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To Be Customer-Centric, You Have To Be Data-Centric

In today’s fast-paced world, customers have become more demanding than ever before. Customer-centric organizations need to build their models after critically analyzing their customers, and this requires them to be data-centric.

Today, customers expect companies to be available 24/7 to solve their queries. They expect companies to provide them with seamless information about their products and services. Not getting such features can have a serious impact on their buying decision. Customer-centric organizations need to adopt a data-centric approach not just for targeted customer interactions, but also to survive competition from peers who are data-centric.

Customer-centric organizations need to go data-centric

Why?

Today, customers enquire a lot before making a decision. And social media enquiries are the most widely used by customers. A satisfactory experience is not limited to prompt answers to customer queries alone. Customers need a good experience before making the purchase, during the installment of product or deployment of service, and even after making the purchase. Thus, to retain a customer’s loyalty and to drive in regular profits, companies need to be customer-centric. And that can only happen if companies adopt a data-centric approach. Big data comes handy in developing a model that gives optimum customer experience. It helps build a profound understanding of the customer, such as what they like and value the most and the customer lifetime value to the company. Besides, every department in a data-centric organization can have the same view about its customer, which guarantees efficient customer interactions. Companies like Amazon and Zappos are the best examples of customer-centric organizations that heavily depend on data to provide a unique experience to their customers. This has clearly helped them come a long way.

How?

Companies can collect a lot of information that can help them become customer-centric. Here are some ways in which they can do so:

  • Keep a close eye on any kind of new data that could help them stay competitive, such as their product prices and the money they invest in logistics and in-product promotion. They need to constantly monitor the data that tells them about the drivers of these income sources.
  • Reach out to customers from different fields with varying skill sets to derive as many insights as possible so as to help make a better product.
  • Develop a full-scale data project that will help them collect data and apply it to make a good data strategy and develop a successful business case.

Today, there is no escaping customer expectations. Companies need to satisfy customers for repeat business. Customer satisfaction is the backbone of selling products and services, maintaining a steady flow of revenue, and for the certainty of business. And for all of that to happen, companies need to gather and democratize as much information about their customers as possible.

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

Author: Naveen Joshi, Founder and CEO of Allerin

The Difference Between Customer Experience And User Experience

There are a lot of buzzwords thrown around in the customer sphere, but two of the big ones relate to experiences—customer and user. Although CX and UX are different and unique, they must work together for a company to have success.

User experience deals with customers’ interaction with a product, website, or app. It is measured in things like abandonment rate, error rate, and clicks to completion. Essentially, if a product or technology is difficult to use or navigate, it has a poor user experience.

Customer experience on the other hand focuses on the general experience a customer has with a company. It tends to exist higher in the clouds and can involve a number of interactions. It is measured by net promoter score, customer loyalty, and customer satisfaction.

Both customer experience and user experience are incredibly important and can’t truly exist and thrive without each other. If a website or mobile app has a bad layout and is cumbersome to navigate, it will be difficult for customers to find what they need and can lead to frustration. If customers can’t easily open the mobile app from an email on their phone, they likely won’t purchase your product. Likewise, if the product layout is clunky, customers likely won’t recommend it to a friend no matter how innovative it is. User experience is a huge part of customer experience and needs to play a major role when thinking like a customer.

Although UX and CX are different, they need to work closely together to truly be successful. Customer experience representatives should be working alongside product engineers to make sure everything works together. By taking themselves through the entire customer journey, they can see how each role plays into a customer’s overall satisfaction with the product and the company. The ultimate goal is a website or product that beautifully meshes the required elements of navigation and ease with the extra features that will help the brand stand out with customers.

When thinking about customer experience, user experience definitely shouldn’t be left behind. Make both unique features an essential part of your customer plan to build a brand that customers love all around.

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

Author Bio: Blake Morgan is a customer experience futurist, author of More Is More, and keynote speaker.

Go farther and create knock your socks-off customer experiences in your organization by enrolling in her new Customer Experience School.

Leverage Service Objects’ Industry Expertise to Reach Your Data Quality Goals

At Service Objects, we are fully committed to our customers’ success, which is a main factor in why over 90% of our business is from repeat customers. And with over 16 years of experience in contact validation, we have accumulated a broad base of industry expertise, created numerous best practices and are considered thought leaders in global data validation.

