Your marketing efforts live or die on the quality of your leads. Automated lead scoring capabilities can help figure out who is a potential purchaser for your products or services, and substantially improve the efficiency of your marketing efforts. But the term sometimes confuses people, because there is more than one kind of lead scoring. Let’s examine some of the differences.

Lead scoring versus lead scoring

If you use a marketing automation platform (MAP), it is likely to have some kind of lead scoring capabilities. Contact data quality providers, such as ourselves, also offer lead scoring – in our case, in the form of our DOTS Lead Validation and DOTS Lead Validation – International products. Similar terms, but each kind of lead scoring has a totally different meaning.

Marketing automation platforms often score leads by examining criteria such as demographics, purchase history, or so-called BANT (budget, authority, need and timeline) data: Marketo, for example, publishes a useful cheat sheet regarding lead scoring strategies. These scores may involve capturing data such as location, visiting your website, downloading a white paper, past purchases, and more.

Our lead scoring is different. We filter out potentially bad leads from your contact data, before you spend time and effort marketing to them. This is because we approach lead scoring from a data quality perspective, as opposed to predicting purchasing behavior. Here are examples of some of the bad actors we can help catch:

• Someone who signed up for your mailing list with a name of “Donald Duck” and a bogus address, so they could get a free marketing goodie
• A contact whose mailing address is in Tennessee, but whose IP address is in Tajikistan
• Leads that came from an automated bot designed to scrape information from your site
• Contact data that has gone out of date or is incomplete

So which kind of lead scoring should you use? The right answer is usually BOTH: make sure you have a database of genuine, accurate and up-to-date contacts first, and then analyze their potential value as prospects. This helps ensure you are working with clean data from people who are most ready to buy.

How we score leads

Both of our lead validation products analyze over 130 data points with your contact data, returning an overall validation score between 0 and 100. The six primary components we analyze include name, address, phone number, email address, IP address, and business data. Our Director of Engineering has written two recent blog articles taking a deeper dive into how we validate and score lead data, including this article on basic capabilities, and this article on advanced features.

A key feature for both products is the ability to set specific test types, which allow you to customize your analysis for specific use cases. This feature lets you customize which criteria are put to use in processing your contact data, such as favoring business or residential criteria, or not penalizing some data for being incomplete. For complex or custom use cases, we also offer the ability to create custom test cases employing your own business logic.

Building an integrated lead scoring strategy

Service Objects’ lead validation capabilities are designed to ensure the quality of your leads at the point of entry, using a simple numerical score that can be customized to suit your specific needs. These capabilities can be integrated directly into popular marketing automation platforms including Salesforce, Marketo, Hubspot and others using real-time API interfaces.

Want to learn more? Download our free white paper Marketing with Bad Contact Data: A Recipe for Disaster, or contact our friendly product experts to discuss your own specific needs. We’re here to help put more power and efficiency into your marketing efforts and create more ROI for your lead data.

Last month, we published a blog about DOTS Lead Validation, taking a deep dive into the services and core components that make up the building blocks of the service. This blog is designed to be a companion to that one – a Part 2 – taking a step back and looking at how those components fit together, as well as other important parts of the Lead Validation service.

Quick recap on Lead Validation’s components and scoring

In the previous blog, we focused on the core components of Lead Validation: Name, Address, Phone, Email, IP Address, and Business. Each component is analyzed independently using the tools and services previously described. The purpose of these tests is to determine how each given component looks unto itself. For example, if IP Address is being tested, we are looking at things like:

• What is the IP’s location?
• Is it a proxy?
• Is the proxy anonymously hiding the user’s information?
• Is it from a high risk country?
• Is it potentially a bot?
• Is it a mobile device?

After the components have been individually analyzed and scored, they are all cross-checked. Taking the same example of IP Address, we can look for things like this:

• Does the IP’s location seem to match the location of the phone and address?
• Are the IP and email linked?
• Can we connect the IP to a given business?

The final component’s score is based on whether it is valid and whether it matches other components. This means that a failing score for the IP Address component could be either because a major red flag about the IP itself was found, or because it was clearly not a match for the overall lead itself.

The purpose of Lead Validation is to grade leads as a whole, rather than how they are as individual components. There are a few ways to tell why the component was given a failing score, which will be described later in the “Messaging” section.

All components are given the same treatment described for IP Validation, and those component scores (each 0-100) are added together to get an overall score, which is Service Objects’ recommendation for that lead. A bit more detail on this will also be described in the “Test Types” section below.

