Editor’s note: Levi King is the CEO and co-founder of Creditera and was previously president and co-founder of Lendio.
First we went online to learn. Then we naturally started buying stuff. Smart retailers learned to target us based on our behavior. We searched and they reacted through pay-per-click and display. Then folks like Amazon used purchase history data to get smart about predicting what else we’d buy (based primarily on other’s purchase data, not our own).
Amazon associated their suggestions with “other people also bought.” That’s less creepy than, “We know everything about you, and dammit, we know what you’re buying next.”
Amazon and eBay had to become unicorns before they had enough customer data to pull off predictive targeting. Now, companies like Facebook, LinkedIn, Credit Karma and Square are getting in the data game, too, using a core offer, where meaningful, kick-ass data is inherent to create sticky user bases.
But do customers trust them to use that data to the customers’ benefit? Creepy factor eliminated? It depends. Customers expect Credit Karma to serve up better offers because that was the founding expectation of the relationship. But with Facebook, that was not and is not the case. Facebook has a great model for built-in data, but will always struggle with customer trust.
The key differentiation of these data-first models is transparency and founding customer expectation. Consider these examples:
- Amazon is commerce first, then data, then more commerce.
- Facebook is social first, non-transparent data second, and commerce without permission third.
- Credit Karma is data first, commerce second (transparent and with permission), all predictive and reactive based on credit and financial data. Credit Karma represents the new data unicorn, where data isn’t a consequence of the business – data IS the business. They have taken transactional behavior (consumer financing events), and turned it into a recurring transactional model.
- Square is dipping its toe into the water of post-core-data-service-offer with Square Cash. The business owner already trusts them because the founding relationship was on transparency, simplicity, and saving the business money. Leveling the playing field between tiny retailers, micro businesses and the big retailers. That trusted relationship lends itself well to new offers. Data is the business – data first, commerce second, built around a recurring data core service – just like Credit Karma.
The incumbents have to be extremely careful not to be creepy. For example, companies like Intuit and First Data have realized they are sitting on a trove of valuable data, inherent to their core business, but how do they use that data to create offers without making you feel like they’re invading your privacy?
I’ve used QuickBooks in multiple businesses since 2000 and I sure as hell haven’t ever considered myself to have a “relationship” with Intuit. It would be bothersome if I found out they were using my data for anything because I imagine them to be a software provider, with the data being solely mine, not theirs. The same is true with my merchant processor. I imagine them to be a tiny bit friendlier than a credit bureau, which feels like a natural adversary, not advocate, and certainly not a company with my best interests in mind.
Ultimately, I see five unicorn categories involving heavy data:
- Incumbent retailers like Amazon, Apple, and Intuit, which have enough commerce to have data second and leverage the hell out of it for new opportunities bolted on by their own creations or third-party creations.
- Data science companies like Palantir, Radius and countless startups trying to model “big data” to the benefit of big corporations and the government.
- Data-first services like Credit Karma and Square, where the founding relationship is of trust and transparency.
- Something-else-first services like Facebook and LinkedIn, where valuable data is inherent, but not the founding relationship or expectation with the customer.
- Trusted data repositories – the future permission-based, transparent repositories of data. These are the super unicorns of the future — companies with a founding relationship with their customers built on the expectation that they can be trusted to make predictive and reactive recommendations.
Many data science companies (No. 2) will become unicorns, but they’ll always be creepy as hell to individuals and small businesses. Who wants some faceless company “modeling” them and selling it to the highest bidder? That didn’t bother us with reactive targeting like ads showing up after Google searches because it seemed helpful and not creepy (albeit annoying sometimes). Plus we could see it. Most new data science companies operate outside the view of the subject.
What about modernized credit repositories? Intuit’s Mint.com and Credit Karma could be the first examples if they make a successful transition from No. 3 to No. 5. I believe many of the data-first companies will become permission-based repositories of data.
Credit Karma took a big step toward becoming a repository versus just a data-first service company when it added financial account data. Now a consumer could trust them with their credit data and personal checking account data. That’s a lot of trust being extended to Credit Karma, and earning that trust wasn’t easy.
The future of commerce marketing is permission-based and transparent. They will become the master brokers of B2C and B2B commerce. And these new super unicorns will have one thing in common – they will emerge from fintech.
Just as companies like Amazon have been successful in diverting people from going to Google to search, data repository businesses will eventually divert people from going to Amazon or Google. They are the furthest up the activity stream, where the earliest intention or reaction data is born, and it’s not creepy if it’s an expectation of the relationship (and transparent).
In 10 years consumers and small businesses will place and control all their data in a repository with the expectation that the repository will make recommendations in the best interest of the customer, with full transparency, and the predictive/reactive nature of the data will yield the most accurate results, hence the best customer experience. The repository will hold credit + banking + transactional + social data (at least).
The incumbent unicorns will continue to bolt on small to medium-sized opportunities built on the natural data generated by their core businesses (e.g. Amazon Financing, QuickBooks Financing). Their limitation will be the lack of global data view of the customer, as well as customer trust. PayPal financing risk underwriting is based on inherent PayPal data, but there isn’t a good value proposition to get the user to connect the rest of their data (creepy factor), so the narrow data view leads to a narrow, limited product offering.
Lots of medium-sized opportunities will come through successful partnerships with the data-first service providers – like financing companies partnering with Credit Karma. Who would you rather be? Credit Karma with a recurring relationship of trust built on data and transparency, or the transactional service provider begging to get bolted onto Credit Karma’s 33 million-plus customer base? Who calls the shots in that scenario?
In a future post, I’ll address what permission-based data models do to ancillary product/services customer acquisition costs, removal of acquisition friction, and no more relationship underwriting “turn downs.” The efficiency savings will be to the benefit of the user and kill middlemen.