Viewing entries in
Best Practices

Looking for a New Product Idea? Just Ask.

(Part One- Continues Next Week)

Where do really good ideas for new data products come from? Not surprisingly, I am asked this question a lot. Perhaps surprisingly, the answer isn’t all that complicated.

The best ideas for new data products almost invariably come from personal need. History shows that the data products that succeed most readily tend to be highly specialized in terms of content and user base – and they were typically surfaced by people who would use such a data product themselves, if someone else produced it. The person who sees the opportunities knows just how useful and valuable the new product would be, that nothing else like it currently exists in the market, and that there are many other people in similar roles in other companies who would benefit from it. Right there, you have all the ingredients for a winning data product, and I have seen dozens of them over the years, in almost every case started by someone with no data publishing experience, but who did have a deep understanding of the need for the data. As just one example, a recent news article talks about a professor, frustrated by the lack of information on sustainable building products manufacturers, decided to compile his own directory. Despite being published as a print directory, it’s already in its second edition – the need was out there for this information.

Why did a professor of architectural technology and building science decide to become a publisher? Likely because he didn’t feel he had any options. And that’s not surprising. For despite the intense interest of B2B media companies in new data products, not one that I know tries to reach out to its audience for new product ideas. That’s a shame, because in my experience it’s mid-level executives buried deep in large organizations who are the best source of these new opportunities. All you have to do is ask. 

Meet Three of the Best…

We created the Infocommerce Models of Excellence program back in 2003 to recognize data products that provided good examples of innovation in business models, markets served, content innovation and technology.

The point is that they offer fresh ideas and approaches that are applicable across many market verticals, and that’s why they’re worthy of attention and study.

The three honorees this year, in no particular order are:

Franklin Trust Ratings, a healthcare data provider that has not only done an impressive job integrating nearly a dozen public domain databases, but has an innovative business model as well. Franklin Trust founder John Morrow is building his business around the idea of “democratization of data.” In simple terms, this means that that he is consciously building an end-user analytics tool, using a powerful but simple user interface with pricing that makes it accessible to all. In an era of five- and six-figure analytics-driven data products built for trained data analysts, Franklin Trust has built an analytics product that can be used by anyone, and that anyone can afford.

Savio has developed a talent marketplace for the marketing research industry. Talent marketplaces aren’t a new concept. Indeed, it can be argued that they helped jumpstart the growth of the gig economy. Savio has bigger ambitions, however, seeking to tap into the growing shift to automated vendor discovery and procurement, as well as to start to evolve its existing online buying guide product to a truly transactional meeting place for buyers and sellers. It’s almost inevitable that all buying guides will have to move in this direction. Savio is blazing the way.

LexisNexis Risk Solutions is one of the largest and best-known data players out there, but that’s not inhibiting it on the innovation front. Consider its new Active Insights product for the insurance industry. How many millions (billions?) of dollars have been spent building out cutting-edge lead generation technology. Whatever the number is, it’s huge. How much has been spent on similar technology for custom retention? It’s a tiny amount by comparison.

What Active Insight does is simple yet brilliant. It flips lead gen technology on its head and applies it to customer retention. An insurance company supplies its custom file to LexisNexis Risk Solutions, which monitors them in real-time for trigger events. Did a customer just put her house up for sale? LexisNexis Risk Solutions spots the real estate listing and tells the insurance agent to get in touch with the customer ASAP to help her seamlessly transfer her coverage to her new home. We have the technology. This is just a great new way to put it to use.

All three of our 2017 honorees will be presenting at the annual BIMS conference next week in Ft. Lauderdale just. Their creators are people you’ll want to meet to put their experience and innovation to work for you in your industry. See you there.

 

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.

 

Can You Over-Monetize?

To avoid accusations of commercial blasphemy, I am going to pose this as a question, not a statement: can you over-monetize a data product?

