The consumer Internet is a treacherous place. The last 10 years have seen a number of high profile consumer Internet applications rise in prominence whilst trying to answer the question, “but how will it make money?”.
Whilst the upper echelon of consumer Internet applications do eventually turn profitable, the method is always the same. Advertising!
Advertising is a fine way to monetise a consumer application, especially in today’s climate of big data and granular targeting of adverts against tight demographics. There really hasn’t been a better time to create an ad network off the back of your hot new social application. The market for online advertising is hotting up and there is an increasing amount of inventory as more and more people spend time accessing the Internet.
However, competing in this world means you have to go up against the juggernauts of Google and Facebook. These billion dollar businesses are trying to capture as much of the online advertising market as they possible can. This makes creating an ad network an increasingly difficult proposition.
Whilst competing against Google or Facebook can seem like an unsurmountable task, there is another way to monetise consumer applications.
Advertising allows organisations to target users based on their usage of your product. However advertising is a cut-throat industry because inventory is spread across the entire Internet, making one platform compete against another.
However, an area that you will have a monopoly over is the aggregate data of your application.
Problems with monetising consumer applications
There are many ways to monetise a consumer application these days, but each has its own unique positives and negatives. Forgetting about how each method fits with the characteristics of your product for one moment, let’s look at your options.
Positives - This is probably the easiest form of monetisation because you can essentially get going from day one with no permission. Before you reach scale you can simply plug into one of the existing ad networks to start earning money from page views. Once you reach scale you can start brokering your own deals.
Negatives - CPMs are likely going to be very low. This means it will take a significant amount of time before you are really generating a lot of revenue. Advertising is also not very welcomed by users as it is seen as distracting from the user’s experience.
Positives - Subscriptions allow your most loyal users to pay to use your service. When Instagram changed their Terms of Service, many people lamented advertising and how they wished they could pay a subscription to use the service.
Negatives - This is going to seriously stunt your growth. Whilst a core group of users will happily pay for your product, the majority of potential users aren’t going to give your product a shot if it’s not free.
In Product Purchases
Positives - By allowing anyone to use your product for free it will significantly increase the broad appeal to the market. The majority of users will only try a new product if there is no investment and no risk in doing so. This method of monetisation also allows your most loyal users to pay to enhance their experience of using your product.
Negatives - Finding the right balance of what to charge for and what not to charge for is difficult. You also need to give your users enough incentives to want to keep paying you. This method works extremely well for mobile and social games, however it hasn’t really been proved to be an amazing success for other types of applications. Path is trying to use this method with premium stickers, and Tumblr tried to use this method, but didn’t have convincing success.
So as you can see, whilst there are many opportunities for monetising a consumer application, there really isn’t a clear winner. Advertising is kind of the default option because it’s so easy to get going with.
But surely there is a better way?
The opportunity in aggregate data insights
Everyone knows nearly all advertising blows. Unless it is a really creative campaign that is highly targeted to the user, advertising will always ruin the experience of using a product.
Currently I’m really interested in the opportunity of monetising through aggregate data. This allows you to run either a free consumer application, or a heavily subsidised enterprise application where the real business is selling insights into the passive data that you are able to generate.
This is essentially what advertising is to the mass market, but it is packaged in a way that takes the commoditised inventory of page views, and instead sells premium, unique insights into structured data sets.
To illustrate how this business model works more clearly, I will give you two examples of existing companies that are already using it to their advantage.
Probably the most well known online business that is using this model is LinkedIn. Whilst LinkedIn isn’t considered as “sexy” as Facebook, arguably it has a much stronger business.
LinkedIn provides free professional social networking for anyone who wants to use the service. Joining the LinkedIn network is probably one of the best things you can do online to progress your career because it puts you in touch with professionals from all over the world. LinkedIn is so beneficial to a certain group of users that it offers many different premium services. This allows individual users to get access to better search results, better visibility across the network and better tools to reach out to other users.
All of the data that LinkedIn collects about professional people from all over the world is also extremely valuable to recruiters, job seekers and sales professionals.
LinkedIn does not need to rely on advertising to create a very healthy revenue business. Instead, using the power of it’s network and by providing premium tools to it’s users, LinkedIn can create provide a lot of value whilst also making a lot of money.
Nifti is a relatively new company that is looking to capitalise on consumers desire to find the best prices whilst shopping online. Nifti allows it’s users to track the prices of products so that they purchase at optimum time. Consumers can save a lot of money on online purchases if they are willing to put the work in to track price fluctuations. Nifti cuts out this work by automatically pinging users with notifications on products that they have chosen to watch.
Once a product is added to the Nifti network, any user is able to see historical data about the price fluctuations of that product. So it’s easy to imagine that as time passes, Nifti’s aggregate data over price fluctuations and shopping insights will become extremely valuable to a number of potential users.
For consumers, it allows them to see price fluctuations from across the Internet. This is like a consumer shopping heartbeat that constantly watches over what is happening online. By tracking this data, Nifti allows it’s users to rank products by how their current price ranks historically and what is currently the best opportunity to buy.
