One of the perks to running a digital transformation company is working with incredible talent in the digital space. The team at my company, Centric Digital, works in the trenches with our clients every day and they're on the bleeding edge of the latest trends in our field.
So, stemming from my recent article on benchmarking, I asked my team to share how today's trends in data can help drive business success. The insight they gave can help leaders throughout any organization consider new ways to use data to improve business, save money, and even increase revenue. Here's what they had to say.
Marrying digital and analog KPIs
"A business can have a lot of digital tools today and pay for a lot of tracking," Data Strategist Asher Feldman explains. "But you need to have a strategy so you can supplement that data with real-world information--you need to marry digital Key Performance Indicators (KPIs) to the analog ones to get the full picture."
"A digital strategy works to re-imagine an analog process and make it better for the consumer. When you replace those analog touch points, you still have to pay attention to the real-world version of what that means for your business. Unfortunately, many companies encounter attribution issues, where the company has trouble attributing the digital data into the real world. The smart companies are the ones doing the legwork on the analog touch points, factoring in things like brand image scores, awareness, satisfaction scores, net promoter scores, and general recognition and popularity."
Disney Parks is an excellent illustration of Asher's point in action. A few years ago, Disney World introduced MagicBands--a FitBit-type of wristband Disney guests can wear inside the parks. These bands track movement, can be used at the entrance gates, food stands, and kiosks, and allow users quick access to ride photos and can even open their hotel room door. Disney invested $1 billion into this digital tool that would provide them with valuable data--including transaction records, popular rides, average dollar spent, etc. But Disney managed to marry the data they collected from these bands and used it to improve operations in order to accommodate 3,000 more guests in the parks per day.
Enabling total automation of data collection and analysis
With the overwhelming--and growing--amount of big data available today, the need for total automation for collection and analysis is in demand. Many companies are turning to data management platforms or other software solutions to collect, house, sort, and analyze information in a way that's easy for end-users to see and understand. This automation process works to streamline the analysis of data and can also put an end to fragmented data silos across an organization.
"The idea of total automation is really popular right now," explains Taylor Wallick, Director of Digital Strategy at Centric Digital. "Digital tools today can allow you to deliver real-time information to various stakeholders throughout an organization without a single person having to dig through the data and build a presentation around it. Instead, an executive can pull up the numbers on a dashboard and see exactly what is going on in real time."
Aside from data visualization dashboards and data management platforms--like Adobe Audience Manager--another interesting illustration of total automation can be found in the rising popularity of Application Programming Interfaces (APIs). These systems of tools can be used to automate applications using data in a number of ways. It can be as simple as automating communication based on a user's actions--like an auto-response message sent to every new Twitter follower--or as complex as building an entire website populated on data points.
Weather.com and Zillow are examples of APIs that are built using a set of logic that displays certain information in real-time by accessing public data points. So, if it starts down-pouring in Alpine, Texas, the National Weather Service will collect and post that data, which will then feed to Weather.com. As that data moves through the site's logic, the site will render the image of a rain cloud next to that city's current forecast information.
Even smaller companies are using APIs on their sites. This is most commonly used with the small business's manufacturers or distributors that provide small businesses with datasets on inventory and pricing. That data will then feed to the business's websites in real time.
Making educated guesses
"Predictive analytics are increasingly gaining more traction," Michael Aiello, Digital Strategist at Centric Digital explains. "Companies are using data mining and complex math to dig into massive amounts of information and produce insights on something that might happen in the future."
While this isn't necessarily a new trend, it is becoming increasingly sophisticated. In 2012, Target's algorithm managed to predict a teenage girl was pregnant before her own parents knew. The girl's shopping patterns matched similar trends that Target had identified as behavior exhibited by pregnant women. The company then started sending the girl coupons for baby gear based on its
Today, however, it's now commonplace to see predictive analytics at work when we shop on Amazon or look for a movie on Netflix. Amazon offers customers additional products based on predicted shopping behaviors, and Netflix recently stated that nearly 80% of hours streamed are the result of their algorithm's recommendations.
Adding context to your metrics
An important trend all three experts agreed upon is ensuring your data has context. This helps you avoid the practice of using data for data's sake. Sure, it's great to know your app got three million downloads the day it was released, but there's more to it than that. Did users delete the app the next day? Are they using the app the way it was intended to be used? Does the app add to or take away from customer satisfaction? These are the types of contextual questions you should be asking around any metrics or KPIs.
The capacity to collect data and use it to drive success increases with a business's digital maturity level. The more digital touch points a company has, the richer the information they'll be able to analyze and use. Yet, digital maturity aside, the first step for any company is to ensure they have a data strategy in place first. Only then can they accurately assess whether or not the latest trends in data will make sense to their business or be used in a way that will benefit the customer.