GIS Business Model Check-up

By Adena Schutzberg

One of my favorite questions to ask a new geospatial or location-based technology startup entrepreneur is about the business model. It’s a simple question that boils down to: “How do you plan to make money?” I’m excited to find new, compelling or creative answers. 

To brush up on the topic of business models I dug into a series of articles noted in an end-of-the-year post titled Managing Startups: Best Posts of 2012 on Platforms and Networks that address the topic. In this article I want to share what I learned; it applies to the geospatial marketplace.
Bill Gurley argues that all markets are not equal and offers 10 Factors To Consider When Evaluating Digital Marketplaces. He lists the stark realities involved in creating a successful online destination for buying and selling. Not sure what a marketplace is? Think of Amazon or eBay or Zappos. Can you name a geospatially related one? To what site would you go to identify and buy geospatial software? Geospatial data? Geospatial programming services? I can think of a few startup efforts, but can’t name one that I’d consider the GIS version of Amazon.
Why not?
High buyer and supplier fragmentation is a huge positive for an online marketplace. Likewise, a concentrated supplier (or purchaser) base greatly diminishes the likelihood of a successful online marketplace. A highly concentrated supplier base will be reluctant to allow a new intermediary in their market, and as a result will likely fight rather than support your arrival.
I suggest that we have a concentrated supplier in Esri for many of the products and services and I could be convinced we are moving toward a concentrated purchaser with more federal, state and regional contracting options. For example, a new contract just appeared for GIS cloud services for those in the Western States Contracting Alliance.
Dave Beisel discusses strategies and approaches for overcoming what he calls “cold-start inertia” in Start Your Marketplace Engines. What is cold-start inertia? It’s the challenge of attracting both sellers and buyers to get the marketplace off the ground. My favorite suggestion to overcome it has to do with geography.
Brute force a mini-market and expand. Rather than create a broad market at the outset, another approach is to concentrate deeply to create very specific marketplace liquidity and branch out from there. Often this focus can be on a specific geography or vertical. Some startups which have started in Boston with this strategy are TaskRabbit (personal assistance in particular location), Zintro (experts in particular domain), and (caregivers in a specific vertical and geography) have utilized this methodology.
Simon Rothman describes How To Structure A Marketplace and makes this suggestion, worthy of reading twice.
For every aspect of the marketplace, ask: does the user do the work or does the platform do the work?
Depending on the nature of the product or service, one end of the continuum or the other, or somewhere in between, may be appropriate. The trick is to find the right mix. Years ago I attempted to buy some satellite imagery via the Web. The platform asked far too much of me and I had to call the company directly to complete the purchase. These days I find the process sliding more toward the middle of continuum.
Online Commerce
Fred Wilson lists and explains online Revenue Models - Commerce. He basically lists all the ways you can make money “selling stuff” online. Retailing, buying goods at one price and selling them at a higher price, works differently online than offline. That explains why so many of us shop at Amazon. 
Other models include:
  • The marketplace (discussed above), where the owner matches sellers and buyers and takes a cut
  • "Vertically integrated retailing," where the seller makes the goods in question
  • Flash sales and daily deals, where prices are discounted on a single product for a limited time until “they are gone”
Traditional retailing is done in our space. GIS resellers and partners sell products (software, hardware and data) created by others. As products become even more commoditized I wonder how much longer that will last? Proprietary software vendors are essentially doing vertically integrated retailing; Intergraph makes the software and sells the software. I’ve seen flash sales and limited-time deals in geospatial, mostly within the surveying arena (not sure why). They’ve certainly not taken off like Groupon and friends. My hunch is there’s not a big enough market for the products and the products are far too specialized for this model to work in geospatial.
Rishi Shah penned Freemium Pricing for SaaS: Optimizing Paid Conversion Upgrades which addresses how to define service levels with an eye toward eventually gaining paying customers from users of the free service. He gets right to the heart of the matter:
We need our free plan to be something amazing so people will sign up. However we don't want it to be so amazing that they don't ever need to upgrade.
He gives some examples of what successful companies have done. My favorites:
  • 37 Signals at startup had a free plan and promoted it. Once there was uptake, it still offered the free plan, but didn’t mention it.
  • Wufoo puts the highest cost plan at the left and the lowest cost one at the right. Since we read left to right, as Shah puts it, “The $14.95 price tag doesn't seem so bad when you just read the $199.95 price.”
  • Either have a 30-day free trial or a free plan, not both.
  • DropBox lives on referrals. Those who refer new customers get more storage space.
Many “easy to use” consumer/educational mapping websites have free and paid for options. ZeeMaps has tiered offerings from free to hundreds of dollars a year. In the professional space, ArcGIS Online includes a personal account (with newly updated features, APB coverage), but I can’t think of any others. In 2011, Google moved from an “all-you-can-eat” Google Maps API model to one that costs once transactions hit a magic number (APB coverage).
