Recently in Address Standardization Category

Introducing Business Coder for United Kingdom

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Melissa is happy to announce the release of our Business Coder service for UK, where you can verify, validate, and append firmographics for businesses in the UK. Originally servicing only the US, our webservice now expands to the UK as one of our more popular demands for business identification.

Our Business Coder UK webservice can help provide address cleansing and verification, along with business verification and appending of firmographic data. Our SIC Codes and Descriptions can help identify industries that the targeted businesses belong to, along with incorporation dates to help verify the correct businesses.

Similar to Business Coder US, our familiar result codes can help determine any issues with address or business validation. Ensure that the data returned along with our results help verify correct businesses in your data.

Powered by our Global Address engine, our address validation system thoroughly covers streets across the United Kingdom. With quality data ensured by experts and reliable sources such as the Royal Mail, be sure that you standardize and correct any addresses for your list of businesses to ensure that your deliveries do not go to waste.

And don't forget, this is only an announcement for our initial release. We're constantly striving to improve our webservice, as we plan to add additional fields and features to Business Coder UK. Check out our wiki and be on the lookout for new updates for the webservice!

Please note that for our release, Business Coder US and Business Coder UK will have separate URLs to make web service requests to. Additionally, Business Coder UK requires a separate subscription from Business Coder US. Please visit our wiki for more information on how to what to expect out of the new Business Coder.

Business Coder UK wiki: http://wiki.melissadata.com/index.php?title=Business_Coder_UK

5 Ecommerce Issues You Forgot--And How to Fix Them

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Want to increase conversions, provide customers with a better shopping experience, and cut down on cart abandonment? Check out these five ecommerce issues you probably forgot and how to fix them to solve these problems and more.

1. The Fat Finger Syndrome

Customers are terrible at typing--especially when it comes to filling out incredibly small contact forms on their smartphones. The fat finger syndrome accounts for many name misspellings, incorrect addresses, email bouncebacks, and invalid order submissions. To take the burden off the customer, try implementing a real-time autocomplete solution. By automatically showing verified addresses and emails as the customer types, you'll help alleviate fat finger syndrome and cut down on form abandonment.

 

2. International Postal Standards Vary

Did you know that in Japan, the last name goes first on shipping labels? And in Canada, the postal codes consist of letters and numbers arranged in a specific way? Those are just two examples of how address standardization can differ from country to country. So, if you're planning to go international, be mindful of varying postal requirements and make sure you have an address verification solution that can verify, standardize, format and transliterate. Solutions like Melissa's Global Address Verification do all of this and more--like adding precise lat/long coordinates to addresses for 40+ countries.

 

3. Upfront Shipping Matters

Amazon has shown the way towards better conversions, more sales, and cost-effective shipping with upfront shipping costs and delivery dates shown at every step of the order process. Now, you can, too! With Decimal, a comprehensive shipping rates manager and delivery dates predictor, you can provide your customers with calculations for shipping while they shop, without interrupting their purchase. That means more customers hitting Submit Order without delay.

 

4. Clean Data Affects Everything

Are you sure you're only storing accurate customer data? The data you collect directly on your site, via call-in orders, through internal systems, and mobile all need to match to show accurate customer records in order to better know your customers, increase upsell opportunities, and provide good customer service. By cleaning data before it enters your database and maintaining it after, you can ensure that every customer's name, address, phone, and email are accurate and verified.

 

5. Fraud Costs More than Lost Sales

Let's look at some stats--every year, businesses lose $3.5 trillion in revenue to financial crimes, and 15.4 million consumers were victims of identity theft in 2016 alone. Don't let fraud and chargeback costs steal your bottom line. Instead, use an ID verification solution like Personator®, which combs through 2.1 billion records to match name-to-address and verify that every customer is exactly who they say they are.

 

Melissa provides numerous APIs to handle the standardization, cleansing and verification of various data elements such as addresses, names, phones and emails. Often times we get asked by our customers as to what are some ways to improve the speed when processing records using our APIs. Below are some performance tips to consider when implementing our APIs:

 

Storage

The type of medium where the data files are stored may have an impact on processing speed. We recommend the use of solid state drives to store our data files as they have faster seek & read times compared to spinning disk drives.


We have also sometimes seen clients store the data files on a network share which we definitely don't recommend. Typically, trying to access the files over a network introduces latency which impacts the processing speed when blocks of data need to be fetched quickly. Data files, therefore, should often be stored locally on the machine.

 

Memory

The amount of memory available and speed can also affect processing. While using the APIs, once data is read from the hard drive, the data is cached and stored temporarily into memory in case the data needs to be accessed again shortly.

 

A simple example below, we have a list of phone numbers that were verified using our Phone Object API along with the times in milliseconds indicating the amount of time to verify the phone number.