It is because of this knowledge that some of our customers turn to us when they lack the internal resources to carry out their data quality project. Whether it is assistance in implementing a data quality initiative, asking for customization to our products to meet specific business needs or help integrating our solutions into Marketing or Sales Automation platforms, Service Objects’ Professional Services can assist your business in achieving optimal results on your project in a quick and efficient manner.

Here are just three of the ways we can help:

Integration Programming and Code Support

If your team is overwhelmed or lacks the technical resources to integrate data quality solutions into your existing systems, Service Objects can step in and quickly get your project moving. We provide your team with the technical knowledge, support, and best practices needed to implement your chosen solution in a timely fashion and within your budget.

CRM or Marketing Automation Platform Integration

We have created cloud connectors for the leading sales and marketing platforms and have developed extensive knowledge on how these systems work with our data quality solutions. We enable your organization to implement best practices, allowing your business to verify, correct and append contact data at the point of entry. The result is your contact database contains records that are as genuine, accurate and up-to-date as they can possibly be.

Custom Services

Our engineers have years of experience creating, implementing and supporting data quality services in many different programming languages. As a result, we can customize our existing services to solve a challenge that is specific to your business. Our proactive support services team will work with your technical team to refine, test and implement the custom service to work for your business’ specifications.

These are just some of the ways we can help. For more information about how you leverage our industry expertise and technical knowledge, contact us.

Three Things I am Thankful for This Thanksgiving

Thanksgiving in the United States is about much more than taking a couple of days off from work, eating too much turkey, or starting your holiday shopping. This holiday has always had a higher purpose: to reflect and give thanks every year. So what am I thankful for?

There are three things on my list. First and foremost, I am thankful for you, our customers. Obviously every CEO is thankful for paying customers, but I also mean it from a different perspective: you are a very diverse and talented group of people, and we enjoy working with you. Our customers run the whole gamut of applications: increasing museum attendance through demographic analysis, creating precise address lists to expand rural broadband coverage, geocoding maps of hurricane refugees, and much more. It is truly never boring to come to work here.

Which leads me to the next thing on my list: I am thankful that Service Objects is a great place to work. We began as a small startup in 2001, but today we are a growing organization whose management team has over a century of combined experience in our respective fields.  And we hire really cool people! We have a strong culture that emphasizes teamwork, healthy living and environmental awareness. And who wouldn’t be thankful for coming to work in sunny Santa Barbara, California every morning?

More important, everyone here is extremely good at what they do, whether it is technology, service, or operations. We operate in a very competitive space, and quite frankly the talent of our people – and the clear service culture people experience when they work with us – is our biggest competitive differentiator. If you look at the many customer success stories on our website, you will find clients raving about our technology AND our people, and I am very proud of that.

Finally, one of the biggest things I am thankful for is the chance to make a real difference in the environment we share on this planet. Many people know that I first started this company in response to the problem of excessive junk mail in the waste stream, developing mathematical models for ways to mitigate this massive waste of resources. Our focus on real-time contact validation, and all the products and services that follow from there always has had its roots in resource conservation.

Today, we are proud to have processed nearly three billion transactions. This translates directly to less waste and more efficient use of our precious resources, saving 23 million gallons of water and 11 thousand cubic yards of landfill space each and every year. Since Service Objects’ inception in 2001 this adds up to 12 million trees and 150 million pounds of paper saved – and counting. This is a legacy we frankly cherish as much as any quarterly sales figures.

SO what are you thankful for?

Hope you have a very happy Thanksgiving holiday!

Service Objects Launches Newly Redesigned Website

Service Objects is excited to announce that we have launched a newly redesigned website, www.serviceobjects.com. The redesign effort was undertaken to enhance the user experience and features a new graphical feel, enhanced content and improved technical functionality. Visitors can now more quickly find information on how Service Objects’ contact validation solutions solve a variety of challenges in global address validation, phone validation, email validation, eCommerce and lead validation. Free trial keys for all 23 data quality services can also be readily accessed.

As part of the launch, Service Objects also made significant updates to its data quality and contact validation blog, which contains hundreds of posts on topics such as fraud protection, address validation and verification, data quality best practices, eCommerce, marketing automation, CRM integration and much more. New content is published weekly and visitors can subscribe to have new content and updates sent to them directly.

