Author Archive

Why You Need to Establish Your Company Core Values List

When working with companies on developing customer-focused growth cultures, I often get asked about this idea of a company core values list. It seems that every company has a core values list, but oftentimes the words used are similar — and they can be words that mean many different things to different people. Does a company core values list even matter, then? Will it drive your growth in some way?

Absolutely it matters — and yes, it drives growth.

Why Does a Company Core Values List Matter?

When I wrote I Love You More Than My Dog, this idea was often top of mind for me: if you look at the ‘beloved’ companies mentioned in the book, the one major aspect they all have in common is that they operate from a different, elevated place. They’re guided by their core values; their company core values list is a living, breathing document and not just a one-off that HR eventually owns. That, I think, is the key difference between a great company that’s able to focus entirely on customer experience — and a so-so company that struggles often to focus on its customers.

Think of the living, breathing document idea this way: you can list your company core values all you want, and maybe a few scattered people in your organization will believe them at face value all the time. But what really needs to happen beyond the creation of the document is the leaders of the organization living out the document.

Every employee needs to see leaders living out the company core values list, because that in turn gives the employees permission to ‘model’ that behavior. For better or worse, people are always going to model the behavior of leadership in a company — so you need to make sure your company is in the ‘better’ column and not the ‘worse’ one.

The First Tier of a Company Core Values List

Let’s say a company lists one of its core values as “operate with trust.” (This is just an example, not any specific company.) If that’s a listed core value, but then employees regularly see back-stabbing and in-fighting among the leadership, the core value has absolutely no meaning anymore. But if those same employees see collaboration and silo-crossing among the leadership, they’ll start to think “Operate with trust does seem important, and it’s the way we do things here.” Now the core value means something.

That’s the first tier of a company core values list — making sure the core values (a) mean something and (b) are lived every day by the leadership, and thus modeled by the rest of the organization. If you get to this stage, you’re doing a good job — and you will be well-positioned to build a customer-focused growth engine.

The Advanced Stage of a Company Core Values List

The more ‘advanced’ stage of having a company core values list is having that set of core values guide everything you do, including:

  • Recruiting
  • Hiring
  • Day-to-day behavior
  • Promotion strategies

The Container Store is a good example there: they hire less than 3% of applicants, but have a turnover rate of less than 10%. Many executives would love those numbers: you’re getting the best of the best applicant-wise and not losing them (thus keeping organizational knowledge in-house and potentially away from competitors). How does The Container Store achieve something like that? There are different approaches and considerations they take to hiring, yes — they believe 3 ‘good’ employees equal 1 ‘great’ one, for example — but the central idea is that they live their core values. There’s alignment between purpose, ideology, action, and behavior from the leadership on down. Even if your salary isn’t astronomical, most people don’t leave a place like that.

If you’re in the startup or entrepreneur phase of developing a company, there are a million and five things to do — from incorporation to processes and systems to legal needs and staffing. It can be overwhelming, and oftentimes a company core values list is one of the last things you’ll consider in a crush of day-to-day tasks. It honestly might be the most important if you want to become a company beloved by your customers, though.

Reprinted from LinkedIn with permission from the author. View original post here.

 

Editor’s Note: Service Objects believes strongly in awarding our employees who stand out amongst their peers because of their consistent support of our corporate core values. Employees that meet and exceed expectations while they complete their daily tasks, going above and beyond with regard to the quality of their work are voted for the quarterly “Core Values Award” by their peers. The award is designed to celebrate the embodiment of each of Service Objects Four Core Values: Customer Service Above All, a Happy and Healthy Workplace, Corporate Conservation, and Network Excellence.

Author’s Bio: Jeanne Bliss, Founder & CEO, CustomerBliss

Jeanne Bliss pioneered the role of the Chief Customer Officer, holding the first-ever CCO role at Lands’ End, Microsoft, Coldwell Banker and Allstate Corporations. Reporting to each company’s CEO, she moved the customer to the strategic agenda, redirecting priorities to create transformational changes to each brands’ customer experience. Her latest book, “Chief Customer Officer 2.0” (Wiley) was published on June 15, 2015.

