Big Data, Small Startups: One Angle On Turning Data Into Money

Thanks to commodity computing power, it’s possible to build a startup business based around big data and analytics. But what does it take to do this, and how can you make money? 

It’s no surprise that in the time since Varian’s opining (2008), we’ve seen oodles of small startups setting their sights to capitalize on Big Data. And now, we’re learning from their failures. But Big Data doesn’t need to be the place bright startups go to die. After a number of startup breakups with El Data Grande, Pete Warden came up with a tangible analysis of what the path is from stacks to riches.How To Turn Data Into Money is one way to approach a complex topic in a landscape of changing tools, and it’s well worth a look. He describes the process of identifying how to make data turn a profit. Warden reinforces the notion that we’re still in the early days of really knowing where the ‘big wins’ are with Big Data.

The overall issue is this: From the outlay, many startups are going to be sitting on a large bucket of data but won’t be in a position to imediately know where the monetization sweet spot lies. As Warden suggests, they will have to go through a series of processes that enables them to zero in on how to provide the maximum amount of value by iterating in partnership with their customers/users.

The first step might be to summarize the data and provide simple graphs. This allows everyone, your customers and your own team, to really understand what the data might show.

As feedback is obtained from this initial process, key metrics and other indicators can be focused on in reports. This will begin to allow you to answer specific questions that will (hopefully) be of value to your customers.

It’s no surprise that your customers, once identified, are going to be where you go for answers to their needs. Iterating your business in response to working with your customers – which is always valuable no matter what vertical you are in – will ultimately bring you to a point where you can provide business intelligence and actionable recommendations for your customers based on what they are already doing with the data.

Being able to point out specific trends, suggestions and points of friction (contextual to your data’s domain) should be of great value and something your current and future customers will be willing to pay for.

Finally, Warden touches on how your shiny data should be presented – dashboards are commonplace, but clearly we’re in very early days in this space. What’s important to remember is that what’s being built here is a combination of product and consultation. If you need an initial framework to begin tackling the problem Warden’s post works as a great framework, but given that Big Data could be about anything, you will need to consider your domain space, the nature of the data and your own expertise to be able to know whether this will work for you.

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Data as a new marketing channel – Chief Marketing Technologist

Link: Data as a new marketing channel – Chief Marketing Technologist

Just as companies who were quick to embrace the web, search marketing, and social media used that as a competitive advantage, a similar dynamic is likely to exist with the web of data.

  • Whose data will be the authoritative source in each market out there?
  • Whose data will be embedded in the most exciting third-party applications?
  • Whose industry-specific vocabularies will become de facto standards?
  • Whose open data will be most linked to within other data sets, generating a positive feedback loop around a data-level brand?

Those are strategic questions that marketers should begin thinking about.

The shift to data web marketing will take a little getting used too — we’ve had 30 years of clinging to data as something to be squirreled away. Gaining organizational experience in the web-facing data tactics above is a good start, but more forward-thinking leaders in marketing should encourage their teams to connect the dots between these initiatives. They should contemplate what Tim Berners-Lee said in an interview with Talis, advising company leaders on what the semantic web can really mean for them:

You should take an inventory of what you have got in the way of data and you should think about how valuable each piece of data in the company would be if it were available to other people across the company, or if it were available publicly, and if it were available to your partners.

That is the essence of data web marketing.


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