“The recent launch of DOTS Address Validation International and DOTS Lead Validation International has firmly established Service Objects as the leader in global intelligence,” said Geoff Grow, CEO and Founder, Service Objects. “We redesigned our website to more prominently communicate Service Objects’ expertise in the global intelligence marketplace and continue to reinforce what is most important to our customers: in-depth developer resources, guaranteed system availability, 24/7/365 customer support and bank grade security.”

New features also include three ways to connect with our services: API integration, Cloud Connectors or sending us a list.  We hope you will take a look at our new website and blog and send us your feedback at marketing@serviceobjects.com.

API Integration: Where We Stand

Applications programming interfaces or APIs continues to be one of the hottest trends in applications development, growing in usage by nearly 800% between 2010 and 2016 according to a recent 2017 survey from API integration vendor, Cloud Elements. Understandably, this growth is fueling an increased demand for API integration, in areas ranging from standardized protocols to authentication and security.

API integration is a subject near and dear to our hearts at Service Objects, given how many of our clients integrate our data quality capabilities into their application environments. Using these survey results as a base, let’s look at where we stand on key API integration issues.

Web service communications protocols

This year’s survey results bring to mind the old song, “A Little Bit of Soap” – because even though the web services arena has become dominated by representational state transfer (REST) interfaces, used by 83% of respondents, a substantial 15% still use the legacy Simple Object Access Protocol (SOAP) – a figure corroborated by the experiences of our own integrators.

This is why Service Objects supports both REST and SOAP among most if not all services. We want our APIs to be flexible enough for all needs, we want them to work for a broad spectrum of clients, and we want the client to be able to choose what they want, whether it is SOAP or REST, XML or JSON.  And there are valid arguments for both in our environment.

SOAP is widely viewed as being more cumbersome to implement versus REST, however tools like C# in Visual Studio can do most of the hard work of SOAP for you. Conversely, REST – being URL http/get focused – does carry a higher risk of creating broken requests if care is not taken.  Addresses, being a key component in many of our services, often contain URL-breaking special characters.  SOAP inherently protects these values, while REST on a GET call does not properly encode the values and could create broken URLs. For many clients, it is less about preference and more about tools available.

Webhooks: The new kid on the block

Webhooks is the new approach that everyone wants, but few have implemented yet. Based on posting messages to a URL in response to an event, it represents a straightforward and modular approach versus polling for data. Citing figures from Wufoo, the survey notes that over 80% of developers would prefer this approach to polling. We agree that webhooks are an important trend for the future, and we have already created custom ones for several leading marketing automation platforms, with more in the works.

Ease of integration

In a world where both applications and interfaces continue to proliferate, there is growing pressure toward easier integration between tools: using figures cited from SmartBear’s State of the APIs Report 2016, Cloud Elements notes that this is a key issue for a substantial 39% of respondents.

This is a primary motivation for us as well, because Service Objects’ entire business model revolves around having easy-to-integrate APIs that a client can get up and running rapidly. We address this issue on two fronts. The first is through tools and education: we create sample code for all major languages, how-to documents, videos and blogs, design reference guides and webhooks for various CRM and marketing automation platforms. The second is a focus on rapid onboarding, using multiple methods for clients to connect with us (including API, batch, DataTumbler, and lookups) to allow easy access while APIs are being integrated.

Security and Authentication

We mentioned above that ease of integration was a key issue among survey respondents – however, this was their second-biggest concern. Their first? Security and authentication. Although there is a move toward multi-factor and delegated authentication strategies, we use API keys as our primary security.

Why? The nature of Service Objects’ applications lend themselves well to using API keys for security because no client data is stored. Rather, each transaction is “one and done” in our system, once our APIs perform validation on the provided data, it is immediately purged from our system and of course, Service Objects supports and promotes SSL over HTTPS for even greater protection.  In the worst-case scenario, a fraudster that gains someone’s key could do transactions on someone else’s behalf, but they would never have access to the client’s data and certainly would not be able to connect the dots between the client and their data.

Overall, there are two clear trends in the API world – explosive growth, and increasing moves toward unified interfaces and ease of implementation. And for the business community, this latter trend can’t come soon enough. In the meantime, you can count on Service Objects to stay on top of the rapidly evolving API environment.

The Talent Gap In Data Analytics

According to a recent blog by Villanova University, the amount of data generated annually has grown tremendously over the last two decades due to increased web connectivity, as well as the ever-growing popularity of internet-enabled mobile devices. Some organizations have found it difficult to take advantage of the data at their disposal due to a shortage of data-analytics experts. Primarily, small-to-medium enterprises (SMBs) who struggle to match the salaries offered by larger businesses are the most affected. This shortage of qualified and experienced professionals is creating a unique opportunity for those looking to break into a data-analysis career.

