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Thoughts on Data Quality and Contact Validation

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Posts Tagged ‘CRM’

New CRM or ERP? Reduce Your Migration Risk

Birds and data have one thing in common: migration is one of the biggest dangers they face. In the case of our feathered friends, their annual migration subjects them to risks ranging from exhaustion to unfamiliar predators. In the case of your data, moving it to a new CRM or ERP system carries serious risks as well. But with the right steps, you can mitigate these risks, and preserve the asset value of your contact database as it moves to a new system.

In general, there are two key flavors of data migration, each with their own unique challenges:

The Big Bang Approach. This involves conducting data migration within a small, defined processing window during a period when employees are not actively using the system – for example, over a long weekend or holiday break.

This approach sounds appealing for many sites, because it is the quickest way to complete the data migration process. However, its biggest challenge involves data verification and sign-off. Businesses seldom conduct a dry run before going live with migration, resulting in the quality of migrated data often being compromised.

One particular issue is the interface between a new enterprise system and internal corporate systems. According to TechRepublic, enterprise software vendors still suffer from a lack of standardization across their APIs, with the result that every integration requires at least some custom configuration, leading to concerns about both data integrity and follow-on maintenance.

The Trickle Approach. Done with real-time processes, this approach is where old and new data systems run in parallel and are migrated in phases. Its key advantage is that this method requires zero downtime.

The biggest challenge with this approach revolves around what happens when data changes, and how to track and maintain these changes across two systems. When changes occur, they must be re-migrated between the two systems, particularly if both systems are in use. This means that it is imperative for the process to be overseen by an operator from start to finish, around the clock.

Beyond these two strategies, there is the question of metadata-driven migration versus content-driven migration – another major hurdle in the quest to migrate genuine, accurate, and up to date data. IT might be more focused on the location of the source and the characteristics of each column, whereas marketing depends upon the accuracy of the content within each field. According to Oracle, this often leads to content that does not match up with its description, and underscores the need for close inter-departmental coordination.

Above all, it is critical that a data validation and verification system be in place before moving forward with or signing-off on any data migration process. The common denominator here is that you must conduct data validation and verification BEFORE, DURING, and AFTER the migration process. This is where Service Objects comes into play.

Service Objects offers a complete suite of validation solutions that provide real-time data synchronization and verification, running behind the scenes and keeping your data genuine, accurate, and up to date. These tools include:

One particular capability that is useful for data migration is our Address Detective service, which uses fuzzy logic to fill in the gaps of missing address data in your contact records, validates the result against current USPS data, and returns a confidence score – perfect for cleaning contact records that may have been modified or lost field data during the migration process.

Taking steps to validate all data sources will save your company time and extra money. With Service Objects data validation services, we’ll help you avoid the costs associated with running manual verifications, retesting, and re-migration. And then, like the birds, it will be much easier for you and your data to fly through a major migration effort.

ERP: Data Quality and the Data-Driven Enterprise

Enterprise resource planning, or ERP for short, integrates the functions of an organization around a common database and applications suite. A brainchild of the late 20th century – the term was coined by the Gartner Group in the 1990s – the concept of ERP has grown to become ubiquitous for organizations of all sizes, in what has now become over a US $25 billion dollar industry annually.

ERP systems often encompass areas such as human resources, manufacturing, finance, supply chain management, marketing and customer relationships. Their integration not only automates many of the operations of these functions, but provides a new level of strategic visibility about your business. In the ERP era, we can now explore questions like:

  • Where your most productive facilities are
  • How much it costs to manufacture a part
  • How best to optimize your delivery routes
  • The costs of your back office operations
  • And many more

Its functions often interface with customer relationship management or CRM (discussed in a previous blog post), which provides visibility on post-sale customer interactions. CRM is often integrated within ERP product suites, adding market intelligence to the business intelligence of ERP.

ERP data generally falls into one of three categories:

Organizational data, which describes the infrastructure of the organization, such as its divisions and facilities. For most firms, this data changes very slowly over time.

