In the coming years, the deluge of data from internet connected sensors and other devices will be significant. The revenues generated from integrating, storing, analyzing, and presenting Internet of Things (IoT) data will reach $5.7 billion in 2015, according the the latest global market study by ABI Research.
A recent Cambridge/Stanford study showed that Facebook data can generate a more accurate view of a person's personality than their friends, family - even their partners. This is another wake-up call to the power of social media data, something all marketers need to be taking seriously.
Today’s volume and variety of consumer data has presented businesses with a unique paradox: understanding customers and providing them with increasingly relevant experiences is both more possible and more difficult than ever before.
Just one week in and 2015 is proving to be a volatile year for news and social media-attention grabbing headlines. Freedoms of both press and speech have been threatened around the world, illustrated through a deadly terrorist attack in Paris and a knee-jerk (and immature) reaction by a US congressman to a press mention.
What's the best way to measure the effectiveness of your content? We'll always have the old standby metrics – social shares, pageviews and the like. But do these metrics help you understand how well your content resonates with audiences, converts lookers to buyers, and works toward the achievement of your business goals? For that, we need content analytics.
Social media analytics is your direct connection to the voice of the customer and their needs. It is a massive opportunity to make the customer the focus of your business and use the data to improve your products, your customer service, your marketing, and every aspect of your business. But, most importantly, it is a great way for you to form long-term relationships with just your customers, but your partners, stakeholders, and beyond.
In the past, brands have relied on data that lumps them into broad groups or data that allowed them to predict what a user will do based on their past actions. It’s time, however, to refine that data, putting highly relevant ads in front of buyers as they are making their buying decision, not after the decision is made.