In Customer Service Chat, You Have to do More Than Answer

Customer service chat is popular with companies and customers alike. It’s easy, it’s quick, and it works well on mobile devices. But easy and popular doesn’t always equal good. Read this chat with customer service agent “Jack” at Vizio. It is a set of customer service blunders, large and small.

Here’s the chat transcript

Visitor: Hi I just bought a 50″ M501d-A2R tv. i am trying to set it up. I can’t put in the password to my wifi because my password is longer than the number of characters allowed. I don’t want to reset my password on my Cisco cable router. Can you help?

Jack: Here at VIZIO we pride ourselves in providing best in class U.S. based support. I’m happy to assist you today. How many digits is your wireless password?

Visitor: 26 digits

Jack: The TV will support up to 22 digits. Unfortunately the password would need to be shortened to work with our TVs.

Visitor: Hmm i am not glad to hear that

Jack: I apologize for the inconvenience.

Visitor: Ok. Please email me a transcript of this chat. Thank you.

Jack: You’re welcome! You will receive a copy of this chat transcript as soon as the chat window has closed. Thank you for chatting with VIZIO today. If you have any questions feel free to contact our support team at 1-877-878-4946, online at chat.vizio.com, or email us at techsupp@vizio.com! We would also like you to join VIZIO Fandemonium today to earn points and win prizes only at VIZIOfanzone.com Thanks again, and have a great day.

Here’s how this chat needs to be improved:

Stop the chest-thumping about being US-based. This should NOT be the first thing Jack says to the customer. In fact, Jack shouldn’t say this at all. It doesn’t matter whether Vizio’s support is based in the US. The customer wants a high-quality chat. He wants a quick, correct, complete answer. Jack’s first statement really causes problems because the support he provides isn’t worth the company’s pride and it isn’t best-in-class. The cultural elitism of this statement is really unattractive, especially given the poor quality of the chat.

Use the customer’s name. The impersonal use of “Visitor” rather than the customer’s name clashes with the parts of the chat that are quite good. Some of Jack’s replies are specific and personal. For example, when he asks, “How many digits is your wireless password?”, it is clear he’s read what Visitor has written. The chat system should be configured to use the customer’s name. Why would any customer service organization want to refer to a customer by an anonymous term?

Be sincere. I was really sad when Jack laid down the classic customer service trope: “I apologize for the inconvenience.” In this case, this statement is insincere and unnecessary. There’s no need for an apology because neither Jack nor Vizio has done anything wrong. And it’s a true service failure to simply apologize when the customer needs help solving the problem.

Help the customer. Don’t merely answer the customer’s question. Visitor got an answer to his question about the length of his password. His is four digits too long. But Jack never helped him. Even if Jack can’t actually help Visitor reset the password on the Cisco router, he should have written something like, “Refer to the user guide that came with your Cisco router to find instructions on how to reset and shorten your password…”

Omit the marketing. Vizio clearly thinks, “We’ve got Visitor’s attention, so let’s pitch him Fandemonium.” But this pitch doesn’t belong in this chat, especially given the poor service Vizio has provided. And it’s not good marketing copy, either. Points? For what? Prizes? What kind? What’s In It For Me?

Reprinted from LinkedIn with permission from the author. View original post here.

 

Editor’s Note: Service Objects prides itself on customer service and tech support for effective resolutions to all questions, issues and inquiries. We’re always striving to improve our customer support, and have found chat to be an integral part of our everyday communication with those who visit our site seeking answers to their data validation problems.

Author’s Bio: Leslie O’Flahavan, Principal, E-WRITE

As E-WRITE owner since 1996, Leslie has been writing content and teaching customized writing courses for Fortune 500 companies, government agencies, and non-profit organizations. Leslie is a frequent and sought-after conference presenter, a faculty member at DigitalGov University, and the co-author of Clear, Correct, Concise E-Mail: A Writing Workbook for Customer Service Agents. Leslie can help the most stubborn, inexperienced, or word-phobic employees at your organization improve their writing skills.