There are over 200 tests occurring in each run of a lead in Lead Validation, each of which is set to either true or false. Lead scores rise or fall based on passing or failing tests.

Lead Validation’s Test Types

Test types are a critical part of each run through the Lead Validation service. A test type is essentially a set of instructions that tells Lead Validation how to process and score the lead. It tells the service which components to test, which tests to perform and how to weigh and score each component. Components are given influence (the percentage the component contributes to the overall score) and threshold scores for when they are considered Accept, Review or Reject.

Each test is linked to a component and has the possibility of contributing a positive score for a pass and a negative score for a fail. Not all tests have both a positive and negative possibility. For example, taking the test that compares the IP Address and the Business together, it gets a big positive score if we can match them together but does not get a negative score if we cannot. It is a very good sign if we can connect the dots between them, but is not necessarily bad because we cannot, so it does not make sense to penalize for a failed test there.

Test types exist because not all needs are the same. Test types cover most combinations of input data as well as how they should be handled. For example, one user might consistently have Name, Address, Phone but occasionally collect Email. They might want two test types, one to handle Name, Address and Phone and one to handle Name, Address, Phone and Email. In this case they do not want to harshly score a lead for not including Email since they consider it optional. Another user may collect these same fields but while they only occasionally get email, they may want the system to score users lower who do not submit it. So, they would use the test type that expects all four inputs.

There are sets of test types that tell the system to process the lead as a residential lead, penalizing when given business data. There are also sets that tell the system to strictly process the lead as a business, penalizing harshly for residential data. And there are test types that are primarily focused on businesses but allow for residential data, focusing more on success in matching than penalizing because a business lead was given a personal email. There are also test types designed to work better with students. They are a bit harder to score, but students would be potentially more mobile, meaning some of the comparisons testing should be less harsh for mismatches. New test types can easily be added to the system as well as custom test types that are tailored to a specific user’s needs. More on that next.

Customizations and custom test types

There is a wide range of test types available that fit most needs, but sometimes clients have very specific needs, and it may be best in these cases to make a custom test type. Custom test types allow us to tweak everything about the test type, from high level balancing of component influences down to specific test scoring. We analyze requests for specific rules and scoring options to determine if a current public test type is needed, or a new public test type makes sense to create, or if the request is so specific that it just makes the most sense to create a private custom test type for our client.

The types of requests we see are things like:

• I want to automatically fail the lead if any residential data shows up,
• I want to fail any lead that returns a free email (Hotmail, Yahoo, etc.),
• I want to fail any number that is a mobile phone regardless of its match to the lead.

Service Objects works with prospects and clients alike to tune and test specific test types to meet their needs.

In addition to custom test types, Lead Validation is highly customizable. When it makes sense, there is an available set of generic fields called InformationComponents that allows new outputs to be seamlessly added to the service without breaking current integrations. Clients interested in making use of available new InformationComponents can do so at their own pace. We could add something if a new data point becomes available that we cannot fit into the current output structure and is considered a good new fit for the service. Often we are also able to seamlessly add new features via Lead Validation’s Notes messaging system. More on that in the next section.

Messaging and other key data points

The latest and recommended operation of Lead Validation (ValidateLead_V3) contains a new improved messaging system that allows us to easily communicate key messages to our users. These are represented in the outputs by the following field categories: General Notes, Name Notes, Email Notes, IP Notes, Phone Notes and Address Notes.

General Notes contain information specific to the overall lead – primarily the results of various matchings between components. These notes give users a good idea of how well the components connected to each other (or didn’t). The other notes sections (Email, IP, etc.) have more detailed information on specific things we found out about the individual components (both good and bad) and give a good indication of why a high or low score was returned. A complete list of notes for all categories can be found here:

docs.serviceobjects.com/display/devguide/DOTS+Lead+Validation#DOTSLeadValidation-LeadEvaluation

Notes allow us to easily communicate important things we found out about the component. For example, going back to the IP Address component: IsPublicProxy identifies IP Addresses that have potentially been compromised and used fraudulently, IsBadSyntax identifies IP Addresses that do not follow the normal IP format, and IsHighRiskCountryIP identifies IP Addresses coming from countries known to conduct more fraudulent activities. In a soon to be released new build, IsBad and IsGood notes will be added to each component, giving a bird’s eye view of our best guess for the component. These are intended to help users determine if the components themselves are considered good or bad independently of how they fit in with the overall lead.

