Bottlenose earlier this month raised $3.6 million in Series A funding to help with its launch of Bottlenose Enterprise, the upcoming tool aimed at helping large companies discover and visualize trends from among a host of data sources, measuring and comparing them for those with the most “trendfluence.” Users will get a realtime dynamic view of change as it happens and a host of analytics for automating insights, the company says.

The Enterprise edition will be a big departure from the current Bottlenose Lite version for individual professionals. That difference starts with the amount of data it can handle. “The free, Lite version looks only at public API data like Twitter’s. The enterprise version uses the firehose,” says CEO Nova Spivack. Another big difference is that the enterprise version adds a lot more views and analytics, in comparison to the personal-use edition, where its Sonar technology provides the chief service of real-time detection of talk around topics personalized to users’ interests so they can visualize and track those topics over time.

Spivack calls what Enterprise does “enterprise-scale trend detection in the cloud,” leveraging a massive Hadoop infrastructure and technologies including Cassandra, MongoDB, and the Storm distributed realtime computation system to process data for deep dives. The cloud handles the computation, and results are shared at the edge, where certain kinds of analytics and visualizations occur locally in the browser for a realtime expience with no latency. With sources such as social streams, stock information, even a company’s proprietary data, and more, the Enterprise version helps brands discover important trends like keywords to bid on or viral content to share, who are their influencers and detractors, what sentiment and demographic movements are taking shape, and to create correlations across data points, too.

“As an individual using the Lite version, maybe you are monitoring messages one by one, but the companies we are dealing with for the Enterprise version are looking at tens or hundreds of millions of messages and tracking millions of trends,” Spivack says. That’s a lot of noise to filter out in the process of seeing what matters. Natural language and sentiment analytics weigh in with Bottlenose to discover what has meaning, and what meaning is, and to surface it in a contextually relevant way. “It can transform all contextual data that we have semantically analyzed and turn that into numeric time series data, and measure higher-order time dynamics to detect trends with impact. So it’s measuring the collective mind and emotion of the market.”

Among the features to expect, Spivack says, is a very powerful sentiment solution, which Bottlenose has undertaken in partnership with Lexalytics. “That will provide extremely tunable sentiment with about 95 percent accuracy,” he says. Correlations discovery can help, for example, with understanding the connection between social conversations about a brand and the company’s stock price or volume; “which conversations may have impact on trading volume, for instance, or which audience segments and conversations around what topics and where have an impact on sales,…or which conversations impact activity on your site or correlate with ad campaigns on TV.”

 

It’s all important to what Spivack says is the coming conversion of social intelligence, which the free version of Bottlenose was all about, and business intelligence. In the Enterprise version, the two meet. “Social and business intelligence will be the same thing; social intelligence is a key new piece of business intelligence,” he says – maybe even more important than more traditional BI signals. When social signals are tied appropriately into the context of other business goals – not just marketing but sales, HR, strategy or product innovation – then all aspects of the enterprise can benefit, he says.

Spivack wants to clear up the confusion he’s seen even with the Lite version, which often was interpreted as a social media dashboard rather than a discovery tool that goes beyond helping users find what they’re explicitly searching for, but rather hone in on the things “they don’t know to ask for but which turn out to be important.” Its topic detection of trends is pattern-based rather than dictionary-based, so there’s no pre-conceived notion around what to look for, but rather “scanning the horizon and seeing the unknown unknowns, that which you couldn’t have anticipated and can be very  valuable discoveries.” Bottlenose Enterprise, he says, should be considered more competitive with vendors like Radian6, Networked Insights, and Netbase, to name a few, as well as with other offerings boasting strong measurement and insight capabilities. “The companies we compete with tell the story. It’s Big Data analytics and discovery companies,” he says.

When you think of Bottlenose Enterprise, think of it this way: “We are creating an artificial analyst team that lives in the cloud and scales massively beyond what any human team can handle,” Spivack says. Even if data scientists and analysts weren’t in short supply, and companies could annually triple the number they employ, “you won’t keep up with the growth of information. No team of analysts can scale to keep up with the volume of information in social around a major brand. That has to be augmented and they need a solution to help with that,” he says. “We are filling that need.”

Around ten or so big companies are currently piloting an early release of the technology. That includes Pepsi, which is using it to track live and emerging trends around Pepsi brands, advertising and marketing initiatives, customer communities and industry, and FleishmanHillard, which is using it for live mission controls for real-time crisis management for global clients, and for monitoring major live events such as SXSW and the Oscars, industry conferences, and product launches. Digital agencies DigitasLBi and Razorfish also are in the mix. Spivack says the plan is to do a formal launch of Bottlenose Enterprise in the fall.