App Store or App Storage?

In a recent article in Talking New Media, a writer with the pseudonym Alain Parkeat takes the Apple App Store to task for its incredibly bad design.

While I am not a frequent user of the App Store, every time I have to access it, I wince. For a company that hangs its hat on its relentless pursuit of perfection in design and user experience, everything about its App Store is slipshod and half-baked.

Really, you couldn’t do it much worse. The problems start right at the core of the whole App Store concept: in a rush to have the most apps, it’s necessarily assembled a collection of the worst apps. And here I am not just talking about the quality of the apps. Rather, I find I must tread warily with every search, because the App Store is riddled with frauds and imposters. Search on the trademarked name of a popular product, and you’ll invariably get not only that product, but lookalikes clearly designed to fool those who are not careful. They use deceptively similar names, logos and trade dress. They also are apparently allowed to use competitive product names as search keywords. Scariest of all, many of these lookalike apps are free – and thus likely to be nefarious ploys to gain access to your data or your passwords.

Searching the app store is also remarkably difficult. You think basic search functionality wouldn’t be too tough to implement, but with the App Store, you’d be wrong. Searching is about as literal as you can get, meaning that you better get your input exactly right, because the search engine isn’t going to help much at all.

This of course leads to categorization. Yup, the App Store is all over that, with 25 categories to classify a reported one million apps. I guess I’ll just click on the category “business” and start browsing. Clearly, with an average of 40,000 apps per category, this isn’t a very effective discovery mechanism.

But the App Store does feature apps, and since these apps are about the only thing you can easily discover in the App Store, they get enormous numbers of downloads. How does one become one of the few, the proud, the featured? Well, you need a lot of downloads first. Yes, if you want to be successful in the App Store, you better be successful before you get to the App Store. Otherwise, you better be very lucky.

Perhaps the most remarkable thing about the Apple App Store is that this is not some obligatory thing Apple threw together to keep customers happy. Indeed, it’s a major source of revenue, generating over $1 billion per month, with Apple helping itself to a nice share of the pie.

For most publishers, the harsh reality is that the App Store is, more accurately, the App Repository. Apple’s value is providing a central location for apps and easy downloads. As far as discovery goes, you’re on your own. If only there was an app for that!

Evolving From Data Providers to Market Makers

Trucker Path is a young company, founded only in 2013. Yet its mobile app, providing truckers with basic directory information such as location of rest stops, parking, diesel fuel stations, weigh stations and more has already attracted over 250,000 users. Its formula for success is a familiar one to data publishers: collect information that is really needed by a specific niche market but not readily available in one place elsewhere.

Another mobile app success story to be sure. And Trucker Path could have rested on its laurels. But just a few days ago, it signaled a much more ambitious vision with the launch of a new product called Trucker Marketplace. It is exactly what the name implies: a marketplace where truckers can find and connect with those who need to ship freight, either regionally or nationally.

It’s a simple concept, and it’s also not a new concept. Many companies have sought an intermediary role in this inefficient marketplace, particularly in the area of backhauls, where trucks often return home empty after delivering a load. And the opportunity is huge: more than 75% of all freight in the U.S. is delivered by truck.

Obviously, Trucker Path has a natural point of leverage in that it can offer this service to its existing base of satisfied directory users. But in another twist I find both significant and smart, Trucker Path is embracing freight brokers, not trying to disintermediate them. Rather than embracing the standard tech playbook of trying to blow up an inefficient industry in order to carve out a position, Trucker Path is simply trying to graft a new layer of efficiency onto an existing market. I would argue they’re trading a bit of potential upside for a radically increased chance of success.

Trucker Path does some other tried and true things such as providing credit, insurance and license data to its marketplace participants, a tested way to increase both value and trust.

Trucker Path is a case study for my long-held view that B2B data publishers in market verticals are well positioned to consider the marketplace model. They’ve got a brand, they’ve got the audience, and they know how to use data (e.g., license and credit information) to create the trusted environment that is essential to driving transaction volume. And despite their noisy collapse after the dot com bust (too much, too soon),  I am very optimistic about the future of B2B exchanges. We all now recognize the value of workflow integration: if you’re enabling the flow of work for an entire industry, you’re obviously in a very good place.

A Review of Reviews

Reviews are important. That’s no secret. Almost everyone uses them now as part of their pre-purchase research. We depend on them. We want them. And in the time and attention deficit world we all live in, we need them to help us quickly make smart decisions.

The basic premise of online reviews can be summed up as "in numbers, truth.” If you have enough people reviewing something, the real answer will emerge. And it will overwhelm all the cheaters, frauds and manipulators who are posting reviews as well.

But in order for a review site to build the volume of reviews, it needs to focus. If you want reviews on all the hotels in the world, you need to stay true to that mission. Same if you’re trying to be the authority on restaurants. There’s always time to expand your scope later, once you are established, known and successful. This is a simple, but key driver behind the success of sites like TripAdvisor and Yelp. If you want people to come to your site to read reviews, you better have reviews to read. And once they’re reading, getting them to post reviews is pretty easy as experience has shown.

