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Interview: Big data and the importance of identity

Interview: Big data and the importance of identity

When it comes to big data, many companies are now adept at collecting it, but the harder part is knowing how to organise it and what to do with the data once you have it.

The idea of identity is a vital one, as marketers can transformed this data into an actual representation of their current and potential customers, therefore providing valuable and actionable insight.

To shed more light on the subject, we spoke to Richard Lack, the Director of Sales in Northern Europe at Gigya. The full interview can be found below.

  1. How would you define big data?

There’s not yet a textbook definition of Big Data that everyone universally agrees with. As a broad concept, Big Data includes large, complex data sets that struggle to fit within traditional, relational data management systems. These complex data sets are often used to uncover new correlations and solve challenging problems. 

As consumers, our digital lives are no longer played out on a single device. In this modern world of smartphones, tablets, wearables and other Internet-enabled objects, Big Data isn’t useful unless these connected devices are able to communicate with one another and learn from each other. Tying these objects and the data produced by these objects back to the user’s identity, and using that single identity as the connecting thread, is where Big Data garners its true value.

When leveraged properly, Big Data gives brands a huge competitive advantage. The key to benefiting from consumers using multiple devices across multiple touchpoints in today’s Big Data landscape is harnessing the power of identity.

  1. What mistakes are companies making when it comes to big data?

If we accept the fact that identity underpins the value of all consumer data collection, then clearly the biggest mistake companies make is their failure to be stringent about capturing accurate identity data. Too many brands simply accept an email address or a made-up username in place of a real user identity. This makes registration more difficult and neglects the opportunity to persuade potential customers to voluntarily part with certain data points, such as age or gender, which are essential for effective targeting.

As a marketer, if you expect a consumer to make up an identity in order to interact with your business, then you can expect said identity to be void of any useful data. Allow consumers to bring their existing, authentic digital identities with them. For example, allow them to leverage their verified profiles from identity providers such as Facebook, LinkedIn or VKontakte.

Even more frustrating is the tendency of enterprises to collect valuable, first-party data from their customers (which has been freely volunteered), and then fail to use the information to communicate with customers like they are individuals rather than names on a list.

For example, if I tell a brand that I am a female who wears a size 12, then I have an expectation that the brand will use that data to make my shopping experience better. The technology is there, but businesses are not capitalising on it effectively. That’s a great way to increase unsubscribe rates and lose customers.

  1. How can companies classify data to make it more effective?

The most important classification is first-party data versus third-party data.

For starters, businesses should understand that first-party data collected with the consent of identified users is far more valuable and accurate than third-party data, which is often bought or acquired from questionable sources such as data brokers who have no real vested interest in the upkeep of the information.

Third-party data is often inferred and subject to the vagaries of guesswork – people living in this postcode earn this much, etc. Third-party data also rarely carries a timestamp, and can be years out-of-date by the time it reaches a brand’s database.

Beyond this basic precaution, there are three key types of data that businesses should be collecting and using, and by using them together, brands can truly understand their customers.

These three types are demographic data, interest data and behavioural data. In general, a business requires a few valuable data points to target accurately. Brands should think carefully about which data points to ask for, and what to offer consumers in exchange for this information. Incentivising is key.

  1. How can companies find the right balance between bombarding customers with messages and collecting enough information?

First-party customer data is one of the most valuable assets a business can have. The key to collecting enough information is incentivising consumers to provide the data, and transparently communicating a value exchange for the information. For example, a brand can send special discounts on a customer’s birthday in exchange for that data point.

The benefit is clear: brands that leverage this rich data to provide personalised, relevant offers and experiences will be rewarded with significantly higher conversion rates than brands that do not. If a brand is sending relevant, tailored messages, consumers will not feel bombarded.

  1. Once companies have collected all this data, how can they keep it secure?

Security is clearly top-of-mind for all organisations. At a minimum, businesses should look to house their customer data in an identity management environment that meets ISO27001 certification and has a systematic policy of encrypting data at rest as well as in transit.

  1. What big data trends do you expect to see in the next 6 months?

The future of Big Data is becoming intertwined with the rise of the Internet of Things (IoT). As the number of digital devices that can connect with one another increases across the globe, brands are collecting more data from their consumers. The key to making this phenomenon successful will be focusing on identity.

By tying all of the data points generated from connected devices back to a user’s identity, businesses are able to create truly personalised and lifestyle-based experiences for individual consumers.

This reconciliation and attribution of data to a single consumer identity is what will enable a user’s toothbrush to successfully communicate with his or her smartphone, cloud-based calendar and dentist’s patient scheduling portal.

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