With so much data being constantly collected, it’s easy to get lost in how all of it is applied in our real lives. Let’s take a quick look at a few examples starting with one that most of us encounter daily.

Online Forms
One of the most common and fairly simple to understand instances we come across on a daily basis is completing online forms. When we complete an online form, our contact record data points, like; name, email, phone and address, are being individually verified and corrected in real time to ensure each piece of data is genuine, accurate and up to date. Not only does this verification process help mitigate fraud for the companies but it also ensures that the submitted data is correct. The confidence in data accuracy allows for streamlined online purchases and efficient deliveries to us, the customers. Having our accurate information in the company’s data base also helps streamline customer service should there be a discrepancy with the purchase or we have follow up questions about the product. The company can easily pull up our information with any of the data points initially provided (name, email, phone, address and more) to start resolving the issue faster than ever (at least where companies are dedicated to good customer service).

For the most part we are all familiar with business scenarios like the one described above. Let’s shift to India & New Orleans for a couple new examples of how cities are applying data to improve the day-to-day lives of citizens.

Addressing the Unaddressed in India
According to the U.S. Census Bureau, India is the second most populated country in the world with 1,281,935,911 people. With such a large population there is a shortage of affordable housing in many developed cities, leading to about 37 million households residing in unofficial housing areas referred to as slums. Being “unofficial” housing areas means they are not mapped nor addressed leaving residents with very little in terms of identification. However, the Community Foundation of Ireland (a Dublin based non-profit organization) and the Hope Foundation recently began working together to provide each home for Kolkata’s Chetla slum their very first form of address consisting of a nine-digit unique ID. Beside overcoming obvious challenges like giving someone directions to their home and being able to finally receive mail, the implementation of addresses has given residents the ability to open bank accounts and access social benefits. Having addresses has also helped officials identify the needs in a slum, including healthcare and education.

Smoke Detectors in New Orleans
A recent article, The Rise of the Smart City, from The Wall Street Journal highlights how cities closer to home have started using data to bring about city wide enhancements. New Orleans, in particular, is ensuring that high risk properties are provided smoke detectors. Although the fire department has been distributing smoke detectors for years, residents were required to request them. To change this, the city’s Office of Performance and Accountability, used Census Bureau surveys and other data along with advanced machine-learning techniques to create a map for the fire department that better targets areas more susceptible to deaths caused by fire. With the application of big data, more homes are being supplied with smoke detectors increasing safety for entire neighbors and the city as a whole.

FIRE RISK | By combining census with additional data points, New Orleans mapped the combined risk of missing smoke alarms and fire deaths, helping officials target distribution of smoke detectors. PHOTO: CITY OF NEW ORLEANS/OPA

While these are merely a few examples of how data is applied to our day to day lives around the world, I hope they helped make “Big Data” a bit more relatable. Let us know if we can answer any questions about how data solutions can be applied to help your company as well.

The US Census Bureau uses the term “place” to refer to an area associated with a concentrated population, such as a municipality, city, town, village or community. These statistical areas have a defined boundary and they may or may not have a legal administration of power that performs some level of government function. The US Census Bureau uses class (CLASSFP) codes to classify different types of places and areas. The Bureau currently lists 70 different CLASSFP codes; however, all places are either a legally incorporated place or a Census Designated Place (CDP).

Incorporated Place

The US Census Bureau defines an incorporated place as a geographic area with legally defined municipal boundaries under the laws of the state in which it is located. Incorporated places are established to provide governmental functions for a population, typically with elected officials and the means to provide local municipal services such as water, sanitation, schools and police departments.  Each state has its own requirements for incorporation that typically include population and land area thresholds. 

Census Designated Place (CDP)

A Census Designated Place (CDP) is the statistical counterpart of an incorporated place. In general, CDPs are not legally incorporated under the laws of the state in which they are located, nor do they have elected officials to serve governmental functions.  Municipal services for CDPs are normally provided by either the county, a minor civil division (MCD), or by a nearby incorporated place.  A CDP is also commonly known or referred to as an unincorporated place.

Identifying Incorporated and Unincorporated Places when Geocoding Addresses

The DOTS Address Geocode US service makes use of various datasets from the US Census Bureau. This data is compiled and organized into detailed street level data and place wide boundary data. The street level data allows the geocoding service to know which side of the street the address is on. This lets the service know which block the address is on and it is helpful in some edge case scenarios where an address may fall on the edge of a boundary.