That’s why I was puzzled to read recently that a Danish site called TrustPilot had just raised over $73 million in new funding. There must be innovation here, right?

Well, TrustPilot is indeed innovative, but not the way I had imagined. As far as I can see, TrustPilot wants to review every business in the world (and it’s already pushing into product reviews as well). Nothing wrong with being ambitious, but in this case is TrustPilot trying to be too ambitious?

Let’s look at the numbers: TrustPilot currently has about 10 million reviews of 90,000 businesses … worldwide. Further, it’s organized by overly broad categories such as “Services” and “Transportation.” In a nice feature, it ranks the top companies in each category based on their review scores, but in all the categories I examined, I had trouble finding any companies whose names I actually knew. TrustPilot is a great vehicle to post reviews, but as a purchase research tool, it’s a mile wide and an inch deep.

Sure, $73 million buys a lot of growth. But it seems like long odds against TrustPilot getting enough review volume across all its categories to reach critical mass. First they need enough companies to become a real go-to destination. Then they need enough reviews of each company for the truth to emerge.

My review: in a business that depends on volume, don’t start out by trying to be everything to everybody.

Everyone into the (data) Pool

There’s a quiet revolution going on in agriculture, much of it riding under the label of “precision agriculture.” What this means is that farms are finding they can use data both to increase their productivity and their crop yields.

To provide just one vivid example, unmanned tractors now routinely plow fields, guided by GPS and information on how deep to dig in which sections of the field for optimal results. Seeds are being planted variably as well. Instead of just dumping seeds in the earth and hoping for the best, precision machinery, guided by soil data, now determines what seeds are planted and where, almost on an inch-by-inch basis.

It’s a big opportunity, with big dollars attached to it, and everyone is jockeying to collect and own this data. The seed companies want to own it. The farm equipment companies want to own it. Even farm supply stores – the folks who sell farmers their fertilizer and other supplies want to own it. In fact, everyone is clamoring to own the data, except perhaps the farmer.

Why not? Because a farmer’s own soil data is effectively a sample size of one. Not too valuable. Value is added when it  is aggregated to data from other farmers to find patterns and establish benchmarks. It’s a natural opportunity for someone to enable farmers to share their data to mutual benefit. This is a content model we call the “closed data pool,” where a carefully selected group agrees to contribute its data, and pay to receive back the insights gleaned from the aggregated dataset.

One great example of this model is Farmers Business Network. Farmers pool their data and pay $500 per year to access the benchmarks and insights it generates. Farmers Business Network is staffed with data scientists to make sense of the data. Very importantly, Farmers Business Network is a neutral player: it doesn’t sell seeds or tractors. Its business model is transparent, and farmers can get data insights without being tied to a particular vendor. Farmers Business Network makes its case brilliantly in its promotional video, which is well worth watching: https://www.youtube.com/watch?v=IS4KIrcRMMU

Market neutrality and a high level of trust are essential to building content using the closed data pool model. But it’s a powerful, sticky model that benefits every player involved. Many data publishers and other media companies are well positioned to create products using this model because they already have the neutral market position and market trust. Closed data pools are worth a closer look. Google certainly agrees: it just invested $15 million into Farmers Business Network.

There's No Substitute for Structured Data

Cloud-based contact management software provider Nimble recently introduced a new feature called its “Smart Contacts App.” Load the app to a supported browser, and if you see the name of a person or company that interests you, whether reading a news story or in Facebook or Twitter, just highlight the name and Nimble constructs a full profile on the fly. In addition to basic background information, Nimble also searches a number of social networks to find matching accounts. The goal is to build the richest possible profile of the person or organization, and it’s all real-time. With one more click, you can load the profile into your Nimble contact manager.

This isn’t an entirely new concept, but it’s slickly executed. After putting a magnifying glass up to the various screen captures provided by Nimble, what I think I see is that a lot of the magic depends on LinkedIn. And guess what? LinkedIn is a data product. Nimble’s ability to associate social media accounts is impressive, but still imperfect. Indeed, it asks the user to explicitly confirm every social media account match. Nimble also does a nice job integrating with email so that it can pop up a profile of anyone who sends you an email. Microsoft has offered this for a while now, but this is part of a bigger push by Nimble to have its customers do all their work in Nimble so all prospect and customer data resides in one place, all tightly linked and readily accessible.

I draw two insights from all this:

•  The push to tightly integrate sales prospecting data is serious and intense. The idea of any contact manager (and this includes Salesforce) having a button that says “click to view profile” is quickly getting dated. That means data has to be more tightly integrated into these systems to a degree we haven’t yet seen, and that means software companies will need to license more data from data publishers to get this level of deep integration.
   
• For all its sizzle, this new offering from Nimble isn’t creating data; it’s assembling data from other data sources. To be valuable, Nimble needs data that is accurate, rich and most importantly, structured. You can’t assemble that out of thin air. And that unique characteristic – structure – is what makes data so powerful and so valuable.