I Like Big Data And I Cannot Lie

November 22, 2013 5:00 am0 comments

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5 Things Marketers Shouldn’t Deny About Analytics

Marketers are increasingly informed about what big data is, why it’s here, what it means and how it’s used. But for data providers, there are still key points to share—there are depths to the issue of data that everyday individuals may find mysterious, or not know anything about. Data is a tool with many sides and understanding big data’s opportunities, problems, and key priorities—as well as knowing what it means to consumers and the world of business—can make it clearer, removing concerns and answering multiple questions. There are more things to know about big data than defining and monetizing its volume, velocity, variability!

1. Big data is more of an opportunity than a threat…

…it’s a chance to better understand and engage with consumers. It’s true that data is often viewed as a threat, as something scary and invisible. It’s easy to understand that perspective. But in reality, if data is harnessed transparently, responsibly, and correctly, consumers can be well informed of how their data is used to advance lives. Honest transparency and enhanced understanding of data’s advantages builds trust on both sides. Increased trust then creates increased opportunities—big data analytics sees the most innovative usage opportunities when data is used to learn something new, and perhaps unexpected, from a consumer audience.

2. Big data is more of an evolution of data than something fundamentally new.

Big data is not all that new. Organisations have been using consumer data to target products and services, facilitate countless services and improve lives for decades. Previously, however, available data sources used to create unique customer profiles were relatively few and far between. But as the world becomes increasingly digitised, data availability (and value—not all data is useful!) has skyrocketed, growing in amount (volume), speed of generation and shelf-life (velocity), and type (variety), from social networking data to locational data or purchasing preferences. The data process will continue to evolve as it already has and in a few years will have advanced again, hugely. This means that the signal to noise ratio (where signal is useful data and noise is everything else) will continue to be something that must be carefully managed and monitored to ensure monetizsable data is easier to locate. But in order to find that signal and monetize it you must maintain a clear strategy!

3. Big data should firstly be a business strategy and secondly be about hardware and software.

It’s not so much what you’ve got, it’s knowing how to use it. Technology is not the be-all-and-end-all of data, though it does play a crucial part. Defining data strategies and key goals should be the first priority for data projects. Without a clear brief and core, projects cannot hope to reap meaningful analytic results, regardless of the data collected, or how well it’s curated. Before technologies are invested in or data collated, exact aims and specific purposes (such as optimizing relevancy, better understanding unique customers to enhance loyalty and revenue) must be decided and continually referenced throughout any data marketing activity for success to be meaningful and sustainable.

4.  Big data is also about process, structure and talent—it’s a whole business issue.

As with any business, the quality of the staff reflects the quality of the product. With big data this is no different, and human resources are seen as the drivers of data, transforming information into valuable assets. But because big data analytics  is such a niche industry, employable candidates can be scarce. Finding quality data scientists and engineers is a common industry concern and issue. Investing in experienced staff that posses good transferable skills often requires efficient headhunting, retraining and careful individual cultivation. Even once an organisation has the staff needed to monetize data, it’s important that each individual understands the structure and key objectives of the data strategy in place. Without this understanding, the whole process will not work!

5. Big data needs to be seen as an opportunity…

…but handled with great care in terms of privacy, compliance and security. Through transparency and clarity of use and purpose, public perspectives on big data become increasingly positive, and data’s potential for opportunity understood. Maintenance of that positivity however requires stringent responsible use. Everyday consumers should know and be informed that data providers are bound by data regulation and responsibility—privacy, protection, security and appropriate use are long-term priorities. Data providers must always, by law, comply with privacy legislation, know who has what rights to what information, and should notify consumers of how they will use and protect data and privacy.   While it’s true abundant data better informs marketers and adds certainty, any uses of data must always be legitimate, relevant, and securely encrypted. Such trusted use fosters continued data success—so know that consumer data will always be subject to a fair usage approach, and never be shared without good reason! Deliver value, earn trust, use the data you’re entrusted with and deliver yet more value.

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