Those of you who have been reading this blog have hopefully found it usefull, amusing, or maybe both. Thanks for your support,
For the new year, I've taken a new approach to things. Someone recently asked me what I do for a living, and when I told him I consulted with auto dealers, he responded by saying, "Oh, you're one of those guys who go into a business and tell them everything that is wrong!"
The more I though abouth that statement, the more it seemed to ring true. So, for 2008, I'm changing what I do for a living. I'm no longer a consultant; now I'm a COACH!
Coaches tell you how to improve the things you are doing, to make you better. They don't criticize, they work along side you. That's what I intend to do.
In making this change, I decided to change this blog as well. You will now be able to find future articles at http://subprimecoach.blogspot.com/.
I look foward to seeing you there soon!
For YOUR success,
Geoff
Thursday, January 31, 2008
Wednesday, January 16, 2008
“Subprime” Voted 2007 Word of the Year by American Dialect Society
Jan 07, 2008 Chicago — In its 18th annual words of the year vote, the American Dialect Society voted “subprime” as the Word of the Year. As ADS defines it, subprime is an adjective used to describe a risky or less-than-ideal loan, mortgage or investment. Subprime was also winner of a brand-new 2007 category for real estate words, a category which reflects the preoccupation of the press and public for the past year with a deepening mortgage crisis.
Presiding at the Jan. 4 voting session were ADS Executive Secretary Allan Metcalf of McMurray College and Professor Wayne Glowka, Dean of Arts and Humanities of Reinhardt College, chair of the New Words Committee of the American Dialect Society. Wayne edits the column “Among the New Words” in the society’s quarterly journal American Speech.
“When you have investment companies losing billions of dollars over something like bundled subprime loans, then you have to consider whether it’s important,” Professor Glowka said. “You probably also want to think about paying off that third mortgage.” Word of the Year is interpreted in its broader sense as “vocabulary item”—not just words but phrases. The words or phrases do not have to be brand-new, but they have to be newly prominent or notable in the past year, in the manner of Time magazine’s Person of the Year.
The vote is the longest-running such vote anywhere, the only one not tied to commercial interests, and the word-of-the-year event up to which all others lead. It is fully informed by the members’ expertise in the study of words, but it is far from a solemn occasion. Members in the 118-year-old organization include linguists, lexicographers, etymologists, grammarians, historians, researchers, writers, authors, editors, professors, university students, and independent scholars. In conducting the vote, they act in fun and do not pretend to be officially inducting words into the English language. Instead they are highlighting that language change is normal, ongoing and entertaining.
In a companion vote, sibling organization the American Name Society voted “Betray Us” as Name of the Year for 2007 in its fourth annual contest. Other notable recognitions included the Most Useful “green,” designating environmental concern; the Most Creative word in Googelganger, which describes a person who put his or her name into Google’s search engine; and “Happy Kwanhanamas” was deemed Most Unnecessary, as it is intended as a “happy holiday” greeting that covers religious holidays Kwanza, Hanukkah and Christmas
Presiding at the Jan. 4 voting session were ADS Executive Secretary Allan Metcalf of McMurray College and Professor Wayne Glowka, Dean of Arts and Humanities of Reinhardt College, chair of the New Words Committee of the American Dialect Society. Wayne edits the column “Among the New Words” in the society’s quarterly journal American Speech.
“When you have investment companies losing billions of dollars over something like bundled subprime loans, then you have to consider whether it’s important,” Professor Glowka said. “You probably also want to think about paying off that third mortgage.” Word of the Year is interpreted in its broader sense as “vocabulary item”—not just words but phrases. The words or phrases do not have to be brand-new, but they have to be newly prominent or notable in the past year, in the manner of Time magazine’s Person of the Year.
The vote is the longest-running such vote anywhere, the only one not tied to commercial interests, and the word-of-the-year event up to which all others lead. It is fully informed by the members’ expertise in the study of words, but it is far from a solemn occasion. Members in the 118-year-old organization include linguists, lexicographers, etymologists, grammarians, historians, researchers, writers, authors, editors, professors, university students, and independent scholars. In conducting the vote, they act in fun and do not pretend to be officially inducting words into the English language. Instead they are highlighting that language change is normal, ongoing and entertaining.
