Data-driven optimization: The critical role of AI in martech
In an increasingly data-driven world, there is tremendous value in capturing and making sense of marketing data, including information on users, accounts, contacts, purchases, downloads, link clicks, form submissions, video plays, transactions, and so on. While this top-level, event data may seem like everything a savvy marketer would need, it is the metadata – data about the event data – that gives it the most valuable context. Metadata can be more revealing than event data itself when collected and analyzed in aggregate. But there is so much data available these days that it can cause paralysis. This is where AI comes in – marketers need to become increasingly adept at using advanced technologies to make data functional.
We have been seeing a steady rise in the use of artificial intelligence across industries – marketing is no different. Some of the world’s largest companies rely on AI for all sorts of reasons, but inmartech, it holds promises that will bring even more disruption to the industry.
The application of algorithms, machine learning, and AI to solve major marketing challenges – for example, attribution, intelligence gathering, predictive workflows, and campaign suggestions – will enable the industry to market better, for less money, more success, and happier customers.
Two years ago, when the volume of data generated worldwide was estimated to be a staggering 2.5 quintillion bytes of data a day, the industry projected that by this year, 2020, every individual on earth would be generating 1.7 MB of data every second of every day.
While we don’t know where that number actually stands today, it’s likely been driven even higher as a result of the global pandemic. What we do know is that legacy analytics tools are not capable enough to ingest the amount of data being created in today’s martech stacks to make sense of it.
There are more than 8,000 different companies developing software in the space and all the data to go along with them. While the growth of the ecosystem has been empowering, it is also a curse.
Which is why a premium should be put on data integration and management solutions. For much of the industry, one of the fundamental issues is bringing data together efficiently and effectively.
In a multi or omnichannel marketing environment, how you develop actionable insights from a range of different marketing campaigns is one of the things that separates a good marketer from a great marketer.
A great marketer knows how to optimize campaigns, how to leverage historical data, and how to use marketing intelligence to map where to spend their next dollar for optimal impact.
Data density is an important component of artificial intelligence.
While Big Tech companies have enough data density to build predictive algorithms, smaller companies similarly need to be more resourceful to follow suit.