Other key fields that users can expect to see are:

• A standardized address based on the given address.
• The best fit phone contact we found.
• Locations for relevant components such as IP, address and phone.
• A Lead Type which uses name, email, phone and address to help determine if the given data was more likely tied to a residence, a business or a mix.
• A Lead Country that uses the various locations found by IP, address, phone and email to determine the best country fit for the lead.
• InformationComponents, which do not currently have any results but will in the future.

Conclusion

Hopefully this blog, in conjunction with the previous one, will give you a great overview to Lead Validation and what it can do. If you would like to learn more about Lead Validation, please visit our product page and developer guide.

DOTS Lead Validation International is easily our most robust and valuable service. This service improves the quality of your leads by correcting or eliminating unreliable contact record data while providing you with an overall quality score, so you can make informed business decisions. This service cross-references prospects’ name, address, phone, email, and IP address to ensure the lead information is genuine, accurate and up-to-date.

The quality of each of these data points is analyzed and scored separately and also combined to provide a weighted composite score for the overall lead quality and certainty. These individual and composite scores are included in the fifty-plus outputs the service provides, allowing you to tailor business logic to meet your needs.

Lead Validation International can be used like our other services; as a real-time API, as a cloud connector for major CRMs and marketing automation platforms, or as an FTP service. If none of these work for you, you can send us your list and we will validate and correct the leads for you.

Customizing Lead Validation International to Meet Your Needs

Even if you are missing some of the contact record data points (e.g., email, phone, address, name, or IP) that the service uses to validate leads, our service can be customized to use the data you do have, correct any issues with it and provide certainty scores. To customize our service to work with your available data, we suggest using the variable, TestType. There are a number different test types that address common variations of available data points and the needs of our clients. These test types can be further configured to meet the specific needs of your application and business. If you are not sure about what test type you should use, please don’t hesitate to reach out, we will gladly help with best recommendations. We are committed to making sure you receive the full benefit and power of our Lead Validation International service, and if none of the available test types meet your needs, we are happy to create custom ones that will.

Interpreting API Responses

Interpreting the response from our API is an important first step in determining the best ways to use the service and how the resulting validated data can benefit your business. There are only three “required” inputs to Lead Validation International: Country, TestType, and LicenseKey. If all three of these inputs are provided, Lead Validation International will attempt to process all the lead information that is present. If the required inputs are not provided, here are some of the errors you might encounter:

1. Error Code 1 – Authorization Codes

These errors indicate there is something wrong with the license key and we recommend that you double check you are using the correct key. One of the most common causes for this type of error is using a test key in a live environment (or vice-versa). Fortunately, this type of error is simple to detect and correct. In the test environment, the request URL should start with “https://trial.serviceobjects…” and be used with the test key sent to you. Production keys and URLs are different and issued only to customers. For other errors, please do not hesitate to reach out to us to help troubleshoot.

Error Description Code	Error Description	Additional Description
1	Please provide a valid license key for this web service.	There was no license key submitted to the service. Often, this occurs when the URL encoding has not occurred correctly.
2	The daily allowable number of transactions for this license key has been exceeded.	This does not apply to all keys, but some have a daily maximum transactions limit.
3	The monthly allowable number of transactions for this license key has been exceeded.	Some keys have a monthly maximum. You will encounter this value if you pass the monthly maximum.
4	The total allowable number of transactions for this license key has been exceeded.	The overall amount of transactions has been exceeded.

 

2. Error Code 2 – User Input 

Something is wrong with the inputs. Either necessary fields were left blank, or the inputs entered are too long.

Error Description Code	Error Description	Additional Description
1	That does not appear to be a valid TestType.	The given test type was either blank or an invalid test type. Please contact us to help assist with a test type that would suit your needs.
2	The Country input is missing.	There was no value in the Country field of the input. This is a required field that allows the service to cross reference different data points.

 

3. Error Code 3 – Fatal Errors 

This unlikely error indicates that the web service is behaving in an unexpected way. If you see this error in a production environment, please notify Service Objects at once.

Error Description Code	Error Description	Additional Description
1	Unhandled error. Please contact Service Objects.	Like it says, please contact Service Objects immediately and let us know what inputs you used to create this error.

