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IoT and everyday life; how interconnected are we?

IoT and everyday life; how interconnected are we?

The Internet of Things (IoT) is a term spanning a variety of ‘smart’ applications. This ranges from things like smart fridges, to smart cities. This idea of ‘smart’ or IoT is the connectedness between everything and the internet. 

It’s hard to grasp the amount of data one person creates each day and understanding where IoT fits into that. And with this new era of ‘smart’ everything, the realm of knowledge is pushed even farther away. 

To understand just how much our smart technologies follow our everyday behaviours, let’s focus on only one person’s use of a smartwatch. 

But first, what are the implications of a smartwatch? This wearable technology gained its popularity starting in 2012, giving users the ability to track their health and set fitness goals at the tap of their wrist. Since then, smartwatches have infiltrated all sorts of markets, from the ability to pay using the watch, take phone calls, or update a Facebook status.

The technology in our lives has become so interconnected, de-identifying our data, while achievable, on a grand scale, is seemingly complicated. Take the smartwatch, our unique footprints, recreated each day are logged and monitored through the small screen on our wrist. While the data created is anonymized to an extent, it’s not sufficient

But why not? After all, technology has moved mountains in the last decade. To better understand this connectedness of our data, let’s follow one person’s day through the point of view of just their smartwatch. 

Imagine Tom is a 30-year-old man in excellent health who, like the rest of us, follows a pretty general routine during his workweek. Outside of the many technologies that collect Tom’s data, what might just his smartwatch collect? 

Let’s take a look. 

Every morning, Tom’s smartwatch alerts him at 7:30 am to wake up and start his day. After a few days of logging Tom’s breathing patterns and heart rate, and monitoring his previous alarm settings, Tom’s smartwatch has learned the average time Tom should be awake and alerts Tom to set a 7:30 alarm each night before bed. 

Before ever having to tell his watch which time he gets up in the morning, his watch already knows. 

Similar to his smartwatches alarm system, this watch knows and labels the locations of 6 specific places that Tom spends most time in the week. Tom didn’t have to tell his watch where he was and why; based on the hours of the day Tom spends at this location, with his sleeping patterns and other movements, his watch already knows. 

Not only are these places determined from his geographical location, but from the other information, his watch creates. 

When Tom is at the gym, his sped-up heart rate and lost calories are logged. When Tom goes to his local grocery store or coffee shop, Tom uses his smartwatch to pay. At his workplace, Tom’s watch records the amount of time spent at the location and is able to determine the two main places Tom spends his time is between his home location and his work. 

Based on a collection of spatial-temporal data, transactional data, health data and repeated behaviour, it is easy to create a very accurate picture of who Tom is.

Let’s keep in mind that this is all created without Tom having to explicitly tell his smartwatch where he is or what he is doing at each minute. Tom’s smartwatch operates on learned behaviours based on the unique pattern Tom creates each day.

This small peak into Tom’s life, according to his watch, isn’t even much of a “peak” at all. We could analyze the data retained by his smartwatch with each purchase, each movement of location or only by the data pertaining to his health. 

This technology is seen in our cars, fridges, phones and TVs. Thus, understanding how just one device collects and understands so much about your person is critical to how we interact with these technologies. What’s essential to understand next is how this data is dealt with, protected and shared. 

The more advanced our technology gets, the easier it is to connect a person based on the data the technology collects. It’s important more than ever to understand the impacts of our technology use, what of our data is being collected, and where it is going. 

At CryptoNumerics we have been developing a solution that can de-identify this data without destroying its analytical value. 

If your company has transactional and/or spatio-temporal data that needs to be privacy-protected, contact us to learn more about our solution.

The Three P’s of Retail Success

The Three P’s of Retail Success

Facebook privacy issues

As a retailer, you have a limited view of your customer based on what you gather from your POS data and social media because you don’t know how customers are spending their money outside of your store. All this can be solved if you acquire access to a very useful piece of data –financial data.