Below is some more information on this topic.

Data-Analytics Career Outlook

Job openings for computer and research scientists are expected to grow by 11 percent from 2014 to 2024. In comparison, job openings for all occupations are projected to grow by 7 percent over the same period. Besides this, 82 percent of organizations in the US say that they are planning to advertise positions that require data-analytics expertise. This is in addition to 72 percent of organizations that have already hired talent to fill open analytics positions in the last year. However, up to 78 percent of businesses say they have experienced challenges filling open data-analytics positions over the last 12 months.

Data-Analytics Skills

The skills that data scientists require vary depending on the nature of data to be analyzed as well as the scale and scope of analytical work. Nevertheless, analytics experts require a wide range of skills to excel. For starters, data scientists say they spend up to 60 percent of their time cleaning and aggregating data. This is necessary because most of the data that organizations collect is unstructured and comes from diverse sources. Making sense of such data is challenging, because the majority of modern databases and data-analytics tools only support structured data. Besides this, data scientists spend at least 19 percent of their time collecting data sets from different sources.

Common Job Responsibilities

To start with, 69 percent of data scientists perform exploratory data-analytics tasks, which in turn form the basis for more in-depth querying. Moreover, 61 percent perform analytics with the aim of answering specific questions, 58 percent are expected to deliver actionable insights to decision-makers, and 53 percent undertake data cleaning. Additionally, 49 percent are tasked with creating data visualizations, 47 percent leverage data wrangling to identify problems that can be resolved via data-driven processes, and 43 percent perform feature extraction, while 43 percent have the responsibility of developing data-based prototype models.

In-demand Programming-Language Skills

In-depth understanding of SQL is a key requirement cited in 56 percent of job listings for data scientists. Other leading programming-language skills include Hadoop (49 percent of job listings), Python (39 percent), Java (36 percent), and R (32 percent).

The Big-Data Revolution

The big-data revolution witnessed in the last few years has changed the way businesses operate substantially. In fact, 78 percent of corporate organizations believe big data is likely to fundamentally change their operational style over the next three years, while 71 percent of businesses expect the same resource to spawn new revenue opportunities. Only 58 percent of executives believe that their employer has the capability to leverage the power of big data. Nevertheless, 53 percent of companies are planning to roll out data-driven initiatives in the next 12 months.

Recruiting Trends

Companies across all industries are facing a serious shortage of experienced data scientists, which means they risk losing business opportunities to firms that have found the right talent. Common responsibilities among these professionals include developing data visualizations, collecting data, cleaning and aggregating unstructured data, and delivering actionable insights to decision-makers. Leading employers include the financial services, marketing, corporate and technology industries.

View the full infographic created by Villanova University’s Online Master of Science in Analytics degree program.

http://taxandbusinessonline.villanova.edu/resources-business/infographic-business/the-talent-gap-in-data-analytics.html

Reprinted with permission.

Getting the Most Out of Data-Driven Marketing

How well do you know your prospects and customers?

This question lies at the heart of what we call data-driven marketing. Because the more you know about the people you contact, the better you can target your offerings. Nowadays smart marketers are increasingly taking advantage of data to get the most bang from their marketing budgets.

Suppose that you offer a deal on a new razor, and limit the audience to adult men. Or take people who already eat fish at your restaurant on Tuesdays, and promote a Friday fish fry. Or laser-target a new lifestyle product to the exact demographic group that is most likely to purchase it. All of these are examples where a little bit of data analytics can make a big difference in the success and response rate of a marketing campaign.

According to UK data marketing firm Jaywing, 95% of marketers surveyed personalize their offerings based on data, although less than half currently measure the ROI of these efforts, and less than 10% take advantage of full one-to-one cross-channel personalization. But these efforts are poised to keep growing, notes their Data Management Practice Director Inderjit Mund: “Data availability is growing exponentially. Adopting best practice data management is the only way marketers can maintain a competitive advantage.”

Of course, data-driven marketing can also go sideways. For example, bestselling business author and television host Carol Roth once found herself peppered with offers for baby merchandise – including an unsolicited package of baby formula – even though she is not the least bit pregnant. Her suspicion? Purchasing baby oil regularly from a major chain store, which she uses in the shower, made their data wonks mistakenly think that she was a new mother. Worse yet, this kind of targeted marketing also led the same chain to unwittingly tip off a father that his daughter was pregnant.