 

Service as a Differentiator

Service quality is one of the most misused concepts in business. You can’t see it or smell it. It is hard to quantify except in hindsight, even though there are real live academic journals about it. If you look at company websites, they will all tell you that theirs is great, of course – often replete with pictures of smiling attractive people with headsets. But in real life, it is often one of the greatest differentiators between companies.

Here is a personal example. Once I purchased a laptop computer, in part because its manufacturer touted its service and replacement policies. This was important to me, given my frequent travel. But in reality, any service issues I had were met by indifference, bad answers, and “Sorry, the part’s out of stock. Dunno when it will be in.”

So in one of the great ironies of my career, I later visited a consulting client on the West Coast – an organization with an excellent service reputation – and discovered that they shared a parking lot with this laptop maker. And one morning I made it a point to come in early and watch everyone come in to work. My client’s employees were engaged and chipper, while the other company’s employees trudged in with their heads down like they were marching off to jail.

Now, back to my original point about service quality. This laptop maker had the same support automation tools as most people. They clearly had CRM systems and interactive voice response queues. And their support policies, at least on paper, were a cut above their competitors. But they couldn’t deliver what they promised. Clearly, at this company, support was a cost to be reduced as much as possible. And soon after they reduced their costs to zero, because they lost market share and exited the market.

So what really creates good service quality? A marriage of the right policies AND the right systems. When I managed a 24/7 tech support center, here were some of the factors that led us to have both near-perfect customer satisfaction scores and near-zero turnover:

  • Our team constantly educated itself. We devoted an average of over three weeks per year to product and skills training, versus an industry average of less than one week.
  • We constantly benchmarked customer experience. From the way people were greeted to the oversight we gave to inbound cases, we were constantly aware and constantly improving.
  • We measured quality first and productivity second. Did you know that service metrics often kill service quality? When an agent is measured for how quickly they resolve call, they will be quick, by golly – even if you get sent packing with bad answers. Our agents were rewarded for keeping customers happy and working as a team, and only coached for performance when it varied far from the norm.
  • We had service standards that met the needs of our customer base. From personal assigned support representatives to 24/7 access, we delivered what a high-end audience in a mission-critical environment needed.
  • We realized that service was delivered by human beings. Which meant that we went out of our way to keep employees happy, whether it was plenty of individual recognition and professional development, or a team hiring strategy that let people have a say in who joined “the club,” or annual best practices workshops where team input led to real policy change.

All of these mechanics – most of which never show up on a company’s website – are why service leaders like Disney, Southwest Airlines or my former employer deliver a very different service experience from their competitors. Making it happen requires planning, execution, and a mindset that steers people away from whatever is cheapest or most expedient in the moment. Above all, it is one of the most powerful and cost-effective business strategies an organization can adopt.

 

Editor’s Note: Service Objects was founded around many of this author’s service principles. From the expertise of our staff, to our fanaticism to 99.995% uptime, to our 24/7 customer service, we invest in strategies that lead to a tangible difference in customer experience.

Author’s Bio: Rich Gallagher is a former customer support executive and practicing psychotherapist who heads Point of Contact Group, a training and development firm based in Ithaca, NY. He is the author of nine books including two #1 customer service bestsellers, What to Say to a Porcupine and The Customer Service Survival Kit. Visit him at www.pointofcontactgroup.com.

The Inevitable Switch to IPv6 or: How I Learned to Procrastinate, Because if the World Ends Tomorrow I Won’t Have to Do It

Despite being created as a replacement for IPv4 back in December of 1995, an official world launch of IPv6 did not come about until June 6th, 2012. Maybe somewhere in the back of our minds we really did think that 2012 would be the year the world ended, so everyone just decided to procrastinate? Whatever the reason for the delay, IPv6 appears to be slowly but surely picking up steam.