However, Nifti’s dataset will also clearly be of extremely high value to enterprise customers. By offering this aggregate purchasing data to retailers, they can allow targeted product opportunities and exclusive discounts to specific users.
Whilst data on what a user has “liked” or the people they follow is valuable, actually purchase history is of a much higher value to retailers who are looking to target specific people with their offers.
How to create an aggregate data business
So how do you go about building this type of company? Well there are 5 steps that I would add to a roadmap if I were going to start a company in this space today.
Whilst I think this is an opportunity for both pure play consumer applications and more enterprise type service applications, I would say it is going to be significantly easier to create a product that you can at least charge something for from day one.
No matter what your business model is, building a successful pure play consumer application is incredibly hard. Getting traction is often like catching lightning in a bottle, but even if you do, it can be difficult to support this type of high growth if you are not ready to monetise.
1. Create a service that creates passive data
So the first thing to do is to actually think of a product that is going to create passive data. This is an easy enough task because almost every product will create data of some value. However, you need to narrow your search down to a product that creates passive data that is not only valuable, but also solves a real problem for a tight niche of people who are willing to pay to solve this problem.
2. Offer a low cost “premium” service
In order to generate enough aggregate data, you are going to need to leave the flood gates open to the unwashed masses of the Internet. However, if you are bootstrapping this gig, you will also need a way of keeping your service online.
The best way of doing this is to offer a premium version as soon as possible. This could be anything in the early days, such as better tools for analytics or premium options for companies. Whatever it is that fit’s the character of your product, you should be experimenting a lot and talking to your users to understand what problem they are looking to solve and how you can provide value to them.
3. Data blogs are hot
If you are a regular reader of Culttt you will know that I’m a big fan of Content Marketing. I still believe Content Marketing is one of the best ways to grow traction for an unknown business on the internet.
As you are growing your business you should aim to be recognised as the best source of information for the problem you are solving. This means, give away a little bit of the goodness you are generating by writing insightful blog posts and creating beautiful infographics on the data that you are producing.
A couple of years ago, OKCupid made a splash with their blog on the aggregate data of online dating. Many other companies have since used this tactic as a source of content inspiration.
These types of blogs are easy to grow because you are offering unique and interesting insights that the reader won’t be able to find anywhere else.
4. Build the tools to leverage the data
As you begin to amass a wealth of data, you need to invest heavily into building the tools to turn that data into information. This means not only cutting the code to sift through and search the data, but also being able to accurately draw conclusions and figure out the value.
When it comes to actually offering the tools to end users, your customer shouldn’t need to be a data scientist to get value. Instead, there should be a very narrow set of objectives and value that can be derived from your dataset.
Many companies are trying to tackle this opportunity without really ever nailing what problem they are trying to solve. In order to continue to attract customers, you need to be the go to place to solve a very specific problem.
5. Sell aggregate data and insights to bigger companies
And finally, once you hit the big leagues you can start to sell aggregate data to much larger organisations. For example, in the case of Nifti, they could sell their consumer purchasing data to any number of massive traditional offline retailers who don’t have the scope of Amazon but are trying their best to compete.
Now obviously it is going to take years to reach this stage, so there isn’t much point in pinning your hopes on this outcome just yet. But do keep in mind that these bigger opportunities should be your end objective.
What kinds of industries would this work for?
As I mentioned earlier, I think this is going to be pretty hard to do as a pure consumer play. Social consumer applications are hard enough to build as it is, and so this is probably not the best model for trying to grow that type of company.
However, there are many industries that I think are ripe for this type of opportunity. Including:
Insurance - By creating an application for smaller brokerages to use as a CRM you could draw industry insights.
Medical - Whilst anything to do with patients records is probably going to be out of the question, I’m sure there are many problems that small medical practices face that could you could solve in order to create passive data on the state of healthcare.
Marketing - Marketing is an easy one as anything to do with consumer purchasing is always going to be valuable to retailers across the world. Nifti is already going after tracking price fluctuations, but I’m sure there’s more opportunities to be had.
Journalism - Finding stories, tracking a newsroom, finding sources are all possibilities in the field of journalism.
Over the last couple of weeks I’ve looked at Should I use advertising to monetise my product? as well as Build traction for your product through meta-modelling. Whilst advertising continues to be the dominant form of revenue for online consumer companies, I think the path LinkedIn has chosen to follow is potentially a much bigger opportunity.
The world of online advertising is a big place. Online advertising is still massively dwarfed by television advertising and it offers a lot of amazing opportunities for to connect with consumers.
However I really feel strongly about building a business that does not rely upon advertising to generate revenue. I think the business model of gathering insights from passive data is a much more interesting opportunity.
Only time will tell whether online advertising continues to be the dominant online consumer business model. However whilst LinkedIn is often overlooked or forgotten about, I think they might have stumbled upon the real long term online business model opportunity.