All of today’s marketing leaders and innovators want to make Artificial Intelligence work for marketing; but to many, its application seems a far-reaching future vision, rather than a practical reality.
Let’s think about your customers: they’re delivered a seamless set of interactions, personalized emails and customer service interactions based on their behavior – from instant chat to call center – free from human errors found in your team’s noble attempts to make relevance work at scale. They really receive the right message, in the right context to help them towards what they want – and luckily for you, so do millions of other individuals interested in your brand.
Imagine if your data-driven team didn’t have to spend time behind the scenes organizing and activating datasets into ways which make business sense: no spamming the disengaged with expensive ads, and instead creating customer journeys which match intent.
And your creatives? They’re part of a feedback loop which could help them make hyper-personalized assets and customer recommendations to really write home about – based on their automated placement in the perfect context for every potential browser, booker or buyer.
For all the impressive tricks ‘it’ can perform, and the far-reaching impact software vendors profess AI has for marketing, its real value can be found not in solving puzzles, writing poems and stealing the jobs of copywriters, but in very specific contexts to create greater efficiencies, by smartening relevance en masse:
Businesses can apply Artificial Intelligence models on an industry level for marketing, to make billions of targeted, data-driven decisions in real-time.
The promise of personalization at scale is a highly sought-after reality, but our fickle marketing world continues to change shape with an infinite stream of martech solutions – for as many customer-facing screens, apps, platforms and channels.
The golden circle of capabilities is completed when industry-specific AI models are used to fuel flexible Orchestration across the marketing ecosystem – applying Artificial Intelligence to make smart insights work in practice at scale, across impossible volumes of clean data. This means using specific rules to predict outcomes like ‘likelihood to book’ based on a combination of 1st and 2nd party data, to engineer ads into rewarding interactions.