In a companion vote, sibling organization the American Name Society voted “Betray Us” as Name of the Year for 2007 in its fourth annual contest. Other notable recognitions included the Most Useful “green,” designating environmental concern; the Most Creative word in Googelganger, which describes a person who put his or her name into Google’s search engine; and “Happy Kwanhanamas” was deemed Most Unnecessary, as it is intended as a “happy holiday” greeting that covers religious holidays Kwanza, Hanukkah and Christmas
Selling Value to Your Subprime Customers
I tend to think that the one thing that universally seems to motivate people are pictures of Washington, Lincoln, Hamilton, Jackson, Grant and Franklin. These are the guys that appear on our money.
Value is what a customer looks for. Build value in what you can do for them. In Subprime, the value is more than just getting a vehicle. There is substantial value in a customer’s ability to rebuild their credit. You have to show them how credit problems can affect not only their auto loan but may also have an impact on their:
• Car insurance - Some companies base auto insurance premiums on credit scores.
• Cell phones - Providers increasingly rely on credit scores to sort the good risks from the bad credit.
• Elective medical procedures – Some doctors pull credit to see if you qualify for the monthly payment plan.
• Employment –Many companies will check credit before they decide to hire a candidate.
• Education – Low credit scores can disqualify applicants for university and federally funded student loans.
• Housing - Rental property owners may reject tenant applications with poor credit scores.
• Marriage - You can't marry your way out of a bad FICO rating. A married couple does not get a combined credit score.
• Utilities - Slow credit indications may require a sizable security deposit before utility service can be established
Many customers don’t realize that bad credit can affect almost every aspect of their life. What’s the value in helping them fix it? How many “presidential portraits” can they save by improving their credit? We probably are talking about hundreds, if not thousands of dollars, in their pockets.
Value is what a customer looks for. Build value in what you can do for them. In Subprime, the value is more than just getting a vehicle. There is substantial value in a customer’s ability to rebuild their credit. You have to show them how credit problems can affect not only their auto loan but may also have an impact on their:
• Car insurance - Some companies base auto insurance premiums on credit scores.
• Cell phones - Providers increasingly rely on credit scores to sort the good risks from the bad credit.
• Elective medical procedures – Some doctors pull credit to see if you qualify for the monthly payment plan.
• Employment –Many companies will check credit before they decide to hire a candidate.
• Education – Low credit scores can disqualify applicants for university and federally funded student loans.
• Housing - Rental property owners may reject tenant applications with poor credit scores.
• Marriage - You can't marry your way out of a bad FICO rating. A married couple does not get a combined credit score.
• Utilities - Slow credit indications may require a sizable security deposit before utility service can be established
Many customers don’t realize that bad credit can affect almost every aspect of their life. What’s the value in helping them fix it? How many “presidential portraits” can they save by improving their credit? We probably are talking about hundreds, if not thousands of dollars, in their pockets.
Tuesday, January 15, 2008
Forbes Magazine lists the 10 Best and 10 Worst Selling Models for 2007
The Forbes lists are based on sales reported from January through October 2007 and are compared to sales from the same period in 2006.
In the columns below the models are listed in the order found in the Forbes Magazine article. Next to each is the number of units reported sold for 10 months of 2007. The percentage up or down is the comparison of those reported sales with the same period in 2006.
2007 Best Selling Models:
1. Ford F-Series 588,952 -12.5%
2. Chev Silverado 526,575 -2.4%
3. Toyota Camry 398,868 +6.4%
4. Honda Accord 332,815 +10.2%
5. Toyota Corolla 317,796 -4.0%
6. Honda Civic 278,764 +2.2%
7. Chev Impala 270,504 +12.6%
8. Nissan Altima 239,800 +26.6%
9. Dodge Ram 214,569 -29.3%
10. Honda CR-V 184,003 +34.9%
2007 Worst Selling Models:
1. Cadillac XLR 1,525 -42.7%
2. Mazda B-Series 2,363 -35.3%
3. Isuzu Ascender 2,523 -40.3%
4. Jaguar X-Type 2,599 -44.2%
5. Jaguar S-Type 2,973 -44.3%
6. Audi A8/S8 3,092 -27.2%
7. Porsche Boxer 3,148 -21.5%
8. Lexus SC430 3,311 -33.2%
9. Isuzu i290/370 3,575 +21.1%
10. Jaguar XJ 3,637 -11.2%
In the columns below the models are listed in the order found in the Forbes Magazine article. Next to each is the number of units reported sold for 10 months of 2007. The percentage up or down is the comparison of those reported sales with the same period in 2006.
