UNO April 2019

Data-driven branding: More than just data and algorithms

According to a 2018 ranking, 13 of the 100 companies with the highest brand value are technology companies that have made data and artificial intelligence fundamental components of their connections with customers. Other companies, operating in sectors such as retail and media, have also used these same tools as strategic assets from the start for their paths to growth. As a general, none of these sectors avoided the Big Data 2.0 revolution.

After almost 15 years since its inception, with many promises and expectations to fulfill, Big Data is finally transforming how we interact with customers and, at the same time, how we do business, build reputations and create, maintain and nourish our brands. In its infancy, the data revolution promised companies access to a greater volume of information regarding different varieties of data at a much higher velocity—the famous three Vs.

Over time, companies began to understand that the focus cannot be on the data itself, but rather on its capacity to generate value. In the business world, the virtuous circle of value is the master driving a company’s survival and dominance. The customer is the main value generator for companies, which must, in turn, generate value for consumers to ensure their loyalty. When this virtuous circle becomes a company’s mission and vision, brand reputation and positioning is guaranteed over time. This is where data takes a leading role, becoming a strategic enabler of this symbiotic relationship between customers and companies.

“The customer is the main value generator for companies, which must, in turn, generate value for consumers to ensure their loyalty”

On a basic level, data generates value through its ability to quickly give us a high-resolution photograph of our relationships with customers while simultaneously facilitating more granular and accurate monitoring of company and market health. Thanks to descriptive analysis, we can, among other things, understand what customers are doing at any important moment.

But data also allows us to imagine more ambitious ways of generating value. For example, one of marketing professionals’ collective dreams is to offer the right customer the right product for the right price at the right time. Alternatively, what company wouldn’t want to quickly identify the negatives caused by a poorly designed product, wasteful complaint process or, simply, any experience below customer expectations? This world of almost perfect customization and proactive customer interaction is now possible, thanks to the predictive and prescriptive capacity at the heart of the Big Data 2.0 revolution.

This new predictive technology—known as data revolution, machine learning or advanced analytics—seeks to take advantage of all the information we have about our customers and company activities so that, using sophisticated algorithms, we can respond to specific business questions and generate a high potential for increasing symbiotic value.

Let’s quickly look at some of its features to understand how it impacts brand creation, construction and maintenance. It’s enough to discuss the three necessary ingredients, starting with a change in company culture and the adoption of modern technologies, alongside the aforementioned three Vs of data.

First and foremost, it adapts scientific methodology to the businesses. Thus, through systematic use of trial and error, it seeks to learn from customer data and interactions to identify the best overlap between what we offer and what customers need. This way of operating, guided by data and evidence, requires an important cultural shift that is forcing companies to break down organizational silos to ensure work is agile and transversal. This process, although painful, generates important value in the medium-term and is a solid brand differentiator in the long-term.

“If we use the information generated by customer interactions, we can build predictive models of their satisfaction in real time”

Technology also plays a fundamental role. Data held in the cloud or company data centers promises to eliminate information storage and can process, in seconds, information with a 360° view of customers and their interactions with companies. Accompanied by data governance programs that guarantee their veracity and quality, development and automation processes can obtain the necessary scale to become truly transformative.

Finally, machine learning algorithms play a central role. For example, let’s take facial recognition or natural language processing algorithms. Today we can recognize emotions from facial images or intensity and tonality in a conversation. If we also use the information generated by customer interactions, we can build predictive models of their satisfaction in real time. The dream of a customer-focused company can come true, becoming a fundamental pillar for brand creation.

How, then, can you create a powerful brand based on data and evidence? You must start with the culture. In the new economy, the Big Data 2.0 economy, the virtuous circle of value must not only be consistent with the company’s culture, mission and vision, but should also be based on a data-driven culture.

Machines will not replace creative capacity in generating emotional connections. Here, humans have no rival, but it is inconceivable to think that, in the data economy, a brand can enhance its sustainability without the Big Data 2.0 revolution’s methods.

Daniel Vaughan
Director of Big Data at Telefónica Mexico
As director of Big Data at Telefónica Mexico, he is responsible for leading all Big Data and data science initiatives, heading the Advanced Analytics Center of Excellence and developing the company’s data strategy. He previously led advanced analytics efforts at Banorte in his role as senior data scientist and was a researcher at the Bank of Mexico. He is always seeking to improve decision-making capabilities using data and advanced analytical models. With a Ph.D. in Economics from New York University (NYU), he has taught at NYU (USA and Abu Dhabi), Universidad de los Andes (Colombia), CIDE and TEC de Monterrey (Mexico). In his spare time, he enjoys spending time with his dogs, Cuban percussion and watching Netflix. [Mexico]

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