Master data, which encompasses entities associated with the organization such as customers, employees and suppliers. This data changes periodically with the normal flow of business.

Transactional data, based on sales and customer interactions. This data, which is the lifeblood of your revenue pipeline, is constantly changing.

Note that two out of three of these key areas involve contact information, which in turn can come in to the system from a variety of sources – each of which is a potential source or error. Causes of these errors can range from incorrect data entry to intentional fraud, not to mention the natural process of changing addresses, phone numbers and email addresses. And this bad data can propagate throughout the system, causing consequences that can include wasted manpower, incorrect shipments, missed sales and marketing opportunities, and more.

According to one research paper, data quality issues are often a key driver for moving to ERP, and yet remain a concern following ERP implementation as well. This leads to a key concept for making ERP work for you: automated systems require automated solutions for data quality. Solutions such as Service Objects’ data verification tools ensure that good data comes into the system in the first place, leveraging constantly updated databases from sources such as the USPS and others. The end result is contact data quality that doesn’t depend on human efforts, in a chain that has many human touch points.

ERP is part of a much larger trend in business computing, towards centralized databases that streamline information flow, automate critical operations, and more importantly have strategic value for business intelligence. With the advent of inexpensive, cloud-based software, the use of these systems are spreading rapidly to businesses of all sizes. The result is a world that depends more than ever on good data quality – and the need to use tools that ensure this quality automatically.

What Is Data Onboarding – And Why Is It Important?

Photo female hands holding modern tablet and man touching screen.Businessmans crew working new investment project office.Using electronic devices.Graphics icons, stock exchanges interface.

What is the best marketing database of all?

Statistically, it is your own customers. It has long been common wisdom that existing customers are much easier to sell to than new prospects – but what you may not know is how valuable this market is. According to the Online Marketing Institute, repeat customers represent over 40 percent of online revenue in the United States, while being much less price-sensitive and much less costly to market to. Moreover, they are often your strongest brand advocates.

So how do you tap into these customers in your online marketing? They didn’t share their eBay account or their Facebook page with you – just their contact information. But the science of data onboarding helps you turn your offline data into online data for marketing. And then you can do content channel or social media marketing to people who are not just like your customers, but are your customers.

According to Wikipedia, data onboarding is the process of transferring offline data to an online environment for marketing purposes. It generally involves taking this offline data, anonymizing it to protect individual privacy, and matching components of it to online data sources such as social media or content providers. Beyond monetizing customer information such as your CRM data, it has a host of other applications, including:

  • Look-alike marketing, where you grow your business by marketing to people who behave like your customers
  • Marketing channel assessment, where you determine whether your ads were seen and led to increased sales across multiple channels
  • Personalization, where you target your marketing content to specific customer attributes
  • Benchmarking against customer behavior, where you test the effectiveness of your marketing efforts against actual customer purchasing trends

This leads directly to the question of data quality. The promise of marketing technologies such as data onboarding pivots around having accurate, up-to-date and verified data. Bad data always has a cost in time and resources for your marketing efforts, but this problem is magnified with identity-based marketing: you lose control of who you are marketing to and risk delivering inappropriate or confusing brand messages. Worse, you lose the benefits of customizing your message to your target market.

This means that data validation tools that verify customer data, such as email addresses, help preserve and enhance the asset value of your offline databases. Moreover, you can predictively assess the value of marketing leads through cross-validating data such as name, street address, phone number, email address and IP address, getting a composite score that lets you identify promising or high-value customer data at the point-of-entry.

Online marketers have always had many options for targeting people, based on their demographics, activity, or many other criteria. Now your existing customer database is part of this mix as well. As your data becomes an increasingly valuable marketing asset, taking a proactive approach to data quality is a simple and cost-effective way to guard the value of this information to your marketing – and ultimately, your bottom line.

The Difference Between Webhooks and APIs

The word “webhook” sounds really cool, and it is, but what exactly is it? What does a webhook do and how is it different from an API? What do webhooks have to do with Service Objects’ APIs?

What is an API?

