The Changing Value of Data

Gordon Wyner
Marketing Insights
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Key Takeaways

​What? As data expands, its value changes.

So what? If data availability becomes the gateway to insights, then practitioners need to understand how this both expands and limits what they can accomplish.

Now what? There’s still ample room for asking strategic marketing questions that are not easily addressed with Big Data.

 

​As the applications of data expand, its value is changing, just as is the value of those who mine it and the bargaining power of those who hand it over

The future of marketing insights may be quite different than the past. Traditionally, the goals focused on understanding customer needs and priorities to design and develop products and services. Marketing effectiveness measurement methods were designed to evaluate performance and improve the return on investment. Marketers still must understand customers and wisely deploy their resources. But digital technology could dramatically alter what are considered insights and how they are developed from data within a changing landscape.  

The starting point is the massive increase in data on consumers that captures their behaviors, exposure to marketing stimuli and potential links to financial outcomes. The potential for this information to be captured passively, in high granularity, spatially and continuously suggests a very different source for insights. Data and insight have been, to a great extent, separate from actual marketing implementation. Traditionally, a distinct enterprise engaged in the development of research to provide insight and another one to apply results in the market. The trend is toward more data being closely tied to marketing implementation itself.

Second is the increase in apps, particularly the kind of software tools that enable products and services to be packaged, targeted, purchased and used. The increase in data is associated with an increase in this intermediate layer of apps that links the consumer to the product. Today’s smartphone is central to the process, across industries and markets that draw on newly available data and use it to deliver service and value to consumers. As more sectors of commerce are influenced and controlled by apps, it suggests that marketing insights must increasingly address the role of apps. 

If data availability becomes the gateway to insights, then practitioners need to understand how this both expands and limits what they can accomplish.

Reversing the information flow

The typical sequence of activity used to be: set research objective, design and conduct research for insight and implement in market. Increasingly the sequence is reversed: The starting point is having data that is already part of an operational business process, followed by an analysis plan to derive insights from it. In many instances the new data is “collected” on an ongoing basis, driven by considerations other than research.

Consider, for example, the auto transportation market. Software and engine sensors can track driving behavior within a car. How can this information be used, and by whom? Ride-sharing companies like Uber are considering this type of information to measure and evaluate the driving behavior of their drivers, including measuring speeding, hard braking actions, tight turns or texting while driving. This information could help manage the driver’s performance. Insurance companies might want to have this information to assess risk for policy underwriting. Manufacturers would, of course, be interested in information to inform their development efforts. Software businesses directly benefit. Police and state motor vehicle agencies have yet another interest. One of the biggest challenges may be to determine who owns the information and how it can be used for public and private business purposes.

Will this type of data impact use of traditional market research techniques in these various sectors? This scenario suggests that traditional product market boundaries will be breached in the future. The owner of the information may be in a strong position to define the future market opportunities, fostering competition among providers of software, telecommunications, cars, insurance and ride-sharing wherein each has an interest in making commercial use of the information. The nature of the marketing issues and research topics (e.g. finding the next big application) would be quite different than the current ones, which focus within traditional boundaries (e.g. finding the next big product).

Future market projections suggest that the automotive market will grow substantially due to these developments, e.g., trends in shared usage of vehicles, communication connectivity of cars, and more self-driving capabilities. The data-driven elements of the market will grow faster than the vehicle sales themselves.

Is this evolutionary scenario in the transportation market just an isolated case? The hospitality and housing markets have some of the same characteristics. The success of Airbnb involves sharing of existing assets and also cuts across traditional industry boundaries. It seems to tap into a need and willingness of consumers to think differently about how they leverage their own property. Its success is heavily based on information technology, and it generates a lot of information in the process that has potential commercial value, benefit to the consumer and risk. The capital market puts considerable value on this venture—approximately the same amount as some major established hotel chains.

Customer-focused insights professionals try to identify the types of apps that consumers will want or benefit from. The auto example points out that the number of industry players that have an interest is potentially large. The number of ways the information could be used is huge.

What’s more, the traditional survey approach to finding out what consumers want would be challenged by the fact that apps are often totally new products. Would concept testing have predicted five years ago that ride-share services or shared housing would emerge quickly and become financially successful by leveraging information technology?  


Of course there are traditional research tools for testing new-to-the-world concepts. But the new types of behavioral data available call for new ways to discover consumer interests. What types of data would have been useful to anticipate the market?

Starting with data first may become a more prominent way to gauge market changes and evolving customer priorities. Through data ubiquity marketers will be better able to detect small changes in trends that can be applied quickly to new product and app development. Since the data is not designed or structured to answer research questions per se, it will take more effort to synthesize. This insight development process may look quite different than the current research paradigm but may prove quite effective. Pilot testing an actual product or app on a small scale may become more prevalent, depending upon the financial and logistical challenges.

The asset-management sector of the financial-services industry provides another illustration of industry evolution that might be relevant to marketing. Along with data proliferation, automation continues to absorb more functions that have historically been performed by humans, e.g. investment evaluation and recommendations for portfolio management. Consumers are given a tradeoff between personal contact, appetite for financial risk, customized personal recommendations and fees that goes well beyond prior innovations in low-cost trading and index funds for low-cost investing. 

Now robots can scan massive amounts of existing research data, reports and conclusions and make sophisticated analyses and recommendations, not just manage passive investment portfolios at low cost. This time it’s the highly trained financial analysts whose jobs are at risk of being automated out of existence. This change has the potential to significantly alter the landscape and reshape the way consumers interact with the industry.

If something like this scenario plays out in the marketing insights industry, it may shift the balance towards Big Data-driven insights from traditional research methods. There’s still ample room for asking strategic marketing questions that are not easily addressed with Big Data. What kind of information would be desirable to have to understand the market, to complement the passive information that is available? Are there insight gaps that can be filled by thinking beyond what is measurable in the market today? And what could be?

 

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Author Bio:

 
Gordon Wyner
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