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Artificial Intelligence Will Help Brands Align With Influencers

One of the biggest challenges brands face today when utilizing social media is finding the right influencer to align with – and while a “wrong” choice likely won’t hurt a brand in most cases, it could be more of a wasted effort. However, in a worst case scenario working with the wrong influencer can have a detrimental impact on a brand.

According to a survey conducted by Salesforce Research last year, 92% of consumers surveyed report that trusting a brand makes them more likely to buy products and services. In addition, nearly a third – 32% – of consumers also said that the influencer’s core values should also align with that of the consumer’s.

While human marketing teams can comb through the social media feeds of influencers for past posts to judge appropriateness as well as effectiveness, which can be a time consuming endeavor, and could still miss something important. It is important to find an influencer that is the right fit but is also actually going to provide a reasonable return on investment (ROI) in terms of sales or traffic.

Now, just as artificial intelligence (AI) and machine learning are using predictive algorithms to determine a customer’s lifecycle including the key areas of acquisition, relationship growth, retention and win-back; the same technology is being utilized to help brands identify influencers that might best align with brand values.

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Last week IBM announced the launch of Watson Advertising Social Targeting with Influential, a social target tool that can help brands communicate with an audience. It leverages IBM Watson Natural Language Understanding on the IBM public cloud to process and analyze social media data, which can then help expedite influencer identification.

It can be used to identify brand-safe influencers by gauging profanity ratings to ensure that brands partner with those of shared values, while it can also marry online behavior with offline purchases to help drive ROI based on real-time campaign measurement across brand perception, consumer engagement, online conversation, offline sales and foot traffic.

The technology originally was to leverage Watson APIs including NLP (Natural Language Processing) to analyze brand health and potential influencer candidates and provide a strategic recommendation on whom to target.

It can also eliminate waste in media buys, as the AI/machine learning can be used to deliver the tone appropriate ads to real people at the right time to further help drive engagement.

“Our company forever changed in 2015 when we integrated IBM Watson APIs into our technology,” said Influential CEO, Ryan Detert. “This latest expansion of our relationship with IBM, via IBM Watson Advertising, will help us continue to be the industry leader in influencers, content, and measurement.”

Pairing Influencers To Brands

This new solution from within Watson Advertising draws from an Influential’s invite-only network, which includes more than 500,000 leading social influencers on Twitter, Instagram, Snapchat, YouTube and Facebook. This network of influencers currently reaches more than 5-billion followers.

“Now more than ever, it’s essential for brands to meet consumers where they are – on social media – to foster connections that engage, raise awareness and lead to actions,” said Dave Olesnevich, head of product, IBM Watson Advertising.

“IBM Watson Advertising Social Targeting with Influential harnesses AI to help brands identify the influencers that they can trust to align to their brand values,” added Olesnevich. “Leveraging AI to make faster, smarter, data-driven decisions is crucial to ensure success as the advertising industry readies for a future that still demands personalization at scale, but without the aid of identifiers.”