In order to better understand webhooks, let’s first define API, or “application program interface.” APIs are pieces of code developed to execute some sort of logic. They are building blocks used to create other software, which can include creating other APIs. They serve as a common interface between two separate applications, allowing them to interact by sending and receiving data.

APIs can be used internally to support other processes within a company or they can be provided to the public as a paid or unpaid service. Google Maps API, for example, makes it possible to embed a Google map on a webpage. By using the Google Maps API, a web developer has a simple way to include an official Google map pinpointing their business’s exact location. There’s no need for any special coding or reinventing of the proverbial wheel.

Another example would be Service Objects’ address validation API, which makes it possible for our customers to input an address and receive standardized and corrected address information from our USPS CASS Certified database engine.

What is a Webhook?

Webhooks, for the most part, use APIs. Applications that have a mechanism for webhooks will often use a webhook when an event requiring custom logic has been triggered. Events are typically triggered by a workflow or some type of data entry, but other event types exist.

Webhooks give external developers opportunities to implement some sort of custom logic that either executes and returns results or executes custom logic for processes or purposes outside of the given application or both.

Using Marketo marketing automation software and Service Objects’ data validation APIs as an example, when an address is saved or added to a contact in Marketo, a webhook could be used to automatically validate the address using one of our address validation APIs such as our DOTS Address Validation – US 3 API. When the data is available, it is sent to an API call. In this case, there’s no polling from an external application of the host to check back periodically for data to validate.

So, from the standpoint of providing a webhook to a third party such as Service Objects, the intent is to enable that third party to push data back into your Marketo instance or trigger other operations outside of it. In our example, Marketo can send address data to Service Objects and trigger the address validation API thanks to the webhooks that provide this ability. Learn more about Service Objects for Marketo here.

In contrast, from the standpoint providing an API without webhooks, the intent is to enable others to trigger responses from your API to use strictly in their own applications.

There is no purpose to a webhook without an API, but the reverse is not true.

What Does All of This Mean to You?

It means that data validation is easy! Sign up for a free trial and find out just how easy and effective our webhook-powered APIs are.

The Importance of Data Quality for CRM

The Importance of Business Data for CRM, Service ObjectsWhat are your customers telling you about your business?

This question has always been the key argument for customer relationship management, or CRM for short. Capturing data about your customers can tell you how many people eat steak at your restaurant on Thursdays, or who buys polo shirts at your clothing store. It provides visibility about who is calling with customer issues, so you can improve your products and service delivery. And in an increasingly interconnected world, related tools such as identity graphs can now track customer behaviors across different vendors and channels – for example, who bought a product, with what credit card, after seeing it on a specific social media platform .

Perhaps most importantly, CRM does what its name implies: it helps you understand and manage the relationship between you and your customers. Good CRM also benefits the customer as well as your business. Done correctly, it represents a single view of the customer across all departments in the organization, to build a cohesive experience for these customers. Knowing who your customers are is strategic and personal at the same time, and its impact ranges from remembering their birthdays to driving customer growth and retention.

So how important is CRM data quality? Bad data isn’t just an annoyance – it is a real, make-or-break cost for many companies. According to a Gartner survey, users of one major CRM system disclosed that poor data quality cost their companies over US $8 million per year on average, with some respondents citing costs of over $100 million annually ! These costs range everywhere from time and money spent catching and managing these mistakes, all the way to losing customers to poor service or missed opportunities. For companies of all sizes, the amount of inaccurate or outdated CRM data ranges from 10% to 40% of their data per year.

Where does bad CRM data come from? A number of sources. For example:

  • Fraudulently entered data: for example, customers who enter “Donald Duck” or key in a phony phone number to get a customer perk or avoid customer registration
  • Errors at the data entry level
  • Duplicate information
  • The natural moves and changes that take place in business every year

Whatever the sources of bad data, simply waiting and letting it accumulate can quickly degrade the value of your CRM database, along with concomitant costs in human intervention as a result of invalid or incorrect customer records. And without a database management plan in place, and specific stakeholders taking ownership of it, the economic value of this data will continue to degrade over time.

