In his analysis of big data, Skift contributor Colin Nagy wrote, “Data should be in service to the human touch.” We couldn’t agree more. In fact, we believe data leaders and CIOs should keep in mind that for greatest business impact, it’s wise to consider data that’s been informed by both art and science.
Which leads us to the first data trend:
Data interpretation is the new intelligence.
2017 is the year of data. It’s everywhere. And having a lot of data can feel great. It can make possibilities seem endless and the future seem boundless—until you look at all the data and realize you don’t know what to do with it. That’s where the art of interpretation comes in.
In every industry, talented data scientists and researchers are helping companies truly innovate by giving them interpretations of data that are useable—and impactful. Stan Sthanunathan, Head of Consumer and Market Intelligence at Unilever, noted, “What matters now is not so much the quantity of data a firm can amass but its ability to connect the dots and extract value from the information.”
Consumers expect brands to deliver personalization through data.
It’s not just companies that need data interpreted intelligently. Consumers of brands want it too. Today, sophisticated consumers expect any brand they are interacting with to not only know who they are but also know what they want—even before they want it. Consumers realize that brands collect their data and in return, they expect the brands to use this data smartly.
Former Starwood CEO Frits van Paaschen, in a speech last September, said, “There’s an extraordinary amount of information available, but a real dearth of information that’s potentially relevant to any one individual.” That’s why the data scientist that can also help a brand deliver personalization through data is gold. Airbnb Global Head of Hospitality and Strategy and Joie de Vivre Hotels founder Chip Conley confirms this. He noted, “We need to get really smart around data science. It helps us personalize choices.”
Analytics must gratify. Now.
Good or bad, most executives want results that give them actionable data. And they don’t just want results now, they wanted them yesterday. Luckily, fast can still be rigorous. Today’s research technologies allow for fast, high-quality, action-generating data.
In our experience, finding gratifying analytics that also deliver real intelligence doesn’t have to be a slow or costly experience, it just has to be focused with the right rigor and insight. This means that the research being done or the data being analyzed is serving the overall business objective so that the insights gleaned are actionable. For example, just recently, we used in-depth, but incredibly quick research to inform decisions for Hilton’s 13th hotel brand, Tru by Hilton. Our research, combining rigor and speed, has contributed to making Tru by Hilton one of the fastest growing hospitality brands ever.
Rigorous research can also entail an orchestrated balance of qualitative and quantitative methods in order to truly hear the voice of the customer so that you can best position your brand, offer the right products and services at the right price, communicate effectively, and ultimately drive business growth.
Dark data is coming into the light.
The amount of seemingly useless information, just within companies, is astounding. There are paper documents. There are photos. There are videos. There are social media posts. And there is search engine history. This dark data, or operational data that is not being used, could be used. And it could be used in big data aggregation to drive company growth.
So search the vault. Dig through the storage closet. Bring out the search engine stats. Assets await that can give companies more comprehensive views of who they are and where they’re headed. For the first time, the technology needed to analyze dark data and find valuable business, customer, and operational information is here. By putting dark data into the light, historical performance trends can be found, product cycles may be discovered, and even things like employee retention rates can be shown.
For example, according to Dark analytics: Illuminating opportunities hidden within unstructured data, an article published by Deloitte University Press, an insurance company, which mapped its employees’ home addresses and parking pass assignments with their workplace satisfaction ratings and retention data, found that this combination of seemingly useless data revealed something extremely valuable: that commuting time was one of the biggest factors causing voluntary turnover.
A.I. solutions must be considered.
Artificial Intelligence. It’s here. And it will soon be part of our lives if it isn’t already. Both start-up brands and data analytics are identifying A.I. solutions as a way to simplify worlds that are becoming more and more complex for consumers. Pinpoint analytics, for example, can predict consumer needs as they arise.
Mark Zuckerberg, Facebook’s CEO, believes A.I.-powered virtual robots will alter how companies interact with customers. And this could happen in as little as five years. Will these robots have human qualities? Should they?
Only time will tell how A.I. and other forms of data will allow brands to connect with consumers in game-changing ways—ways that will alter the future of branding as well as daily life.
