the diverse portfolio of digital assets via mobile

The portfolio of digital assets at your disposal is as vast as the ocean. While Ripple might be your starting point, there’s a whole world of cryptocurrencies to explore. Modern mobile platforms offer an array of options, and they’re equipped with tools to help you understand each one’s ebb and flow. From in-depth charts to historical data analysis, these mobile apps ensure that you have a comprehensive understanding of the market dynamics. This enables you to make informed decisions, be it a small ripple or a massive wave, as you manage your investments wherever you are.

The post A smooth-sailing journey into mobile crypto trading appeared first on Mobile Marketing Watch.

The following is a guest contributed post from Dr. Mona Yousry, Chief Data Scientist, Sabio Mobile.

The amount of data that people generate simply by living their lives can be used to tell stories filled with context and insights. This information, combined with digital data, enriches our understanding of consumers and, by extension, the physical world. Big data, mobile phones, social media and behavior analytics each play a vital role in teasing out this understanding; as a result, they allow companies to gain a competitive edge, and are the future of business intelligence.

But what does data intelligence really mean? To put it simply, data intelligence is the ability to identify and analyze relationships, and to visualize the data associated with them. That is to say, business intelligence unifies sources of unstructured data together with up-to-date visualizations in order to access information on trends and experiences quickly.

Most people will already be familiar with the term “big data”. But what many people don’t realize is that the number of data sources that big data can draw from is increasing at a rapid clip, which in turn affects the quality of the insights that business applications will be able to generate. Having more – and better – data also allows for better AI, because the more high-quality data you have to train your systems, the better your AI algorithms will be.

Data opportunities and challenges

Implementing big data successfully is often a challenge for businesses, in part because of the oft-cited “Vs” of big data. Gartner’s 3Vs, variety, velocity, and volume, have traditionally been the way that most practitioners understand big data.

However, in some ways, the traditional way of thinking about big data ignores the larger picture – that is to say, how to interpret such massive amounts of data. As a result, we need to look beyond the original Vs, to what I call the 6V Wheel. In addition to variety, velocity, and volume, organizations also need to be thinking about validity, verification, and visualization.

Let’s start with the traditional Vs. Variety refers to the fact that not all data is created equally. No longer is it a set of observations and measurements that we can apply regression or time series to; instead, we think of data as a set of patterns that can drive amazing insights, particularly when made up of information from multiple sources. In the near past, a retailer might have relied on information drawn from e-commerce sites and social media – but now, with advances in location technology, one can look at data gathered from physical retail locations and points of sale, and subsequently gain more insight into shopping trends and behaviors. As mobile apps and devices have become smarter and more responsive to their environments, the variety of data available has exponentially increased. Most of this information is already in the hands of organizations, yet few are using it to drive value.

Velocity is a characteristic of data, frequently equated to real-time analytics. It is the rate of changes – about linking data sets that are coming with different speeds and bursts of activities. When the spatio-temporal relationship between two or more data sets changes, then everything else changes, even the definition of a “data event.”

Volume refers simply to the amount of data. Keep in mind that simply having more information than your competitor is not a guarantor of success; rather, it comes down to how effectively that information is being used to drive business performance.

Now for the three new Vs:

Validity refers to a question that our AI and machine learning intelligence is continuously addressing: how effective are these methods? For us, it is the accuracy and  how pervasive is our model. We look at many combinations to relate interactions, habits and behaviors, as only then can we start to understand audience needs (with their privacy still intact). For businesses, the power  is in the insights that allow them to measure performance, create value, drive awareness for new offerings, improve loyalty, increase sales, and countless other actions that are beneficial for their organizations. All of this is a validation of big data.

Verification is the process of establishing the accuracy of something; in other words, the establishment by empirical means of the validity of a proposition. Can a business verify that a customer responds well to a specific notification? How do you know if a particular ad was the reason someone visited a store? How good are your campaigns at driving attribution? How relevant are your ads to people? With AI, and the new types of data that are being collected, all of these questions can now be answered.