While ensuring data accuracy is important, it is also one of the least favorite tasks for busy people – particularly for information such as CRM data. This is where companies like Service Objects come in: our focus is on automated validation and verification tools that can run through an integrated API, a batch process or a web-based lookup. These tools range from simple address and phone verification all the way to lead and order validation, a sophisticated multi-factor process that ranks a customer’s contact information with a validity score from zero to 100. All of these tools validate and cross-verify a contacts’ name, location, phone, email address, and device against hundreds of authoritative data sources.

CRM data truly represents the voice of your customer, and it can serve as a valuable asset for strategic planning, sales growth, service quality, and everything in between. Using the right tools, you can painlessly make sure that this data asset maintains its economic value, now and in the future. In the process, you can leverage technology to get closer to your customers than ever.

Name Deduplication Techniques

Name Tag, Hello My name is ....

Identifying Duplicate Records

The bane of any Database Administrator is maintaining duplicate records. They take up unnecessary space and generally do not provide any added value to contact records. A more challenging task for Database Administrators is how to identify and merge records which might be duplicates, and in particular, duplicate names.

There may be variants for a given name which might not be easily identified in a query, but they are invariantly linked. A common example might be Joe Smith vs Joseph Smith. Both could be referring to the same person depending on how the user may have entered their name.

Name Variants, Finding the Common Name

A particularly useful feature of the Name Validation 2 service is the Related Names output field. This field provides a comma separated list of first name variants for a provided name. For example using the given name; Joe, related names returned include Joel, Joeseph, Joey, Josef, Joseph, and José.

With this information, it becomes easier to identify names which are related but in a different form. There may be cases, however, where names cannot be identified as related but can be linked from similarity. Some examples include names that are misspelled or alternate names which are not related but similar. These names can still be identified through the Similar Names output fields of the Name Validation 2 service.

Similar Sounding Names

DOTS Name Validation 2 employs sophisticated similar name matching algorithms to match names drawing from a database of international names with up to 1.4 million first names and 2.75 million last names. First and last name similar results are returned in a comma separated list which can be used to compare against names that already exist in the database.

An example similar name result for the given name; Robert Smith, would return similar first names Rhobert,Róbert,Robertt,Roebert,Roibert,Rubert,Robbert, and similar last names Smyth,Smithe,Smiith,Smiyth. Of the similar names that are found, names are returned in order of most common to least common.

Merge and Promote the Winning Record

Using these results, a query can potentially link similar or related names and identify records which are duplicates. Once duplicate records are identified, the question becomes which should be promoted as the winning record? This decision can depend on factors based on business logic, perhaps a record which contains other vital contact points such as address or phone number or perhaps entry date is chosen as the winning record. Once a winning record is chosen, a merge process is incorporated to merge contact fields from identified duplicates to build a complete record.

Conclusion

Ridding your database of duplicate contact records can be an arduous task, but with the help of Name Validation 2, it doesn’t have to be. Leveraging the vast quantity of names that Name Validation 2 draws upon yields a top quality solution to identifying duplicates through related and similar names.

For more information about Name Validation 2 service, or to receive a free trial key, click here.

For developers, our Name Validation 2 documentation can be found here.

Impacts of Bad Data Lead to Negative Consequences

Marketing Automation and Your Contact Records: A Five Part Series That Every Marketer Can’t Miss (Part 2)

Data integrity is beyond a doubt “the” cornerstone of your marketing campaigns. Think carefully about this. ALL company decisions, both operational and strategic, are based on the information you collect from your data. And we’ve already acknowledged that bad data exists in your marketing automation platform. So just how deep do these impacts go? Let’s dive right in, looking closely at the top two offenders: Mistrust and Costs.

