7 ways to gain value from customer data

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By: Wise Marketer Staff |

Posted on October 1, 2009

7 ways to gain value from customer data

Marketers generally fall into two groups when it comes to customer data: either they feel it's too complex to deal with, or they use it to drive value and relevance in their communications with customers, according to Giles Desforges, client director for Beyond Analysis.

But there is a third group: those who are willing to explore ways in which they can drive not only better customer relationships but also additional revenue by commercialising their data.

Customer data is not simply an internal marketing or process management tool, Desforges argues. It can also be of great value to others. If it is handled in the right way, one company's data can be a profit-making, customer-acquiring, relationship-building tool for other partner companies.

By "commercialisation", Desforges does not mean selling customer data indiscriminately to anyone that will buy it. Instead the idea is to drive value - for the company, the partner, and the consumer alike - from existing data over and above the use for which it was originally collected.

For example, commercial uses for customer data could include anything from developing reporting solutions through to new media propositions. But, according to Desforges, all of these uses must be built on an understanding of the customer. These functions can then be made available (for a fee) to the company's extended business networks, suppliers and partners, all of which should be able to benefit from a better understanding of customer behaviours.

There are many opportunities to generate significant revenues from customer data. For example, marketers often talk in hushed tones of the grocery retailer approach to data commercialisation that was pioneered by Tesco and Dunnhumby. By developing a reporting solution that enabled its suppliers to understand its customer base more clearly and accurately, Tesco was able not only to change the nature of its negotiations with suppliers, but also to build a significant revenue stream. The suppliers have a unique view of the behaviours of the people buying their products and, through targeted media, are able to communicate with the most relevant consumers. But most importantly the customers also win. Not only do they get the products they want at the right price, but they also receive information and offers on products that are most likely to be relevant to them. The rewards of Tesco's data commercialisation have been significant, brining reported external revenues equating to a 2% improvement in profits.

There are, according to Beyond Analysis, seven key steps involved in the successful commercialisation of customer data:

  1. Understand the data Before you consider all the revenue opportunities from your data, you must clearly know what data assets you have, where they are, and be able to offer a clear picture of the ownership and permissions associated with that data. Data commercialisation must be about creating incremental value, and must consider how it fits into the company's overall customer, data and insight strategy.  
  2. Develop a value proposition Although it is clearly a key aim, data commercialisation should not be driven purely from a revenue perspective. You also have to consider the benefits that it will drive for consumers and partners. You should consider how it can deliver value to your consumers. For example, if you are developing a targeted advertising system, the value is only there if people don't opt out. Consequently, the more relevant you can be in your targeted communications, the more benefit there will be to you, your partners, and your customers.  
  3. Take legal and regulatory advice Customer data is precious and it has to be protected. Before you get too deeply involved in this process, it is vital that you take the right legal and regulatory advice. Consider that your data may not be governed only by data protection legislation but also by regulations relevant to your market sector (such as those in place for sensitive areas such as financial services and telecommunications). Also be aware of the possible impact of competition regulations and of legislation at a regional or international level.  
  4. Plan the roll-out carefully Plan and understand how any data sharing proposition will tie into day-to-day operations, and consider whether this is something that you can do as an outsourced or internally-managed service (or a blend of both). Consider how this planning will impact the business as a whole, and what impact it will practically have on individual departments (e.g. marketing, customer services, operations, or IT).  
  5. Prove the concept first A detailed business case is a general requirement for most major business decisions. But these are often built on assumptions, and it is only when concepts are tested in the real world that businesses can really quantify the true costs and benefits of data commercialisation. By building up step-by-step from a small test model, you will have more opportunities to optimise the service and maximise your revenue opportunities.  
  6. Don't forget the customer Data commercialisation is built on your understanding of the customer, so you must ensure that you do not overlook or forget them. As you move from proposition to concept, and finally to launch, you will need to be constantly considering the customer. Most importantly, when you launch a commercialisation product or service, you must ensure that you can clearly communicate what you are doing and why, and what benefits customers will gain from the product.  
  7. Don't stall. Go to market! Some organisations tend to deprioritise any challenging new concepts or propositions because they seem too complex at the time. But, when done correctly and in a planned manner, data commercialisation can benefit both the business and the consumer.

"The marketplace for data products continues to grow," concluded Desforges. "Recent analysis shows that, outside of credit-based products, the market in the UK alone is worth in excess of 1 billion per annum."

More Info: 

http://www.beyondanalysis.net