Roughly 10% of all users who access Google are doing so over IPv6

Check out Google’s adoption statistics page to see how IPv6 adoption has grown over time. There is also a map of IPv6 adoption per country. While overall IPv6 adoption may only be at 10%, countries such as the United States, Portugal, and Greece are ahead of the curve with a little over 20% adoption. Belgium, however, is leading the way with approximately 40% IPv6 adoption. According to an article by Iljitsch van Beijnum at ArsTechnica, if the current adoption trend continues then we should see 100% worldwide adoption by the summer of 2020, which at the time of this writing is only 4 years away. If you are interested in learning more about IPv6 and IPv4, then I highly recommend reading the article.

Slow business adoption and security concerns

If we take a closer look at Google’s IPv6 adoption graph we see a distinct trend where IPv6 usage spikes on the weekends. This would suggest that more people are using IPv6 at home than they are at work. Many of the world’s major Internet Service Providers (ISPs) pledged to start switching to IPv6 back in 2012, and so far it appears that they have for the most part stayed committed to their promise. Most businesses, on the other hand, made no such promises, and for good reason.

IPv6 is not backwards compatible, so you can only communicate with other IPv6 adopters on a 100% IPv6 network connection. If any part of the connection between the source and the destination does not support IPv6 then it will fail, in which case a failover connection via IPv4 should be made. So immediately we see two reasons for why businesses may not be jumping on to IPv6:

1) The IPv6 infrastructure and user base is still in its infancy.
2) IPv6 adopters will also support IPv4, so why bother setting up IPv6 on your end if you can still use IPv4?

How we currently combat spam and malicious activity

There is also a myriad of concerns associated with switching to IPv6, but let’s look past the initial concerns of migration cost and complexity. Let’s say that we have already made the migration and opened the doors to IPv6 traffic.

We are now in the growing pains stage. The internet can be a scary place, filled with malicious bots and users. Have you ever seen a Distributed Denial of Service (DDoS) attack? The visualization can be quite memorizing (not a DDoS attack visualization, still cool nonetheless), but the reality can be very damaging. How do you feel about spam, of the email variety and not the canned food? If you are like most people then you probably hate spam, and if you are responsible for managing a mail server or firewall then you probably REALLY hate it.

To admins and hackers alike, IPv6 is just another vulnerability waiting to be exploited. So why take the chance? Not everyone is so worried, though.
Currently, our popular choices for fighting spam and other malicious activity is to use statistical and reputation based methods as well as blacklists. These methods are IP version agnostic and they can be used by businesses that have adopted IPv6. However, new and existing business who try to switch to IPv6 may find that they have been locked out of some standard and crucial features that they depend on, such as SMTP, FTP and/or UDP. IPv6 was built from the ground up to be inherently more secure than IPv4, but some ISPs are blocking critical features for everyone rather than risk letting a single malicious user run amok.

Switching entirely to IPv6 is not worth the extra work

Even with IPv6 and its almost limitless number IP addresses, ISP will group many users together under the same small address space instead of segregate them into their own small pool. Some ISPs have learned the hard way for why this was not a good idea as the whole address block will get blacklisted. ISPs now know that grouping IP addresses together under the same small blocks is dangerous, but instead of changing their deployment model many have opted to simply just lock it all down until more businesses complain or a better solution arises. Since IPv6 is still relatively new, ISPs and businesses haven’t quite figured out all of the best practices yet. The overall community consensus, for now, appears to be that IPv6 is just not worth the extra effort.

Eventually, the IPv4 address market space will saturate

There is almost little to no incentive for businesses to switch to IPv6 until the IPv4 address space reaches near detrimental saturation. This is not to say that IPv6 adoption will not continue to grow, because it will. As more mobile devices hit the consumer market and the ‘Internet of Things’ continues to expand, the adoption of IPv6 will not only grow, but become necessary. However, protocols such as SMTP for sending mail will likely remain on IPv4 because of the community reluctance to support them on IPv6. Many ISPs are already recommending that their IPv6 clients make use of third party mail provider services instead of configuring their own mail servers as they normally would.