Finally, Visualization refers to how we dynamically see the data – and the intelligent decisions we make as a result of understanding those insights. Understanding data can be a complicated matter, and it needs to be easily digestible so that marketers and management can quickly assess what is and isn’t working, and make the right decisions.

While Gartner’s 3Vs provide a good baseline, this new 6Vs Vision creates a more holistic and comprehensive way to view data. This is especially vital as the importance of app science, geolocation, and mobile continue to grow exponentially, and as big data continues to create value for organizations.

The post 3Vs are Good, But 6Vs Are Better: A New Way of Understanding Big Data appeared first on Mobile Marketing Watch.

NextGen consumers are leading the retail industry to a new view on loyalty, according to Alliance Data’s card services business, a provider of market-leading private label, co-brand, and business credit card programs.

The newly released study, “The Rules of NextGen Loyalty,” reveals how Gen Z and Millennials have been empowered by unique experiences, technology, and the power of choice to engage brands and experience loyalty in truly new ways.

“This study really unpacks the shopping and loyalty preferences of today’s youngest consumer segment,” said Shannon Andrick, vice president of marketing advancement for Alliance Data’s card services business. “One-to-one conversations with real people supported by in-depth research has provided a unique view into the mindset of today’s youngest generations and what they expect from brand relationships. The loyalty landscape has truly shifted from brands driving loyalty to brands earning loyalty.”

Conducted by Alliance Data’s Analytics & Insights Institute, “The Rules of NextGen Loyalty” study used a combination of qualitative and quantitative research methods including mobile diaries and digital app tracking to determine behaviors, follow-up one-on-one Skype conversations to provide context, and a survey to identify the differences, perspectives, and preferences among younger generations.

Some highlights from the report:

• Loyalty is earned. Understanding the role of and influences on choice is more important than ever before: 63% of younger consumers agree they have many choices of where to shop, so a brand must show them loyalty to earn their business. Once brands recognize the unique motivations of Gen Z and Millennials, they have taken the critical first step in building deep brand connectivity and earning lasting loyalty.
• Loyalty is complex. Traditionally, loyalty has been viewed as one-dimensional. Yet, loyalty is anything but simple. Research shows when it comes to life loyalty and brand loyalty, a continuum emerges spanning a range from functional to emotional. Different types of loyalty span the continuum from traditional, mostly functional loyalty, to brand love, emotional loyalty. Re-thinking a brand’s approach to loyalty means understanding that true loyalty requires a combination of function and emotion.
• Loyalty is fragile. Today’s younger consumers are increasingly unforgiving. They are empowered by instant access and greater choice to want more and “put up” with less. In fact, 76% of younger consumers only give brands two to three chances before they stop shopping them. One in three consumers said nothing could be done when asked what a brand could do to win them back.

To check out the full report, click here.

The post Marketers Take Heed: Brands Must Show Loyalty to Earn Loyalty appeared first on Mobile Marketing Watch.

The following is a guest contributed post from Jeremy Fain, CEO and founder of Cognitiv.

A lot of people have asked me about my thoughts for 2018, and what I think the overarching trends in advertising technology and deep learning will be in the coming year. Far be it from me to disappoint my fans – so here’s my take on next year’s biggest topics:

1. Marketers will have to start thinking seriously about deep learning.

AI has been a buzzword for the past several years, as clearly evidenced by the vast numbers of products claiming to be AI currently on the market. While most of these applications don’t really live up to the picture of AI that most people have in their heads of a Jetsons-like robot, there have lately been a series of discoveries, most notably in the field of deep learning, that are sure to have a serious impact on the way that most businesses operate.

Deep learning and neural networks are at the heart of some of the most astonishing machine learning developments, from image recognition to the natural language processing that enables gadgets like Amazon’s Alexa and Google Home to operate. But access to the technology and insights of deep learning is no longer limited to the big players, as new tools have arrived to bring the computing power and analytical insight of deep learning to marketers.