Mistrust:

“If you can’t trust the data, what else will you base your decisions on? If you can’t trust the data, how much effort will be wasted checking and rechecking certain results to figure out which is correct? And how much effort will be spent in investigations, root cause analysis and corrective actions required to fix data problems?” Carol Newcomb, Consultant with SAS Data Management Consulting

It’s no joke. Mistrust happens both internally and externally. Remember in our last post we stressed the importance of establishing trust between your marketing and sales teams (internal)? Well, that same nurturing needs to happen with your vendors and customers (external). Especially since their data is tied to everything in your organization. I would venture to guess that your CRM is connected to accounting. What if, after all your hard work to gain your customer, their invoice was sent to the wrong address? It’s going to get back to you and YOU are going to need to fix it. But here’s the bigger problem: when mistakes like this become repetitive, your reps stop believing that the data in their contact records is genuine, accurate, and up to date. They oftentimes feel compelled to update their own records. What’s worse, your customers and vendors will become annoyed, being asked over and over again, from different sources, for their contact info. Savvy marketers must realize that small missteps like this can lead to bigger issues, putting your company’s reputation and brand directly in harm’s way. Left unaccounted for, mistrust will weaken your company’s foundation in much the same way that a trickle of water slowly erodes bedrock, causing irreversible damage.

This leads us to Costs:

“Most organizations overestimate the quality of their data and underestimate the impact that errors and inconsistencies can have on their bottom line.” The Data Warehouse Institute

Brace yourself…you ARE wasting money. That is, bad data is causing a loss of revenue. How many emails, direct mail, and phone calls go out on any given day? Knowing that 25% of your customer data is inaccurate due to duplicate accounts, intentional and unintentional data entry errors, lost contacts, aging contact records, there is a serious loss of productivity happening here. To demonstrate the cost of quality, let’s apply the 1-10-100 Quality Management rule by George Labovitz and Yu Sang Chang: it costs $1 to verify a record as it is entered, $10 to fix it later, and $100 if NOTHING is done, which leads to loss upon loss upon loss. And, we know that corporate data is growing at an average rate of 60% per year and climbing, so it’s all the more important to screen your data going in and then maintain and manage it over time. The takeaway: quality IN equates to quality OUT, saving you time, resources and money all the way around.

If you’re like me and enjoy a detailed checklist, you’ll appreciate the following. Business2Community has compiled a spot on list highlighting many of the consequences of bad data:

  • Lower customer satisfaction and retention
  • Loss of Revenue
  • Misinformed OR under-informed decisions
  • Dissatisfied sales and distribution channels
  • Lower productivity
  • Higher consumption of resources
  • Invalid reports
  • Failure of your marketing automation initiatives
  • Higher maintenance costs
  • Errors in product/mail deliveries
  • Increased churn rate
  • Distorting campaign success metrics
  • Higher spam counts and un-subscriptions
  • Negative publicity on social media

Hungry for more? Great! Let’s begin focusing on where to find the problems and inconsistencies so we can clean up the mess. In Part 3 of our series, we’ll get up close and personal with a lead form, how these can go wrong, and then how to correct them.

If you are interested, Service Objects provides a free Data Quality Scan that will give you insight into the quality and accuracy of your contact data. Click here to get your free scan.

Up Next: Part 3: Data Breakdown Happens. Know the Reasons “Why” and Protect it from the Start

Make Marketing Automation Work for You

Marketing Automation and Your Contact Records: A Five Part Series That Every Marketer Can’t Miss (Part 1)

Are you keeping up with the competition? If yes, then you’re likely using one of these excellent marketing automation platforms to run your campaigns:

Marketing Automation2No doubt, the planning, coordinating, and executing of your marketing efforts has never been easier. But, here’s the kicker: these platforms are only as good as the quality of your contact data.

There’s a common misconception that the quality of contact record data is automatically maintained within marketing automation platforms, but, in reality, these platforms are not built to correct contact records for accuracy nor genuineness.

Without accurate, genuine, and up-to-date contact records, even the most sophisticated and expensive platforms are handicapped from performing well. According to SiriusDecisions, it is estimated that over 25% contact records contain inaccurate or critical errors. In addition, 70% of your contact records will become obsolete/change over the year. Over time and quite systematically, the integrity of your contact records will become suspect, translating to missed lead opportunities across multiple marketing channels. So how can you decipher whether the quality of your contact records is good or bad? This is something we will look at in this five-part series.

