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Customer Data Integration Effectively Implemented
Customer data integration is a difficult process without the right tools.
Integrating different customer data sources with different field types, address standards, naming conventions, etc is amonumentaltask. Especially when you consider how valuable the information is. The comments and history associated with these records are needed to insure a flawless customer experience.
Keys to effectiveimplementation
- Find someone who has done it before. Data Ladder’s customer integration specialists have completed hundreds of customer data integrations.
- The right tools make all of the difference. Every data integration is unique. Data Ladder’s DataMatch suite has; multiple customizable match definitions so you can identify duplicate and matching customers effectively (Same email, or same address, or same company name, etc.), the ability to merge data into a single golden record that combines duplicate/matching customer data with no data loss, and the ability to save your work for use in future customer data integrations.
- Get started quickly with an affordable solution. Why waste time waiting for large companies to return your phone calls? Why spend $100K on a solution that takes months to approve, and weeks to implement? Get started today and contactus for a free customized WebExdemonstrationon your data.
Increasing Customer Loyalty through Improved CRM Data Quality
Just like any long-term relationship, keeping your customers happy and loyal takes work and effort. In the business world, theres even a special term for it — CRM.
Used effectively, a CRM (customer relationship management) system pumps out reliable customer information and gives a company a birds eye view of a customer. From customer service to marketing, it gives an organization data to make smart decisions about sales strategies and approaches.
Unfortunately, if the information in a companys CRM system isnt accurate, it will not provide a high return on investment. According to DestinationCRM.com, there are three key elements to an effective CRM system: people, process, and technology. While the company itself may directly control the first two elements, some outside help can impact the technology by which the CRM system is managed.
Cleansing software can help streamline your CRM system. Besides input by users, the integrity of a CRM system can be compromised by the input of records from multiple sources, as well as the integration of data between the CRM and other data systems. Cleansing software will clear your system of the duplicates and typographical errors that can make the difference between an optimized CRM system and a non-functional one.
Think of your CRM system as a critical component of your organizations success. As an ever-evolving process for your organization, your CRM system provides important information on customer behavior.
Keeping it accurate through cleansing software can:
- Improve customer service efficiency
- Improve customer profiling and targeting
- Add cross-sell opportunities
- Improve closing rates
- Reduce costs
Let Data Ladder help you manage your CRM system and keep those customers happy. We offer cleansing software solutions for all different types of companies. Contact us for more information.
A Fuzzy Match Made in Data Cleaning Heaven
So, with the thousands of records a typical company database may have at any given time, how does one sort through the duplicates that might exist? How does one know whether Karoline Smith may also be Karol Smith? Well, let fuzzy matching software do the work.
While it may not be a familiar term to the office manager or administrator overseeing an email marketing campaign, fuzzy matching is certainly a key component of any data cleaning program. Using advanced algorithms that determine similarities between sets of data, results are neither true nor false. Fuzzy matching software relies on a set of parameters that finds terms related to query terms.
A sophisticated tool in the data cleaning arsenal, fuzzy matching software uses processes that work at various levels of interpretation from sentences to phrases.
With bad data costing companies nearly $611 billion a year in postage, printing, and staff overhead, it is critical to get on board managing an effective data cleansing program. Data Ladder offers the best in class fast fuzzy matching software with DataMatch 2011 software suite. Try our free trial today.
Stop Seeing Double with Your Email Marketing Program
Creating and sending professional emails for many businesses is an integral part of the online marketingpuzzle. From HTML emails and autoresponders to surveys and event invitations, an effective emailmarketing program can certainly provide streamlined communications from a company to a customer.
But what happens when an email marketing program isnt so streamlined? When a potential customergets two of the same emails in the same day?Unfortunately, your email can be
perceived as spam and lead to unwanted consequences. Duplicateemails are not only frustrating for the recipient, but for the company sending the email as well.
Causes of duplicate email issues can arise from several problems.
- Multiple subscriptions to a mailing list
- Messages matching more than one rule or filter within the software
- Potentially corrupt files
- More than one account or profile configured
Usually the company doesnt realize that they need to remove duplicate emails until they begin seeingthe removal requests from the recipients. Luckily, this problem has an easy solution. Here at DataLadder, we help clients remove duplicate emails from their marketing list.