The street level data lets us do many things but it’s not always complete and it doesn’t always give us the whole picture. In some cases, there are addresses that reside in the outskirts of an area, outside of the incorporated boundaries. These locations are in the unincorporated areas of a minor civil division (MCD) or county. Detailed data for these unincorporated areas is often lacking, usually due to a combination of low population density and large land areas.

After the coordinates for an address have been determined, the service can then use them to determine if they fall in an incorporated place, unincorporated place, or outside of any place boundary and in an unincorporated area. This not only works for addresses in the outskirts of an area but for other situations as well.

Sometimes there are small pocket communities that appear to be within a larger city area but they are not actually a part of it.

The US Census Bureau says that the boundaries of a place should be considered organic, as they can shrink and grow. In some cases, the boundaries of a place will not cleanly stop on the edge of a street or block. Sometimes the boundary will dissect part of a road or block partway, dividing neighboring structures.

Overall, there are many challenging scenarios that can arise when it comes to geocoding an address and determining if it is unincorporated or not. However, using the right data with the right tools and expertise means that we can overcome these challenges to provide accurate and reliable results to our clients.

Few industries or investments grow at a year-over-year rate exceeding ten percent nowadays. But one area that – unfortunately – has had bright growth prospects is retail fraud. Which means that one of the most important things you can do to protect your bottom line is to take reasonable precautions to prevent it.

According to the 2016 LexisNexis® The True Cost of FraudSM Study, the total cost of fraud as a percentage of revenues has risen over 11% in the past year, from 1.32% to 1.47%. This breaks down to record numbers of average monthly fraud attempts and successes (442 and 206, respectively, across the merchants they surveyed), as well as a substantial jump in the average monthly value of these successful fraud transactions ($146 versus $113 in 2015). All told, merchants lose an average of $2.40 per dollar of fraud losses as a result of chargebacks, fees, and merchandise replacement. It is truly a “growth industry.”

A big part of the problem is tied in with the growth of mCommerce, or commerce transacted through mobile devices, along with the broader area of card-not-present (CNP) transactions. In the former case, the percentage of successful fraud transactions taking place over mobile channels has grown year-over-year from 26% to 35% for larger merchants according to Lexis-Nexis. New technology is often a weak link for fraudsters to exploit, and in this case, the massive growth of mobile channel adoption, in general, has often run ahead of a concomitant investment in fraud prevention strategies.

Technology itself can also be part of the problem – for example, iPhone mCommerce apps are not allowed to collect a device’s Universally Unique Identifiers (UUIDs) to track which actual device is being used. In general, newer channels tend to have less infrastructure and fewer processes developed to combat fraud, and people take advantage of this gap.

So what can you do to prevent being a victim of retail fraud yourself? Here are three best practices:

• Have a policy. Paying no attention to fraud makes you vulnerable as a retailer – and at the same time, over-reacting to individual fraud incidents can make it difficult for legitimate purchasers to complete transactions with you. Planning ahead with reasonable guidelines is the best strategy.
• Validate and geolocate mobile device data. According to a recent white paper report on preventing mCommerce fraud, checking the phone number against your customer records and checking the GPS location of the transaction can help filter out questionable transactions . When a number doesn’t match, or a transaction is taking place from an unfamiliar location – such as in developing countries – you can flag these transactions for rejection or further verification.
• Employ lead or order verification. No matter what sales channels you are using, real-time online services exist nowadays that can use multiple factors to assess order quality, while preserving customer experience.

Given the potential cost of fraud to your profit margin, it is generally a wise move to invest in a fraud prevention strategy. No one can eliminate retail fraud completely, but particularly as technology continues to grow, you can take steps to stay one step ahead of most of the bad guys. With the right strategy, both you and your customers can breathe easier as you grow your retail efforts across multiple channels.

Gaining Insight on Customers and Prospects

No question: customers are the backbone of your business and in order to make a connection, and ultimately generate sales, you need to maintain good insight into not only who and where they are, but what they are interested in. Making that connection between a customer’s needs and your product is one of the key components in driving your company to success!

Thus, by gaining insight into your customer’s geographic and demographic details, you will be in a better position to geo-target your marketing and understand the socio-economic levels of your customers. Ultimately these insights will help you to craft more accurate and targeted messages and products to drive sales.

Unlocking Customer Value

With data being the foundation of your marketing campaigns, it’s imperative that you get a handle on the information within your contact records before your marketing efforts, budgets, and customer satisfaction is affected.

So what can happen when customer insight is not on point? Let’s look at a specific scenario:

During a recession year, your company has made the decision to capitalize on existing customers, versus putting exhaustive efforts into acquiring new accounts. Your goal is to increase profitability and customer retention by 80% in the next year.

