Sharing in Private

While there are many, many B2C ratings and review sites where consumers rate and otherwise report their experiences with businesses, there are relatively few B2B sites where businesses rate other businesses. There are multiple reasons for this, but prime among them is that while businesses tend to have a strong interest in using this kind of information, they typically don’t want to supply this kind of information. In short, they see competitive advantage in keeping their vendor experiences confidential.

One fascinating example of this in the legal market is a company called Courtroom Insight. Originally founded with the simple and reasonable idea of creating a website where lawyers could rate expert witnesses (experts hired by lawyers to testify in court), the company hit this exact wall: lawyers didn’t want to tell other lawyers about which experts they did and didn’t like.

Rather than close up shop, though, Courtroom Insights pivoted, in an interesting way. It discovered that large law firms were very sloppy about keeping records of their own expert witnesses. So, Courtroom Insights built a database of expert witness from public sources and licensed data. It then went to large law firms an offered them an expert witness management database. Not only could lawyers search for expert witnesses and verify their credentials, it could flag those experts they used, along with private notes that could be shared freely within the law firm, but not externally.

This pivot created a nice business for Courtroom Insights but it wasn’t done. Since all of its large law firm clients were sharing the same database, but also individually flagging the experts they were using, could Courtroom Insights convince them to share that information among themselves? Recently, they offered this “who’s using who” data to its clients on a voluntary, opt-in basis. And it worked. While not every client opted in, enough did so that Courtroom Insights could make another level of valuable information available.

While this is just my personal prediction, I think Courtroom Insights will ultimately be able to offer the expert witness ratings that it originally tried to provide. How? By using the protected space of its system to let lawyers trade this high-value information with each other. It will probably start small: perhaps lawyers could click a simple “thumbs up/thumbs down” icon next to each expert that could be shared. But I also suspect that if Courtroom Insights can crack the initial resistance to share information, the floodgates will open, because lawyers will realize they are communicating only with other lawyers, and because the benefits of “give to get” information exchange becomes so compelling.

The Courtroom Insights story provides a fine example of the power of what we call the Closed Data Pool in our Business Information Framework. Sometimes data that nobody will share publicly can in fact be shared among a restricted group of participants, with of course, a trusted, neutral data publisher making it all happen.

Subscription Package Pricing: The Right Choice Makes All the Difference

The rush to adopt the subscription model to all kinds of businesses has become a frenzy. After all, what business wouldn’t want to make its revenue more dependable and automatic? But the subscription model needs to be fully understood and properly executed to reap its benefits. Let me explain.

When I recently made the move from a PC to a Mac, I knew I would have to buy some software over again. I dutifully went to the Adobe site to get the Mac version of Adobe Acrobat. Imagine my surprise when I discovered Adobe only sells software by subscription, in this case $12.99 per month, forever. Sorry, I just don’t make that many PDFs. Perhaps Adobe made a conscious decision to lose some of its customers as it shifted itself to a recurring revenue model, but forcing your customer base to buy on a subscription basis is a risky one.

Another company I looked at has a neat online product where you input raw data and it makes very impressive, high-end charts that you can download. I felt I could make regular use of this product, and was willing to pay some modest amount per month for it. But the company only offered three subscription options: a “free” plan that was so limited it wasn’t much more than a product demo; $14.99 per month for a “pro” version that still had annoying limitations (for example, the company’s name would appear in every slide), and an “organization” version for $1,000 per month – finally, all the features, but at a heady price. In short, these plans provided no option for a serious by low-volume commercial user. Sorry, no sale.

Poorly conceived subscription plans are everywhere. Here are four things to consider as you plan your subscription packages:

• Free plans are meant to build loyalty and usage among low-volume users, some of whom will eventually move up to a paid plan with you. If you cripple your free offering to the point where nobody can get any real value out of it, you’ve shot yourself in the foot. A free plan is not the same as a product demo. It’s used to attract users and grow them over time into customers.
• To maximize revenue, design a plan for serious but low-volume users. There are lots of people who want access to all your product features but won’t use your product every day. A plan that offers a low monthly fee but only offers half your features is not the same thing.
• Limiting features in your mid-priced subscription plans in order to “force” users to buy your premium plan often will backfire. If I am a single user, I will never by a 5-user plan for a lot more money to get the features I want
• Carefully consider price differentials between plans. I have seen products that offered three price points: free with limited functionality, $999 per year and $10,000 per year. Three sizes will rarely fit all user profiles.

The subscription model is a great model. But its success lies in how you choose to implement it. 

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.