Category: Online F&I

Worry about Mobility, Continued

This week, we examine the fourth piece of McKinsey’s automotive revolution, shared mobility.  This is really a collection of trends including car sharing, ride hailing, and mass transit.  I will show how to gauge whether a new program has the potential to be disruptive.  But first, let’s dispense with mass transit.

From Munich, you can ride the U-Bahn to the Schnellbahn, and get anywhere in Europe by fast rail.  This is where McKinsey’s analysis shows its European bias.  Europe’s population density is three times that of the United States, and her various rail systems carry twenty times the passengers.

American cities are linked by air, of course, but relatively few have commuter rail systems.  When you deplane at Las Vegas, for example, or Orlando, you are headed for the car rental counter.

“What’s happening in general, millennials, younger people, car ownership in and of itself is not the most important thing.”

When I worked at BMW, twenty years ago, they were already styling themselves a “mobility” company, and not solely a car company.  At the time, that meant mass transit.  If you look at BMW today, their investments tell a different story.  I won’t try to categorize Fair, Shift, Skurt, Scoop, and ReachNow – not today, anyway. Today I want to talk about capacity utilization.

If you’re like most people, you drive your car to and from work, plus errands and recreation.  Let’s call it 20 hours of use for the 112 hours per week you’re awake, or 18%.  In theory, any mobility scheme that increases capacity utilization will cause a proportional decrease in car sales. There is a variety of schemes, known collectively as Mobility as a Service.

“The success of a MaaS provider will be determined by how much utilization they can gain from their accessible fleet.”

Uber is the obvious example.  It increases utilization for the drivers, and reduces the riders’ inclination to buy a car of their own.  I meet people every day who won’t buy a car, or won’t buy a second car, because Uber meets their occasional driving needs.  In major urban areas, people have long gotten by without cars.  The way I see it, Uber has widened this circle out into the suburbs.

Uber will also take a bite out of traditional car rental, as will hourly rental services like Maven. Maven is basically Uber without the driver, good for business travelers who just want to attend their meeting and go back to the hotel.  Business travelers I know will often choose Uber over Hertz, depending on the city.

“Millennials like having an easy process, but they hate commitment,” Bauer said. “I think the next step for leasing has to be no fixed term, or a different way of term.”

Here in Atlanta, we have two subscription car programs, Flexdrive and Clutch.  It is wonderful to live in the nexus of so much new-auto activity.  Flexdrive is a joint venture of Cox Automotive and Holman Auto Group.  You choose from a variety of vehicles, and your monthly subscription includes insurance, maintenance, and roadside assistance.

The average car payment in America is $500.  Depending on the figures you use for gas, insurance, and maintenance, your car costs at least $7 per hour of use.  This may sound fanciful, accounting for the car as a utility, but this is exactly the way a new generation of mobility providers look at it.  A monthly subscription of $500 is the price point advertised by Fair.  Zipcar and Maven hourly rates start at $8.

The chart above shows that car sales per capita have declined, in fits and starts, by about one in six over the last forty years.  This reflects trends like gradually increasing urbanization and longer-lived cars, which are minor worries for our industry.  Increasing utilization, through various forms of renting and sharing, has the potential to be a major worry.

Predictive Selling in F&I

We have all seen how Amazon uses predictive selling, and now this approach is finding its way into our industry.  In this article I compare and contrast different implementations, and discuss how the technique may be better suited to online than to the F&I suite.

If you read Tom Clancy, you might like Lee Childs.  If you bought a circular saw, you might need safety goggles.  To draw these inferences, Amazon scans for products that frequently occur together in the order histories of its customers.  You can imagine that given their volume of business, Amazon can fine-tune the results by timeframe, department, price, and so on.

The effectiveness of predictive selling depends on two things: the strength of your algorithms, and the depth of your database.  Automotive Mastermind claims to use “thousands of data points,” mined from the DMS, social media, and credit bureaus.  An online auto retailer or platform site (see my taxonomy here) will also have data about which web pages the customer viewed.  Your typical F&I menu is lucky if it can read data from the DMS.