Our high powered softwarepackage offers an easy way to manage and maintain your email addresses quickly and easily. Intuitiveand user-friendly, our software can remove duplicate emails in addition to maintaining a clean, smartlist.
Avoid embarrassing situations with your customers! Contact our sales department for more informationon our software suite.
Email Marketing That Truly Delivers
A recent article in BtoB Magazine highlighted the benefits of data quality in email marketing campaigns.
How effective can your email marketing campaign truly be if it isnt delivering what you want to who you want? The article highlights some valid points that can help improve the data quality of your email marketing campaign:
- Limit email bounces and spam complaints through double opt-in
- Segment inactive users for a welcome back campaign, and determine interest from response rate
- Manage data hygiene through removing duplicates, inactive or incorrect addresses
Its more than just about growing your businessit is also about reputation management with your most important people your customers.
Data Ladder can help maintain your reputation and your data hygiene through regular data cleansing services.
Download Free Trial or Contact us today for a consultation.
Spring Cleaning Takes on New Meaning for the Data Quality Tools Market
In business, theres nothing more important than operating at the highest level of efficiency. Good news for the world of data quality tools, where this critical need has led to a staggering $800 million industry.
From financial services to retail venues, data quality software have led the way in managing data and monitoring business intelligence. In fact, the demand has become so great in the industry that a growing number of data quality tool providers are looking for ways to converge with related markets in dataintegration and MDM (master data management) products.
Keeping up with the market demand can mean other important changes ahead for players in the dataquality tools market. From changing service platforms to addressing flexibility issues, it will be critical toaddress the integration of rapidly evolving technology.
According to Gartner research, by the end of 2010 the industry had seen 12.6% growth over theprevious year. The data quality tools industry is all encompassing, including data profiling, cleansing,parsing, standardization, matching, and monitoring.
A big trend moving forward for data quality tool vendors? Improving data quality in multiple areas, suchas customer/party or product/material lists. The flexibility required to manage a wide range of subjectareas will be a selling point for data quality tool vendors in upcoming years. It is estimated that 40% ofdata quality tool users are actively seeking solutions to improve data in multiple domains.
With forecasts for growth estimated at 16% over the next five years, things are looking pretty neat forthe data quality tools market.
Institutional Markets: Eliminating the Data Headache of an Untapped Goldmine
Hospitals, libraries, and schoolswhat do all these entities have in common?
Besides providing important services for our nation, these non-commercial organizations represent approximately 1/3 of the U.S. economy, and nearly $4 trillion of the GDP, according to MCH Strategic Data. This is an important fact for business to business marketers, who may want to consider the untapped potential of this huge market. In fact, these institutions actually have more buying power than most commercial businesses due to size and scope, and have been growing faster than many businesses for the last 50 years.
From a data quality perspective, this is critical information for marketers who want to work with this large segment. Unfortunately, many databases dont treat these institutions as the large potential revenue generators that they are due to the quality of the information provided, often leading to very poor, inaccurate data!
While these institutions can be a great source of business for an organization, treating these non-commercial entities like businesses in databases creates huge problems with data quality for several reasons:
- The SIC system used to classify businesses is out of date and doesnt work appropriately for institutions
- Many institutions share the same physical addresses and may have similar names
- Many typical business attributes do not work for institutions
From irrelevant records and duplicates to typographical and spelling errors, having poor,inaccurate data on this large group of prospects can be very unsettling from a data quality perspective. Institutions represent a large group of potential revenue, and it is important to have this data cleaned and appropriately segmented for use.
Using the appropriate attributes can help clean up some of the data. For example,using number of employees as a business attribute may be misleading for an institution such as a church, where a majority of the employees are actually volunteers.
Another issue arises with name similarity. Many institutions have similar names due to the fact they are publicly funded and may use their city as part of the name. This can be a challenge indata matching.
Data Ladder can help your organization sort through the data. From data cleansing to data matching services, we work with all types of data and can provide the right services make your databases work for you. Contact us for a consultation.