2007 Best Selling Models:
1. Ford F-Series 588,952 -12.5%
2. Chev Silverado 526,575 -2.4%
3. Toyota Camry 398,868 +6.4%
4. Honda Accord 332,815 +10.2%
5. Toyota Corolla 317,796 -4.0%
6. Honda Civic 278,764 +2.2%
7. Chev Impala 270,504 +12.6%
8. Nissan Altima 239,800 +26.6%
9. Dodge Ram 214,569 -29.3%
10. Honda CR-V 184,003 +34.9%
2007 Worst Selling Models:
1. Cadillac XLR 1,525 -42.7%
2. Mazda B-Series 2,363 -35.3%
3. Isuzu Ascender 2,523 -40.3%
4. Jaguar X-Type 2,599 -44.2%
5. Jaguar S-Type 2,973 -44.3%
6. Audi A8/S8 3,092 -27.2%
7. Porsche Boxer 3,148 -21.5%
8. Lexus SC430 3,311 -33.2%
9. Isuzu i290/370 3,575 +21.1%
10. Jaguar XJ 3,637 -11.2%
Thursday, January 10, 2008
Researchers Explain Why Subprime Loans Default
by Jennifer Reed, Editor, Subprime Auto Finance News, January 10, 2008
CAMBRIDGE, Mass. — A recent report from the National Bureau of Economic Research analyzed the trends of subprime auto defaults at a large U.S. financial institution The data taken into account during the analysis included applications and sales from June 2001 through December 2004. This information was combined with records of loan payments, defaults and recoveries through April 2006.
"This gives us information on the characteristics of potential customers, the terms of the consummated transactions and gives the resulting loan outcomes," officials indicated. "We have additional data on the loan terms being offered at any given time as a function of credit score, and inventory data that allows us to observe the acquisition cost of each car, the amount spent to recondition it and the list price on the lot," they continued.
Overall, the researchers said there were more than 50,000 applications in the sample period. The average applicant was in his mid-30s with the monthly household income of $2,411. "Just over one-third of applicants purchase a car," the writers reported. "The average buyer has a somewhat higher income and somewhat better credit characteristics than the average applicant. In particular, the company assigns each applicant a credit category, which we partition into high, medium and low risk. The applicant pool is 26 percent low risk and 29 percent high risk, while the corresponding percentages for the poof of buyers are 35 and 17. Furthermore, the officials pointed out, "A typical car, and most are around three to five years old, costs around $6,000 to bring to the lot. The average sale price is just under $11,000 (negotiated price rather than list price). The average down payment is a bit less than $1,000, so after taxes and fees, the average loan size is similar to the sales price."
As many would suspect, researchers indicate that many purchasers would rather put down less of a down payment instead of more. "Forty-four percent make exactly the minimum down payment, which varies with the buyer's credit category, but is typically between $400 and $1,000. Some buyers do make down payments that are substantially above the required minimum, but the number is small. Less than 10 percent of buyers make down payments that exceed the required down payment," according to the report.
Moreover, the paper discovered that more than 85 percent of the loans had an annual interest rate of more than 20 percent, with about half of the loans showing the state-mandated maximum APR. Researchers highlighted that the most states, according to the data, had a standard 30-percent cap. "Our data ends before the last payments are due on some loans, but of the loans with uncensored payment periods, only 39 percent are repaid in full.
Moreover, loans that do default tend to default quickly," the analyzers found. In fact, they said, "Nearly half of the defaults occur before a quarter of the payments have been made, that is, within 10 months."
Another commonly known trend identified in the paper was the fact that demand for subprime auto loans tend to occur in a certain season, closely around the time tax rebates are released. "Overall, demand is almost 50 percent higher during tax rebate season than during other parts of the year. This seasonal effect substantially varies with household income and with the number of dependents, closely mirroring the federal earned income tax credit schedule," officials said. According to the report, applications are 23 percent more common in February than in other months, with the approval rate coming in at 40 percent, as opposed to 33 percent during the rest of the year. "These seasonal patterns cannot be attributed to sales or other changes in the firm's offers. In fact, required down payments are almost $150 higher in February, averaging across applicants in our data, than in other months of the year," the paper said. "Indeed, we initially thought these patterns indicated a data problem until the company pointed out that prospective buyers receive their tax rebates this time of year," officials mentioned.