By combining financial data from millions of customers with your POS data, you can achieve a solid 360-degree view of your customer based on their preferences and habits, and grow your ROI by running more targeted marketing strategies. Additionally, you can also outperform your competition by spotting trends and offering better deals.

Adding Financial Data to the Mix: The Benefits

With access to customer’s financial data, not only will you be able to make more informed business decisions, but think of all the efficiencies you would gain from additional customer knowledge and optimized marketing expenditure.

Personalization

   

The amount of personalization possible with all this added financial data allows for stronger customer experience and retention. Talk about a mutual benefit!

There are two advantages when it comes to pairing financial data with POS data to boost personalization: increased customer intimacy and increased customer loyalty. With customer intimacy, we are talking about being able to better anticipate customer needs by analyzing buying patterns and understanding shopper behaviour. On the other hand, with customer loyalty, you can customize your offerings and deals according to a target group’s needs, or even an individual’s needs, to ensure the customers feel heard and important.

Thus, personalization is always adding value to both the customer and the company by boosting relevance and customer retention.

Promotion

   

With financial data in the mix, you are further able to maximize the quality of your marketing spend.

You could optimize your marketing expenditure by combining your sales data (for example, what was purchased at your store, when it was purchased and how much it was purchased for), and financial data (for example, how much was spent at your store versus a competitor’s). Seeing these customer preferences allows you to obtain valuable insights which will help you make smarter products, pricing, and promotional decisions.

Another important aspect of leveraging financial data is knowing what percentage of your customer’s wallet is going towards you as opposed to your competition. But wait, that’s not all! In terms of data insights, unlocking this greater potential will help your organization build more powerful models. Financial data will make it easier to forecast future sales and buying preferences.

Financial data can help to better direct your promotional efforts in terms of efficiency and information such as data insights, saving you both time and money.

Privacy

   

Using privacy-protected financial data that is secure and compliant with all legislative regulation helps you be worry-free and avoid any problems or PR nightmares.

Luckily, there are companies out there that combine security and privacy to form an optimal solution to comply with regulation, ensure privacy and IP protection as well as secure the best possible ROI for your company. Additionally, their privacy and security methods are intact throughout the data pipeline, from acquisition to publishing, using access controls and cryptography.

Combining financial data to your existing pool of information will help you (1) increase local demand, (2) optimize media spending and promotional activities, (3) focus on customer experience, and (4) compliment your privacy compliance. Modelling all these functions will help you forecast future sales and growth as well, thus increasing performance.

Still not convinced? Let’s check out a large corporation that stands by this…

See How Walmart is Implementing this Solution

“Walmart uses big data to make the company’s operations more efficient and improve the lives of customers”.

To power its goal to provide the best shopping experience possible, Walmart is maximizing its use of big data to reveal consumer patterns. Transactional, online, and mobile data, all combine to help them serve the customer better so that they keep coming back.

They use data mining to extrapolate trends from their POS data, to see what the customer buys, when they buy it, how they buy it (online or in-store), and what they buy before or after a certain product. POS data allows the organization to see shopping patterns to determine how to display merchandise and stock shelves. Furthermore, they can send out personalized rollback deals and vouchers based on consumer spending habits. Not only do they use this data to create customer value, they also use it for staffing purposes. For example, to help lower the amount of time it takes to fill a prescription, Walmart looks at how many prescriptions are filled each day to determine staff scheduling and inventory.

Additionally, Walmart has created its own credit card, which gives them firsthand knowledge of their customers. Using the expenses from the financial data of customers helps them gain a solidified understanding of consumer habits and preferences. This enables the company to anticipate demand for each product or service.

The outcome of using this big data includes improving store checkout procedures, managing its supply chain, and optimizing product assortment.

To Sum it Up

Without data, companies are not able to grow and digitally enhance their business model according to the needs of their target market. So, being able to leverage data to its full ability is a competitive advantage on its own, especially with data being such a huge commodity today. Unlock greater potential with respect to increasing your customer value by expanding your access to the data available around you.

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