In some ways, the current wave of AI products is good, because it means that more people, including marketers, have become aware of what AI has the potential to do as well as its possible limitations. As more advanced forms of AI become market-ready, deep learning will be at the forefront of any of those conversations, and marketers will begin to understand the value of using deep learning to buy media and create audiences to advertise against, becoming better equipped to lead their businesses to success in 2018 and beyond.

2. Mobile ad networks will be forced to become more transparent.

Before programmatic became a mainstay of digital advertising, ad networks performed an important function as an intermediary between digital advertisers and publishers. They could help publishers find buyers for their inventory, and they could put inventory from multiple publishers together to make it easier for advertisers to buy. Because most inventory came from smaller publishers, it cost less, and was a cost-effective value proposition for most advertisers.

The rise of programmatic, however, created a way for advertisers to directly buy from any publisher with added transparency into pricing and websites.  Suddenly, ad networks had to deliver more value than just inventory aggregation.  This transition took place in the traditional digital display world years ago but has yet to take place in mobile advertising.  2018 will be the year where mobile ad networks will have to prove their added costs or face the reality that mobile advertisers have begun to use programmatic for user acquisition and retention campaigns.

3. Header bidding will become a problem on the agency side, so its use will diminish.

This relates in some ways to the general theme of greater transparency in the digital advertising markets. Header bidding code allows a publisher to offer the same impression in multiple exchanges at the same time, ultimately leading to the impression being sold for a higher price than if a single exchange was used. This means advertisers are bidding multiple times on the same inventory and, because of the nature of programmatic, they are likely paying more.  Originally, header bidding was meant to allow advertisers to compete programmatically for all of a publisher’s inventory, instead of just the unsold “dregs” that were left over after directly sold insertion orders had been fulfilled.  The technology, however, is now being used to offer the same impression through multiple exchanges to the same DSP.  This has driven DSP costs up because of the skyrocketing number of “duplicate” bid requests being received from multiple exchanges and has given rise to an entirely new ad tech industry of trying to sift through these duplicate impression requests.

A much more elegant, and likely solution in 2018, will be that advertisers through their agencies will require the use of the ads.txt standard.  This file is meant to be made available by every publisher wishing to sell their inventory programmatically.  It lists the exchanges their inventory is available in.  Ads.txt was created to stop a flagrant type of fraud where websites list themselves inaccurately as more valuable websites, but Ads.txt can also be a great tool to cut down on duplicate impressions.  A publisher has the right to sell its inventory any way it chooses, and different exchanges may have different strengths for different types of inventory,  so I do not predict (or advise) that advertisers will require pubs use only one exchange.  In the end though, I predict that header bidding as it is used today is on its way out.  The costs are too high for DSPs and advertisers will realize they are bidding on the same exact impression and ultimately paying a higher price.  I’ve never met an advertiser that liked that.

If there’s any overarching theme here, it’s the idea that marketers and advertisers are constantly getting more savvy about the tools they’re using, whether it’s AI, ad networks, or ad exchanges.  They will begin asking tough questions and demanding accountability in 2018 in new ways that will, as always, lead to big changes in the advertising ecosystem.

The post Opinion: Marketers Have to Start Thinking Seriously About Deep Learning appeared first on Mobile Marketing Watch.

The following is a guest contributed post from Tom Farrell, VP of Marketing at Swrve.

Sometimes you’d be forgiven for considering email as a thing of the past. We’ve all read the thought pieces, and those of us who find ourselves needing to deal with millennials on a consistent basis are well aware that messaging apps appear to be the new-normal when it comes to digital communications.

There’s only one problem with that thesis: the numbers don’t stack up. We’ve gotten so used to talking about the death of email that we haven’t noticed that open rates appear to be remarkably resilient. A smart email strategy starts with understanding why that is and works back from there.

