5 Tools for Brands Looking to Harness Predictive Social Intelligence

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Yesterday’s trends are old news, especially in the fast-paced world of social media marketing. Without a crystal ball to look into the future, marketers often have trouble predicting beforehand which messages will resonate with consumers in their target demographics. Instead of relying on costly surveys and qualitative research studies, large brands, marketers, and agencies are now relying on predictive social intelligence solutions.

Predictive social intelligence platforms use big data to organize, pattern, and predict which online conversations will be happening tomorrow. By contextualizing future online chatter, brands can better target specific audiences on social channels like Facebook, Twitter, and Instagram. The market for these solutions is expanding. According to a report by EverString, a maker of predictive marketing software, 91% of marketers who say they’re defining the future of their companies are either fully committed to predictive marketing or are newly implementing the technology.

Here are five examples of platforms that brands and marketers can use for predictive social intelligence.

1. Blab: Predicting what people will be talking about tomorrow.
Blab provides brands, marketers and public relations teams with data-driven insights to generate social campaigns that align with predicted outcomes. The company’s platform ingests more than 100 million posts a day from 50,000 sources, including news sites, blogs and social channels, and give clients the ability to predict what tomorrow’s online conversations will be. The goal here is for brands to influence cultural conversation and generate consumer-centric communication. Marketers can stay ahead of the story by posting about the topics that Blab predicts consumers will be most likely to care about up to 72 hours in advance.

2. Unmetric: Forecasting the engagement-level of posts
Unmetric is a social media analytics platform that helps businesses improve their strategies on Facebook, Twitter, YouTube, and Instagram. The company uses a predictive algorithm to allow brand marketers to optimize social content before it’s published. Marketers can input details about the content they plan to post on social channels, focusing on the structure, tone, intent, and context. Unmetric’s machine learning algorithm then generates an estimate of the engagement that each post will receive. Actionable recommendations are also available help brands come up with ways to boost the engagement around the content they were planning to publish.

3. Spredfast: Generating insights for brands on social channels
The social software firm Spredfast uses predictive intelligence to enable companies to improve their social strategies with relevant data and actionable insights. The company’s Intelligence solution, which launched in April 2015, predicts the virility of trends and generates insights on how and when brands should engage on platforms like Facebook, Twitter, and Tumblr. Business clients are able to see when certain subjects have started trending downwards and when they should move on from topics with waning interest. Spredfast helps companies plan organic campaigns and optimize paid social campaigns.

4. ExactTarget: Improving the customer experience by using available data
Using available customer data, ExactTarget offers a way for businesses to predict the best message, channel, and timing for individual customer experiences. ExactTarget Marketing Cloud, from Salesforce, gives businesses a way to make real-time decisions to determine the best piece of content for individual customers, whether that’s a product, offer, or an article. The platform delivers content for email, mobile, social, and web programs. ExactTarget’s algorithm takes into account information from social profiles, purchasing histories, click behaviors, and both explicit and implicit customer feedback.

5. Tracx: Predictive scheduling for engaging social audiences
Tracx is a unified social intelligence software platform that brings social channels to the forefront and uses the data being generated by these sources to power its clients’ marketing, product management, sales, and PR efforts. The company’s recommendation engine makes predictions about the best days and times to schedule social media posts based on the type of content a brand is posting (for example, a photo on Facebook vs. a link on Twitter), along with the ages, locations, and genders of consumers in the brand’s target demographics.

Know of other platforms for predictive social intelligence? Leave a description in the comments.

Stephanie Miles is a senior editor at Street Fight.

Stephanie Miles is a journalist who covers personal finance, technology, and real estate. As Street Fight’s senior editor, she is particularly interested in how local merchants and national brands are utilizing hyperlocal technology to reach consumers. She has written for FHM, the Daily News, Working World, Gawker, Cityfile, and Recessionwire.