IPv6 adoption will likely grow first and foremost for device support and domain hosting, but for protocols outside of HTTP, it is likely that they will hold onto IPv4 for as long as they can. Most likely until either better support and security become available or until a better solution presents itself.

The History of the @ Sign

The at sign, or @ as we all know it, is commonly used in email addresses and Twitter handles. Formally called an asperand symbol, the @ sign has become nearly ubiquitous in electronic communications today. A few years ago, the Museum of Modern Art proclaimed the @ symbol a design classic. Though it’s most often associated with email and Twitter, the @ sign has a history that predates email and social media by hundreds of years. 

Theories about the @ Sign

According to an article published on Smithsonian.com, some believe that medieval monks are responsible for creating the @ symbol as a shortcut for ad, which is Latin for “toward.” Remember, monks frequently copied manuscripts by hand with quill and ink — a tedious process. Shortcuts made them more efficient. 

Another theory focuses on the French word for “at” which is à. Think of it as a lazy — or maybe even a fancy — way to add an accent.

Another one suggests that the @ symbol, which looks like an ‘a’ inside of a larger ‘e’, is an abbreviation for “each at.” Merchants used the @ sign in this way to denote units and prices. For example, if you were to list twenty widgets for sale at a price of $20 each, you might express this transaction as: 20 widgets @ $20. Since the @ sign means each at in this example, the total cost would be $400. This usage of the @ sign dates back to the 1500s.

Each of these theories share writing efficiency in common. The @ sign was simply used as a shortcut.

The @ Sign’s Rise to Prominence

ray-tomlinson-photoThough the @ sign had its purposes, it wasn’t widely used until email claimed it as its own. Early typewriters and computer tabulating systems did not feature it, but later ones did. The @ sign remained largely ignored until the forerunner of the Internet, Arpanet, emerged. Ray Tomlinson, a computer scientist involved in Arpanet, needed a means of addressing electronic messages to someone on a connected computer. Just as you address a letter to a person’s name and identify the person’s home address, electronic letters (hello email!) needed to include the person’s name and identify the person’s computer by name. 

Tomlinson needed a symbol that wasn’t commonly used in programming, and the @ symbol was it. Though he could have used some other obscure symbol, the @ sign was perfect thanks to its French translation: at. Tomlinson created the email naming system we know and use today, and he’s credited with sending the first email message.  

The @ Sign and Email Validation

Though Tomlinson’s email addressing system has withstood the test of time, addressing mistakes happen, making email validation necessary. 

With email validation, the words in front of and behind the @ sign are treated differently. Our email validation software understands email addressing conventions: the person’s name comes in front of the @ sign and the person’s computer address comes after it. Thus, if you have a contact named John Johns and his email address begins with “john.jones@,” you’re going to have a high level of confidence that his email address is genuine. On the other hand, if it’s “mickeymouse@,” your confidence level will be lower. 

Email validation software validates what comes after the @ sign as well. For example, it can correct common domain name misspellings such as @gmeal.com or typos like @gmail.c0m. 

The humble asperand symbol has been the domain of monks, merchants, computer scientists, and Internet users. We believe it’s here to stay.

