Edmunds.com Yields Multi-Million Dollar Revenue Opportunity from its Free API

APIs, which stand for Application Programming Interfaces, are all the rage these days. APIs, which can be described as online back doors into your database, allow programmers to seamlessly integrate your data into their products, particularly, but not necessarily, mobile apps. Increasingly, customers are asking companies selling subscription data products for “API access” to their data. The reason for this is that these companies want to integrate commercial datasets into their own internal software applications. So you’ve got application developers looking for API access to your data in order to build it into software products for resale. You’ve also got companies that want API access to your data to power their own internal software. If you are charging a high enough price for your data that reflects the convenience and power of API access, as well as the expanded audiences your data will reach, APIs are nothing but great news for data publishers. But can you also make money giving away API access to your data for free? A growing number of companies think so. We recently spoke with Ismail Elshareef, Senior Director, Open Platform Initiatives for Edmunds.com. Edmunds makes its data available via API for free, and can directly attribute millions of dollars in recurring revenue to this initiative.

According to Ismail, Edmunds.com launched its API about two years ago, primarily as a way to get more exposure for the Edmunds.com brand. The second objective was one we often hear from those with open APIs: a desire to encourage innovation. As Ismail puts it, “We can’t hire all the smart people out there.” The goal is to put Edmunds data in the hands of a broad array of talented developers and see what they can do with it – whether it’s new applications software to leverage the data, or even entirely new and unintuitive uses for the data itself.

The additional brand exposure for Edmunds worked exactly as planned, according to Ismail, who said it has become “a huge differentiator.” Edmunds displaced a number of competitors who were charging money for equivalent data, and with the “powered by Edmunds” attribution on so many different products, Edmunds saw immediate brand benefit, not the least of which was more advertisers specifically acknowledging the reach of Edmunds in sales meetings.

Overall, Edmunds has found a number of partner deals came together more quickly as well, “because using the API, they can get comfortable with our data first.” A great example of this is a major deal Edmunds put together with eBay. Ismail emphasized the growing popularity of this “try before you buy” approach to data content, and that publishers need to respond to this growing preference among data buyers.

Ismail is careful to note that Edmunds wasn’t seeking to actively disrupt paid data providers in its vertical; the free data it offers simply reflects lower barriers to entry, and to an extent, the increasing commoditization of much of data it offers for free.

And while additional market exposure is clearly beneficial, as Edmunds saw it, the big upside opportunity was to see what dozens or even hundreds of talented, motivated independent developers would do with the data. And that’s exactly where Edmunds found gold. Acknowledging that of the apps developed around its data, “only 1 in a 100 is really interesting,” Ismail noted that one really interesting application emerged after only seven months of offering the free API. An independent software provider in the Northeast built a cutting-edge application for automobile dealerships. But while they had a great solution, they didn’t have a sales force to market it to dealers. Edmunds contacted the CEO of the software company, struck a partnership deal, and already the product generates millions of dollar in annual revenues.

One of the keys to Edmunds’ success is that while its data is free, it isn’t free for the taking. Every developer who wants to use Edmunds data has to adhere to a terms of service agreement, which specifies the attribution that Edmunds is to receive, as well as reserving the right for Edmunds to cut off data delivery to anyone who acts irresponsibly, though Ismail notes that most developers are very responsible and “know what’s cool and what’s not.” Also important to the Edmund’s model is that it initially only provides enough free data to developers for testing purposes. Before raising a developer’s API quota, Edmunds looks at each application to make sure attribution and back-links are correct, and that the application overall is using the data correctly (not incorrectly labeling data elements or incorrect calculations) and that the application is a quality product that Edmunds is comfortable being associated with.

As guidance to other data publishers interested in pursuing an open API, Ismail feels it is essential to use a service that provides an API management layer. After extensive research, Edmunds went with Mashery, which stood out to Ismail in particular because “Mashery already works with major publishers like the New York Times and USA Today, so they know the issues that are specific to publishers. They also have a huge developer outreach program, now over 100,000+ developers, which made it easy for us to get the word out in the developer community.”

Internally, Ismail notes that the Edmunds API was initially a tough sell. Not everyone believed in the concept, so executive support was a huge factor. It was only because the company’s chairman was such a believer that the API became a reality. As Ismail notes, “ultimately a free API is a leap of faith.” Ismail also noted the difficulties in getting the concept cleared by the company’s lawyers, who simply weren't initially comfortable with exposing our data to everyone." Executive sponsorship was key to ultimately clearing these legal impediments as well.

