The Macro Problems with Micropayments

Micropayments companies – companies that make it somewhat faster and easier to purchase small units of content such as a company profile or an article – have existed since the early days of the Internet. You may remember names such as First Virtual, Cybercoin, Digicash, Millicent, Payword, Micromint … and that’s just a partial list. And despite a raft of failures in this space, new players keep coming. For example, a start-up called CoinTent just raised $1 million to pursue its vision for micropayments.

Why are micropayments so hard? I see two primary issues. The first is in establishing market traction. A successful micropayments play needs to not only get a lot of users, its needs to get a lot of publishers, and it needs to grow both sides simultaneously. Moreover, there needs to be a big overlap in terms of interests. I’ve always thought a B2B micropayments start-up might succeed more easily than a broad-based B2C micropayments venture. But then I look at my own web research habits: I’m all over the web, and the content I am most willing to pay for is typically the most obscure. Even if a micropayments company could sign up 10% of online content providers, an unimaginable percentage, it wouldn’t much simplify my life.

More subtly, and more significantly, is the natural hesitation about buying something that the seller won’t show you in advance. Content is an experience good – you can’t assign a value to it until you’ve seen it. And of course, content providers can’t really show their content in a meaningful way prior to the sale. Over the years, I have purchased “articles” that turned out to be 24 words long. I have bought “books” that were 14 pages. Of particular concern to data publishers, I have purchased company profiles that contained little more than the company name and address. It turns out this data publisher had a lot of detailed, high value company information, but on only some of the companies in its database. And it’s not just an issue of length or depth. I have purchased journal articles that were quite lengthy and detailed, but that touched only fleetingly on the topic I wanted to learn about, something that’s very difficult to discern in advance.

In short, micropayments for content is hard, because there’s so much content out there, and the inherent need to say “trust me” to potential buyers. At least at this stage of development, micropayments don’t look like a big opportunity for content publishers, data publishers in particular.

Tapping Into Phone Data

For all marketers, B2B marketers in particular, the telephone has long been both a great friend and a big problem. Telephones are a great friend, because someone who calls you, particularly if it’s in response to your advertising, is a top quality prospect. At the same time, telephone calls resulting from ad campaigns have remained difficult to count, measure and evaluate.

And it’s not for lack of trying. I go back in this industry long enough to remember the glory days of “key phone” numbers. In essence, publishers would convince advertisers to use a dedicated phone number in each ad campaign as a crude way to track results. This approach worked, but because they really only yielded call counts, all they could do is prove a point for the publisher. Key phone yielded very little insight into the nature and quality of these calls.

Lest you think key phones are a dated concept, it’s interesting to note that this is essentially what Google is doing with its recent launch of call tracking for AdWords. Intriguingly, Google hasn’t really advanced this technology much – it’s all about using dedicated phone numbers to count the calls generated by your AdWord campaign.

Yes, for 30 years, call tracking technology hasn’t advanced very much. At least that’s what I thought until I recently ran across a company called Convirza.

Convirza offers basic call counting. But it goes much, much further. It has developed software that analyzes every incoming call (most companies already announce that incoming calls may be recorded, putting to bed any privacy issues), actually listening to each call to provide a call quality score. It can measure the outcome of the call, presumably by listening for keywords, to measure call conversion rate. It can even flag calls where it feels the salesperson left money on the table by not trying to upsell or cross-sell the customer. More generally, it can provide a quantitative assessment of the quality of each salesperson’s selling skills.

But wait, there’s more. Convirza integrates with marketing automation software, and can even be used to adjust online ad spending in real-time. If a particular program is generating a solid percentage of calls that convert, that program can be immediately scaled up.

This isn’t even everything that Convirza does, but you get the idea. By analyzing and deconstructing recorded phone conversations, Convirza is generating high-value, actionable data where none existed before. And stunningly, it’s left Google in the dust, because while Google is fine for counting calls, Convirza solves for the “last mile” problem: whether or not that call converted.

We should follow Convirza’s example and expand our thinking about how to extract data from unconventional sources to solve real-world business problems. It’s also a technology that advertising-based publishers could likely adapt to provide not only proof of performance, but a remarkable level of added value to their online advertisers.

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!

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.

Getting Your Data Into the (Work)Flow

In a fascinating move this week, Salesforce announced a new plug-in offering tight integration with Microsoft Outlook. This new capability, still in beta release, is offered free to Salesforce customers with its Enterprise plan or higher.

Why is this fascinating? First of all, Salesforce compete head-to-head with Microsoft in the CRM space, so this is arguably a shot across Microsoft’s bow on that front. But more importantly, it’s showing the growing importance of both applications and tight integration to data publishers.

One of the great weak spots of most CRMs has long been email integration. Getting email from one’s email client to the CRM has tended to be clunky and far from automatic. Getting salespeople to send email from the CRM tended not to be practical, and nobody wanted email messages spread across two systems.

This new integration from Salesforce doesn’t magically solve all these issues, but it’s a big step forward to making the user’s preferred systems and processes more powerful. And that’s exactly the mantra we’ve been preaching to the data industry for many years now. Get into the user’s work environment and get in deep. This is a great example of this principle at work. And even better, the many data publishers already leveraging the Salesforce platform can leverage it immediately and for free.

This brings up a larger discussion about data publishers becoming dependent on third-party platforms. Sometimes it makes sense and sometimes it doesn’t. And part of that decision process involves an honest assessment about whether or not you can reasonably achieve deep embedment like this yourself.

Another useful point this new plug-in highlights: for all its issues and flaws, email isn’t going away anytime soon. And because it is arguably the most core workflow tool at most companies, it is arguably the most important place to seek to embed your data … provided your data makes sense in this context.