First of all, it’s a general fallacy to assume that young people today will simply continue their habits into middle and old age. I call it the “death of jazz” effect. A music critic notes few young people at jazz concerts and fears jazz will die out with its audience, but misses the obvious point that people’s interests change as they get closer to their 40th birthday.

The same applies to email. In the business world, we understand that a single persistent store of communications, which supports longer and more thoughtful arguments, is actually useful. We apply that recognition to our leisure time, and learn to appreciate and use email in every sphere of our lives. But before we all get too complacent, that is NOT to say that nothing has changed and our expectations remain the same–quite the opposite.

How Mobile Changes Everything

While we still use and respond to email, we don’t do so very often from a the desktop computer. Close to 70 percent of our ‘digital minutes’ are spent on mobile, and that changes things – a lot.

I won’t dwell on the importance of ensuring your email communications are incredibly ‘responsive’ to mobile (i.e. they display okay on a phone) or ‘mobile-first’. Frankly, if a business hasn’t got that message by 2017, it’s already too far behind.

Instead, let’s stop for a moment and consider how mobile access changes the way we as consumers behave, and what we expect from brands and marketers. We carry our phones with us every hour of every day. We sleep with them beside us. We check them 100 times a day. That makes the mobile a powerful opportunity to marketers. But it comes with an accompanying risk: irritation.

In the mobile world, it is no longer good enough to ‘spam’ the user with largely irrelevant content. Not when so many people (quite reasonably) receive alerts for incoming mail on their device. At best, you are training your users to ignore your brand. At worst you are actively damaging the relationship you have. And the surest way to alienate users is to keep on emailing in the way we we did at the turn of the millennium.

Here are a few warning behaviors to check for. If you find yourself doing any of these on a regular basis, you may have paradigm problem:

• Sending a single email to more than 10,000 people at a time
• Trying to decide the right time to send an email by instinct
• Constructing elaborate ‘segments’ for email campaigns

At this point you might be scratching your head and wondering what is wrong with some of these practices. The answer: the mobile generation don’t respond well to the batched marketing model that was tolerated on desktop (where emails that aren’t relevant are easier to ignore).

So What Does Great Mobile Email Look Like?

It doesn’t look like just more of the same. Great email is no longer about ‘campaigns’ but is instead interactive, dynamic one-to-one communication – just as it is between human beings. Mobile leaders are already doing this today. Successful mobile email:

• Is personalized by in terms of personal detail and relevant content
• Is sent to an individual at the time that they are most likely to read and respond (based on data)
• Is usually triggered by a specific individual behavior (in any channel – not just web activity but also in the ‘real world’ and mobile apps) rather than the fact that the user has been put into a ‘bucket’ by marketers

In other words, email is no longer about large-scale marketing ‘campaigns’ and more about highly personal, relevant and helpful messages sent to individuals, rather than groups, and sent at a time that suits that individual. Taking this approach will deliver real benefits when it comes to making email effective and keeping it relevant to your business.

Unfortunately, traditional ways of thinking about marketing can keep you from connecting with your customers. Good communication requires rejecting that old model and embracing the mobile opportunity.

The post Op-Ed: Email In a Mobile Age appeared first on Mobile Marketing Watch.

The following is a guest contributed post from Jeremy Fain, CEO and founder of Cognitiv.

A lot of people have asked me about my thoughts for 2018, and what I think the overarching trends in advertising technology and deep learning will be in the coming year. Far be it from me to disappoint my fans – so here’s my take on next year’s biggest topics:

1. Marketers will have to start thinking seriously about deep learning.

AI has been a buzzword for the past several years, as clearly evidenced by the vast numbers of products claiming to be AI currently on the market. While most of these applications don’t really live up to the picture of AI that most people have in their heads of a Jetsons-like robot, there have lately been a series of discoveries, most notably in the field of deep learning, that are sure to have a serious impact on the way that most businesses operate.