 

4. Error Code 4 – Domain Specific 

Some of our other services return Domain Specific errors which indicate the validity or lack thereof of the information sent to the service. Lead Validation International works a bit differently since it is a composite service and cross-checks data points to provide an overall score for the lead. Currently, there are no Domain Specific errors in our Lead Validation International service.

Validated International Lead Outputs

If everything is working as expected, the service will return over fifty outputs including validated and corrected data, quality scores and any additional notes that might be helpful. The table below shows the most common outputs and a brief description of what they mean.

Return Value	Description
OverallCertainty	This is the total lead score. It represents how likely it is that the given lead is valid. 100 is the best score, and 0 is the worst.
OverallQuality	There are only three different values that can be returned for this field: Reject, Review or Accept. This is a quick and easy flag that can be used to identify the overall quality of the lead. If necessary, separate reject, review, and accept flags can be developed internally.
LeadType	Provides a classification that helps flag the type of lead given. Values will be Residential, Business, or Unknown.
LeadCountry	The country associated with the given lead. It is presented in ISO2 format.
NoteCodes	These will be an enumerated list of the overall codes associated with the lead. These note nodes will provide further information about the quality of the lead and the different data points that did or did not match up. As a general rule, NoteCodes that are lower than 100 are marks against a lead and notes higher than 100 are data points that indicate cross data matching in the lead.
NoteDesc	These will be the descriptions that are associated with the NoteCodes.
NameScore	This is the first of the different component scores that Lead Validation International provides. Along with an overall certainty score, Lead Validation International will provide a score for each of the different pieces of information given as inputs. This field ranges from 0 to 100 and indicates the probability that the given data name is valid.
NameQuality	Values will be Reject, Review or Accept. A quick and easy flag to accept or reject the name portion of the lead.
FirstName	The first name without diacritic (i.e., accented) characters.
LastName	The parsed out last name of the lead.
FirstNameClean	The first name without diacritic (i.e., accented) characters.
NameNoteCodes	An enumerated list of note codes that provide further information on the quality of the name.
NameNoteDesc	The text-based descriptions associated with the codes in the previous field.
AddressScore	The overall score of the address portion of the lead. It ranges from 0 to 100.
AddressQuality	A simple reject, review or accept flag indicating the quality of the address portion.
Address1	The validated Address1 line of the input address.
Address2	The validated Address2 line of the input address.
Address3	The validated Address3 line of the input address.
Address4	The validated Address4 line of the input address.
Address5	The validated Address5 line of the input address.
AddressLocality	The locality associated with the given input address. This is typically the City of the address.
AddressAdminArea	The Administrative Area associated with the input address. Typically corresponds to the State or province of an address.
AddressPostalCode	Validated postal code of the input address.
AddressCountry	Validated country associated with the input address.
AddressResolutionLevel	The resolution level to which the input address could be resolved. This will give some information on whether there is DPV, premise, or other data available for an address.
AddressNoteCodes	An enumerated list of codes that provide more information on the quality of an address.
AddressNoteDesc	Descriptive notes that correspond to the note codes for this field.
EmailScore	A score between 0 and 100 that ranks the validity of the given email address.
EmailQuality	A reject, review or accept flag that gives a simple flag on the quality of the input email address.
EmailCorrected	A True or False flag that indicates whether or not the input email address was corrected.
EmailNoteCodes	An enumerated list of codes that provide more information about the quality of the email address.
EmailNoteDesc	Descriptive notes that correspond to the note codes.
IPAddressScore	A score between 0 and 100 representing the validity of the given IP address.
IPAddressQuality	A simple reject, review and accept flag that will highlight the validity of the IP address portion of the lead.
IPCountry	The country associated with the IP Address.
IPLocality	The locality associated with the IP Address.
IPAdminArea	The Administrative area associated with the IP Address.
IPNoteCodes	An enumerated list of note codes that provide additional information about the quality of the IP address.
IPNoteDesc	Descriptive notes that correspond to the note codes.
Phone1Score	A simple reject, review, or accept flag that that indicates the quality of the given phone number.
Phone1Quality	A Simple reject, review or accept flag that that indicates the quality of the given phone number.
Phone1Locality	The Locality associated with the Phone1 field.
Phone1AdminArea	The Admin Area associated with the Phone1 field.
Phone1Country	The Country associated with the Phone1 field.
Phone1NoteCodes	An enumerated list of note codes that provide additional information about the quality of the Phone Number.
Phone1NoteDesc	Descriptive notes that correspond to the codes in the previous fields.
Phone2Score	A score between 0 and 100 that indicates the validity of the phone number in the Phone2 field.
Phone2Locality	A simple reject, review or accept flag that that indicates the quality of the given phone number.
Phone2Locality	The Locality associated with the Phone2 field.
Phone2AdminArea	The Admin Area associated with the Phone2 field.
Phone2Country	The Country associated with the Phone2 field.
Phone2NoteCodes	An enumerated list of note codes that provide additional information about the quality of the Phone Number.
Phone2NoteDesc	Descriptive notes that correspond to the codes in the previous fields.
PhoneContact	A Phone Contact Object. We will list this below.
InformationComponents	An array of information components. These are key-value pairs that can allow us to additional outputs and features to Lead Validation in the future.

