AI Marketing Predictions For 2018If last year was a huge success for digital marketing, it's going to be unstoppable in 2017. With the growth of online communities, shared resources, tools and APIs, a conversational UX design party has truly started. Now is an incredibly exciting time to be a UX/UI practitioner exploring bot and AI automation and machine learning in natural language messaging interfaces.
It's safe to say that the way people perceive virtual assistants and chatbots is very confused. On the one hand, they are a silly bit of technology that falls over, on the other, they are ultra-intelligent and about to embark on world-domination. In truth, neither image is reflective of, what is essentially, an enterprise level technology that is being used to aid a variety of businesses in a number of purposes, from customer service to internal HR.
Ellett interviewed Lux Narayan, CEO of Unmetric, which is a company specializing in social media metrics, on this subject. Narayan says, The whole social space has a lot of noise. It's very difficult to disambiguate one company from the other. But I think there are distinctive patterns in what companies do. And indeed, in where they're starting to deploy AI within each of those subdomains. More specifically, they fit into six broad areas within social.? Narayan points to these six areas: content creation, consumer intelligence, customer service, influencer marketing, content optimization, and competitive intelligence. We decided to dig deeper into the area of content optimization for examples of tools companies can use.
Online lingerie brand Adore Me used Optimove 's AI to segment its customer list into different types of prospects and customers to increase purchases and subscribers to its membership pricing program. The AI automated the segmentation process and started sending customized content based on each recipient's lifecycle stage via email, text messages, and in-app notifications. Segmenting customers and contacting them on different platforms helped Adore Me increase its monthly recurring revenue (MRR), average sales price (ASP), along with doubling its active customer base.
While it's true that part of the appeal of using AI is its low cost and high levels of efficiency, there are only so many things AIs can replicate. In fact, some of the best use cases for AI in this blog post involve AIs and humans working together to solve problems and achieve goals faster and more efficiently. So don't think of AI like a robot trying to steal your job - think of AI like technology that will make your job easier, much like computers and internet did over the last century.
Consider the current experience for consumers making travel plans. Currently, apps are able to give customers information on flight times, costs, and connections. But if the app provider knows their customer far more intimately, they're able to look at previous behaviors and declared preferences, and offer personalized advice on the best routes and schedules for every customer. Because the company understands the customer in far more detail, the solutions they provide can be more relevant and valuable, and offered in service of the customer reaching their goals.
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