Deep learning and neural networks are at the heart of some of the most astonishing machine learning developments, from image recognition to the natural language processing that enables gadgets like Amazon’s Alexa and Google Home to operate. But access to the technology and insights of deep learning is no longer limited to the big players, as new tools have arrived to bring the computing power and analytical insight of deep learning to marketers.

In some ways, the current wave of AI products is good, because it means that more people, including marketers, have become aware of what AI has the potential to do as well as its possible limitations. As more advanced forms of AI become market-ready, deep learning will be at the forefront of any of those conversations, and marketers will begin to understand the value of using deep learning to buy media and create audiences to advertise against, becoming better equipped to lead their businesses to success in 2018 and beyond.

2. Mobile ad networks will be forced to become more transparent.

Before programmatic became a mainstay of digital advertising, ad networks performed an important function as an intermediary between digital advertisers and publishers. They could help publishers find buyers for their inventory, and they could put inventory from multiple publishers together to make it easier for advertisers to buy. Because most inventory came from smaller publishers, it cost less, and was a cost-effective value proposition for most advertisers.

The rise of programmatic, however, created a way for advertisers to directly buy from any publisher with added transparency into pricing and websites.  Suddenly, ad networks had to deliver more value than just inventory aggregation.  This transition took place in the traditional digital display world years ago but has yet to take place in mobile advertising.  2018 will be the year where mobile ad networks will have to prove their added costs or face the reality that mobile advertisers have begun to use programmatic for user acquisition and retention campaigns.

3. Header bidding will become a problem on the agency side, so its use will diminish.

This relates in some ways to the general theme of greater transparency in the digital advertising markets. Header bidding code allows a publisher to offer the same impression in multiple exchanges at the same time, ultimately leading to the impression being sold for a higher price than if a single exchange was used. This means advertisers are bidding multiple times on the same inventory and, because of the nature of programmatic, they are likely paying more.  Originally, header bidding was meant to allow advertisers to compete programmatically for all of a publisher’s inventory, instead of just the unsold “dregs” that were left over after directly sold insertion orders had been fulfilled.  The technology, however, is now being used to offer the same impression through multiple exchanges to the same DSP.  This has driven DSP costs up because of the skyrocketing number of “duplicate” bid requests being received from multiple exchanges and has given rise to an entirely new ad tech industry of trying to sift through these duplicate impression requests.

A much more elegant, and likely solution in 2018, will be that advertisers through their agencies will require the use of the ads.txt standard.  This file is meant to be made available by every publisher wishing to sell their inventory programmatically.  It lists the exchanges their inventory is available in.  Ads.txt was created to stop a flagrant type of fraud where websites list themselves inaccurately as more valuable websites, but Ads.txt can also be a great tool to cut down on duplicate impressions.  A publisher has the right to sell its inventory any way it chooses, and different exchanges may have different strengths for different types of inventory,  so I do not predict (or advise) that advertisers will require pubs use only one exchange.  In the end though, I predict that header bidding as it is used today is on its way out.  The costs are too high for DSPs and advertisers will realize they are bidding on the same exact impression and ultimately paying a higher price.  I’ve never met an advertiser that liked that.

If there’s any overarching theme here, it’s the idea that marketers and advertisers are constantly getting more savvy about the tools they’re using, whether it’s AI, ad networks, or ad exchanges.  They will begin asking tough questions and demanding accountability in 2018 in new ways that will, as always, lead to big changes in the advertising ecosystem.

The post 2018 Will Be The Year of Deep Learning appeared first on Mobile Marketing Watch.

This year’s three-day event is happening January 26 through 28 at the Caribe Royale in Orlando, Florida, encompassing education, networking, and informational displays exclusively for the automotive, marine and aviation Mobile Reconditioning (Recon) Industry.

Originated by Kevin Halewood, publisher of Detailer’s Digest and Mobile Tech Digest, the Mobile Tech Expo now welcomes an international following of thousands, with more than 175 vendor exhibition booths. The International Paintless Dent Repair (PDR) Olympics Is a popular highlight.