This really sums up the promise, and the peril, of using data to guide your marketing efforts. Do it wrong, and you not only waste marketing resources – you risk appearing inept, or worse, offending a poorly targeted segment of your market base. But when you do it right, you can dramatically improve the reach and efficiency of your marketing for a minimal cost.

This aligns very closely with our view of a marketing environment that is increasingly fueled by data. Among the best practices recommended by Jaywing for data-driven marketing, data quality is front and center with guidelines such as focusing on data management, having the right technology in place, and partnering with data experts. And they are not alone: according to a recent KPMG CEO survey, nearly half of respondents are concerned about the integrity of the data on which they base decisions.

There is a clear consensus nowadays that powering your marketing with data is no longer just an option. This starts with ensuring clean contact data, at the time of data entry and the time of use. Beyond that, smart firms leverage this contact data to gain customer insight in demographic areas such as location, census and socioeconomic data, to add fuel to their address or email-based marketing. With cost-effective tools that automate these processes inside or outside of your applications, the days of scattershot, data-blind marketing efforts are quickly becoming a thing of the past.

How to Use DOTS Email Validation 3

The DOTS Email Validation 3 (EV3) service has been designed to be robust enough to accommodate the particular needs of a detailed oriented programmer and simple enough to be used by a marketing assistant who needs to run an email campaign. The service can meet various needs that can essentially be narrowed down to two use cases, form validation and post-processing jobs such as batches and database hygiene. Before we discuss those two cases we will first go over the recommended service operation and review some of the important result fields.

Which Operation Should I Use?

The recommended service operation for EV3 is the ValidateEmailAddress method. This operation performs real-time server-to-server email verification. It lets the user specify a timeout value, in milliseconds, for how long it can take to perform real-time server checks. A minimum value of 200 milliseconds is required; however, results are dependent on the network speed of an email’s host, which may require several seconds to verify. Average mail server response times are approximately between 2-3 seconds, but some slower mail servers may take 15 seconds or more to verify.

Please note that the above information is also available in the service developer guide.

Understanding the Results

The service returns many results that can be used to meet a programmer’s particular email validation needs, but the easiest way to determine if an email should be accepted or rejected is by looking at either the IsDeliverable value or the Score value.

Score:

For most cases it is recommended to use the Score along with other output values to cater to your particular needs. Here are the possible score values.

Score Description Notes
0 Email is Good Indicates with high confidence that the email address is deliverable and good. The email address was verified with the host mail server and no malicious warnings were found.
1 Email is Probably Good Indicates that the email is deliverable but one or more lesser warnings were found. For example the email may be a potential alias or a role, which are sometimes used as disposable addresses.
2 Unknown Indicates that not enough information was available to determine deliverability and integrity. Unknowns most commonly occur for slow mail servers that do not respond to the web service in time. They also occur for catch-all mail servers and greylists.
3 Email is Probably Bad Indicates that one or more warnings were found, such as a potential vulgarity or a string of garbage-like characters.
4 Email is Bad Indicates with high confidence that the email address is bad and/or undeliverable. Occurs for email addresses that fail critical checks such as syntax validation and DNS verification. Most commonly occurs for email addresses where the actual host mail server verified that the email does not exist. Also occurs for deliverable email addresses that are known spam traps or bots.

IsDeliverable:

The simplest way to use the service is to look at the IsDeliverable field. This field will return true, false or unknown. If your primary concern is to be able to send out email with the lowest possible chance of a hard bounceback then this field alone will suffice. However, this field does not take spamtraps, vulgarities, bots or other factors into consideration. It simply indicates if the service was able to verify the deliverability of an email address with the host mail server. It does not measure the overall integrity of the email address.

If you choose to only look at one result value then it is our recommendation that you use the Score value instead of the IsDeliverable value. The Score evaluates the overall integrity of the email address and not just its deliverability. Either one of these fields can be used in conjunction with other result values to more intelligently evaluate an email address if the need arises. For example, if an email comes back as unknown in either the Score or in IsDeliverable, then we can refer to the following outputs to help us decide if we should accept, reject or retry the email address.

