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.
Good data yields good analysis. Bad data…or even limited data, can lead even the most well-intentioned marketer astray. Don’t forget to vet your data!
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.
GDPR isn’t going anywhere. 1st-party data is increasingly important as organizations move towards personalizing content for their audiences.
A great new post on Moz’s blog discusses a case study in growth hacking that increased traffic to a blog by 650%.
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.
…to create a symbiotic AI workforce, organizations will need to use human-centered AI processes that motivate workers, retrain them in the context of their workflow,
