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10 things I learned in my first year selling data at Unacast

I’ve been in the marketing and advertising world for 19 years, but it’s only in the last year, since joining Unacast and building the C2.Ventures portfolio, that I’ve really been embedded in data-as-a-service (DaaS) models. These are a few of things I’ve learned after 12 short months as a data guy.

Chris Cunningham

Chief Revenue Officer

Apr

10

2017

Chris Cunningham
Chief Revenue Officer
Apr 10, 2017

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I’ve been in the marketing and advertising world for 19 years. In that time I’ve helped to pioneer emerging monetization models for apps, widgets and native ads. But it’s only in the last year, since joining Unacast and building the C2.Ventures portfolio, that I’ve really been embedded in data-as-a-service (DaaS) models.

I have to say I am thankful. It has been an eye-opening, career-altering experience. I have learned a ton and my entire perspective on how marketing and advertising create value for brands has evolved as result. Without further adieu, here’s 10  things I learned in my first 12 months as a data and software guy leading commercial efforts at Unacast.

  1. Data has a common currency. In ‘our’ world, mobile IDs (IDFA for iOS, AAID for Android) are what the market trades in. Yet, many times I’ll talk to a well-known company and it’s ‘Yeah, we have data and we’d love to monetize it,’ but then they send us a data sample and it doesn’t have any unique criteria anchored by  device ID. The point is, unless you’re swimming with the market current, it doesn't matter if you have billions of rows of data, or hundreds of millions of X this, or Y that. if your core currency isn’t native to how the money flows, there’s little value in it.
  2. Even data with value is useless if it can’t be traded. This is interesting . . . let’s say you have another type of data currency, like cookies, or emails. These are valuable, but to work in conjunction with location, they need to convert from one to the other. Email companies like LiveIntent are great but to work with location data they first need to hash email to device ID. The same is true for mobile web companies, etc. That puts an extra step into the trade process.
  3. Data collection is the wild west. Data rights and ownership is critical. To belabour my earlier point, If you don’t own device ID , or something you can convert to device ID, you better have a partner, or vendor, who can. And they better be able to help you actually do something with it because dusty data is valueless data. Which brings me to my next point . . .
  4. Parking data isn’t enough; you still need to trade it. Everyone likes to park data (on MediaMath, Tradedesk, Krux, LiveRamp etc. -- all great companies). We all see the announcements about data partnerships that imply massive value waiting to be unleashed via revenue sharing or some such. But that does not equate to a) data actually being traded, or b) anyone making money. Net-net, some companies are making money by parking data but a lot of others seem to be waiting for something to happen.
  5. Long live DaaS deals. The market still thinks in terms of CPM and revenue sharing. I don’t do many of those deals anymore. Some people tell me I’m being a pain the ass, but when I do a licensing deal I know we’re getting 12 months of guaranteed revenue. I know when we’re getting it, and I know we have a partner that’s in this thing with us. CPM and revenue share are fine but they just don’t have the same kind of predictability.
  6. Dwell time is important.  CPI, ARPDAU, Retention . . . all important indicators, but I’m starting to believe that dwell time is the best stat to tell you about consumer intent based on real behaviors. Paired with location data, it is pure marketing and advertising gold. If you know I spent 2 minutes in your store trying on a pair of Nikes, and 20 minutes trying out the Adidas while simultaneously Instagramming a pic of the shoes to my wife, you know what what my consumer intent is, period. I think dwell time will be a very important KPI in the future of data trading.
  7. Marketers are getting smarter about data really, really fast. When I first started with Unacast, the conversation about how to use data was all about retargeting. Then it morphed into a conversation about attribution, then data modelling and (currently) verification. Moore’s Law is incapable of keeping up with how fast marketer’s understanding of data is evolving (a lot of this is powered by rapid iterations of programmatic and martech tools.)
  8. There’s more partnership opportunities than competition. Sometime in the last several months a light went on over the marketplace and, all of a sudden, everybody started to understand that cooperation (e.g. audience sharing via so-called ‘second-party’ data swaps) is where it’s at. And why not? Safe, secure data-sharing helps brands get better at creating personalized engagements for their own customers and can instantly scale target markets for brands with similar audiences. It makes sense, so it had to happen.
  9. Data is a two-sided market with lots of buyer profiles. To fast track a sale you need to engage with both commercial and product people. To drive usage you need to connect with agencies and brands. Doing this well is part of what made both BlueKai and now MOAT successful. Finding new ways to excel in this diverse market is something I think we’ll see more investment in moving-forward. 
  10. Stay true to your identity and don't take quick money. Staying the course in the data market is critical, otherwise, you risk confusing the market. At Unacast, our brand is clearly built on proximity and quality. Perhaps we could have secured more revenue to-date by vacillating from that identity, but establishing a clear presence in this space is essential. It’s always better to walk a straight and steady line than run around wildly looking for the quick buck.