Blockchain: The Next Big Thing

We all lived through the heights of the social media craze when every new product needed a social aspect in order to succeed (success is defined as getting funding). My personal favorite was the backyard grill thermometer that posted the temperatures of what you were cooking to Facebook and Twitter. (Okay, there was a little more to it than that, but not much).

But as an Internet fad, social is starting to cycle down, meaning that another Internet fad needs to take its place. My nomination: blockchain.

You have doubtless heard of blockchain, although the odds are you don’t know exactly what it is or what it does. Most people don’t. My understanding of it is sketchy. But when it comes to the Internet, complexity is a benefit because everyone salutes when they hear about a new service using blockchain, without being able to ask any tough questions about how or why.

A great example of this is a restaurant review site called Munchee. Munchee plans to disrupt sites such as Yelp and Zagat in part by using blockchain technology. Think about that for a while. Or better yet, don’t think about it. You’ll get a headache.

Munchee has a few interesting twists to it. First, it’s meant to be more granular than sites like Yelp, by focusing on the individual dishes a restaurant serves, based on the belief that all dishes served by a particular restaurant are unlikely to be of equal quality. You might doubt the need, but it’s a plausible idea.

Munchee also wants to correct for sample bias in reviews. It’s well understood that people are more likely to post a review when they are dissatisfied. Munchee wants to get around this problem be rewarding all reviews with tokens that can be redeemed at restaurants or even sold to other Munchee participants for cash. If you are getting paid for every review, the reasoning goes, you’re as likely to create a positive review as a negative one. Again, an interesting idea.

To get even more accuracy, Munchee wants all reviews to be peer-reviewed by other Munchee users. Munchee intends to recruit peer reviewers by using (buzzword alert) machine learning to find the other Munchee users best qualified to pass judgment on the review. Still again, the notion of peer review is an interesting one.

So where exactly does blockchain come in? Does it, for example, somehow definitively tie the reviewer to the restaurant, in order to eliminate false reviews? Well, no. Instead, those award tokens that Munchee offers are actually crypto-tokens that are tied to the Ethereum blockchain. That’s it.

Munchee actually has some fresh approaches to review platforms, but it apparently couldn’t resist the temptation to bolt on a tenuous blockchain application to sound even cooler and more cutting-edge. Unfortunately, that works to obscure the more basic ideas it has that are likely to be where the real value is created. We all need to be careful not to fall into the trap of rushing to adopt new technologies just because they get a buzz around them. You’ll only end up confusing your customers … and yourself … about the true ways you offer value.

ADS.DATA

It’s not news that fraud is rampant in online advertising. It turns out that one of the biggest reasons is the fact that the buyers and sellers of online advertising in large part do not deal directly. They transact through third party brokers and marketplaces. Increasingly, it’s now computers ordering through third party brokers and marketplaces – the wonderful world we call programmatic. With no humans watching, much less policing the buying process, it is notsurprising that crooks and thieves have rushed in.

One of the easiest types of fraud is simply to misrepresent yourself online. You can tell an online marketplace that you represent the CNN website, collect the revenue, then run the ads you sold on some other website, often one that gets lots of bot traffic and other fake clicks in order to show performance.

To fight this type of misrepresentation, the Internet Advertising Bureau (IAB) created a new standard called ADS.TXT. It’s a small standardized format file that a website owner creates and places on the website that lists all the website’s authorized sellers. If you’re familiar with ROBOTS.TXT, it is exactly analogous.

The idea is that programmatic advertising buyers can easily and confidently check a website’s list of authorized resellers. It’s a full, workable solution to a significant problem, but it comes with one big catch: the ADS.TXT file is necessarily open to everyone who wants to view it. And a lot of publishers and other website owners aren’t thrilled about exposing what they consider proprietary information.

The solution? In my view, it’s a central database, operated by an independent third party. The same information can be placed in the database, but access can be easily restricted to those who “need to know” the information. I’ve always liked opportunities where an industry needs to share information but at the same time doesn’t want to make that information public. A neutral data provider is most times the perfect answer, as I think it is in this case.

Moreover, a central database can add additional value, because it can track what is happening. It can automatically nag website owners who don’t update their reseller lists regularly. It can check which advertising marketplaces are using the service. In these and many other ways, it can actively work to keep all players engaged and honest.

And of course, data being data, there’s an easy opportunity to aggregate this reseller data to look for sales trends and market share. This information can be given or sold back to the industry without any privacy concerns.

ADS.TXT is just one example of a good idea that could be a much better idea if there was a trusted data provider in the middle, protecting privacy while mediating and recording access to insure compliance and data accuracy. I’d like to see ADS.TXT as what you might call ADS.DATA. You’d be wise to look for analogous opportunities in your own market.

