Like millions of Americans I was glued to my television on Tuesday evening (and into the wee hours of Wednesday) watching the Presidential election unfold in real-time. Working for a company that develops an analytics platform, I couldn’t help but think about how directors of digital products on news editorial teams must have viewed the election as a great opportunity to test new features and grow their user base.
As the election came to its conclusion, it was a final opportunity for media outlets to win over casual news consumers to not only read more news, but read more from their particular outlet and keep readers on their sites longer. They chose to do this with analytics.
Media empires have been cut down for many reasons, but there was one they could readily combat on election night: Commoditization. Just this month, The New York Times reported a 97% reduction in profit in the most recent quarter.
There are hundreds of polls, dozens of projection sites and lots of opinion journalism. In order to win readers over, news organizations needed to show that their coverage went beyond the simple recitation of data and became more relevant, contextual and useful. Election night was a great time to demonstrate this through the use of analytics.
There were three key elements that made these analytics successful:
1. They were embedded. Voters didn’t need to hunt for insight. The data and visualizations were white-labeled and located alongside the news content. They were easy to use, understand and find. Switching from one state to another was quick, and a consistent user interface made finding and consuming content simple.
2. They were updated in real-time. Another critical element was to keep voters engaged and on the page. This drove critical KPIs – such as time on site, reducing bounce rates and increasing page views – which in turn drives advertising dollars.
3. They offered a preview of advanced capabilities. The New York Times offered an interface that relied on basic predictive models to predict the outcome of each race and natural language generation (NLG) to put textual context around the data being displayed.
The efforts of the news outlets must be applauded, but their attempts also risk putting forth an incorrect narrative that analytics are just about dashboards and reports. In fact, what news outlets did was actually quite basic because they don’t have the same challenges Product Managers at software companies or enterprises face.
1. They didn’t need to worry about security. The press wanted as many people as possible to access their data – so there was no worry about data protection. Security is an area of great concern for product managers because it prevents unauthorized access to data – but integrating with existing security is a big challenge.
2. Data protection at the row-cell level. Because news outlets wanted to provide access to everyone there was no concern over row/cell level data protection. In a company, a CEO will have different data access than a Director or a Manager and implementing this type of security is not easy.
3. Kicking off a Workflow. For businesses – having the ability to kick off an action from data is useful. For example, if a campaign subscribed to a data set, they could segment voters based on which states they were losing in, select a demographic profile of a group in which they were under-performing, and with the click of a button create an e-mail campaign to that audience to remember to vote.
It’s clear that customers want analytics and that’s why analytics are popping up throughout media sites. Whether you work for an editorial team trying to draw readership, or you’re a product manager trying to drive user adoption of your app, it’s important to think beyond dashboards and visualizations. All application owners must consider the business implications of analytics and how they can rapidly add, iterate and improve on these capabilities to give users the information they need, when they need it.
On election night there was a clear mandate from the world: PMs need to make sure their apps have analytics, or risk losing the user.