Category: Online F&I

Workflow for Online Car Buying

A few years ago, I published a precedence diagram for the key operations of online car buying.  I was arguing against a linear process, and calling attention to some deadlocks.  Since then, I have been following the industry’s experiments with new process models, and coming to realize that these deadlocks are the great, unanalyzed, obstacle to process reform.

Practices that seem unfair, deceptive, or abusive may actually be crude attempts to solve the deadlock problem.

One example of a deadlock is that you can’t quote an accurate payment until you know the buy rate, and for that you need to submit a credit application.  This is usually solved by iteration.  You do a pre-approval or quote the floor rate, and then change it later.

Likewise, you can’t price protection products until you know the vehicle, but the customer wants to shop by payment.  Protection products are also priced by term, and you don’t know the desired term until you finish structuring the deal.

In fact, even the customer’s choice of vehicle depends on the monthly payment, which is downstream of everything else.  Virtually the only operation that’s not blocked by another operation is valuing the trade.Like an interlocking puzzle, “we don’t know anything until we know everything.”  Choosing any one item to lock first, without iteration, will result in a suboptimal deal – buying too much car, for too long a term, or overlooking the protection products.

Practices that seem unfair, deceptive, or abusive may actually be crude attempts to solve the deadlock problem.  For instance, quoting a payment with some leg in it, or goal-seeking the full approval amount.

Can you see how this ties into current debates about the hybrid sales model?  F&I presents a menu with a six-month term bump, which might not be optimal, just to compensate for too tight a payment from the desk.

Fortunately, in the world of online car buying, the customer is free to resolve deadlocks through iteration.  This means:

  1. Set up the deal one way
  2. Change any feature, like the term
  3. The change “cascades,” undoing other features
  4. Revisit those other features
  5. Repeat until all features look good together

The in-store process does not support iteration well, and probably never will, but an online process can.  All you need is the well-known concept of a “dirty” flag, to keep track of the cascading changes, along with navigation and a completeness gauge to guide the customer through steps #4 and 5.

You could analyze step #3 at the level of a dozen individual features.  I made that chart, too, but I believe it’s more useful to collect them into the canonical five pages shown here.

By the way, I have previously described the products page in some detail, along with the analytics to drive it.  Discussion of the “random survey question” is here.  Today’s diagram contemplates a mobile app, as do my recent posts, but the same approach will work for a web site.

Menu Selling on an iPhone

Followers of my Twitter feed know that I have lately been looking at mobile apps, to see if anyone can present protection products on an iPhone.  I wrote about this three years ago and, according to my informal survey, the field is still open.

I don’t think anybody has a good way to present a menu on a consumer web site, much less an iPhone.

Not only is the iPhone a restrictive form factor but we must assume that the customer, not an F&I person, is operating it.  We would like to apply our Best Practices for Menu Selling, but the app must be able to apply them on its own.

For example, if we want to retain the package concept with the carefully chosen payment intervals, we can use an accordion control.  I proposed this for a client once, in an F&I context, but it doesn’t make sense for consumer use.

No, the best way to “present all the products, all the time,” is simply to make one long column with everything in it.  The iPhone presents challenges, but there are offsetting advantages.  We can show fifteen products in one column, and the customer has his leisure to scroll through them.

I prefer scrolling to swiping for a few reasons.  In the prototype shown here, we have the obligatory vehicle photo.  After the first scroll, that’s gone and the screen space is devoted to products.

The prototype shows monthly prices for the vehicle and the products.  This assumes the finance process is settled, and the app can choose products matching the finance term.  Touching any of the products will open up a full page with details, coverage choices, and a “sales tool” as in the earlier article.

I recommend using analytics to determine the sequence of products in the column, and even to A/B test the format of the product blurbs.  I have in mind a few different formats:

  • Text with graphic and price, as shown here.
  • No price ‘til you open it.
  • Lead with the sales tool.

I discuss analytics here, but I am not a fan of the full “ownership survey.”  Of the eight standard questions, maybe you can sneak in one or two elsewhere in the process.  Apart from that, we’re counting on data points found in the deal itself.

I also think “less is more” when confronting the customer with choices.  As you can see in the mockup above, there must be no complicated grades of coverage (or deductible).  If you’re configuring the app for a specific dealer, you may want to filter some options out of the dealer’s product table.

Depending on who’s managing the app, the products themselves may be rethought.  If you want to offer chemical, dent, key, and windshield as a combo product, then that’s a single choice.  Alternatively – since we have unlimited  column space – you can offer each one individually.  What you do not want is a product having fifteen different combinations.

Coming back to my informal survey of mobile apps, and the workflow given here, I believe there are already good examples of vehicle selection, credit application, trade valuation, and payment calculator.  Menu selling has been the only missing link, until now.

