New ways for turning data into dollars now

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Big Data is transforming the way companies do business.  But many firms are finding that it requires significant investments of time and money before seeing the value.  We believe that by providing businesses with controlled access to their data ecosystems, companies can monetize their data to help fund the longer-term Big Data journey.

This approach differs from traditional data selling – where revenues are minimal and privacy concerns significant – in three ways. First, the customer opts in to have their data shared in return for receiving something of value in return, such as personalized offers. Second, the firm that generates the data shares access in a controlled, traceable fashion. And finally, companies enhance the data provided to partners through analytics, segmentation, targeting, and other services.

For instance, the supermarket group Tesco uses a data ecosystem to monetize data from its loyalty program, the Tesco ClubCard, through its customer science subsidiary, dunnhumby. In return for opting in to ClubCard, customers receive personalized offers. Then, for a subscription fee, dunnhumby provides consumer packaged goods (CPG) suppliers with an analytics platform which they can use to query anonymized retail transaction data, understand category dynamics and develop targeting strategies.  The analytics platform also controls suppliers’ access to the data (preventing direct customer contact, for instance). This model has helped dunnhumby generate annual aggregate gross billings of $500 million globally.

There are other examples, too. Merchant-funded offers provide a growing way for credit card players to monetize customer transaction data. Payments networks have begun to provide analytical services to stores and banks using their own data. And Intuit INTU +1.38%’s serves financial data back to the customer in a useful, graphical format, an offering it monetizes through advertising.

Is a data ecosystem right for you?

Three questions can help you decide:

1. “What is my data worth?” To know, consider the following:

  • Size of the ecosystem: Businesses with large, high margin suppliers or partners can generate more value from their data. For example, grocers have relatively data-starved multi-billion dollar CPG suppliers with the size and scale to pay for insights, while vertically-integrated retailers do not.
  • Breadth of data: Companies with national or global scale typically have more valuable data because it is easier to establish a market view and easier to create meaningful sales lift through targeted offers. That said, data on niche segments (e.g., such as high income retirees) can also be valuable.
  • Richness of data: The more companies know about their customers the better their data.Google GOOG +0.33% Ads is so profitable, for instance, because search data reveals powerful insights about customer intent-to-purchase and other factors. By contrast, low touch or low frequency sectors (say buying a car) tend to have less valuable data.
  • Customer engagement and permission: The more engaged the customer is with your brand, the more valuable the data, since engagement drives receptivity and response rates.

2. “To whom is my data valuable?” This can be other players in the value chain who are disintermediated from the end customer, firms with similar target consumers, or even the customer him/herself as in the example, A hotel chain, for instance, could monetize customer data to restaurants, retailers and tourist attractions.

3. “How should I monetize my data?”  In addition to targeted offers, many firms have created (or partnered to create) insights platforms, which provide an analytical engine that companies can use to query data, create customer segmentations, or understand the relative price elasticity of one particular product over another. Data can also be monetized by providing access to the customer, through your mobile app for example.

What to keep in mind

In our experience, the companies that are most successful at monetizing their data with this approach focus on three things. First, they recognize that they are trading on the trust of their customers. They define at the highest levels what the organization is willing and not willing to do with customer data and ensure that the model is transparent and adds value. If you had to stand in front of all your customers and tell them exactly what you are doing with their data, would you be comfortable doing so? Beyond privacy concerns, being more transparent can increase customer engagement – which in turn will drive more value from your ecosystem.

Second, the best companies establish the right data governance upfront. They determine how the organization will manage conflict of interest with partners in a clear and specific manner. A retailer, for instance, may seek to drive private penetration of their brand within a category while the supplier to whom they are selling the data does not. A good governance structure is able to help establish responsibility and determine who has the authority for making decisions. We find that the best-performing governance structures on doing what is right for the customer first, as non-customer-centric behavior is generally not sustainable in the longer-term.

Finally, the best companies realize they often don’t have the core competency to develop this kind of data ecosystem infrastructure and thus they bring in specialist firms that provide analytical engines and the tools. The partnership route can be helpful especially for retailers, banks, and airlines. If you choose to go this route, it is important to have a clear understanding of the economic drivers of the relationship and articulate unambiguously the ‘data rights’ that you are granting to your partner.

Big Data will ultimately transform many industries and firms.  Done properly, data ecosystems can fund the transformation, create value for your customers, and build tighter relationships with other firms and partners.

This article originally appeared on Forbes