Breaking it down further, the analysts discovered that households with monthly incomes below $1,500 and at least two dependents, meaning the rebate could be about $4,000, the number of applications doubles during February, with the number of purchases tripling. On the other hand, for households with incomes above $3,500 and no dependents, meaning the rebate is likely zero, the number of applications and purchases shows no increase whatsoever. "About 65 percent of February purchasers make a down payment above the required minimum, compared to 54 percent in the rest of the year," writers said. "Moreover, we estimate that after controlling for transaction characteristics, the desired down payment of a February buyer is about $300 higher than that of the average buyer. This is an enormous effect given that the average down payment is under $1,000.
"Second, we find that the demand is highly responsive to changes in minimum down payments. A $100 increase in the required down payment, holding car prices fixed, reduced demand by 7 percent. In contrast, generating the same reduction in demand requires an increase in car prices of close to $1,000." The paper found that a $1,000 increase in loan size ramps up the rate of default by more than 16 percent. "This alone provides a rationale for limiting loan sizes because the expected revenue from a loan is not monotonically increasing in the size of the loan. We find that borrowers who are observably at high risk of default are precisely the borrowers who desire the largest loans," the researchers described.
"The company we study assigns buyers into a small number of credit categories. We estimate that all else equal, a buyer in the worst category wants to borrow around $200 more than a buyer in the best category, and is more than twice more likely to default given equally sized loans," they pointed out. The analysts found that risk-based pricing can only help a lender within "observably different risk groups."
"We also look for, and find, evidence of adverse selection within risk groups driven by unobservable characteristics. Specifically, we estimate that a buyer who pays an extra $1,000 down for unobservable reasons will be 8 percent less likely to default than one who does not given identical cars and equivalent loan liabilities," the writer explained.
Offering a word of caution, the paper highlights, "So, while there are limits to what we can conclude with data from a single lender, we think that our results highlight the empirical relevance of informational models of consumer credit markets."
Returning to the company at hand, the officials said, "Almost all buyers finance a large fraction of their purchase with a loan that extends over a period of several years. What makes the company an unusual window into consumer borrowing is its customer population." More specifically, the customers are generally low-income workers, and most are subprime borrowers. Fewer than half of the company's applicants display a FICO score above 500, the paper noted. Furthermore, given the low credit quality of many of the applicants, researchers indicated that the company has invested heavily in proprietary credit-scoring technology.
Turning to another fact, researchers wrote, "Within credit category, buyers who have higher incomes, have bank accounts, do not live with their parents and have higher raw credit scores are all less likely to default. However, the fact that these characteristics predict default and are not directly priced does not necessarily imply a serious adverse selection problem in financing choices. "For example, buyers who live with their parents tend to make larger down payments, but have a greater likelihood of default later
CAMBRIDGE, Mass. — A recent report from the National Bureau of Economic Research analyzed the trends of subprime auto defaults at a large U.S. financial institution The data taken into account during the analysis included applications and sales from June 2001 through December 2004. This information was combined with records of loan payments, defaults and recoveries through April 2006.
"This gives us information on the characteristics of potential customers, the terms of the consummated transactions and gives the resulting loan outcomes," officials indicated. "We have additional data on the loan terms being offered at any given time as a function of credit score, and inventory data that allows us to observe the acquisition cost of each car, the amount spent to recondition it and the list price on the lot," they continued.
Overall, the researchers said there were more than 50,000 applications in the sample period. The average applicant was in his mid-30s with the monthly household income of $2,411. "Just over one-third of applicants purchase a car," the writers reported. "The average buyer has a somewhat higher income and somewhat better credit characteristics than the average applicant. In particular, the company assigns each applicant a credit category, which we partition into high, medium and low risk. The applicant pool is 26 percent low risk and 29 percent high risk, while the corresponding percentages for the poof of buyers are 35 and 17. Furthermore, the officials pointed out, "A typical car, and most are around three to five years old, costs around $6,000 to bring to the lot. The average sale price is just under $11,000 (negotiated price rather than list price). The average down payment is a bit less than $1,000, so after taxes and fees, the average loan size is similar to the sales price."
As many would suspect, researchers indicate that many purchasers would rather put down less of a down payment instead of more. "Forty-four percent make exactly the minimum down payment, which varies with the buyer's credit category, but is typically between $400 and $1,000. Some buyers do make down payments that are substantially above the required minimum, but the number is small. Less than 10 percent of buyers make down payments that exceed the required down payment," according to the report.