Reaping The Benefits

Switching gears, let’s imagine that your marketing automation is working at its full potential. You’re in a position to see some serious return on investment, along with reaching other important marketing and sales goals. We’ve listed three key benefits below to demonstrate why good data is at the heart of maximizing your marketing automation performance:

  • Cutting expenses—Some marketing platforms charge by the contact record. Simply correcting or eliminating bad records will result in cost savings. And this is just the tip of the iceberg. We will cover this in more detail as part of the series.
  • Increasing revenue—Handing off accurate contact records to your sales team means better contact rates and more sales, not to mention a happy sales team.
  • Accurately tracking and monitoring marketing campaigns—Good decision-making is based on good data. Accurate, measurable data is ESSENTIAL in order for these campaigns to be successful. Data needs to be precise, starting with your contact records.

Sounds so simple right? It absolutely can be, again, as long as your data is accurate, genuine, and up-to-date. And, we’ll repeat this point as many times as it takes: in doing so, you WILL save time and money!

Working Smarter, Not Harder

Think about it: managing contact records is labor-intensive, especially in a large company. Marketing and sales teams need to establish a good workflow to efficiently turn leads into profits. And as we’ve discussed, even the best resources might need a little support themselves in order to get top results. How frustrating is it to hear complaints from your sales team, time, and time again, about bad contact information, incomplete profiles, or lead rejection? As the size, speed, and values of information increase, you might soon be spiraling out of control. The last thing you want is to contribute to the poor quality of customer data which costs U.S. businesses a staggering $611 BILLION annually. Bottom line: there is no room for error. Teams must be able to trust each other and work efficiently together. Period.

So, consider this your wake-up call as we embark on a 5-part series into the realm of contact data integrity and the role it plays in your company. It’s imperative that marketing teams understand what “bad data” is and how it affects their bottom line. We’ll wrap up the series with some solutions about how you can take action and rid your marketing automation platform of bad contact data. Before signing off, here’s something to chew on until our next post:

It’s not a question of “IF” you have bad contact data, it’s a question of “HOW MUCH”.

If you are interested, Service Objects provides a free Data Quality Scan that will give you insight into the quality and accuracy of your contact data. Click here to get your free scan.

Up Next: Part 2: Impacts of Bad Data Lead to Negative Consequences

Increase Your Company’s Worth With Friendly APIs

Customer relationship management (CRM) software has become a powerful business tool. With a CRM tool such as Salesforce, Microsoft Dynamics CRM, Infusionsoft, or Oracle CRM On Demand, all customer data — including interactions and insights — is centralized for easy access and management.

As powerful as CRM applications may be, they are built for a single purpose: customer relationship management. Integrations, such as a data validation plug-in, can extend the functionality of CRMs, but only if APIs are created, and more importantly, well documented so that the third party developers can actually understand them.

CRM Basics

CRMs provide a centralized location for storing customer data and interactions. Early CRM applications, such as ACT! and Telemagic, were basically databases that stored customer phone and address data along with notes about the customer, recent orders, and so forth. Typically shared over a network, these programs allowed other employees to review contact notes as needed. They were also commonly used to create mail merge documents.

Today, modern CRMs are hosted on the cloud and loaded with robust contact relationship management, marketing automation, and social media features. These sophisticated applications are tightly focused on managing the customer’s journey. That’s what they’re designed for, and that’s what they do best. They are purposefully built to this end.

It’s a huge undertaking to create a piece of software to manage both the customer data (names, addresses, and contact information) and every single interaction across a multitude of channels. Small or large, CRM developers maintain a laser focus on their core product and its purpose. They’re concerned about making sure their software lives up to its core promise. They’re not necessarily concerned about extending their software to accommodate various users’ wish lists.

How User-Friendly APIs Ultimately Improve CRMs

While a CRM may have a plethora of tools built into it, the possibilities become endless when the CRM has an API that can be used by third party developers. For example, when Service Objects is able to integrate with a CRM’s API, we are able to create a data validation plug-in to clean up, standardize, and validate the data contained within the CRM.