 

When available, Lead Validation International can return the contact name and address information associated with the phone number.

Name	Name associated with the phone number.
Address	Address associated with the phone number.
City	City associated with the phone number.
State	State associated with the phone number.
Zip	Zip Code associated with the input address.
Type	Indicates the phone contact type. Returns can be Residential, Business or Unknown.

 

Hopefully, this quick primer is the first step to developing a better understanding of our Lead Validation International service and how it can be applied to your needs. Please reach out to us with any questions, and we will gladly provide recommendations, integration assistance or any other help you may need.

DOTS Lead Validation is a service combining many of Service Objects’ key contact validation features: you could think of it as our “greatest hits.” It provides validation for name, address, email, phone, IP and optionally business information. Each of these items are validated, scored and cross-referenced with each other to build a 0-100 score that helps companies tell good leads from fraudulent or fake ones.

Its basic functionality provides a wide spectrum of detailed analysis on contact records. However, many users are not aware of the flexibility this service has, ranging from customizable scoring to completely customized solutions. DOTS Lead Validation is a highly configurable service that can be engineered to fit the needs of any client. Let’s explore how we do this.

The key to this flexibility is what we call a Test Type: a set of rules or instructions that DOTS Lead Validation uses to interface with clients to customize their own evaluation criteria. These Test Types tell the service which inputs the client has, how to weight these inputs, which tests they want to run, and how to score these tests. They can vary by client: for example, one client may require email addresses, another may not have email addresses at all, and still another may not care whether one is there or not. Lead Validation gives you the flexibility to account for any of these options.

Service Objects maintains a substantial library of over 50 Test Types for typical client situations. These cover many combinations of the main inputs: name, business name, email, IP address, phone number and street address. The most common ones are listed in the Lead Validation Developer Guide, but if you have needs that fall outside one of these, just ask us – we might have exactly what you need!

There are four main flavors of Test Type that these combinations are built on:

• The first are the “normal” types. These are for residential contact records, and give preference to consumer leads. If you want to score leads containing personal information, this is the one to use.
• Second, “business only” types are designed for handling strictly business leads, if you want to avoid consumer leads. Adding a personal phone number or address to a business only Test Type will lead to substantial penalties in the lead scoring.
• A third category is the “business” type, which is similar to the business only type but allows for home business leads. It values business data, but prioritizes matching data over the distinction of business versus personal contacts. For example, if someone lists their personal cell phone as their contact number, this will not be penalized if their contact name matches the original given name.
• Finally, “educational” types aim to be a bit more lenient on mobile students. A student is more likely to be a roommate rather than a homeowner, and more likely to have location data that doesn’t match up: for example, they live in Michigan but have a cell phone registered in Ohio.

While Service Objects’ own library of Test Types encompass tried and true scoring models that fit the vast majority of our clients, we are also willing to work with clients with specific needs. Depending on how unique these needs are, we can either create new types to add to our library, or work with a client to create custom test types for their exclusive use. For example:

• A client may want to see everything that’s wrong with an IP address, but not have these errors affect the overall score.
• Another client may want to remove a series of tests from being performed.
• Still another may ask to weight a component differently: for example, they may seek to bump up the influence of an email’s result to 50% of the overall score.

Finally, outside of the Test Type process, we can periodically customize Lead Validation to allow new tests to be integrated. Each of our components (name, email, phone, etcetera) has a Notes section that allows for the addition of true/false responses, while another section called Information Components allows us to add new data values dynamically to the service.  For example, one customer recently asked us to specifically identify non-profit companies in addition to validating their business leads. In this case we added a flag called “IsNonProfit” as an identifier to the Notes section for the lead, and added an identifier for the type of non-profit company in the Information Components section.