Best Practices for Menu Selling

I was asked recently to opine on this topic, which I do today with some reservation, for I can see the venerable four-column menu approaching its sell-by date.  The image shown here is a MenuVantage prototype from 2003.  Don’t get me wrong.  As I wrote here, this is still the best tool for the traditional setting in the F&I office … for as long as that setting prevails.

Best practices for menu selling split into two broad categories: those that are good for selling, and those that are good for compliance.  I will present them in that order.

Every product appropriate to the transaction type and “car status” of the current deal (i.e. Used Lease) should appear in column one.  Some menu systems use deal templates, making it easy to select the proper layout every time.

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.

For most systems, column one automatically drives the layout of the accept/decline “waiver” form.  This is best practice for compliance, and it’s good selling too.  Why have a product that you only present on special occasions?

The practical limit for products in column one is six, maybe eight, so choose wisely when laying out the menu template.  Using bundles will allow you to squeeze in more products.  I generally don’t like bundled products, as I wrote here, but this is a reason to use them.

Every menu should include a second, longer term, with the correct APR for that term.  There is a charming story about this in Six Month Term Bump, plus a downloadable spreadsheet.  Twelve months is overkill, and likely to raise an objection.

The amount of product you can finance without changing the monthly payment is given by this formula.  Without doing the annuity math, a good approximation is: base payment times five.The monthly payment in column four should be roughly $30 more than the base payment without products.  That way, you draw the customer’s attention into the menu without a big price barrier.  Likewise, payments should increase in small increments from right to left across the bottom of the menu.

Obviously, the increments will be larger for more expensive deals, say 10% of the base payment.  This is easy to do, if you are manually setting up each menu.  It takes a little more planning to do this with templates.  You can either tweak the individual products at deal time, or you can set up a different template for highline vehicles.

For example, offer the platinum VSC coverage in column one and the gold in column two.  By the way, do not reuse the VSC coverage choices (like gold, silver, and platinum) as your column headings.  That’s an obvious source of confusion.  Finally, your menu system should feature sales tools and custom content for each product, like the famous depreciation chart for GAP.

I have a few more recommendations, related to compliance.  If you already have a good grasp of unfair and deceptive practices, you can skip this part.  Be warned, though, that consumer watchdogs and regulatory agencies are looking over your shoulder.

The chart below (and the pull quote) is from the National Consumer Law Center.  You can tell that the dealer in green is using a menu system with a fixed markup over dealer cost.  The dealer in red is certainly making more PVR but he is also courting a federal discrimination charge.

Menu trainers like to say, “present all the products to all the customers, all the time.”  They might add, “at the same price.”  The NCLC report goes on to show that minority car buyers are systemically charged more for the same products.  Some dealers simply don’t allow the F&I manager to vary from the calculated retail price.  In states like Florida, that’s the law.

Giving F&I managers the discretion to charge different consumers different prices for the same product … is a recipe for abuse.

The menu should display the price of each product, not just the package price.  Some turn this into a selling feature by also showing the price as a daily amount.  It makes a good layout to have the most expensive product at the top, with prices descending down the column.

All of these measures require some kind of audit trail.  I have seen some very strong systems that track exactly what was presented, by whom, when, for how much, and whether the price was changed.  At a minimum, you should collect the customer’s signature on the waiver form, with all the products, their prices, and your standard disclosure text.

Next week, I will resume writing about the brave new world of flow selling, self-closing, and predictive analytics.  We may find that many of these practices – especially regarding compliance – are still relevant.

The Automotive eCommerce Ecosystem

Around the turn of the century, I was helping RouteOne to build their now-ubiquitous credit system.  Then, I moved on to aggregation models for the “I” side of F&I.  It was a lot of work.

We had to develop scores of unique interfaces for lenders and product providers.  We had to develop deal calculation engines, and then reverse engineer each DMS so our payments would match.  There were no automated sources for finance or product rates.  We had to walk ten miles in the snow …

Today’s eCommerce startups have it easy.  All of the key tasks are supported by readily available services, leaving the entrepreneur to focus on user experience and dealer support.

When I started writing about this space, the key challenges were price negotiation and trade valuation (and the test drive, but I’ll cover that in a later piece).  Today, you have reliable online trade valuation from Kelley, Trade Pending, and others.  Price negotiation can be handled through chat or one-price, generally on used vehicles.

You can have payment calculations, including incentives, from MarketScan, provider networks from PEN or F&I Express, and finance networks from RouteOne or Dealertrack.  Everything in this paragraph is an API, not to mention passing data from your eCommerce platform into the corresponding dealer system. Finally, even the old faithful DMS now exposes a variety of databases, like inventory.

A few months ago, I described the role of venture capital in driving process change.  I think this eCommerce ecosystem is equally important.  Entrepreneurs can enter the space at a very low cost, relative to ten years ago, and meet most of their requirements through interfaces.

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 do 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.