A Little Data Scrubbing Leads to Big Results
A recent article in BtoB Magazine highlights the advantages of data cleansing your email marketing list. Music for All, an Indianapolis-based company that runs school marching band functions and festivals, recently underwent an overhaul of its email database.
And the results are outstanding! From a list of over 120,000 subscribers, the company cut it nearly in half to 54,000. Using a combination of data cleansing, segmentation, and an archiving system, the updated list became an effective marketing tool that led to an increased email click-through rate of 60%! It also led to a 28% increase in the forwarding rate as well.
Any size company can benefit from a smart data cleaner. With Data Ladders suite of services, we can help you identify your data debacles. From our extensive library of name fields (from suffixes to nicknames) to our best in class duplicate record finder, we can help sweep up any confusion. Contact our sales team for more information.
Dirty Data Debacle a $3.1 Trillion Problem
With news about the nations economy broadcast in American living rooms every day, there seems tobe one piece of the financial puzzle that doesnt get much airtime. According to data and integrationexpert Hollis Tibbetts, principal and managing director at Artemis Ventures LLC, bad data is a $3.1 trillionproblem for the U.S. economy.
According to Tibbetts, it is a prevalent problem that goes largely unnoticed. In survey after survey,about half of IT executives consistently agree that data quality and data consistency is one of the biggestroadblocks to them getting full value from their data, yet consistently organizations fail to address thisissue, he said.
Easy to implement solutions do exist that can improve an organizations overall data quality profile.Data Ladder offers a suite of easy to use, affordable solutions for all sizes of business, from Fortune 500corporations to the small business.
Contact our sales team for more information.
Why Data Quality and Data Cleansing Projects Fail
Data Quality and Cleansing initiatives are essential to improving overall operational and IT effectiveness. However many efforts do not get off the ground and get stalled before they really start.
Why?
Time
Lack of focus and an attempt to use large providers (Vendors who charge $100K – $2 M per year) first
Data quality can mean many things, insuring financial transactions are done right, product data accuracy, customer data integrity, etc. It can become overwhelming, especially with the marketing campaigns and industry research sponsored by large providers pushing an enterprise wide fix everything first approach.
(Installing the large data quality solution) was like putting in a new ERP system that had to tie into everything. A big drain on our people, time, and energy. Even the vendor selection stage took four months with all of the presentations and due diligence
- IT Director at a Fortune 1000 Retailer
From the initial Request for proposal to implementation typically takes 6 to 9 months (Based on interviews with 14 customers of large data quality solution providers).
Immediate benefits can come from cleaning up the most important information in any company, customer information. Finding, removing, and merging duplicate customer information has significant vale. Additionally, the data cleansing of customer and sales lead data is easily understood and a good starting point for energizing the organization. Usually these areas are ignored by large scale implementations which typically focus on only internal data and ignore external data, like marketing or sales leads lists.
Money
No Identified ROI (Return on Investment) or TCO (Total Cost of Ownership).
Very few providers provide solid information on what the true ROI will be for the organization because, in all honesty, they dont know, and have seldom followed through to make sure theoretical benefits actually happened. Questions posed to large data quality vendors on this topic are usually not addressed specifically. In addition, most providers do not state the total cost of their software publicly or even within a completed quote. Quotes are left open ended with a variety of potential service charges which in practice increase the cost of an implementation by 36 – 75%. (Based on interviews with 14 large Data quality solution customers.) These facts make it difficult to get approval for six or seven figure data cleansing budgets.
Business users are typically not used and High end internal IT personnel are required for support
Most Data Quality solutions are very complicated and require high end IT personnel to implement. This significantly increases the true total cost of ownership and tends to keep business users and super users from fully embracing the project.
Professional Research has shown widespread doubts of the value of a large data quality solution
Quotes from Gartners 2009 Magic Quadrant for Data QualityTools by Ted Friedman and Andreas Bitterer
Gartner is an IT Industry Research Company with very thorough investigations into the Data Quality Tools segment (Large Providers Only, Over $400,000 per implementation)
Customers report only average satisfaction with the value of(Provide Ds) software relative to its price, and some customerscontinue to struggle with the overall high price of the software
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