This year’s keynote talk will be delivered by master level detailer and trainer Renny Doyle who restores and preserves multi-million-dollar automobiles and aircraft, including the original Air Force One jet.

Friday, January 26, 2018 is the Mobile Tech Expo Education Day, a day-long event filled with seminars and workshops, featuring a rich schedule of Digital Marketing seminars by Martin Brossman & Associates LLC trainers Martin Brossman, Paul Apollonia and Robin Werling.

The team will focus on maximizing the use of Social Media marketing, understanding online review platforms and creating affordable paid digital ads that get measurable results. They will also explain simple ways to sell items online to extend the mobile tech income stream. With over 12 years of experience in small business marketing, the digital marketing expert team brings real world knowledge for gaining more clients and increasing lines of income.

“We love this expo because it is big enough to present a large range of topics and vendors but small enough that participants truly get time to talk to people and network,” Martin Brossman said. “This year we are offering expanded social media and online marketing training, thanks to enthusiastic participation that packed the room at the 2017 Expo. Because keeping up with the latest online marketing trends is a key to success, we focus on results-driven content with strategies and tactics for different levels of marketing budgets.”

The post Mobile Tech Expo 2018 Brings Back Full Digital Marketing Education Track appeared first on Mobile Marketing Watch.

Billed as the performance marketing industry’s premier global gathering, the event attracts more than 6,000 attendees, exhibitors and thought leaders from over 70 countries. ­

If you’re not familiar, Affiliate Summit West brings together a wide range of stakeholders – including global brands, agencies, online publishers, networks, media companies, technology providers and more – to network and learn more about the trends and innovations currently shaping the performance marketing industry.

The event features three main trade show areas that will include 300+ exhibitors and sponsors, as well as engaging presentations and panels from over 100 speakers, covering the top challenges and opportunities for performance marketers, as well as the latest industry developments.

“Performance marketing is demonstrating its value for today’s brands with tangible ROAS,” said Santi Pierini, CAKE President and Chief Operating Officer of Accelerize. “As marketers scale their affiliate programs, they need proven solutions that will enable them to manage, measure and optimize campaigns across multiple channels and partners. This is what we are delivering with Journey by CAKE, and we look forward to sharing our vision for Marketing Intelligence with attendees at Affiliate Summit West.”

The post CAKE by Accelerize Named Sponsor at Affiliate Summit West Las Vegas Event appeared first on Mobile Marketing Watch.

While that news might make retailers giddy, security experts are reiterating their annual warnings that the convenience of online shopping comes with hazards. You could become the target of hackers out to steal your credit card or bank information, or “porch pirates” who prey on those packages left on your doorstep.

“Consumers need to take proper precautions if they don’t want their holiday merriment turning into holiday gloom,” says Gary Miliefsky, CEO of SnoopWall, a company that specializes in cyber security.

Changing all your passwords frequently is one way to protect what’s yours. Deleting smartphone or tablet apps you don’t use is another smart move, Miliefsky says, because many of those apps may be malware that spies on you.

Even porch pirates – generally seen as low-tech thieves who simply cruise neighborhoods looking for packages – can go high tech by infiltrating your smartphone where they can eavesdrop on your orders and deliveries.

“Both porch pirates and hackers count on people being lax with their defenses,” Miliefsky says. “But with a little preparation you can thwart their plans.”