David Skok writes about Why Churn is SO critical to success in SaaS. First, what’s churn? It’s a fancy word for customers canceling their subscription to the service and thus lowering your bottom line. Skok argues for what he calls “negative churn.”
This happens when the expansions/up-sells/cross-sells to your current customer base exceed the revenue that you are losing because of Churn.
Okay, so how do you do that? He offers three possible ways (in addition to limiting churn in the first place):
  • Expand revenue from your current product. Basically, as your users get more successful, charge them more. In storage, the more space you use, the more you pay. That could work in geospatial too: the more data the service hosts or the more hits, the higher the fee.
  • Up-sell.  Encourage customers to move to the next level of service - with more features, more support, etc. In the online storage space that might be quicker uploads or downloads or more control of the storage structure. In geospatial it might mean moving from the service that doesn’t include geocoding to the one that does, or from the one that supports only proprietary data types to the one that supports open standards.
  • Cross-sell. Offer customers additional products or services. Offer better basemaps or services to create a unique interface or specialized tools.
These ideas sound amazingly like how successful geospatial vendors kept their customers before the Internet and cloud computing. The big difference in making expansive, up-sell and cross-sell sales may revolve around communications. Back in the day, the face-to-face meeting and some phone calls were the norm. I recall our Data General representative dropping by the Esri Boston office all the time in the 1990s. Today’s relationships are phone-based and via electronic communications. That may mean that small glitches or concerns in service are not shared by the customer until they are ready to cancel. It’s still easy to think that no news from a customer is good news. That was not true in the past, nor is it in the online world. 
What geospatial (or other) online services have kept you happy and paying? Which have you cancelled? Answering those questions is a good start in determining what works to lower churn, keep customers and increase profits.
Network Effects
Brian Balfour addresses the “chicken and egg” problem in Achieving The Network Effect: Solving The Chicken Or The Egg. What’s the problem? It’s all about getting enough users to make the product not just worthwhile, but more valuable as more people use it. (Great examples: Facebook, Amazon reviews) There are really two types of chicken/egg situations online: marketplaces that need both sellers and buyers to be useful (eBay), and social networks where people are looking for/interacting with people like them (LinkedIn groups). 
A solution in the first situation is to offer value to group that is not dependent on the other. In plain English: you “seed” the marketplace with your own or free stuff. If you are building a geodata delivery marketplace you seed it with free data, say TIGER data. That gets data seekers interested and they, in turn, draw more data providers. SpatialCloud and WeoGeo both featured freely available geodata.
I’ll comment only on the social networks within geospatial. Many, many have launched but just a handful have reached critical mass. I’m thinking of some of the larger GIS LinkedIn groups and GIS StackExchange, in particular. Clearly, those have solved the chicken and egg problem.
Sangeet Choudary looks at the opposite of the network effect, the reverse network effect in Reverse Network Effects: Why Scale May be the Biggest Threat Facing Today’s Social Networks. He argues that the value of social networks comes from three areas:
  • Connection: The more people to meet, the more value.
  • Content: More people means more content is contributed that may be of value.
  • Clout: More people means more followers, reviewers, etc. which may mean more influence, and status, for key contributors.
Sadly, as networks get larger, these benefits may turn into liabilities:
  • Connection: New users joining the online community may lower the quality of interactions and increase noise/spam through unsolicited connection requests.
  • Content: The network may fail to manage or curate the abundance of content.
  • Clout: The network may get inadvertently biased towards early users and promote them over users who join later.
So, how to get around these?
The short answer is enhanced friction. In social networks, the rules can make it harder to join groups or contact members; perhaps a personal referral is needed to join. In content networks (like YouTube or Flickr or GIS StackExchange) good curation by users and/or moderators can keep unwanted or inappropriate documents or questions out and discourage others from contributing similar content. Clout can also require extra work to attain. Twitter is regularly going after Zombie followers, purchased followers and the like to keep follower counts “meaningful.”
I’ve been involved in a handful of LinkedIn groups over the past few months and can see reverse network effect in action. Posts are weak (PR professionals are posting links to articles about their clients, for example) and replies include far too many U’s (“U can do it! UR smart and can get the job!”). I’m also frustrated by responses to questions from months or years ago. I’m not sure how long I’ll last!
Clearly, knowing about GIS or geospatial technology is not enough to create and maintain a successful business in these times. New and existing companies need to select and update business models with care, and then nurture them for long-term success. 

Published Thursday, January 17th, 2013

Written by Adena Schutzberg

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