This is valuable to everyone involved including:

  • The CRM developer — They don’t necessarily have the time or desire to add functions like data validation because their priorities are focused on the core product. With an API, valuable functions can be added without the developer having to expend resources on them.
  • The third party developer— Third party developers benefit by being exposed to the CRM developer’s customer base.
  • The end user — End users are happy to have external tools available through their company’s CRM platform where they can easily add the unique functions they want.

Creating an API for developers opens the door to new possibilities. A company like Service Objects can use the API to access the client’s data within the CRM, validate it, and then push it back in. With data validation plug-ins, the process is seamless for end users, the data quality improves, the business can operate more efficiently with less waste, and operating costs go down.

But there’s a catch: an API has to be available for a developer to use — complete with meaningful and current documentation. Integrations, such as a data validation plug-in for CRM, are magnitudes easier if the API documentation is up to date and organized.

We implore API creators to work hard to make a good API and supporting documentation. Doing so helps us all, and, most importantly, it helps all of our clients.

Moving To A New CRM? Clean Your Data FIRST!

Are you moving to a new customer relationship management (CRM) solution? While you’ve likely included various IT costs and end-user training in your migration budget, have you considered cleaning your data before your move it into your new CRM? Cleaning your data before a CRM migration is a best practice, one that will solve data quality problems, reduce costs, and position your new CRM for a successful implementation.

The Pitfalls of Migrating Dirty Data

Bad data, whether it’s a wrong address, misspelled name, duplicate or redundant, or flat-out fraudulent, is costly — and chances are, you have a lot of it. In fact, an analysis by DataBluePrint, The Cost of Bad Data by the Numbers, estimates that anywhere from 10 to 25 percent of data is inaccurate. This can seriously impact your bottom line time and time again.

For example, let’s say you have a mailing list of 100,000 and that 20 percent of your addresses are bad. That’s 20,000 mailers that disappear into the void, costing you print and material costs, postage, and manpower. Not only that, this waste happens every time you run a direct mail campaign. Meanwhile, you may have inaccurate customer data, resulting in lost or delayed orders, unhappy customers, and bad PR.

Why Fix the Data Problem During the Data Migration?

First, it’s much cheaper to fix data quality issues as part of the migration than it is to let them fester. Rather than continually sending mail to bad addresses, cleaning the data will immediately solve the problem (and many others). Data hygiene quickly pays for itself anytime you do it.

When migrating data, it makes sense to fix the data problem as PART of the migration project. This is the perfect opportunity to focus on data hygiene. Just as most people clean out their junk before moving to a new home, cleaning bad data before you move creates a fresh start.

Cleaning data during migration is much easier than doing it after your new CRM goes online. After all, your old system is familiar, making it much easier to find and resolve data quality issues. If you wait until the data is in your new CRM, you’ll probably have a much harder time because everything is new and different.

It’s generally easier to approve a data hygiene project as part of the CRM upgrade than as an after-the-fact add-on. When included as part of the upgrade, the data hygiene element is understood to be a contributing — and necessary — success factor. If you tag it on after the migration is complete, you’ll probably encounter pushback and repercussions for lacking the foresight to clean the data before the move.

Fixing Bad Data During Data Migration is Easier Than You May Think with the Right Tools

As part of the data migration, you will need to export your data from your legacy system and then import it into your new CRM. However, before you import it, you have the opportunity to clean it using an external data validation tool such as Service Objects’ data verification API. Service Objects’ CASS-certified data hygiene tools quickly identify and clean bad data by comparing records against a series of massive databases containing millions of accurate, standardized contact records.

This intermediary step is well worth doing as it instantly weeds out the bad data, leaving only accurate, verified data to import into your new CRM. If you’re planning a move, don’t forget to do a deep cleaning — of your data.

Sources: The Cost of Bad Data by the Numbers

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

Service Objects has verified over 2.5 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