Moreover, the paper discovered that more than 85 percent of the loans had an annual interest rate of more than 20 percent, with about half of the loans showing the state-mandated maximum APR. Researchers highlighted that the most states, according to the data, had a standard 30-percent cap. "Our data ends before the last payments are due on some loans, but of the loans with uncensored payment periods, only 39 percent are repaid in full.
Moreover, loans that do default tend to default quickly," the analyzers found. In fact, they said, "Nearly half of the defaults occur before a quarter of the payments have been made, that is, within 10 months."
Another commonly known trend identified in the paper was the fact that demand for subprime auto loans tend to occur in a certain season, closely around the time tax rebates are released. "Overall, demand is almost 50 percent higher during tax rebate season than during other parts of the year. This seasonal effect substantially varies with household income and with the number of dependents, closely mirroring the federal earned income tax credit schedule," officials said. According to the report, applications are 23 percent more common in February than in other months, with the approval rate coming in at 40 percent, as opposed to 33 percent during the rest of the year. "These seasonal patterns cannot be attributed to sales or other changes in the firm's offers. In fact, required down payments are almost $150 higher in February, averaging across applicants in our data, than in other months of the year," the paper said. "Indeed, we initially thought these patterns indicated a data problem until the company pointed out that prospective buyers receive their tax rebates this time of year," officials mentioned.
Breaking it down further, the analysts discovered that households with monthly incomes below $1,500 and at least two dependents, meaning the rebate could be about $4,000, the number of applications doubles during February, with the number of purchases tripling. On the other hand, for households with incomes above $3,500 and no dependents, meaning the rebate is likely zero, the number of applications and purchases shows no increase whatsoever. "About 65 percent of February purchasers make a down payment above the required minimum, compared to 54 percent in the rest of the year," writers said. "Moreover, we estimate that after controlling for transaction characteristics, the desired down payment of a February buyer is about $300 higher than that of the average buyer. This is an enormous effect given that the average down payment is under $1,000.
"Second, we find that the demand is highly responsive to changes in minimum down payments. A $100 increase in the required down payment, holding car prices fixed, reduced demand by 7 percent. In contrast, generating the same reduction in demand requires an increase in car prices of close to $1,000." The paper found that a $1,000 increase in loan size ramps up the rate of default by more than 16 percent. "This alone provides a rationale for limiting loan sizes because the expected revenue from a loan is not monotonically increasing in the size of the loan. We find that borrowers who are observably at high risk of default are precisely the borrowers who desire the largest loans," the researchers described.
"The company we study assigns buyers into a small number of credit categories. We estimate that all else equal, a buyer in the worst category wants to borrow around $200 more than a buyer in the best category, and is more than twice more likely to default given equally sized loans," they pointed out. The analysts found that risk-based pricing can only help a lender within "observably different risk groups."
"We also look for, and find, evidence of adverse selection within risk groups driven by unobservable characteristics. Specifically, we estimate that a buyer who pays an extra $1,000 down for unobservable reasons will be 8 percent less likely to default than one who does not given identical cars and equivalent loan liabilities," the writer explained.
Offering a word of caution, the paper highlights, "So, while there are limits to what we can conclude with data from a single lender, we think that our results highlight the empirical relevance of informational models of consumer credit markets."
Returning to the company at hand, the officials said, "Almost all buyers finance a large fraction of their purchase with a loan that extends over a period of several years. What makes the company an unusual window into consumer borrowing is its customer population." More specifically, the customers are generally low-income workers, and most are subprime borrowers. Fewer than half of the company's applicants display a FICO score above 500, the paper noted. Furthermore, given the low credit quality of many of the applicants, researchers indicated that the company has invested heavily in proprietary credit-scoring technology.
Turning to another fact, researchers wrote, "Within credit category, buyers who have higher incomes, have bank accounts, do not live with their parents and have higher raw credit scores are all less likely to default. However, the fact that these characteristics predict default and are not directly priced does not necessarily imply a serious adverse selection problem in financing choices. "For example, buyers who live with their parents tend to make larger down payments, but have a greater likelihood of default later
Wednesday, January 9, 2008
Do You Know Where Your Special Finance Leads Have Been?
by Jim Wagner.