The face of predictive selling in F&I is the automated interview.  We all know the standard questions:

  • How long to you plan on keeping the car?
  • How far do you drive to work?
  • Do you park the car in a garage?
  • Do you drive on a gravel road?
  • Do you transport children or pets?

A system that emulates the behavior of an expert interviewer is called, appropriately, an “expert system.”  I alluded to expert systems for F&I here, in 2015, having proposed one for a client around the same time.  This is where we can begin to make some distinctions.

Rather than a set of canned questions, a proper expert system includes a “rules editor” wherein the administrator can add new questions, and an “inference engine” that collates the results.  Of course, the best questions are those you can answer from deal data, and not have to impose on the customer.

A data scientist may mine the data for buying patterns, an approach known as “analytics,” or she may have a system to mine the data automatically, an approach known as “machine learning.”  You know you have good analytics when the system turns up an original and unanticipated buying pattern.  Maybe, for example, customers are more or less likely to buy appearance protection based on the color of their vehicle.

At the most basic level, predictive selling is about statistical inference.  Let’s say your data mining tells you that, of customers planning to keep the car more than five years, 75% have bought a service contract.  You may infer that the next such customer is 75% likely to follow suit, which makes the service contract a better pitch than some other product with a 60% track record.  One statistic per product hardly rises to the level of “analytics,” but it’s better than nothing.

Another thing to look at is the size of the database.  If our 75% rule for service contract is based on hundreds of deals, it’s probably pretty accurate.  If it’s based on thousands of deals, that’s better.  Our humble data scientist won’t see many used, leased, beige minivans unless she has “big data.”  Here is where a dealer group that can pool data across many stores, or an online selling site, has an advantage.

If you are implementing such a system, you not only have a challenge getting enough data, you also have to worry about contaminating the data you’ve got.  You see, pace Werner Heisenberg, using the data also changes the data.  Customers don’t arrive in F&I already familiar with the products, according to research from IHS.

Consider our service contract example.  Your statistics tell you to present it only for customers keeping their vehicle more than five years.  That now becomes a self-fulfilling prophecy.  Going forward, your database will fill up with service contract customers who meet that criterion because you never show it to anyone else.

You can never know when a customer is going to buy some random product.  This is why F&I trainers tell you to “present every product to every customer, every time.”  There is a technical fix, which is to segregate your sample data (also known as “training data” for machine learning) from your result data.  The system must flag deals where prediction was used to restrict the presentation, and never use these deals for statistics.

Doesn’t that mean you’ll run out of raw data?  It might, if you don’t have a rich supply.  One way to maintain fresh training data is periodically to abandon prediction, show all products, let the F&I manager do his job, and then put that deal into the pool of training data.

Customers complete a thinly disguised “survey” while they’re waiting on F&I, which their software uses to discern which products to offer and which ones the customer is most likely to buy based upon their responses.

Regulatory compliance is another reason F&I trainers tell you to present every product every time.  Try telling the CFPB that “my statistics told me not to present GAP on this deal.”  There’s not a technical fix for that.

One motivation for the interview approach, versus a four-column menu, is that it’s better suited to form factors like mobile and chat.  This is a strong inducement for the online selling sites.  In the F&I suite, however, the arguments are not as strong.  Trainers are uniformly against the idea that you can simply hand over the iPad and let it do the job for you.

No, I have not gone over to the Luddites.  This article offers advice to people developing (or evaluating) predictive selling systems, and most of the advantages accrue to the online people.  The “home court advantage” in the F&I suite is that you can do a four-column menu, and there is a professional there to present it.