Sources:

http://www.smithsonianmag.com/science-nature/the-accidental-history-of-the-symbol-18054936/?no-ist
http://en.wikipedia.org/wiki/At_sign  
http://www.theguardian.com/theobserver/2010/mar/28/moma-asperand-ray-tomlinson-design

 

Popular Myths about Big Data

Everyone’s talking about big data and data quality services. The hubbub isn’t likely to shrink any time soon because big data is only getting bigger and becoming increasingly important to rein in and manage. As with any topic receiving a great deal of attention, several myths have emerged. Ready for some myth-busting? 

data-myth-1

Ted Friedman, Vice President and analyst from Gartner, debunked this myth at Gartner’s 2014 Business Intelligence & Analytics Summit in Munich, Germany. IT leaders believe that the huge volume of data that organizations now manage makes individual data quality flaws insignificant due to the “law of large numbers.” Their view is that individual data quality flaws don’t influence the overall outcome when the data is analyzed because each flaw is only a tiny part of the mass of data in their organization.  “In reality, although each individual flaw has a much smaller impact on the whole dataset than it did when there was less data, there are more flaws than before because there is more data,”1 said Ted Friedman, vice president and distinguished analyst at Gartner. Instead of ignoring minor flaws, easy-to-use data quality tools can quickly correct or remove them.

data-myth-2

This myth comes courtesy of Michel Guillet of Juice Analytics who shared some myths in an INC article, 3 Big Myths about Big Data. Comparing big data choices to grocery store shelves, Guillet illustrated how too many big data choices (i.e., metrics, chart choices, and so on) can quickly become overwhelming. Guillet suggests that when faced with uncertainty about data options, users may simply ask for all of it. 

What he doesn’t say, however, is that too many choices often lead to indecision. For example, if you’re faced with, and overwhelmed by, too many different potato chip flavors plus traditional, low-fat, gluten-free, and baked options, name brands and store brands, you may grab one just to be done with it. Or, you might not choose one at all.  

Guillet says that users want guidance, not more uncertainty and that expressing an interest in more data is an indicator of uncertainty. What they really want? According to Guillet, “…they want the data presented so as to remove uncertainty, not just raise more questions. They won’t invest more than a few minutes using data to try to answer their questions.”

data-myth-3 

Sure, customers may own their own data, but they don’t necessarily know how to extract meaningful information from that raw data. Guillet explains that you’re not selling them access to their own data. Rather, you’re selling algorithms, metrics, insights, benchmarks, visualizations, and other data quality services that increase the data’s value.

data-myth-4

Not necessarily. While it seems like everyone else has already adopted a big data solution, or is in the process of doing so, according to Gartner, interest in big data technologies and services is at a record high, with 73 percent of the organizations Gartner surveyed in 2014 investing or planning to invest in them. But most organizations are still in the very early stages of adoption — only 13 percent of those we surveyed had actually deployed these solutions.1 The majority remain in the early stages of adoption. 

While you may feel like you’re late to the big data and data quality services party, the party is just getting started! In fact, this is the perfect time to investigate your big data options. Data quality tools have been around long enough to be both innovative and yet mature enough to have had the bugs worked out of them. 

These myths continue to make their rounds, but rest assured: our data quality services take care of data quality so even the tiniest of flaws are removed or corrected. We provide expert guidance, helping you to get the most out of the data quality tools available to you. Moreover, it’s not too late to get started. Simply sign up for a free trial key and try our data quality services in a matter of minutes.

Sources: 

1 Gartner Newsroom, Gartner Debunks Five of the Biggest Data Myths,
http://www.gartner.com/newsroom/id/2854917 

http://www.inc.com/eric-holtzclaw/3-big-myths-about-big-data-.html

Origins of Contact Data

You have a database filled with contact information. Great! However, before you launch that next direct mail campaign, you may want to do some preliminary contact verification. Depending on where your data came from, your database could have a serious case of the poor data quality blues. How your data fares in terms of data quality depends on where it came from, how old it is, and how long it’s been since the list underwent address verification.

So, where did your contact data come from? Generally speaking, you can either have first party, second, or third party contact data, or a mix of the three.

What is First Party Data?

First party contact data is contact data provided directly from your customers and prospects. For example, when a customer orders a product from your website and supplies you with his or her name, phone number, email address, and shipping address. While presumably genuine and accurate, contact verification is still recommended for verifying first party data due to occasional typos, autocorrect errors, spelling errors, mistakes, and even concerns about fraudulent orders. In addition, due to frequent address changes, plan on using data quality software to verify and correct contact information on a regular basis.