IsSMTPServerGood:

Returns true, false or unknown to indicate if the email’s host mail server was responsive at the time of the check. This is a one of the service’s critical checks. If this value comes back false then it will be reflected in the IsDeliverable value and in the score. Refer to this value if the email is unknown. If the value for this field is also unknown then the service most likely did not have enough time to finish verifying the email address with its host mail server. In these cases the service will continue to try and verify the email in a background process even though the request has finished. Chances are high that if you wait one or more hours and check the email again that the service will have been able to finish verifying the email addresses with the host mail server.

IsCatchAllDomain:

Returns true, false or unknown to indicate if the email’s host mail server is a catch-all. A catch-all mail server will say that an email address is deliverable even if it is not.  This is because catch-all mail servers do not reject email addresses during the initial SMTP session. This means that a catch-all mail server cannot be trusted to verify the deliverability of an email address because it may or may not reject the email address until after an email message is sent. If an email address is unknown and this value is false then chances are good that if the email is checked again at a later time then the service will have verified its deliverability. If catchall is true and there are no warnings, then we know that the mail server is good and that the email does not appear to be bad. In general this scenario leads to a 55% chance that the email is deliverable and won’t result in a hard bounce.
IsSMTPMailBoxGood:

Returns true, false or unknown to indicate if the service was able to verify the email address with its host mail server. This value can be treated similarly to the IsDeliverable value. A true value indicates that the email address is deliverable. If the value comes back false then the mail server verified that the email is undeliverable. A false will be accompanied by the warning flag, ‘Email is Bad – Subsequent checks halted.‘ Some common reasons why this value will return unknown; the mail server is a catch-all, the service ran out of time when communicating with the host mail server or the host mail server used a defensive tactic such as a greylist.

A complete list of the output fields and values are available in the service developer guide.

The result fields given above are useful when it comes to sorting, grouping and filtering all of your validated email addresses. This is useful when working on a post-processing email job, which we will discuss later. Next, we will look at some of the descriptive flags that the service will return. These flags can be used programmatically or at a glance to determine the status of an email address.

Warning Codes & Descriptions:

There are many warning flags that the service may return but we will look at some of the more common and critical ones.

DisposableEmail, SpamTrap, KnownSpammer and Bot

An email address may be deliverable but if one or more of these warning flags is returned then it is highly recommended to reject it.

Alias, Bogus and Vulgar

If one of these warning flags is returned then you may want to either reject the email or set it aside for later review, depending on how strict you want to be.

InvalidSyntax, InvalidDomainSpecificSyntax and InvalidDNS

These are warnings for critical checks that failed. If one of these flags appears then it will be immediately followed by the warning flag ‘Email is Bad – Subsequent checks halted.

Email is Bad – Subsequent checks halted

This warning indicates that the email failed a critical check and is undeliverable. If the flag is not preceded by one of the critical warning flags then it simply means that the email’s host mail server verified that the email address is undeliverable.

A complete list of warning codes and their descriptors are available in the dev guide.

Note Codes & Descriptions:

The note flags will return descriptive information about the email, not all of which will affect the score, but we will focus on the ones that will explain why some email addresses came back as unknown.

GreyListed

The service is good at detecting greylist behavior from mail servers and has procedures in place to avoid them, but not all greylists are avoidable. If the service encounters a greylist then it is temporarily unable to verify the email address with its host mail server. If you encounter a greylist then chances are good that if you try to validate the email again a couple of hours later that you will get a better response.

MailServerTemporarilyUnavailable

This flag indicates that the service was able to connect to the email’s host mail server, but that the server was temporarily busy or unavailable and it was unable to verify the email for us. If you encounter this flag then try and validate the email again a few of hours later to see if the server becomes more responsive then.

ServerConnectTimeout

This flag indicates that the service was unable to establish a connection with a host mail server. A possible reasons for the connection failure could be that the mail server is completely offline or it is responding too slow and unable to respond in time. Some mail servers are configured to commonly respond slowly, taking as long as 60 seconds to respond to a connection. This behavior is rare but it is not entirely uncommon. If an email returns this flag then try and enter a longer timeout time to allow the service the time it needs to verify the email.

MailBoxTimeout

This flag indicates that the service was unable to finish verifying the email address with the host mail server in the time allowed. The mail server could be responding very slowly or the timeout time given to the service was too short. If an email returns this flag then try and enter a longer timeout time to allow the service the time it needs to verify the email.

A complete list of note codes and their descriptors are available in the developer guide.