Have Your Special Finance Leads Been Around the Block?
As you probably know, special finance leads have become big business. The other day I was talking to someone very involved in the automotive lead business who told me that there are over 1.5 million leads generated every month. That, he believes, is a conservative number. Four or five years ago there were only a handful of players in the auto lead business. Now there are over two dozen.
A side effect of this expansion is that marketing firms not primarily associated with automotive leads are entering the space. They are generating leads that are not necessarily genuine auto shoppers, but consumers who are initially interested in other products. These leads are being disseminated on the wholesale market. With the average cost of leads currently over $20, it pays to learn how to distinguish genuine auto shoppers and leads from people not primarily looking for auto loans. How do you go about doing so? In an article you’ll never find in a trade magazine, we’re going to tell you how.
The Wholesale Lead Network
Most of the leads that you’ve been purchasing are generated when a consumer starts searching for alternate finance options on the internet. Most of the time, these shoppers will use a search engine, such as Google, and use keywords like “auto loan” or “car finance“. Special finance lead generators pay big money to ensure that their landing pages, like the one below, come up high on the page when these terms are submitted.
If your lead provider is sending 100% of these leads to you, then you’re getting what you were promised. Of course, you’re not going to close every one of these leads, but at least you’re getting your money’s worth.
Wholesale Leads and Coregistration
When you sign a contract with a lead generator and ask for 150 leads a month, his goal is to organically produce these leads on his own landing pages. Let’s call him Generator A. However, he may have several dealerships in your area. Or, you may exist in a lead scarce market. If that’s the case, and he does not have enough “inventory”, then he’s going to look to the wholesale market for more leads to meet your demand.
Generator A will have pre-arranged partnerships, let’s say with Generator B and Generator C, where he can buy leads when his inventory runs out or sell when he has excess leads. This takes place automatically, so nobody feels the difference. As long as he’s done his homework about his wholesale partners and has investigated their lead quality, everyone wins. He gets the supply he needs and you are a happy paying customer.
However, the demand for leads has put pressure on everybody to source more and more volume. Let’s say, responding to this demand, A decides to start two new partnerships, with Generators D and E. Let’s also assume that D is in the payday loan business, and E is in the prepaid credit card business. Those leads are going to perform differently than the others because they are not organic auto shoppers. How does D and E generate auto leads if they are not in the auto business? Through a process called coregistration.
Coregistration
Coregistration is a common tactic online marketers use to generate many leads from a single customer. Simply put, a coreg lead is generated when a consumer, interested in a particular offer or product (such as the payday and credit card examples) is asked to “opt in” on related offers. If they agree, and choose “auto loans”, then a special finance lead is generated, sent through the wholesale network, and sold as a special finance lead to a dealership.
Before you panic and call your lead generator, understand that not all coreg leads are the same. For example, a consumer who subscribes to a free credit report service in order to prepare for an automobile purchase is a genuine auto shopper. This lead will perform as well as any other. I would feel good about buying these leads.
How can you ensure that the leads you buy are genuine auto buyers? How do you protect your close rate and maximize your return on investment? Unfortunately, there is no simple answer. You’re going to have to do your homework.
Have Your Special Finance Leads Been Around the Block?
As you probably know, special finance leads have become big business. The other day I was talking to someone very involved in the automotive lead business who told me that there are over 1.5 million leads generated every month. That, he believes, is a conservative number. Four or five years ago there were only a handful of players in the auto lead business. Now there are over two dozen.
A side effect of this expansion is that marketing firms not primarily associated with automotive leads are entering the space. They are generating leads that are not necessarily genuine auto shoppers, but consumers who are initially interested in other products. These leads are being disseminated on the wholesale market. With the average cost of leads currently over $20, it pays to learn how to distinguish genuine auto shoppers and leads from people not primarily looking for auto loans. How do you go about doing so? In an article you’ll never find in a trade magazine, we’re going to tell you how.
The Wholesale Lead Network
Most of the leads that you’ve been purchasing are generated when a consumer starts searching for alternate finance options on the internet. Most of the time, these shoppers will use a search engine, such as Google, and use keywords like “auto loan” or “car finance“. Special finance lead generators pay big money to ensure that their landing pages, like the one below, come up high on the page when these terms are submitted.
If your lead provider is sending 100% of these leads to you, then you’re getting what you were promised. Of course, you’re not going to close every one of these leads, but at least you’re getting your money’s worth.