What is Second Party Data?

Second party contact data is data sourced from indirect channels such as via a partnership with another business. Here’s how Retargeter.com describes second party data: “…somebody else’s first party data.”

Like first party data, contract verification is important. While this data is presumably “clean” because your partner’s customers and prospects provided it directly, mistakes and errors are common and should be corrected and all addresses standardized. Data quality software makes this a snap. Plus, when was the last time your partner ran address verification on its list, and how old is that data? Again, you’ll want to run both an initial address verification check as well as cleanse the list on a regular basis to ensure you have the most current contact information possible.

What is Third Party Data?

Third party data, as the name implies, comes from a third party. It is generated externally from your company, and often aggregated from various sources. In fact, providers of third party data are frequently referred to as “data aggregators.” For example, when you buy demographic data or a mailing list from a data aggregator, that data is third party data. Though third party data has its place, it’s not necessarily as trustworthy as first party data. It really depends on the source.

Depending on the source, and depending on whether or not the data aggregator uses data quality software of its own, third party data could be filled with inaccurate contact information. Contact verification is an absolute must to clean up this data before you use it.

The Importance of Using Data Quality Software for Contact Verification
No matter how high quality your data may have been originally, as contact and demographic data ages, its quality degrades. People sell their homes and move away, business professionals move from one company to another, cities rename their streets, and so on.

So, a few mailers will come back as undeliverable; what’s the big deal? It’s not a big deal if you have a small list and are willing to manually correct addresses, but it becomes a big problem as your list size grows.

Service Objects’ real-time address verification API instantly corrects addresses and reduces costs, helping to ensure that your marketing dollars are well-spent and that you messages reach their intended audience. Whether you have first, second, or third party data, don’t you want that data to be current and accurate? Sign up for a free trial key and recover from the poor data quality blues.

5 Trending Data Buzzwords

Here at Service Objects, we love data almost as much as we love our dogs. Few things make us happier than exploring or talking about data. Turns out, we’re not the only ones obsessed with data. Checkout the following data buzzwords and join the conversation.

big-data-buzzwords

Smart data – In the last 30 days, “smart data” was mentioned on Twitter 9,234 times. What is it? You know what big data is, right? It’s massive, but it doesn’t always make sense. Denis Igin from NXCBlog explained smart data this way:

“…big data is what we know about consumer behavior, while smart data is how we discover the underlying rationale and predict repetition of such behavior… In short, smart data is adding advanced business intelligence (BI) on top of big data, in order to provide actionable insights.”

Business intelligence and data quality software help you make sense of data. Now that’s smart!

Data warehousing – Another 1,000+ conversations on Twitter in the last month have centered on “data warehousing.” What is it? Wisegeek explains it best:

Data warehousing combines data from multiple, usually varied, sources into one comprehensive and easily manipulated database.

For example, Service Objects’ data quality services tap into our massive database which pulls data from various sources such as the US Postal Service, telephone databases, and GPS mapping databases to validate, standardize, and enhance data.

Dark data – Topsy’s Social Analytics reveals nearly 1,700 Twitter mentions for “dark data” in the last month. According to Gartner’s IT Glossary, dark data is defined as:

“… the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).”1

In other words, dark data is data that’s not being used. It’s often kept solely for compliance purposes. What if you could enhance that data and put it to good use? Using data quality software, for example, you could validate older, potentially obsolete, addresses and create a direct marketing campaign targeting former customers.

Big analytics – With over 23,000 mentions in the last month, “big analytics” is definitely buzzworthy.

Big data analytics is the process of examining large data sets containing a variety of data types — i.e., big data — to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information.

Big analytics goes hand-in-hand with big data. When big analytics and data quality services work together, your data becomes much smarter and easier to work with.