In order to carry this out effectively, you need to better understand not only who your customers are but where they live and what specific interests are driving them to market, or better yet, to your product/services.

After extensive research, your team realizes that there are many missing data points within your customer contact records, precluding you from creating a better customer value management solution. Without solid customer insight, you are not able to understand, target, reach, and interact with their customers in the most effective way possible. 

To avoid this type of scenario in your organization, you need to have a solution that enables you to tap into the hidden insights that are waiting to be discovered within your contact records. After all, the better you can communicate with your prospects and customers, the more likely the chance that you will increase new sales opportunities and upsell your products and solutions to existing customers.

Service Objects proprietary algorithms enable you to append over 130 data points to a contact record, such as household income, age distribution, ethnic distribution, education and much more, enabling you to make more informed business decisions, and clearly determine new revenue opportunities and gain a competitive advantage.

You found a Magikarp in your neighbor’s swimming pool or met a few new friends collecting Pokémon characters at the local duck pond. It’s all good fun until…

…Until you realize that your location, your social networks, and your data are being tracked. Early reports that Niantic, the parent company of Pokémon Go, may be collecting a wealth of personal information caused an immediate uproar among data privacy advocates and concerned players. Turns out, the Apple App Store version of Pokémon Go initially had full access to users’ Google accounts. This included access to your Google Drive documents and read and write access to your Gmail.

Fortunately, Niantic was quick to respond, and the problem has already been resolved. That said, the game may still be able to collect the following information:

• Your email address
• Your user name
• Your location(s)
• Your IP address
• Your date of birth
• Recent webpage visits

While you may not object to Niantic knowing your email address or location, what happens if hackers hack into Niantic’s servers? With millions of reported users within just a week of its release, you can bet that hackers are checking out Niantic. How will they use your personal data?

Here’s something else to be alarmed about: location, location, location. The app knows exactly where you are. Granted, that’s part of its charm, but we urge caution.

Remember that Magikarp in your neighbor’s swimming pool? How did the app know to put a fish-like character right there? It’s not magic; it’s geocoding. The app integrates with existing maps and global location databases, making it able to distinguish items like private swimming pools, fountains, parks, and churches — all at the local level.

For example, fountains are commonly designated as Pokéstops, a place where you can get fresh virtual supplies. Public places like churches, parks, and football fields are often designated as “training gyms” where players gather to train and become “King” of the gym.

Here at Service Objects, we hate to be Pokémon party poopers, especially because we love geocoding, and Pikachu is adorable. The app’s geocoding element is quite simply brilliant. Like our own address validation API, Pokémon Go uses detailed maps and address databases to accurately understand a given geographic location and its features. In our case, our USPS CASS certified address validation service compares geographic information against the address data contained within USPS and other address databases. This allows us to confirm, standardize, append, and correct address data, as well as return specific geocodes to pinpoint the location on a map. In theory, if we wanted to superimpose a cute animated character over a specific address based on location data, we could do that. The technology is virtually the same.

In Pokémon Go’s case, the developers are using an existing Ingress global intel map and database compiled by Ingress players around the world. Players of this earlier Niantic location-based game had contributed to this massive database, uploading geocodes, descriptions, and photos over time. One of the major tasks in Ingress involves capturing portals at public places which is why Pokémon Go has a wealth of existing geolocations marked such as playgrounds, fountains, public art, landmarks, and monuments. Niantic was formerly part of Google, and may have also tapped into the Google Maps API (as many app developers do).

Why should you be concerned about geocoding in a game? At some point, advertisers may be interested in your whereabouts, but here’s another thought: While it’s fun to find a fish in a swimming pool and interact with other players at a public site like a church for “training” in a Pokémon gym, you may wonder who else is playing the game?

The fact that neighborhood playgrounds are designated gathering places for players is yet another cause for alarm — especially given the fact that children, adults, and hackers alike are all attracted to the game. And criminals are already using Pokémon Go to their advantage. For example, according to the St. Louis Dispatch, armed robbers staked out known gathering spots for Pokémon Go players and then robbed them in over the weekend.

Even without the criminal element, Pokémon Go’s surging popularity coupled with its incredibly granular, block-by-block map data may soon make it one of the most, if not the most, detailed location-based social graphs ever compiled. If you’re going to play, go in with your eyes wide open.

One benefit or problem, depending on your inclinations, of being in the marketing business is that you become acutely aware of the marketing that goes on around you. In many ways, that awareness is a great thing. Every day you can see great, and not so great, marketing ideas, concepts, and implementations. We learn from what others do. Now that marketing has become such a data-driven endeavor, the combination of ideas and data are the key to marketing and business success, and especially in political advertising.

