Skip to main content

Informal Catalog of Business Models for Internet of Things (IoT)

This article mostly contains public knowledge, however seeing the data compiled all together in this way may help to rationalize it and apply it in a more rigorous way.

I hope this express catalog helps others the same way it helps me. By running new hypothetical product concepts or existing offerings through these "filters" helps to understand their strengths and weaknesses.

Which monetization models would you add to the following list?

Selling IoT devices for end users

I this case the device in itself delivers the key functional capabilities, with enough customer value to pay for its price tag.
Many time these products leverage existing infrastructures such as Wi-Fi, a Smart Phone, etc.

Even if this model centers around the IoT device, a software and/or cloud service may be necessary as a companion for a rounded UX.
Software and/or services put more pressure on R&D and ongoing operational cost, and consequently in the product margin; which usually has already a constrained delta between price and cost.

The product must have truly differentiated capabilities to succeed, since commoditization, price, scale, and competitive mass distribution channels will put a lot of stress to this model.
Mostly high end products with decent margins or low margin and large scale ones will be more successful, making it more difficult for middle tier contenders.

Constant innovation, first mover advantage, and fast new versions releases are another must for this type of products. In the case of the consumer segments, better to go to market in partnership with a large brand with a massive distribution channel.
Competition on price and distribution is much higher in consumer segments, targeted B2B offerings often have more room for higher prices and higher margins.

(Debatable) Examples: Droplet, Kevo Smart Lock, Taski Intellibot, etc.

Selling hardware at low margin and charge for additional services

Multiple sub-variants may exist in this model, from selling product at low margin, to at cost, to fully subsidized hardware. In any case the device is just a vehicle to charge for something else, most of the time a subscription for a related service, charge per transaction, additional cloud storage, being a retail outlet, etc.

The customer value may still be related to the hardware piece, however the underlying service is the one that completes the offering and/or captures the value as revenue. An example of this could be an intelligent pet food dispenser.

In this example the customer values the device and its associated automation and convenience, however, from the company perspective, a food replenishment service and the markup on selling the food in specific containers could be a more profitable approach. At the same time, this creates a long term recurring revenue stream, arguably more appealing than the one-time margin obtained from selling the IoT dispenser for a one time price.

This model is not mutually exclusive with the one before, some IoT products are profitable being sold at a relatively high price and margin, and at the same time they offer companion paid services for supplemental revenue.

This a very familiar and straight forward model in the consumer space, very evident in IoT products from Google such as the Nest line or the Echo or Dash products from Amazon.
This companies use the data that you generate, using this device for advertisement, e-commerce, and related revenue.

Margins, operations efficiency, and certain exclusivity/proprietary angle are key ingredients for profitable service behind these IoT products.

(Debatable) Examples: Amazon Dash, Canary Monthly Membership, MedMinder, etc.

Revenue share via recommendations

Sometimes IoT devices have access to valuable customer information that can be monetized but the device manufacturer may not have the expertise or resources to commercially exploit it.

In this case the company charges or gives away a device, software, and/or service that provides some level of valuable functionality to the user.
The user activity sensed by the device (current location, movement speed, ambient temperature, biometrics, timestamps of activity, etc.) can be collected, mined, and/or machine learned (ML) to drive consumer insights.

The provider of the IoT offering in this case knows a lot about the customer and it may also have a trusted relationship with the user, it may even have a personal user experience that could become a great channel to offer additional products or services in a transactional way.

The IoT provider may not have the in-house "inventory" of ideal products or services matching the needs of the consumer segments that it serves, however it has the "right" to offer customized picks of product or services tailored to the user profile (which happens to know very well due to the data it collets from her).

The right product/service recommendation to the right person at the right time has a highly valuable marketing edge and high revenue potential.

The described scenario is ideal for strong partnerships between the IoT provider and third party service providers or product vendors in the shape of recommendations, referrals, or similar shared transactions.

You may find this model similar to others in this catalog, the subtle difference in this case in that the company providing the IoT solution cannot provide or may not want to provide the products/services themselves but just their recommendations, in this way they can focus on the IoT expertise and leave the commercial exploitation to others.

Example: IGS Home Warranty recommended by Nest products, Fitbit make recommendations to local fitness events, etc.

Selling hardware at low cost to obtain customer data and then sell it to third parties

In a first impression you may find this model similar to the previous one, the main difference is that in this case the IoT vendor may not be or want to be in the position of making recommendations to the end user, it may even not have a direct user experience or communication channel with their customers, therefore it may prefer to just collect data and sell it to third parties.