Use Case 1 – Using Validate Email Address for Form Validation

The ValidateEmailAddress method has four input fields that are all required.

Input Field Name Description Notes
EmailAddress The email address you wish to validate.
AlowCorrections Accepts true or false. The service will attempt to correct an email address if set to true. Otherwise the email address will be left unaltered if set to false. The majority of the email corrections are being performed on the domain. The local part of the email address, the portion before the @ symbol, is generally left untouched.
Timeout Accepts an integer as a string. Timeout time is in milliseconds. Do not include any commas or non-numeric values. This value specifies how long the service is allowed to wait for all real-time network level checks to finish. Real-time checks consist primarily of DNS and SMTP level verification. A minimum value of 200ms is required. When it comes to form validation it is recommended to use a timeout time that is short enough to not keep your user impatiently waiting, but long enough to allow the server-to-server communication time to finish. A relatively short timeout time between 2 to 4 seconds is generally recommended.

 

LicenseKey Your license key to use the service.

Accept, Reject or Review & Retry

ACCEPT

Emails with a score of 0, 1 or 2. In general it is recommended to not be too strict when accepting emails in a form because you do not want to potentially lose an end user.  Also, when performing form validation an end user may become agitated if they have to wait more than 5 seconds for the validation process to complete, but some slow mail servers may not be able to respond in that short amount of time.

REJECT

Emails with a score of 3 or 4. If you do not want to be too strict then you can accept 3 for review, but you should always reject an email that receives a score of 4.

REVIEW & RETRY

Depending on how strict/cautious you want to be you can choose to not initially accept emails with a score of 2 and instead put them aside to have them reviewed. If the IsCatchAllDomain field is not true then you can try and validate the email again later. Email addresses that return a score of 3 can also be set aside for review if you do not want to initially reject all of them. An email will commonly be given a score of 3 if a potential vulgarity or string of garbage characters is found.

In form validation the programmer is sometimes allowed some luxuries while others are taken away. For example, a programmer can be given the opportunity to communicate a result back to the end user but is usually restricted to a shorter timeout time so that the end user is not kept waiting too long. If you have the ability to communicate back the end user then ask the user to check for a typo and try again or try a different email address. If you don’t want to accept a role or alias type email address because they are commonly not accepted by mass email marketers then you can catch for that and tell the user to try again with a different email address.

Use Case 2 – Using ValidateEmailAdress for Batches, Email Campaigns and Data Hygiene

The ValidateEmailAddress method has four input fields that are all required.

Input Field Name Description Notes
EmailAddress The email address you wish to validate.
AlowCorrections Accepts true or false. The service will attempt to correct an email address if set to true. Otherwise the email address will be left unaltered if set to false. The majority of the email corrections are being performed on the domain. The local part of the email address, the portion before the @ symbol, is generally left untouched. Since you are unable to ask a user to re-enter and try again if they make a mistake you can set this value to true and allow the service to make corrections.
Timeout Accepts an integer as a string. Timeout time is in milliseconds. Do not include any commas or non-numeric values. This value specifies how long the service is allowed to wait for all real-time network level checks to finish. Real-time checks consist primarily of DNS and SMTP level verification. A minimum value of 200ms is required. For non-form validation it is recommended to give the service plenty of time to verify an email address with its host mail server. Most mail servers will only take about 2 seconds on average to verify an email address, but for the occasional slow mail server that requires more time it is recommended to set the timeout time to 65 seconds. The number of mail servers that require this much time is generally minimal, so the long timeout should not make a big impact on the overall batch job.

 

LicenseKey Your license key to use the service.

Accept, Reject or Review & Retry

ACCEPT

Emails with a score of 0 or 1.

REJECT

Emails with a score of 3 or 4. If you do not want to be too strict then you can accept 3 for review, but you should always reject an email that receives a score of 4.

REVIEW & RETRY

Emails with a score of 2, unless the IsCatchAllDomain field value is true. An email that gets an unknown score  due to a greylist, timeout or temporarily busy server should be checked again a couple of hours later.

If you would like to discuss your particular use case for recommendations and best practices contact us!

Service Objects is the industry leader in real-time contact validation services.

Service Objects has verified over 3 billion contact records for clients from various industries including retail, technology, government, communications, leisure, utilities, and finance. Since 2001, thousands of businesses and developers have used our APIs to validate transactions to reduce fraud, increase conversions, and enhance incoming leads, Web orders, and customer lists. READ MORE