Dealer Megatrends Part 3 – Process Change

In my previous Megatrends article, I wrote about how advancing technology is changing the role of F&I.  This week, we examine some new business practices.  You already know what I mean.  We’re going to talk about:

  • Hybrid Sales Process
  • No Haggle Pricing
  • Salaried Employees
  • Flat Reserve

High line manufacturers have tried to promote “one face to the customer,” since I was at BMW in the twentieth century.  Lexus Plus is the latest iteration.  Tellingly, BMW called it Retail 2000.  I fondly remember hearing a radio spot for “the last BMW dealer” in San Francisco, because we had styled all the others as retailers.  “If you want to pay retail, go to a retailer,” the ad went, “to get a deal, you need a dealer.”

So, it goes in cycles.  Lexus, or Scion, or AutoNation, will roll out a new process only to be outmaneuvered by the wily dealers.  Then they retrench and, five years later, someone else tries the new process.  They could literally be passing around the same procedure manual.  Look at me.  I have been advocating price transparency since Zag.

One Sonic-One Experience offers no-haggle pricing with one sales rep using an iPad who takes the customer through the entire vehicle sales process, including financing and the F&I product presentation.

A good example of the new process is Jim Deluca’s exposition of the Sonic One Experience.  In their EchoPark process, Sonic also eliminates dealer reserve.  The fight over flats and caps lasted from roughly 2012 to 2014.  See here, and NADA’s endorsement of caps here.  Next, Sonic will leverage their heavy investment in training to roll all of this into an online process called Digital One-Stop.

I suspect that Sonic would soon like to fire all their trained F&I professionals in their self-interest of saving a buck.

Forum comments reveal that old-school practitioners dislike the new process.  It’s funny to hear an F&I manager accuse a dealer of shameless self-interest, but there it is.  On the other side, Sonic’s Jeff Dyke reports good results from hiring people with no prior automotive experience.  Meanwhile, at rival consolidator AutoNation, 70% of the sales staff opted to go on salary.

Well-known F&I trainer Tony Dupaquier is here, advocating the hybrid process at First Texas Honda, and here is Findlay Group’s Las Vegas Subaru.  Savvy dealers everywhere are experimenting with at least two or three of the four new practices (online selling and iPads come up a lot, too).

Smart people have told me that the hybrid process will never produce four-digit PVRs, but many dealers – and certainly the consolidators – reckon that’s a price worth paying for a streamlined process, reduced turnover, and improved customer satisfaction.

Why I Freelance

Recently, Linked-In reminded me that I have been an independent consultant for fifteen years.  Thanks to all who called and wrote with congratulations.  In fact, I have been either consulting, at a startup (or consulting for a startup) since business school.

I used “freelance” in the title because this word is in need of some rehabilitation.  There was a bitter post on Linked-In about how “freelance photographer” means “unemployed guy with a camera.”  I get that all the time.  I spoke with a recruiter recently who was startled to learn this is really what I do, and not just a placeholder on my resume.

According to McKinsey, there are 49 million of us “free agents,” equal in number to those who do it out of necessity.

I started consulting for a Big Six firm, back when there were six, and I noticed that our projects were always a big deal for the client staff.  They felt lucky to be on the client’s once-in-a-lifetime project.  We consultants, meanwhile, were continuously assigned to the good projects, client after client.  It becomes addictive.

If I were recruiting here, I would recount some groovy projects and then pitch the glamour and excitement – but I have a much more practical argument.  When you work for a long time at one company, you accrue specific knowledge about its organization, procedures, and history.  If you ever leave that company, the value of this knowledge falls to zero.

I was engaged by GMAC just before the crash.  Suddenly, my entire department was shuttered – desks empty, lights out.  It was a disaster for the faithful, lifetime employees.  Some were out of work for a year.  The consultants, however, rapidly found new jobs.

Job security no longer exists, and the good wages, generous benefits and secure retirement that used to be guaranteed with full-time employment are in decline or have disappeared.

It is a little scary not knowing where I’ll be working next year.  I won’t deny that.  My point about GMAC is that the people who thought they had job security were mistaken – and they were the ones most at risk.

