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.
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SOURCE IBM