NEW YORK, July 30, 2020 /PRNewswire/ -- IBM (NYSE: IBM) today announced the launch of Watson Advertising Social Targeting with Influential, a new solution that harnesses artificial intelligence (AI) to help brands identify influencers that best align with their brand values. The new solution within the Watson Advertising suite of targeting products marks an expanded collaboration with Influential, a leader in advanced social media technology. As brands shift advertising tactics in an increasingly fluid landscape, the social targeting tool can help brands communicate with an audience.

Harnessing the power of Watson to help clients make data driven decisions that foster connections with consumers, Social Targeting with Influential:

• Leverages IBM Watson Natural Language Understanding on the IBM public cloud to process and analyze social media data to help expedite influencer identification;
• Identifies brand-safe influencers by gauging profanity ratings to recommend potential partners with shared values;
• Marries online behavior with offline purchase to help drive ROI based on real-time campaign measurement across brand perception, consumer engagement, online conversion, offline sales and foot traffic; and
• Delivers tone appropriate ads to real people at the right time to help drive engagement.

"Brand reputation matters now more than ever. Using social media to help drive purchase consideration is important as brands implement influencer marketing strategies to establish real connections with consumers, said Bob Lord, SVP of Cognitive Applications, Blockchain and Ecosystems, IBM. "Together with Influential, we're building trust into the ecosystem by applying IBM Watson to help clients select an influencer that aligns to their brand values, exemplifying our belief that AI can and should be the backbone of the new digital economy."

According to the 2019 Influencer Marketing Global Survey from Rakuten, an insight and analytics company, 87% consumers surveyed stated that they were inspired to make a purchase based on an influencer's recommendation.¹ Further illustrating the power of influencer marketing to guide purchases, 61% of responding consumers stated their intent to click on a sponsored link from an influencer to learn more about a product.² Social Targeting with Influential relies on IBM Watson to align brands with like-minded influencers that demonstrate similar values, further illustrating how brands across industries can harness AI to make more informed decisions. Solidifying the power of "belief-driven buying," in a recent survey conducted by Salesforce Research, 92% of consumers surveyed report that trusting a brand makes them more likely to buy products and services.³ According to an audience poll conducted by IBM Watson Advertising at the MMA Global CEO/CMO Summit on brand trust, 52% of respondents stated that they're likely to pause advertising on Facebook, illustrating the power of preserving brand integrity on social media platforms.⁴

"More than ever, brands seek to make sure every dollar spent drives a measurable return in the online and offline world" said Influential CEO Ryan Detert. "Influencer marketing has evolved into a fully trackable channel that leverages suitable voices to speak on behalf of brands. We've seen how powerful Watson can be and are thrilled to expand our relationship with IBM Watson Advertising to bring this offering to even more brands and influencers."

Establishing the Influential tool's importance as the advertising industry readies for a future without cookies, Social Targeting with Influential does not rely on third-party data, but rather anonymized first-party data generated by an influencer's followers on social media, further developing a relationship between brand and consumer. Acknowledging the value that the Influential tool brings to the marketplace, leading brands like Wells Fargo, McDonald's and the NFL today are using the Influential platform to help drive consumer engagement and ROI.

"Influential's IBM Watson-powered campaigns have helped us identify the right influencers and deliver at scale to help us better connect with our target audiences, added Michael Lacorazza, Executive Vice President, CMO, Head of Integrated Marketing, Wells Fargo.

These brands using the Influential platform saw unprecedented 100% positive sentiment scores among users and an increase in ROAS compared to social benchmarks, further illustrating the importance of harnessing AI technology to make smarter decisions.⁵

About Influential

Influential is an AI-powered social data and conversion technology. Leveraging a network of over 1 Million social media influencers, Influential's technology powers seamless talent discovery, comprehensive brand safety, and creative and execution services. Through strategic partnerships with first and third-party data providers, Influential's Optimized Paid Media offering enables bespoke targeting and measurement solutions, including both online and offline attribution, such as sales lift, TV tune-in lift, foot traffic, as well as brand lift studies. Influential works with Fortune 500 brands, including Walmart, McDonald's, Pepsi, NFL, Nestlé, General Mills, Toyota, Samsung, and Sony Pictures. With offices in Los Angeles, NYC, and Las Vegas, Influential is a developer partner of IBM Watson, a strategic partner of WME and Oracle, and a Facebook and Instagram Marketing Partner. (www.influential.co) 

About IBM and Artificial Intelligence 

A world leader in AI software, services, and technology for business, IBM has deployed Watson AI solutions in thousands of engagements with clients across 20 industries and 80 countries. IBM's Watson AI solutions are widely used in industries, including seven of the 10 largest automotive companies and eight of the 10 largest oil and gas companies.   For more information about IBM, visit ibm.com.  

^1. Influencer Marketing Global Survey, Rakuten, 2019.
^2. Influencer Marketing Global Survey, Rakuten, 2019.
^3. Trends in Customer Trust Report, Salesforce, 2019.
^4. Audience Poll, MMA CEO/CMO Summit, 2020.
^5. The performance data discussed herein is presented as derived under specific operating conditions. Actual results may vary.

SOURCE IBM