He offers a few tips for doing just that:

• Shop online only from websites you trust. If you don’t know where the merchant is located, don’t shop online there. If they don’t have a corporate address or are located in another country, it could be iffy whether you ever see the goods you think you purchased. Also, if their shopping-cart experience is not an HTTPS browser session, then everything you type in – your name, address and credit-card information – is going over the Internet unencrypted, in plain view.
• Pay with credit cards rather than debit cards. If you experience identity theft, credit card laws allow you to keep all of your credit immediately, with no responsibility during an identity theft or fraud investigation. With a debit card, your bank’s policy can be to tie up your money in the amount of the fraudulent transactions for up to 30 days. Some have been known to take up to 60 days to resolve the issue.
• Get permission to ship all your packages to work. That way they aren’t left unguarded at your doorstep for hours where anyone walking by could snatch them. If this arrangement works out, be sure to tell all your friends and family also to ship packages to your work address.
• Ask a friend or neighbor to receive your packages for you. You might not be home on work days, but plenty of people are. Trusted friends who are retired or who work at home might be happy to let you have packages delivered to them for safe keeping.

“It’s wonderful that you can go online and track down those hard-to-find gifts that aren’t available in local shops,” Miliefsky says. “Just make sure you’re taking measures to help keep you and your personal information safe. The holidays will be a whole lot brighter if you do.”

The post How To Outwit Porch Pirates And Hackers During The Holiday Shopping Season appeared first on Mobile Marketing Watch.

The following is a guest contributed post by Blis President Harry Dewhirst.

Current AI systems use training algorithms and brute-force computational strength, as opposed to real intelligence. If an alteration is made to a situation involving AI, it will currently not adapt as it has no ‘understanding’ and therefore cannot recognize new strategic patterns. There’s no doubt that future technologies such as AI and the Internet of Things (IoT) will be put to work properly by marketers, but the questions remain as to when and what it will take.

The limitations of algorithms

Algorithms are limited in their learning to a set of defined tasks, so if a self-driving car approaches a zebra crossing with some pedestrians standing nearby, it will stop and wait for them to cross, even if they have no intention of crossing, and won’t respond to their uniquely human gestures.

The limit to machine learning is data; with new streams constantly feeding in from all directions, there is an opportunity to learn and discover, but also a major technical challenge.  As the volume of new devices like hearables and wearables feeding into the IoT rapidly expands, they provide a treasure trove of data which needs to be speedily and accurately analysed to allow the IoT to live up to its potential. However, the manipulation of Microsoft’s Tay chatbot, which learned to be racist and rude in less than a day, reflecting the information it was fed and the behavior that it mirrored, shows us the importance of being able to logically sift good and bad data inputs.

Extracting meaningful insights

Machine learning can help companies take the billions of data points they have from IoT devices and boil them down to what’s really meaningful, so that better decisions can be made. This is essential to find patterns, correlations and anomalies, since current human approaches of data analytics don’t scale to IoT volumes.

Although location data from connected TVs (CTVs) and other IoT devices that rarely move currently has limited value, smaller mobile devices provide one of the largest location data sets as they are incredibly dynamic by nature, with mobile apps in particular proving very useful input data tools, feeding CTV advertising optimization.

The importance of context

As advertisers build in-depth profiles of users based on data from IoT devices, the importance of context to advertising is increasing. There needs to be a good reason to reach a consumer in their home and, while artistry and storylines are important in engaging audiences, the context in which ads are delivered is today equally as important to engagement as the uniqueness of the ad storyline and copy itself. Based on data insights, personalized ads can now be delivered to the right person, at the right place and time to ensure the message engages and resonates, creating a return on investment. Intelligent analysis of location data is critical because the “where” can significantly influence the choice of campaign served to a particular user at a given time.

Although the volume of data and the challenges and insights presented by our increasingly digital, mobile-centric world have made the job of advertising to consumers more difficult and multi-layered in some ways, if the correct infrastructure is in place, it is extremely helpful. Depending on how these advances are implemented, ads will either cause concern as they become invasive and affect overall privacy or, if they work smoothly, consumers will come to expect them more and more as they seamlessly fit in their lives.

While machine learning is enhancing the capabilities of the industry, real AI is expected to bring further advances; precisely how it will achieve this is hard to predict, but it is likely to generate surprising insights into customers’ requirements.

The post The Future May Be AI Powered – But We’re Not There Yet appeared first on Mobile Marketing Watch.