Data as the Decider

I have discussed before how data providers can leverage their central, neutral market positions to collect highly valuable data that otherwise couldn’t be collected. Examples abound of data providers that have convinced companies to provide them with their information crown jewels – sales data, pricing data and the like – in return for getting it back (on a paid or unpaid basis) in aggregate, anonymized form. Fundamentally, the companies realize that their data, no matter how sensitive they consider it to be, has even more value to them when combined with or compared to a larger set of similar data. These situations are wonderful opportunities for data publishers, and they are cropping up more and more as companies get better about organizing their internal data and then become more sophisticated about how to optimize it.

But there is a level above this enviable market position. It’s when data actually starts to drive commercial transactions. I have worked with companies whose data products actually drive the bonus compensation of salespeople and managers across entire industries. I have seen data products that are used to set valuations of companies for sale. And of course, there are industry giants such a Nielsen, with its well-known television ratings that drive billions in ad dollars.

The commonality among this rarified group of data providers is that their data is survey-driven. These companies leverage not only their neutrality and impartiality, but they are gathering data that no individual organization could easily or credibly collect on its own. In many cases, these data companies are gathering customer and user experiences and actions.

Yes, for the right kind of opportunity, a simple survey can be turned into an extraordinarily valuable data product. Again, the key drivers of such opportunities are: 1) a need to gather customer/subscriber/user opinions/ratings/activities; 2) the information is difficult for industry players to gather themselves; and 3) the need for trust and objectivity in the collected data.

It may sound hard and complicated, but in the right situations, a well-executed survey can be the path to a very valuable data franchise.

Good Databases Are More Than Just Good Data

We can look to the UK for a case study of how a government agency, after several tries, couldn’t build a user-friendly data product, creating a giant opportunity for a for-profit data company.

The story begins with a regulatory agency called the Financial Conduct Authority (FCA) that among other duties, registers and regulates financial advisors and advisory firms. The FCA has a searchable database on its website, but like so many government websites, it is optimized for one purpose: checking the registration status of a known individual or firm. As a tool to assist you in identifying an advisor to help you with your investments, it’s pretty useless.

In recognition of this shortcoming, the FCA called on a quasi-governmental organization called the Money Advice Service (MAS) to help build a better adviser database, and MAS accepted the challenge. I took a look at this website when it first launched, and though I saw some design issues, it had potential.

But even though MAS nominally had the freedom to build a creative database with almost any business model behind it, its need to avoid controversy ultimately resulted in a very limited and timid product. And when, unsurprisingly, there wasn’t a lot of revenue to be had with such a product, MAS buried the database three levels down on its website and moved on to greener pastures.

With two free databases of financial advisers out there, you think there wouldn’t be much opportunity left for anyone. However, a company called Unbiased saw things differently, and said there was indeed an opportunity … for the right product.

Unbiased has been a big hit in the marketplace, and the way it differentiated itself from the free government services with the same basic listing data holds lessons for us all

• Greater visibility – Unbiased wants to be found because its business model depends on driving lots of traffic to its participating advisers
• Deeper data – ratings, discount offers and detailed profiles
• Strong user interface – clean, inviting design and both parametric search and a custom matching service         

If you have ever wondered how you could compete against a free, government online database, Unbiased provides the answer: data presentation can be as valuable as the underlying data itself, particularly if you are serving a consumer market. And aggressive promotion of your online database will let you run circles around government agency databases, that are generally hard to find in addition to being hard to use. 

Data Democratization: A Timely Trend That Empowers Users

“Democratization” is the latest trend in data. While it is rapidly acquiring multiple definitions, the one I find most useful suggests that there is a growing opportunity to open up complex datasets to people who could benefit from them, but haven’t traditionally used them.

With this definition, data democratization usually involves some combination of pricing and user interface design. Reduced pricing is meant to make a data product more broadly accessible, and user interface design is about making the data incredibly easy to use. Putting these two together, those employing a data democratization strategy believe they can significantly expand their markets. In addition, a powerfully simple user interface should result in reduced support costs by enabling less sophisticated data users to start getting the answers they need directly, by themselves.

The best opportunities for data democratization? Look for data silos.  The data provider combines several datasets, doing all the complex normalization and matching that is required. The user interface then lets users painlessly do what amounts to cross-tabulation and filtering with all the complexity carefully hidden. Results are usually in the form of highly visual data presentations.

Data democratization is not “dumbing down” data. Indeed, a democratized data product often has all the power of much more complex and expensive business intelligence (BI) software. The nuance is making the user interface more accessible and less scary, and reducing the price point so that the product isn’t a major purchase decision.

You can see an analogy of sorts with what happened with computers, moving from centralized, expensive installations operated by a few with specialized skills to the amazing desktop computing capabilities we all enjoy today. Whether data democratization is an opportunity of the same scale and profundity as the computer revolution is unclear, but it certainly bears close watching because this is a strategy with a powerful first-mover advantage.

To see a great example of data democratization, check out one of this year’s Models of Excellence, Franklin Trust Ratings.

Better yet, meet the founder behind it. John Morrow, at this year’s Business Information and Media Summit, Nov. 13 – 15 in Ft. Lauderdale. There will be lots of other data trendsetters there too!