The Internet of Things – We saved the biggest buzzword for last: “The Internet of Things. Also commonly referred to as “IoT,” the Internet of Things refers to a dramatically more connected Internet. Remember when the only things connected to the Internet were computers and servers? How quaint is that? Look around your personal space. You may have a desktop scanner that scans documents directly to Dropbox or Evernote. Maybe you’re wearing a Fitbit, which transmits your fitness and health stats directly to Fitbit.com. You may even have Internet-connected light bulbs or video surveillance system. If you’re really fancy, your refrigerator connects, tracking UPC codes and notifying you when your milk is about to go sour. On a larger scale, industrial equipment, parking meters, weather stations, and more are connected.

How many mentions did it get in the last 30 days? Over 150,000 for “Internet of Things” and another 74,000 for “IoT.” Now that’s trending!

As you can imagine, all those IoT “things” are generating data, contributing to big data. Each of these data buzzwords is interrelated and reflects the need for solutions such as data quality services and analytics.

1 Gartner IT Glossary, Dark Data, http://www.gartner.com/it-glossary/dark-data 

Data Quality, Not Just For Scientists

data-quality-scientist-2Scientists and analysts know the importance of data quality. In fact, they attend workshops focused on just that such as the recent Data Infrastructure: The Importance of Quality and Integrity workshop held in late November of last year. While scientists, researchers, and analysts clearly recognize the value of data quality software, data cleansing tools aren’t just for research labs or scientific data. Businesses of all types can benefit from data quality improvements, particularly in contact information. 

Which Types of Data Are Prime for Improvement?

Businesses generate and use massive amounts of data, day in, day out. The sheer volume and diversity of data can quickly prove to be overwhelming. Take a deep breath and think about the data that your business works with the most. Some of the most common data types in need of improvement are: contact information, addresses (including mailing, delivery, and email addresses), sales tax data, and sales and marketing leads. Each of these data types can be improved through the use of data quality software. However, since most businesses gather contact information, we’ll focus on improving data quality for contact information today.

The Problems with Contact Information 

Let’s say you run a brick-and-mortar appliance business and collect your customers’ addresses at the point of sale. Your clerks simply ask your customers for their names, addresses, and phone numbers when ringing up their purchases and scheduling delivery. Easy enough, right? After all, your customers know where they live and there’s no reason for them to offer a fake address or phone number.

That said, what happens when the customer says she lives at 135 Limonite Street but the clerk types in 135 Lemon Street or transposes the street numbers? Suddenly you have a potentially costly problem. Your delivery drivers will end up going to the wrong location and could be hours late. Not only will they have wasted time and fuel, your customer won’t be happy. 

Meanwhile, your resourceful drivers will have solved the problem by using their mobile phones to call the customer to get the correct address. However, will the drivers remember to correct the address in your point of sale system later? Probably not, bringing yet another problem: all of your subsequent mailings will go to the wrong address or be returned as undeliverable.

These same data quality problems occur when customers enter their contact information using self-service portals online. Mistakes — and autocorrect — happen. Not only that, people move all the time but rarely inform the companies that they do business with. Automated address verification solves all of these — and many more — problems.

How Data Quality Software Improves Contact Information

Data cleansing tools exist for all kinds of contact information including address verification, phone verification, reverse phone lookup, demographic information, and more. For example, Service Objects DOTS Address Validation, which has editions available for both the United States and Canada, is a real-time API that instantly compares inputted contact information with a huge database containing millions of current contact records. This data quality software is capable of detecting and correcting typos, standardizing address information against USPS®  data, verifying deliverability, appending secondary suite information for business addresses, and adding missing postal information. With a response time as fast as .15 seconds and various implementation options including a real-time API, PC-based software, FTP batch processing, and quick online lookups, these data cleansing tools quickly verify and correct contact information.

While scientists rely on quality data to further their research, businesses of all sizes can reduce costs, improve deliverability, improve customer satisfaction, and much more with data quality software. While your company likely works with a great deal of data, improving the quality of your contact information is an excellent place to start.

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