DOTS Lead Validation is much more than a powerful marketing validation service – it is also home to a complete infrastructure for effective validation of your unique prospect database. Take advantage of our built-in customization capabilities, or just tell us your special need and we might even be able to incorporate it into the service! Try it today, and see how we can help make your data-driven marketing even more successful.

Service Objects recently released the latest and greatest version of DOTS Lead Validation, our lead verification API that cross-validates five critical lead quality components: name, street address, phone number, email address and IP address. The new service includes a technology update to some of the latest frameworks, a new interface, more options for customization, enhanced reporting and new algorithms.  We explore these in more detail below.

The new operation – ValidateLead_V3 –  offers more options for connecting with Service Objects.  In addition to SOAP, GET or POST, users also have access to a RESTful interface and can now choose XML or JSON for their response.  Current users should expect about the same sub-second speed for a transaction despite the new behind the scenes engine.  While the new engine is faster, it is also doing more work.

Regardless of REST or SOAP preference, users also will have access to a cleaner more descriptive new interface in the new ValidateLead_V3 operation.  The new DOTS Lead Validation fully supports both Residential and Business leads, however, the older interface was designed with Residential leads in mind and the new version was designed for both.  Some newer optional inputs include things like Domain name and EIN (business tax identification number).  Service Objects is working to make their business offerings even stronger and will be rolling out new features month by month.  Other optional inputs include more options for names (pre-split names and salutations).

The biggest difference for Lead Validation will be on the response.  One of the most important new feature is the “Notes” sections.  Each component (name, address, email, IP, phone, etc.) as well as the overall general lead has its own independent Notes section detailing most of the interesting things we discovered about the component.  The previous version of Lead Validation was limited to the three biggest warnings to describe what was going on with a lead.  The new version includes a lot more granularity including items both good and bad.

Individual component Notes contain specific key pieces of information about the component itself that help give more details on why a high or low score might have happened.  Was the IP Address an anonymous proxy or was it known to have been used for malicious purposes?  Is an Address vacant, is it deliverable, or is it missing key information for validation?  Is the name too short to be real, does it contain vulgar words or does it match to a well-known celebrity?  Is the phone number a mobile number, does it belong to a business or it is a google voice number?  These things and many more give clearer insight to the components of a lead.

General Notes contain information about the lead as a whole, considering multiple components.  Did the name and email match up?  Did the phone, name and address match up?  Does the IP Address seem to match the Business name or domain?  General notes often give the best indication about why a lead received a really high score or a really low one.

Other new outputs include some additional component based location information. In the previous version much of that was tracked and scored behind the scenes, but in the new version all three of the main location based components (address, IP address and phone) attempt to return a locality, admin area and Country of origin.  These can help provide some insight when data points do not seem to match up.

See for yourself how DOTS Lead Validation can help your business gain immediate insight into the quality of your leads. Sign up for a free trial key and test up to 500 transactions.

If you are old enough to remember the disco era, one of its biggest hits was “Got to Be Real” by Cheryl Lynn. (And if you’re younger, it’s been sampled over 100 times since.) Decades later, if you work in marketing, this tune should become your new theme song.

The lifeblood of any marketing operation is its lead generation efforts. And sadly, many of these leads aren’t real – according to industry figures, as much as 25% of your contact data is bad from the start, and from there 70% of it goes bad every year as jobs, roles and contact information changes. This ranges from fake or fraudulent contact data, often entered to gain access to lead generation bonuses, all the way to fat-fingered data entry.

Unfortunately, when your contacts aren’t real, the costs involved are very real:

Marketing costs: Direct mail costs can easily total $2-3 or more per piece mailed, while outbound telemarketing costs can top $35 to $60 per lead. In both cases, there is direct cost in both time and resources to working with bad contacts. Nearly any lead conversion strategy has a scalable cost per prospect, and bad or fake leads directly eat into these costs.

Wasted human effort: Take the labor costs, taxes and benefits you pay for the direct employees on your sales and marketing teams. Add in the costs of the overhead and infrastructure they require to do their jobs. Now multiply that by the percentage of time these people spend mitigating bad leads, and this total probably adds up to a very real and tangible cost, as well as impacting sales conversion rates.

