CMOs On Implementing AI Into Their Martech Stacks
Large teams are less agile than smaller ones and the unpredictable benefits of new technologies do not necessarily outweigh the organizational costs at first.
Large teams are less agile than smaller ones and the unpredictable benefits of new technologies do not necessarily outweigh the organizational costs at first.
Machine learning algorithms offer hope to overwhelmed marketers by sifting through data quicklyand alerting human operators to potential opportunities.
Cleaner, better data informs smarter, more effective AI but the real world is messy and tends not to fit perfectly in databases.
AI for content marketing has matured significantly in recent years and we now have enough examples that we can start to see how AI is going to affect the industry.
Google and Facebook have been quietly introducing machine learning algorithms to their platforms for years, essentially kicking off the mainstreaming of AI in the process.
“The last few years have seen a boom in the amount of intelligence B2B marketers can access about the accounts they’re trying to target. But
AI adoption is up 24% from last year, but many businesses are still struggling to get their arms around the technology and integrate it into their business workflows.
Influencer fraud cost brands an estimated $1.3 billion in 2019, and the additional rise in influencer scandals has put pressure on marketers to ensure brand value alignment before collaborating.
Researchers trained a neural network to map audio “voiceprints” from one language to another.
“Now, there are companies out there that can help with different aspects of content. Our partners like Phrasee and Persado, for instance, help with subject line. It’s