Tom Peters writes that job security does not come from allegiance to your company.  It comes from having skills and accomplishments, plus a network of people who know about your skills and accomplishments.  This is where the exciting projects come in.  When I call around looking for work, I want people to recognize me as “the guy who created Provider Exchange Network,” or something like that.

Changing jobs enhances your value by exposing you to new people, technology, and business models.  This has certainly been true for me.  F&I is a small community, but it includes dealer groups, software companies, and finance sources.  This is great because it allows me to move around without violating any non-competes.

This article in Harvard Business Review echoes Peters’ observation about job security.  The author is a B-school prof, who writes that the gig economy is the future.  Focus on finding work, she says, not a job. I am lucky that this attitude (and related skills) were drilled into me at Coopers.   In case you’re inspired to quit your day job, I’ll follow up with a “how to” article.

Dealer Megatrends Part 2 – Fintech

Car dealers today face a growing array of new systems and capabilities.  These are primarily in F&I, thanks to disruptive new entrants in financial technology – fintech, for short.  Mark Rappaport has a nice roundup here, from a lender’s perspective, and I maintain a list on Twitter.

  • AutoFi – Auto finance plug-in for dealer web sites. See Ricart Ford for an example.
  • AutoGravity – Customer obtains financing (via smart phone) before visiting the dealership.
  • Drive – Online car selling, with delivery, from the Drive web site.
  • Honcker – Customer obtains financing (via smart phone) and they deliver the car.
  • Roadster – E-commerce platform for dealers, with full sales capability (as I anticipated here).
  • TrueCar – Customer sets transaction price (via smart phone) before visiting the dealership.

The new entrants blur familiar boundaries in the retail process.  They’re basically lead providers, but all aim to claim a piece of the F&I process.  AutoGravity, for instance, provides a lead already committed to a finance source.  TrueCar provides a lead already committed to a transaction price.  If you’re unfamiliar with the canonical process, see my schematics here and here.

In my previous Megatrends installment, Consolidation, I cited the influence of PE money.  It’s the same with fintech.  AutoGravity, to name one, is backed by $50 million.

The new F&I space is also home to “predictive analytics.”  Automotive Mastermind examines thousands of data points, to produce a single likely-to-buy score.  Similarly, Darwin Automotive can tell you which protection products to pitch.

The technology’s proprietary algorithm crunches thousands of data points, combining DMS information with … social media, financial, product and customer lifecycle information

My specialty is F&I, but it seems pretty clear that predictive analytics has a place in fixed ops as well.  In terms of the earlier article, you can see that consolidators have an edge in evaluating new technology.  Speaking of fixed ops, they’re also better positioned to obtain telematics data.

McKinsey says fintech can help incumbents, not just disrupt them.  That’s why I have focused on technologies a dealer could employ, versus apps like Blinker that are straight threats.  Of course, you have to adopt the technology.  Marguerite Watanabe draws a parallel with the development of credit aggregation systems.

Fintech will induce dealers to adopt an online, customer-driven process.  I see this as an opportunity. On the other hand, those that fail to adapt will be left behind.  This article is aimed at dealers, but the challenge applies equally to lenders, product providers, and software vendors.

Dealer Megatrends Part 1 – Consolidation

In the 2006 data, NADA noted a “moderate consolidation trend.”  Since the recession, sales have recovered but the dealer population has not.  My chart, below, is based on the last eleven years of NADA data.  You can go back as far as you like.  The dealer population has been shrinking steadily for fifty years.

chart

This means the surviving dealers are selling more cars per store, but the real story is consolidation – the powerful trend toward fewer owners and bigger groups.

In 2005, the top 100 dealership groups were 9% of the total.  In 2015, they were 17%.  The Automotive News ranking is by gross revenue but, for simplicity, I am counting stores.  I imagine that the big, efficient groups command more than 17% of the total gross.

Gee group’s purchase of 16 Tonkin stores, backed by private equity, is instructive.  Both groups are family owned, with seven and 21 stores respectively.  Brad Tonkin will join the combined entity as president.  The Automotive News article also describes a Soros-backed purchase by the McLarty group, bringing its count to 19 stores.