Inefficiency: Ultimately, every business must deal with the problem of bad contact data. But the real question is when you deal with it. In many businesses, where data quality is no one’s responsibility, it gets fixed the hard way when prospects don’t answer and direct mail pieces bounce back. We describe it as the 1-10-100 rule, where it may cost a penny to catch bad contacts as they are captured, 10 cents to cleanse them after capture, and a dollar to work with uncorrected data. In addition, bogus leads can bog down your CRM or Marketing Automation platform, driving up costs and negatively impacting marketing campaigns.

Customer service reputation: Your all-important first impression on a potential customer pivots around responding to their requests – and if you fail to respond due to bad or misdirected contact information, the damage is often permanent. For example, if a customer enters their email incorrectly but are waiting to receive information from customer service, causing dissatisfaction and frustration.

The good news is that each of these costs can easily be controlled by automating the data quality process for your contact lead data, using tools that range from address verification to filtering out fraudulent names. For marketing operations, you can also use bundled lead validation capabilities that check over 130 data points to yield a lead quality score from 0 to 100, as well as lead enhancement that appends phone and contact information to your existing lead data.

The key to success in marketing, according to Forbes Magazine, is to know your customer. Data quality – making sure every contact record in your database is as genuine, accurate and up-to-date as it can possibly be – represents an important and cost-saving first step for this. Or as Cheryl Lynn would say, they’ve got to be real.

“We all know that direct marketing can be tough when at least 30 percent of all leads generated online are bogus. Here is the problem: marketing departments are incentivized to bring in as many leads as they can. However, it is nearly impossible to know which leads have potential just by looking at them.” – Geoff Grow, Founder and CEO, Service Objects

Service Objects’ Founder and CEO Geoff Grow understands better than most people the importance of having quality leads, increasing conversion rates and lifetime customer value, while avoiding fraud and waste. This is why Service Objects offers real-time API data quality solutions and cloud-based connectors for leading CRM and Marketing Automation providers. These solutions are designed to improve your marketing efforts through data quality excellence.

This video will show you how you can instantly identify, verify, and qualify lead information at the point of entry. You will learn about tools that verify and correct your contact information, score leads from 0-100 using proven audience and conversion models, validate addresses against geographic IP locations, and append neighborhood-level demographic information to your leads to increase their value.

A recent study by Marketing Sherpa found that when filling out web forms less than 40% of those surveyed provided accurate phone number and custom information—such as address—all of the time. The reality is most people are reluctant to give up their precious contact information when doing research or filling out requests for information. More often than not, the data is inaccurate, incomplete or fraudulent.

Where does this leave marketers, sales managers and lead generators? It leaves them sifting through mountains of contact data with the hope of isolating the true and valid leads that will bring more revenue to the bottom line. According to the Direct Marketing Association, 93% of marketers cite contact data quality as one of their most important issues.

Implementing a lead validation or verification solution is one way marketers and business managers can improve lead quality in real-time and at the source, and ultimately save money by shifting focus to high scoring leads, fixing questionable leads and discarding downright bad leads. 

Do the Math-
Here is a simple calculation showing where businesses save money by validating their leads:

Let’s say your business generates 100 leads per day or around 3,000 per month. 20% or 600 of those leads turn out to be bogus or bad leads. If your telesales team spends around 5 minutes per call and calls each lead an average of 3 times before qualifying and discarding bad leads, that is 15 minutes per lead. At $23/per hour that’s about $5.75 per lead—or $5.75 wasted on pursuing a lead that was ultimately determined to be bad. Multiply that by the estimated 600 bad leads per month and that’s $3,450 per month wasted telesales resources. Using a service like DOTS Lead Validation℠ will validate leads in real-time, before they arrive at telesales, and costs only about $.22 per lead or around $678/month for 3,000 transactions.

That is a savings of $2,772/month-with an ROI on the use of the Lead Validation solution in about 5.8 days.

In a nutshell, lead validation works by:

Validating whether the contact information is real. Is it a real address? Does 100 Main Street actually exist in the zip code provided?
Verifying that the contact name or business is associated or linked with the address, phone number and even IP Address provided.
Correcting address, city, state, and email elements as needed to make the lead data as complete as possible.
Scoring the lead based on the quality of data. Estimating the quality of data entails not only a check on data correctness as entered but quality as established through a method of proprietary checking and sophisticated cross correlation of supplied data with other data sources. An overall score is provided based on the quality of the pieces of contact information such as name, business name, email, IP address, phone number and street address. Recommending that you Accept, Reject or Review the lead.

Download our case study for more details on how DOTS Lead Validation can save your business money today!

Posted by Gretchen N.