Launching the API involved “a lot of small steps in the beginning.” Initially, Ismail worked by himself on the API program. Now, his team consists of four engineers and a designer. And just yesterday, the Edmunds API has been certified for “Best Developer Experience” by Mashery – more evidence of how far Edmunds has come so quickly.

A Business Model Detour

TrueCar.com started out as a data and analytics company, offering insight to consumers as to the actual prices being paid for specific makes and models of cars in their local area. The idea was to aggregate multiple data sources, including actual sales data from dealers themselves to build as much precision as possible into this pricing information. In many respects, TrueCar was duplicating the approach taken by established industry powerhouse Edmunds.com. What TrueCar didn’t duplicate was the business model of Edmunds. Indeed, TrueCar took an entirely different route.

TrueCar moved beyond providing estimates of new car prices to delivering actual prices that dealers would accept. Simply hand your TrueCar number to the dealer, and the car would be yours for that price. It was a fresh approach, and particularly compelling to those consumers not fond of haggling with car dealers.

The idea took off. TrueCar signed up thousands of dealers to accept its pricing. Then, according to published reports, it started marketing itself as offering the lowest prices for new cars. Turns out, its dealers weren’t thrilled with that positioning, in large part because they weren’t offering the lowest prices, and large numbers of them canceled their affiliation with TrueCar.

TrueCar recovered from this, but in an odd way. It now represents itself as offering “fair prices” instead of lowest prices. And from a quick look at its site, you can see that it has morphed into a lead generation service for car dealers. I asked for a price on a car from dealers near my zip code and was presented with three prices from three dealers. That’s a big move away from presenting objective pricing based on aggregated sale price and other data.

So, the TrueCar value proposition has pivoted from providing objective data to providing consumers with a price in advance that certain dealers will honor, thus avoiding the stress and uncertainty of having to negotiate a price. If you look at the TrueCar website now, you’ll be repeatedly assured you are getting a fair, competitive price, but if there’s any data to back up that claim, the company’s no longer talking about it.

TrueCar claims to be responsible for 2.3% of all cars sold annually in the United States, so it seems to have tapped into a real need in the marketplace. At the same time, it’s a rare pivot away from a data-driven business model, to a model that as far as I can see doesn’t require any data at all.

Of course there’s a great lesson here in profiting from adversity, but there’s another lesson here as well: if you dive into the data business without a clear business model, you’ll probably find yourself needing to make an expensive and dangerous u-turn.

The Future Is Not Free

In a speech at the D2 Digital Dialogue conference yesterday, a top Macy's marketing executive, in a true "I'm mad as hell and I'm not going to take it anymore" moment, made the following statement: "Consumers are worried about our use of data, but they're pissed if I don't deliver relevance. … How am I supposed to deliver relevance and magically deliver what they want if I don't look at the data?"

This question speaks directly to the larger issues facing the publishing industry today: how to make money in a world where today’s consumer wants everything … and nothing. Consumers want their content free of charge, free of advertising and free of tracking. And what do content providers get in return for all this freedom? Well, freedom from revenue.

All this stems from the dot com mania when it became both fashionable and conventional wisdom that success online depended on free content. In the process of doing this, we’ve trained an entire generation to expect everything for free, to the extent they become indignant if any modest attempt at monetization offends their delicate sensibilities.

The content industry to a large part created this mess by enabling this unsustainable state of affairs. Ironically, those information companies that stuck to their paid subscription models are the ones in the best shape right now. And therein lies the answer to this problem: let’s move past increasingly intrusive, contorted and ultimately futile efforts to monetize our visitors, and start turning our visitors into subscribers. No, it won’t be easy or painless, but is there a real alternative?

We can look to the newspaper industry for inspiration. The entire industry, to paraphrase Churchill, is finally doing the right thing after having explored every other option. Yes, newspapers are charging for their content. That’s all the more remarkable because newspapers are burdened with a severe commoditization issue. And just this week, People magazine announced a news subscription bundle priced at $100 per year. Yes, People magazine. If that doesn’t embolden you, what will?

So if you are still mired in the dismal world of free content where consumers want to get everything for nothing and advertisers want to pay next to nothing to reach them, there is an option. And if you honestly don’t think you can make the shift, you need to take a hard look at your content. As Sharon Rowlands, former CEO of Penton once said to me, “If our content is as valuable as we say it is, why do we all spend so much money begging people to take it?” Answer that question and your business direction becomes clear.