The pundits are predicting that in the time between now and November, the spending on political advertising will set new records. Some estimates reach as high as $6.5 Billion across TV, print, and digital media. The people who implement political advertising are becoming more sophisticated in the ability to target potential voters due to the tools and techniques that the rest of us marketers use every day.

Here’s where the problems start. Many people and organizations rely solely on email addresses for their marketing. Yet political processes such as elections are largely local processes that rely on real people having real addresses. A great way to waste money is to throw advertising spend at the wrong people. Wasted spend would be so easy to do in this case.

The connection to data quality starts to emerge. One factor in defining the quality is the completeness of the data. Whether data is correct or not is easy to understand. Completeness is a little harder to grasp. In an election scenario, an email address alone certainly may not be of much benefit. Knowing a street address and having some certainty that the address is correct moves us in the right direction. Appending the demographics of the location to the record speeds up the move to valuable data. Being able to attach a score to measure the quality of a lead helps. Yes, for marketing purposes, a potential voter is a lead.

Those of us not in the election business can learn a few things from those that are. The marketing has to be done now. The election date isn’t moving. Getting things right the first time becomes more critical. Time for lots of A/B testing simply doesn’t exist. We can have great creative, but the effectiveness of our work diminishes quickly with poor lists. The need for data quality becomes more apparent due to the compressed timeframe.

If you are in marketing, keep your eyes and ears open in the next few months. What we hear and see from the political process is going to be interesting. The more that data quality plays a part, the more effective all that spend will be.

What an email may say about your potential customers

Today’s marketer knows that the keys to increased conversion and awareness is understanding your target audience and creating a relevant and personalized experience for your customers and potential customers.

The use of real-time data is becoming more and more commonplace as marketers strive to customize their message for potential buyers. Consequently, accurate and attributable data has become that much more important. Recent studies have shown that email is the popular choice of communication among consumers with the most spending power.

Service Objects DOTS Email Insight can link an email address to compelling demographic and geographic information. By using just the email address marketers can now append information such as age, gender, income, location, education-level, home market value and more.

With DOTS Email Insight companies can analyze their email addresses to understand who is purchasing their product or service. With the data they can determine types of consumers who are buying their products and refine their strategies according to marketplace demands. They can also estimate a potential customer’s location and income-level to create a clear and comprehensive picture of them. With this service marketers can better understand their prospects; and tailor a unique message just for them. Finally, marketers can identify concentrations of potential customers to find untapped opportunities for growth.

Here is how it works: We aggregate email data across multiple sources and make it available through our application programming interface (API). DOTS Email Insight is a database of over 310 million email addresses linked to ZIP+4, Census data, compiled household files and other private sources of consumer information.

DOTS Email Insight is based on the principle that “birds of a feather flock together.” It’s a phenomenon that people with similar cultural backgrounds, needs, and perspectives naturally gravitate toward one another. They choose to live in areas offering affordable advantages and compatible lifestyles. That’s why, for instance, many young career singles choose lively urban neighborhoods, and while young families with children prefer the suburbs.

Here is a typical example: Service Objects recently appended demographics and location data to 100,000 email addresses for small California retail chain. The email addresses were culled from the stores’ internal email marketing list. The goal of the project was get more insight into the type of person who shops at their stores; including their gender, age, ZIP code, and household income.

Here’s what we found:

Let us give you more insight on your email data. For starters, send us a list of 500 addresses and we’ll send you back the results for free. Click here to register and submit your list.

The development team here at Service Objects is always hard at work supporting, enhancing, and building new Web services. For this blog, I wanted to take a few minutes to talk to you about two new and enhanced Web services, that we will be releasing in the near future!

DOTS GeoPhone Plus is a new composite service that builds on upon a few of our current Web services, DOTS Phone Exchange, DOTS GeoPhone, and DOTS GeoPhone Wireless.DOTS GeoPhone Plus rolls all of these services into a one-stop shop for telephone number information and validation.

In the past, clients may have purchased up to all three of the previous telephone Web services in order to efficiently access the full range of telephone number information and contact data.Now, clients can access all of same the data with just one transaction of DOTS GeoPhone Plus.

Another new service we are rolling out is DOTS Demographics Plus.In addition to the normal zip code level information returned by the older service, DOTS Demographics, new low level information is also returned.Instead of a zip code, an address is now used as the Web service input. The returned output fields provide resolution down to the block level (about 50 people).Data available at this level includes age, income, and race distributions.

These new services will be available soon and we have many new interesting Web services in the works as well.

Stay tuned!

Jonas S.