The owners may be public, like AutoNation and Penske, private equity, or something in between.  Larry Miller group, for example, is still family owned but independently managed.  An IPO seems the next logical step.  Broker Alan Haig predicts his buy-sell business will continue strong in 2017.

This is about economies of scale, obviously.  The New York Times mentions efficiency in staffing, technology, and inventory management (as I did, here).  There is a lot of money chasing this trend, and only so many operators who know how to exploit scale.  That’s why Haig also has a recruiting arm.

Small dealer groups can compete online only by joining platforms that aggregate inventory.

If you are running a small group, you might want to start thinking about M&A.  That’s not my area, though.  I am interested in the related trends toward technology and process change.  I’ll examine these more in my next post.

One example is online retail.  Small dealer groups can compete online only by joining platforms that aggregate inventory, like TrueCar or Autotrader.  What I am proposing is that the (relatively) little guys compete with the consolidators by consolidating themselves online.

Dealers should seek help from their OEMs and software vendors.  Well, maybe not the OEMs.  GM’s Shop Click Drive only searches inventory for a single dealer, and it makes you choose the dealer first.  Not only will it not give you a price, it won’t even present a model list until you’ve selected a dealer.  No one shops this way anymore.

Modern shoppers will have found a model and trim level, a price, and even a lender, before landing on a dealer.  While Shop Click Drive has the machinery to structure a deal, and even sell protection products, some genius decided to make the “choose dealer” button its primary focus.  Most GM dealers I looked at were also on Autotrader.

I did a survey of platform capabilities last year, with Cox Automotive far in the lead.  The other guys seem still to be in the world of single-dealer web sites.  I also noticed that these sites are mostly hideous, and lacking consistency in even simple functions like credit application.

The consolidators have strong tech teams devoted to online shopping.  Dealers may fail to see the threat, because it’s not a physical presence.  If you owned a hardware store, and Home Depot went up across the street, you would notice.

Stop Worrying About Self-Driving Cars

I am planning an article on car dealer “megatrends,” and this is the first item not making the list.  It’s a sexy topic, though, and journalists can’t leave it alone.  For example, here is top Cox guy Mark O’Neil trying to change the subject.  Mark would rather talk about online sales which, with predictive analytics, is a key trend dealers should be watching.

Autonomous vehicles are part of a cluster of technologies which have the potential to reduce car sales, dramatically in some scenarios.  This McKinsey study does a nice job of explaining the cluster.  In short: car rental fleets go away because everyone uses Uber, and Uber drivers are obsolete because the cars drive themselves.  Car ownership will be fractional, like a time-share.  If you do own a car, it can work as a taxi all day while you’re at the office.

This is indeed a formula for sharply reduced car sales … in Europe.  Most of the U.S. is sparsely populated, and poorly served by public transportation.  The Boston Consulting Group has produced the best study on autonomous vehicles, here, and this is from their study on car sharing:

Car sharing … will not do to the automotive business what iTunes did to music: it will not redirect a stream of revenues to a disruptive upstart, and it will not spark a widespread change in consumption.

The BCG predicts that, by 2021, car-sharing will have a trifling impact on U.S. sales: fifty-two vehicles, total (chart on page 11).  They predict that fully autonomous vehicles will not be available until 2025, and will not be 10% of the market until 2035.  It is only these vehicles that trigger the nightmare scenario for car dealers.  “Driver assistance” systems are luxury features, which boost dealer profits.

sae-levels

NHTSA policy guidance is based on the five-level SAE model.  This roundup, from Automotive News, envisages Level 4 autonomous vehicles by 2021.  No manufacturer is even guessing at a date for Level 5.

Bringing these vehicles to market is an important challenge for the manufacturers, and they will have an important impact on society.  They will not change the business of selling cars, however, for a good long time.  For car dealers, other trends are more urgent.

Links for the two BCG studies, in case you can’t download the PDFs: Car Sharing, Autonomous Vehicles.