 

When the Phone Object API encounters a phone number in a new area code, there are spikes in the verify times as the Phone Object now has to go back and fetch a new block from the data files stored on a hard disk and cache it into memory. The more memory available on the system, the more that can be cached into memory as the API reads more blocks from the data files on the disk. And, as discussed in the previous section, having a faster hard drive will help keep those disk read times low when those data file reads occur.


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Multi-threading

Processors with more than a single core are now common these days. If multiple cores are available on the system, we highly recommend that developers take advantage of that. When multithreading with our APIs, we suggest having each thread contain its own object instantiation for our APIs. 


For example, if you have 8 cores, you may want to create 8 threads with our API instantiated 8 times: once per each thread. Ideally, you would want to create a pool of threads that have our API instantiated already, and therefore ready for processing. If you keep reinitializing/instantiating our API, that will introduce some overhead in the processing.

 

The graph and table below shows some multithreaded testing of our own with our Global Address Object® API with UK addresses and, as shown, there as substantial speed increases that can be obtained through multithreading:


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Melissa's Improvements in Dynamics CRM

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Dirty data, in all forms, is bad for business. Here at Melissa, our primary concern is cleansing it from all of your platforms, including Microsoft Dynamics® CRM. Melissa currently offers many solutions for Dynamics CRM in order to combat problems with bad data.

 

We offer the Personator® solution in order to cleanse and enrich your U.S. and Canadian data. We offer the Global Verify solution to correct and verify your addresses, phone numbers, names, and email addresses on an international level. Soon, we will release the Express Entry® solution in order to prevent bad data from entering your environment. As we strive to offer you the best solutions, Melissa constantly seeks to improve its solutions to better suit your needs.

 

Coming in a future update, we will offer the following new features to our Express Entry service:


•          Personator Workflows

•          Reverse Lookup for Express Entry

•          Express Entry Integration into Global Verify

Personator Workflows

Dynamics CRM is utilized in many different ways in the business world. The creation of contact, account, and lead records is handled through many different environments that may not leverage the standard form. In addition, sometimes users may forget to use our services to cleanse and correct information before saving and storing a record. 


To address these issues, we have created workflows for the Personator solution for the currently supported out-of-box entities. These workflows can be activated to leverage our Personator service on records automatically, such as upon creation of a new record. This will allow users to create records from a different environment, such as a separate portal, to have their information automatically validated through our workflows.

 

Reverse Lookups for Express Entry

Different users enter address information in different orders. With Dynamics CRM's ability to customize forms, it is apparent that not everyone will start by entering a street address. With our new feature, Reverse Lookups, users can enter information starting from the most general piece of information down to the most specific. For example, now a user, after entering his or her default country, can begin by entering the postal code to determine the city and state of the particular record. After filling out these fields, the user can then enter in the street address and select from a list of addresses only in that particular city, state, and postal code.

 

Express Entry Integration into Global Verify

Many customers require different methods of verification. In order to address these concerns, we have integrated our Express Entry service into our Global Verify solution. Now, you can utilize the Express Entry service to autocomplete addresses when entering data as well as verify phone and email with the click of a button.

How to Do It All with Melissa

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With Melissa, you can do it all - see for yourself with the brand new Solutions Catalog. This catalog showcases products to transform your people data (names, addresses, emails, phone numbers) into accurate, actionable insight. Our products are in the Cloud or available via easy plugins and APIs. We provide solutions to power Know Your Customer initiatives, improve mail deliverability and response, drive sales, clean and match data, and boost ROI.

 

Specific solutions include:

·         Cleaning, matching & enriching data
·         Creating a 360 degree profile of every customer
·         Finding more customers like your best ones with lookalike profiling
·         Integrating data from any source, at any time

Other highlights include: global address autocompletion; mobile phone verification; real-time email address ping; a new customer management platform; as well as info on a wealth of data append and mailing list services.

 

Download the catalog now:

http://www.melissa.com/catalogs/solutions/index.html

 

MAILERS Online: On Demand & In the Cloud Presorting

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Say hello to a no-contract, end-to-end mailing solution that's in the cloud and easy to use. MAILERS Online is a one-stop-shop for all your mailing and presort needs, where you can upload your text or Excel® files to our server and let Melissa take it from there. We'll presort your list, based on your selected parameters, to get you the lowest postage rates! MAILERS Online is a flexible, on-demand, software as a service (SaaS).

 

There is nothing to install and MAILERS Online never requires disks or updates. Use on a list-by-list basis--with no contract or subscription, you're never locked in. Use NCOA to locate customers who've moved; clean and verify address data to reduce undeliverable-as-addressed mail; and append missing data like ZIP® Codes, carrier routes, and suite numbers for stronger targeting and more efficient processing and delivery.

 

Find out what can MAILERS Online do for you today:

http://www.melissadata.com/service/presort/uploadws.aspx

Melissa Data is set to attend Dreamforce #DF15 in San Francisco and will showcase its Listware for Salesforce all-in-one data cleansing app. Users are invited to download the app, submit a review to receive a free $15 Starbucks card, and be entered into a drawing for an Apple Watch. Come see us at North Hall Kiosk 1112!