Consider the online real estate listings databases. There are lots of them, all engaged in a fierce battle to the death. They make their money selling listing upgrades to real estate agents, a hotly competitive and demanding group. The product they are selling is homes that can easily cost $1 million and more, with very sizable commission dollars at stake. In such a high ticket and fiercely competitive market, would you want to junk up the user experience with irrelevant advertising, and annoy your real estate agent customers by distracting users from the listings they are paying to enhance? The answer appears to be yes.

Several of these sites have now been designed to display programmatic ads. With all it takes to attract a live buyer to your site, do you really want to risk that buyer clicking on an ad for a local car dealer and leaving your site entirely? Do you want to intersperse listings of homes with ads for mortgages when your primary source of revenue is real estate agents who badly want your site visitors to look at their listings?

You know the saying: real estate is all about “location, location, location.” Does it make sense then that when a potential buyer clicks on a map icon to see where a home is located, she is presented with a map cluttered with logos indicating the location of nearby State Farm insurance offices? Does anyone buy a house based on proximity to an insurance agent? Doubtless someone thought this was a clever marketing gambit, but it distracts, confuses and possibly annoys the potential buyer.

The photo slideshows that are the critical core of each home listing are now increasingly cluttered with advertising. If I was a real estate agent paying to upgrade a listing only to find it was chock full of ads, I’d be furious. I want prospects looking at pictures for the home I am selling, not distracted or annoyed by irrelevant advertising from third parties.

A lot of this comes down to the degradation of the user experience. But in some cases, it’s an even bigger issue: it’s a problem of the data publisher forgetting who they are serving and in some cases, why they are even in business. A little bit of incremental revenue can sometimes have a very high cost attached. And the guiding rule of all things online remains the same: just because you can, doesn’t mean you should.

Monetizing Mediocrity

I laughed out loud while reading a recent Bloomberg article describing how Apple has a secret team hard at work to improve search in Apple’s App Store. Key to this initiative: finding a way to introduce paid search so that app developers can pay to come up first in search results. Oh yes, as a secondary objective, this secret team is also “trying to improve the way customers browse in the App Store.” Note that they’re improving browsing, not search!

Yes, the App Store, which the article correctly notes is a vital part of Apple’s business, urgently needs to be better monetized. Better functionality? Maybe, they’ll look at that too.

The App Store is a case study in bad design and a bad user experience. My sense is that it was created with the notion that users would primarily browse for apps of interest. But with 1.5 million apps and only 25 categories, you better have a lot of time to kill if that’s the way you want to find new apps.

Search is even worse. It starts with the well-hidden search box. Start typing in a word, and the search software will helpfully suggest phrases. But if you click on one of these search phrases, more often than not, you’ll come up with no results. Further, Apple seemingly permits companies to stuff their entries with the names of competitive products too, so you have to be extremely careful what apps you download, something I discussed in an earlier post.

Searching in the App Store is incredibly literal too. Apparently, concepts like wildcars or Soundex or even relevancy eluded Apple’s celebrated designers. In almost every respect, Apple appears to have succeeded in spite of itself.

Besides serving as a useful case study of how not to build an online store, business information companies need to consider how this impacts their products and digital strategies. Most business information companies distribute their apps through the App Store. It’s important not to take for granted that they will be found. Try searching for your own app in the App Store using common searches your typical user might try. I can pretty much guarantee you’ll be disappointed if not shocked by the results. Saying “download our app from the App Store” is unfortunately not enough direction for users. Also, spending some time to really think through your App Store listing is absolutely time well spent.

You should also keep an eye out for scammy apps that may be presenting themselves in confusingly similar ways in the App Store. Apple doesn’t seem to care, but you may be losing business to other app developers that don’t have your user’s best interests as heart, and this could ultimately reflect back on you. There are a stunning number of apps that seem to be gaming the system.

Apple’s planned solution to App Store search seems to be not to improve it, but to charge money for you to get the results you would expect to get if its search functionality worked properly. And much as I hate to say it, it may be worth paying up, because digital adoption starts with your users getting their hands on your app, and Apple is making that incredibly and unnecessarily difficult to do.