The obtained data or the derived insights can be sold to third party companies who can really commercialize it.
For instance, utility companies would pay for insights about domestic energy consumption collected in near real time by IoT devices, since they can make better infrastructure investment or dynamic re-deployment of resources.

In models like this access to data acquisition and possessing a minimal critical mass of data intake instances is critical. Certain scale of data (big data) is necessary to drive representative population samples.
For more profitable results would be ideal to leverage the same sensors/devices to collect multiple types of datasets for different uses with a single hardware deployment, this approach will allow to sell insights with a lower cost of acquisition per data unit.

Key elements for success are: the right level of focus and specialization in a business domain, as well as are as access to a solid pool of partners willing to pay for the data or their inferred insights.
The more value-add is built in the form of insights on top of the raw data then the higher can be the potential margins.

Examples: IOTA Marketplace

IoT to control insurance cost

Sometimes insurance companies offer their own device, others, IoT vendors strike a deal with insurers, but in any case the model is simple: customer data points feed the insurance risk algorithms.

Tailored risk assessments allow insurance companies to reduce their cost and pass those savings to their customers in the shape of promotional incentives.

The IoT vendor sometimes gets the benefits as direct revenue share, sometimes as a business referral, or sometimes as indirect positive PR or brand awareness; always convertible in cash.

This model is often more a complementary indirect revenue stream between the IoT vendors and insurance companies.

Making this model the only revenue stream for an IoT product is not the most common case, only specialized partnerships or actual fee-based contracts with certain exclusivity or proprietary situation can make this model highly profitable.

Examples: Car trackers in exchange for car insurance discount, heath insurance discount on good track record in your wristband, Home safety and security devices drive home insurance discounts, etc.


Again, I invite you to bring additional models and I will try to add them to this catalog. Thanks!




Popular posts from this blog

Dear Tech Entrepreneur! (startup or corporate): Embrace Cloud to Stay Competitive!

As entrepreneur (startup or corporate), you need to deal with so many things, to the point that it is easy to get overwhelmed and loose focus. Many of those things that consume your attention are central to your project while others are critical but at the same time secondary compared to the core of your business. Let's see how Cloud Computing can help on outsourcing the load of what is peripheral and how it can empower what is core to your idea, project, or business. Go ahead and take advantage of the Internet Age: One of the positive side effects of the current times is the pollution of digital services. You have at your disposal plenty of service providers which are happy to take those "secondary" concerns of yours and do them for you for a relatively modest fee.  Some of these services range from addressing new concerns that were born in the digital age like email address validation and search engine optimization to the "webificated" versions of tr

Linux, Cloud, Open Source, Virtualiztion, PaaS, Java, BigData, Mobile, and more in a single event: Red Hat Summit and JBoss World 2012

What is the only high-tech event in the industry that can concentrate, in a charming city like Boston , all the technologies and thought leaders that are driving software innovation today? The answer is Red Hat Summit and JBoss World 2012 on June 27th to 29th, let me prove why... This is not just another software vendor event, in which you only see the vendor's product stack from the angle that they want, as its name implies, Summit 2012 is a multi-perspective open event, in which the open source communities, an ecosystem of Red Hat partners, and independent parties get together in aparticipative event hosted by Red Hat to talk and share experiences as they drive forward the next fronteer in information technology and software development. Let me prove you through the 7 points below why you get the best of the software industry in a single event, and show you how Red Hat is powering many more critical areas than you may think in today's tech world: Watch this cool S

Cloud, SaaS, PaaS, and IaaS Adoption Trends and Forecast

At this point it is clear that the term "Cloud" transcended the buzz word and is already the label of an attractive $100B+ market. Cloud Computing represents the top enterprise IT spending in 2015, even beyond other hot growing technologies like Mobile and IoT. Not just that, budgets for Cloud offerings may even double in 2016. And if we talk about the other two hot tech trends, it is not a surprise that about three quarters of the IoT and Mobile offerings have also a Cloud component. Let me share with you my own direct experiences and my interpretation of some key Cloud Computing statistics over the last few years as well as the trends for the next two or three. In every case contrasting the numbers with qualitative data points and insights. Let's then dissect the Cloud universe in the typical 3 tiers, starting from the bottom... Infrastructure as a Service (IaaS) In 3 years IaaS will represent: ~35% of cloud use cases (compared with a ~65% of PaaS + SaaS)