Wholesale Leads and Coregistration
When you sign a contract with a lead generator and ask for 150 leads a month, his goal is to organically produce these leads on his own landing pages. Let’s call him Generator A. However, he may have several dealerships in your area. Or, you may exist in a lead scarce market. If that’s the case, and he does not have enough “inventory”, then he’s going to look to the wholesale market for more leads to meet your demand.
Generator A will have pre-arranged partnerships, let’s say with Generator B and Generator C, where he can buy leads when his inventory runs out or sell when he has excess leads. This takes place automatically, so nobody feels the difference. As long as he’s done his homework about his wholesale partners and has investigated their lead quality, everyone wins. He gets the supply he needs and you are a happy paying customer.
However, the demand for leads has put pressure on everybody to source more and more volume. Let’s say, responding to this demand, A decides to start two new partnerships, with Generators D and E. Let’s also assume that D is in the payday loan business, and E is in the prepaid credit card business. Those leads are going to perform differently than the others because they are not organic auto shoppers. How does D and E generate auto leads if they are not in the auto business? Through a process called coregistration.
Coregistration
Coregistration is a common tactic online marketers use to generate many leads from a single customer. Simply put, a coreg lead is generated when a consumer, interested in a particular offer or product (such as the payday and credit card examples) is asked to “opt in” on related offers. If they agree, and choose “auto loans”, then a special finance lead is generated, sent through the wholesale network, and sold as a special finance lead to a dealership.
Before you panic and call your lead generator, understand that not all coreg leads are the same. For example, a consumer who subscribes to a free credit report service in order to prepare for an automobile purchase is a genuine auto shopper. This lead will perform as well as any other. I would feel good about buying these leads.
How can you ensure that the leads you buy are genuine auto buyers? How do you protect your close rate and maximize your return on investment? Unfortunately, there is no simple answer. You’re going to have to do your homework.
Thursday, December 27, 2007
New FICO Score to be More Understanding
New FICO Score to be More UnderstandingDec 26, 2007 Consumers caught in the subprime mortgage crisis may find some relief with Fair Isaac’s new FICO 08. Aside from providing a more accurate risk assessment of consumer credit, the new formula also aims to reward customers for keep other credit accounts up to date.
“The main thing we tried to do with the score was to make sure it was in tune with current consumer behaviors,” said Fair Isaac’s Craig Watts. “We changed the formula to improve the predictiveness.”
The new formula takes into account consumer credit behaviors in all credit areas rather than focusing on accounts that have gone delinquent. Now, consumers who’ve fallen behind on one account could be rewarded for remaining in good standing with other credit accounts.
“If a person has a repossession or foreclosure on their credit score today, that casts a shadow over everything else. They are scored along with other people with serious delinquencies,” explained Watts. “But this new formula looks at not just serious delinquencies, but also at whether consumers have other accounts with positive credit histories. The consumer’s score is not penalized as much for serious delinquencies that are uncommon to his or her credit behavior.”
Although a consumer’s credit standing will vary from lender to lender, the new formula may present more opportunities for F&I managers to get consumer loans bought.
“Our expectation is that lenders will reduce the amounts of defaults on loans by 5 to 15 percent in certain demographic groups. It really helps with consumers who already have serious credit problems, those who are new to credit and those who are seeking credit.”
“The main thing we tried to do with the score was to make sure it was in tune with current consumer behaviors,” said Fair Isaac’s Craig Watts. “We changed the formula to improve the predictiveness.”
The new formula takes into account consumer credit behaviors in all credit areas rather than focusing on accounts that have gone delinquent. Now, consumers who’ve fallen behind on one account could be rewarded for remaining in good standing with other credit accounts.
“If a person has a repossession or foreclosure on their credit score today, that casts a shadow over everything else. They are scored along with other people with serious delinquencies,” explained Watts. “But this new formula looks at not just serious delinquencies, but also at whether consumers have other accounts with positive credit histories. The consumer’s score is not penalized as much for serious delinquencies that are uncommon to his or her credit behavior.”
Although a consumer’s credit standing will vary from lender to lender, the new formula may present more opportunities for F&I managers to get consumer loans bought.
“Our expectation is that lenders will reduce the amounts of defaults on loans by 5 to 15 percent in certain demographic groups. It really helps with consumers who already have serious credit problems, those who are new to credit and those who are seeking credit.”
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