Click here for more info!

Online Merchants Can Now Verify and Correct Worldwide Customer Addresses; Better Customer Data Reduces Shipping Costs and
Eliminates Online Fraud


Rancho Santa Margarita, CALIF. - June 25, 2014 - Melissa Data, a leading provider of contact data quality and integration solutions, today announced a new data quality plug-in for users of Shopware, ensuring powerful contact data quality for e-commerce applications. The Shopware plug-in enables online merchants to verify and correct addresses as they are entered, validating information from more than 240 countries and territories in real-time. The plug-in is based on Melissa Data's Global Address Verification capabilities and was developed by NetzTurm GmbH, a service provider for the implementation of online stores, search engine optimization and web design. The two firms are now engaged in an exclusive partnership for data quality in Shopware-based ecommerce sites.

Online merchants can instantly validate and cleanse international addresses, correcting and standardizing them into the official postal format of each geographic locale, and adding missing components such as postal codes or region. Data fields are populated automatically using an efficient type-ahead feature that auto-completes entries after the first few digits or letters have been entered. Data entry is not only correct, but also up to 50 percent faster with reduced keystrokes, improving the customer's online experience and increasing website conversions.

"With data quality integrated into Shopware, online shoppers have only one step between shopping cart and checkout, which can drastically reduce the drop-off rate during the checkout process. Bad data is eliminated at the source, improving the customer's overall shopping experience with faster, easier order entry and fewer delivery errors," said Gary Van Roekel, COO, Melissa Data. "For the online merchant, accurate shipping and billing information is everything - reducing online fraud, enabling smooth operations and ensuring the best overall customer service."

In addition to ensuring lower shipping costs, timely deliveries and lower return rates, better customer data also improves the success rate of merchants' direct marketing activities. The solution also supports online shops in reaching new markets and customer groups. Both Melissa Data and NetzTurm also plan to develop further joint plug-in technologies for other e-commerce platforms in the future.

Click here to download the Shopware data quality plug-in, available as a stand-alone product, or bundled with "One-Page-Checkout" from NetzTurm. The plug-in is available at a net price of 759 € including 5,000 queries valid for one year and the auto-completion feature for international addresses.

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Content Standards for Data Matching and Record Linkage

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By David Loshin

As I suggested in my last post, applying parsing and standardization to normalize data value structure will reduce complexity for exact matching. But what happens if there are errors in the values themselves?

Fortunately, the same methods of parsing and standardization can be used for the content itself. This can address the types of issues I noted in the first post of this series, in which someone entering data about me would have used a nickname such as "Dave" instead of "David."

By introducing a set of rules for pattern recognition, we can organize a number of transformations from an unacceptable value into one that is more acceptable or standardized. Mapping abbreviations and acronyms to fully spelled out words, eliminating punctuation, even reordering letters in words to attempt to correct misspellings - all of these can be accomplished by parsing the values, looking for patterns that the value matches, and then applying a transformation or standardization rule.

In essence, we can create a two-phased standardization process that first attempts to correct the content and then attempts to normalize the structure. Applying these same rules to all data sets results in a standard representation of all the records, which reduces the effort in trying to perform the exact matching.

Yet this process may still allow variance to remain, and for that we have some other algorithms that I will touch upon in upcoming posts.


By David Loshin

In my last few posts, I discussed how structural differences impact the ability to search and match records across different data sets. Fortunately, most data quality tool suites use integrated parsing and standardization algorithms to map structures together.

As long as there is some standard representation, we should be able to come up with a set of rules that can help to rearrange the words in a data value to match that standard.

As an example, we can look at person names (for simplicity, let's focus on name formats common to the United States). The general convention is that people have three names - a first name, a middle name, and a surname. Yet even limiting our scope to just these components (that is, we are ignoring titles, generationals, and other prefixes and suffixes), there is a wide range of variance for representing the name. Here are some examples, using my own name:

• Howard David Loshin
• Howard D Loshin
• Howard D. Loshin
• David Loshin
• Howard Loshin
• H David Loshin
• H. David Loshin
• H D Loshin
• H. D. Loshin
• Loshin, Howard D
• Loshin, Howard D.
• Loshin, H David
• Loshin, H. David
• Loshin, H D
• Loshin, H. D.

There are different versions depending on whether you use abbreviations or full names, punctuation, and the order of the terms. A good parsing engine can be configured with the different patterns and will be able to identify each piece of a name string.

The next piece is standardization: taking the pieces and rearranging them into a desired order. The example might be taking a string of the form "last_name, first_name, initial" and transforming that into the form "first_name, initial, last_name" as a standardized or normalized representation. Using a normalized representation will simplify the comparison process for data matching and record linkage.


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