Don’t Be Embarrassed

“If you’re not at least a little embarrassed by something you just launched, you probably waited too long to start it.” So says Alexis Ohanian, founder of Reddit and a number of other high profile web media products. This statement, provocative as it is, actually is little more than a smart synthesis of the current state of play in the world of online product development. You no doubt hear variants of this theme regularly, sometimes expressed as “minimum viable product,” “rapid iteration,” and even “fast fail.” They all embody the philosophy that it’s more important to launch a new product quickly than launch a really good new product. I credit Google for raising this practice to high art by teaching users that the word “beta” appended to any product name excused the product from delivering much value, or even working properly, for an often extended period of time.

I certainly agree that there is an imperative for speed in the world of online content. We’re surrounded by hordes of competitive start-ups, many of them explicitly attempting to disrupt market incumbents. But before we decide to emulate these companies, it’s important to note their typically distinctive business models.

First, most of these not-ready-for-primetime products are thrown onto the market for free. The companies behind them are betting that if they can build an audience and usage, everything will work out fine in the end, even if they don’t generate any revenue in the short-run. Further, most of these products come from start-ups, so there’s not much in the way of reputation risk. Thirdly, these companies are staffed and funded to iterate rapidly – some actually push out updates and fixes on an almost daily basis. If you’re going to play in this world, you can’t just talk a good line about evolving the product – you have to deliver, and often at a blistering pace.

That’s why I would argue that for most established data publishers with subscription businesses, applying this approach of pushing out half-baked new releases can be very dangerous. When working with an existing customer base, be clear that your subscribers don’t value speed for its own sake – they want clear product improvement. And frankly, this shouldn’t be that hard. You’ve got the advantage of a successful existing product you want to evolve, so you’re not starting from scratch. You’ve got loyal customers who will test with you and offer input. You have a deep understanding of the market you serve, so there’s no need to guess about what might be useful or compelling. Perhaps most importantly, your subscribers often need your data and your tools to conduct business. That’s a world away from a nifty new pizza delivery app. You have an implicit obligation to move prudently and get it “as right as possible” right out of the gate.

So yes, constant evolution of your product is essential. Speed is important. It’s also important to understand that nothing will be perfect the first time around, and that’s okay if you fix problems as quickly as they are identified.

What about new products from established publishers? First off, if you plan to charge for the product from the start, this comes with a much higher level of subscriber expectations. If it’s free (at least initially), expectations are lower, but be aware that those who go away unimpressed probably won’t come back. Finally, being embarrassed may well be an issue for an established publisher known for quality data and solid applications.

So before speeding up, slow down and think it through. The people advocating speed often are in a very different place from you.

TripAdvisor and the Ignorance of Crowds?

We all know the many benefits of user-generated data, including ratings and recommendations. Underlying all of it is a general belief in “truth in numbers” - if enough people say it is so, then it must be so. But what happens when the crowd returns a result that is obviously and intuitively wrong? A small but perfect example of this occurred recently when TripAdvisor published its list of “Americas Top Cities for Pizza.”

I’ll spare you the suspense: the top-rated city for pizza in the United States is (drumroll, please) ... San Diego, California. Are you already checking flights to San Diego or are you shaking your head in disbelief? I am guessing the latter, and that’s exactly my point.

Something went wrong in this tally by TripAdvisor. Most likely the underlying methodology wasn’t sound. TripAdvisor merely rolled up ratings for individual pizzerias and restaurants around the country and ranked them by city. There’s a little problem with that: context. What TripAdvisor converted to a national ranking were individual ratings made in the context of specific geographies. That’s why you see comments for top-rated San Diego along the lines of “it’s just as good as New York.” These people clearly didn’t see themselves voting in a national poll.

Also odd is that TripAdvisor decided to go ahead and publicize the results of this analysis. Clearly, TripAdvisor saw the potential for buzz with its surprising findings. Yet the flip side of this is the creation of a credibility issue: if TripAdvisor thinks the nation’s best pizza is in San Diego, how can I trust the rest of its information?

A few lessons for the rest of us can be found here. First Big Data is only valuable if properly analyzed. Second, evaluating data supplied by a large and disparate crowd can be tricky. Third, always balance the potential for buzz in the marketplace against reputation risk. Say enough dumb things online and you will hurt your credibility.

TripAdvisor will no doubt say in its defense that it is simply reporting what its users are saying. But if your user base is saying something dumb, it’s probably not in your interest to amplify it. And in fact, the TripAdvisor user base isn’t dumb; their individually smart comments were aggregated in such a way that they yielded a dumb result. But most people aren’t going to dig that deep. They’ll simply say that’s one less reason to rely on TripAdvisor.