Social Media as a Massive Collection of 'Demand Moments'
What significant changes did Big Data segment witness in 2013? What did these changes mean to vendors and customers?
One of the broadest changes occurring relates to the type of data we're seeing being produced. Specifically, we are seeing consumer preference shifting from text-based interactions towards rich media. Social networks such as Instagram and Vine, where users share experience and opinion using photos and short videos, represent the new norm. Big data technologies will have to adapt as well. Most players have traditionally focused on text analytics as the key to mining data for insight and opportunity, but leaders in the field will need to be able to glean business intelligence from photos and videos as well. This will need to be automated through technology innovation.
What are some of the changes you had anticipated would happen in 2013 but did not happen
We had anticipated CIOs would be more involved in acquisition of social enterprise platforms. A task that remains mostly the responsibility of CMOs. We do see, however, a trend towards more involvement from IT departments
Can you paint us the picture of how the landscape for this industry segment will change in 2014? What are some of the broader trends you are closely watching?
One very significant change relates to the importance of geo-spatial intelligence. We see that over time more social networks have adopted the "check-in" mentality, whereby users can geo-tag content, and as result, brands can better understand what type of engagement with the consumer makes sense at any given moment. More often brands can understand if the consumer at home, or in retail environment, or at a live event. Technologies will need to convert geo-spaital intelligence into opportunity, whereby brands will be able to insert their voice at the right moment, and in the right context. This will also have implications beyond the individual consumer. Brands will need to interpret broader regional and global trends to optimize business processes such as supply chain management.
How would customer spend change in 2014 for Big Data segment? What makes you think customers will be buying more/ less?
Customer spend this far has been based on 2 primary categories that relate to usage of technology solutions — volume of data collected/processed, and number of licenses (users) granted access to a platform. At Tracx we see social media as a massive collection of "demand moments". When a customer expresses a need for a product or service, or a customer threatens to switch from one brand to another, these are examples of demand moments. In turn, we expect that buyers of big data technologies will agree to move into performance based models, where they might pay per lead, per conversion, or per fulfillment of any kind of demand moment. If a technology solution can identify and manage these moments, clients will be willing to pay for the ROI associated with them. We expect this transformation to increase the value brands recognize in big data technology, and thus the investments made by enterprises.
We also see customer spend increasing due to the proliferation of use cases for big data emerging across the enterprise. Where social media was once considered a channel for marketers and community managers, now we see adoption from customer support, sales, HR, R&D, and other departments who are beginning to understand the opportunity at hand. This means enterprises as a whole will be spending more on big data technology than ever.
What's in store for your company in 2014?
Tracx is very much focused on the union of big data in the cloud with the brick and mortar world. Insights and opportunities surfaced from consumer data will need to be fed to retail and other physical environments to make it actionable and timely. Tracx is looking to automate this process. One example would be identifying people who are actively shopping for a product, such as a car. Here is an opportunity where we could alert the local dealership and route this social lead to them in real-time, so the dealer can engage, and then convert. Tracx already has customers doing this.
Predictive analytics is also a big focal point. There is only so much intelligence that be gained by looking at the past, and only so much that can be done once an opportunity has passed by. Brands are looking to big data players to help them identify threats, opportunities, and trends before they emerge. When it comes to very sensitive sue cases such as crisis management, even a few hours of advance notice can make a huge difference.
We are also trying to usher in the socialization of legacy technologies, such as ERP, CRM, and Marketing Automation. We know that these types of systems are fundamentally unsuited for the real-time nature of social media, and the size of big data in general. Unlike most of the social technology players out there, we are not trying to create a social media silo and we do not want to ignore legacy platforms. In fact, we are looking to do the opposite. We want to infuse our social data into legacy infrastructure, and to enrich them with real-time intelligence. Tracx was designed to play well with others, and we're eager to find partners who are ready for this transformation. We have already developed seamless integrations with CRM, Web Analytics, and Live chat systems.
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