Suppliers of prospecting equipment used by the early California Gold Rush pioneers in the mid-19th Century enjoyed a surprising side hustle. Having unloaded their cargo of prospectors, shovels, pans and dynamite on the West Coast of America, they realized they could load up for the return journey back East with another natural resource that was (at the time) both plentiful and surprisingly lucrative.

This product? Guano (commonly known as bird droppings). Stopping off at various Pacific islands which for thousands of years had been the exclusive domain of millions of seabirds, they could scoop up guano which lay hundreds of feet deep, fill their empty holds, ship it back home, and sell it at a premium as a nitrate-rich fertilizer.

This sparked a ‘poo-rush’ in which hundreds of unoccupied Pacific islands were claimed and mined for this valuable avian by-product. But the activity scared off the seabirds, causing populations to decline and supplies to dry up. By the mid-20th Century, the party was over.

Here in the early 21st century, we are in the middle of a similar rush for a resource that is also created as a by-product. Personal data is the ‘digital exhaust’ we leave behind us as we speed through our busy modern lives. This resource will only ever get bigger, and it can be incredibly valuable to those with the ability to collect it, store it, analyze it and monetize it.

The guano farmers of the 19th Century didn’t share the proceeds of their fertilizer business with the seabirds who provided their raw material, and unfortunately, it is not recorded how their feathered friends felt about this. But where we see the data landscape unfolding in the coming years is for data businesses like ours to recognize that the data we use ultimately originates with each and every individual customer and that we should more equitably share the monetization revenues this data generates with the person who produced it.

Data as a resource

Loyalty programs are in a perfect position to collect the data that proliferates as a by-product of commerce. Nectar, for example, captures data from its members (better known as ‘collectors’) when they shop with coalition partners, swiping or scanning their Nectar barcode to earn points from offline transactions and linking their accounts to earn points from online transactions.

This is the value exchange we have agreed with our collectors. They choose to shop at our partners because we reward them for their spend. That they agree to identify themselves through their Nectar card as part of this transaction is the implicit agreement that we can track who they are and what they buy.

Data that we collect directly from our collectors when shopping at our partners is, of course, first-party data. When someone signs up for a loyalty program they grant it permission to capture and store their transaction data, analyze it to create models, profiles and segments, then use these insights to inform better business decisions and target relevant marketing messages and incentives back to the individual.

If the collector responds to a nudge to shop somewhere or buy a certain product, the loyalty program can observe if and when it happens, then calculate whether the cost of the incentive was worth the value of the transaction.

First-party data for personalization

It is vital that loyalty schemes handle first-party data in a way that builds trust with and creates relevance for, their customers – for instance with personalized discounts on frequently purchased items, or with incentivized challenges. But first-party data sits within a wider ecosystem of four classes of customer data, defined as follows:

  • Zero-party data is information a customer willingly volunteers directly to an organization, for example by providing personal preferences or completing a survey.
  • First-party data, as described above, is permissioned data that is collected directly by an organization when a registered customer interacts or transacts with it.
  • Second-party data is when first-party data is shared with another organization with customer permission and under specific rules of usage, for example working out the overlap between two customer bases in order to create and target a new joint offer.
  • Third-party data is aggregated from multiple public and non-public sources by a third party of whom the customer is unlikely to be aware, and who has not received permission from the customer for their data to be included. This data is usually sold to other businesses for digital targeting purposes. Previously very popular with many marketers, usage is now being constrained.

The future of data?

The future of data is fairness and transparency. Consumers should know they have a right to share in the revenues this data produces.

From a commercial perspective, this is not as counter-intuitive as it may sound. Offering a fair and transparent revenue share model to customers may actually help rebuild trust in how their data is being used and encourage them to grant us additional permissions to access new sources of their personal data (yet in a way that allows them to retain ultimate visibility and control of its usage).

There is some distance still to go and much to be done, but if there is one lesson we can learn from the guano farmers, it is that careless profiteering can inhibit the supply of even the most seemingly infinite resource. That is why the data business can’t afford to ignore the rights of those who create it, and why a fairer settlement for consumers seems both inevitable and desirable for all of us.

Also published in: The Drum

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