Will AI in 2017 be more important than in previous years? For beacon users, the data-powered AI of today is a different creature than its predecessors. Here’s what that means.
Excitement surrounding AI is not new. Still, experts are now pinning Artificial Intelligence as a key new technology for 2017 and the upcoming years. This is largely because of data, and it will definitely affect upcoming solutions. Most importantly, this will be key in solidifying any omnichannel marketing hopes.
Machine learning hit the pop culture radar in recent years, and AI has been in and out of the spotlight for decades. Big data exploded in popular opinion in 2015 and 2016. Yet, somehow, all of this will become hugely impactful in 2017. Forrester named AI one of the year’s key techs, forecasting that investments in related solutions would triple. Gartner, Digital Trends, and everyone in between is looking to AI.
Though not every shopper loves sharing their data with companies, most are sharing more data than ever before. We’re still a few steps away from a blossoming data economy, but the amount of beautiful, accurate consumer data available is enough to bring new marketing efforts to a new level. Users now understand and acknowledge that their data can create better opportunities–for them, the shopper.
This is huge news for the companies collecting that data. With new app downloads and new terms of service accepted, users are exchanging their data for services.
AI in 2017: Needs Proximity Data
The difference for 2017 will be access to the right data and the right tools for leveraging it. Big data has been, in recent history, a game of hoarding. Gather as much as possible and see what happens. Now investment in AI-powered technologies is scaling fast. Vendors are actually embedding cognitive computing components into their solutions.
The clear, initial winner of these highly data-driven features will be marketers. Already, they’re speaking to customers at every step of the buying process. With Bluetooth beacons, they can even speak to customers at the moment of truth–in store. Whereas the data used right now is somewhat limited, AI-centric campaigns could mean more targeted messaging and conversations.
Messaging meets real-time and scale
This is both in B2B and B2C scenarios. For B2B operations, marketers and sales teams will have a better (and more automatically-generated) view of their potential buyers.
In B2C, we can begin to say goodbye to spam, which will be a win for marketers and buyers alike. Better AI combined with that valuable data businesses have been gathering means fully informed, personalized messages delivered at scale.
Aman Naimat, SVP of Technology, Demandbase, explains to Forbes:
“These personalized conversations are already happening between strategic account managers, but in 2017 artificial intelligence will allow these conversations to grow beyond a select group of people. Instead, each of a company’s 10 million website visitors can expect to have a unique conversation with a brand based on their specific needs. From dynamic ad copy, to 1-to-1 emails and customized website experiences, AI will make hyper-personalization at scale possible.”
Marketing will no longer be about shoving a cookie-cutter message out to a batch of users but instead about forming real conversations at every level. That’s what makes the 2017-brand of AI different from its predecessors.
This is how it might work with today’s technology. You approach a local mall you frequent. The mall’s app, installed on your phone, registers your presence. It sends you a notification regarding your current loyalty points at your favorite store.
[Name], don’t forget to stop by [store]! You only need [x] amount of points until your next free gift!
This is already an incredible message. It’s targeted to the user by pulling their past purchases and even includes a great reason to visit that store. However, that’s where it ends. You receive this message. The person after you receives a similar one. The next time you visit, you receive the same message but with different numbers.
The problem with this dialogue is that it’s simply a fill-in-the-blanks game. It’s tailored, but it’s still dry and spammy. There’s nothing versatile or flexible about it. AI-powered conversations, on the other hand, can access all kinds of different data. They could pull in your past purchases, your likes, pain points, information on what has or hasn’t worked in the past. It can see what’s working in your social circle.
AI may recognize there’s a sports tournament coming up or a friend’s birthday. It might see any number of important data points from which it can craft actually meaningful messages. You don’t want to be told to collect points at some store. You want to be told where to buy gear for a game or the right shoes for your new job. AI can do the job of finding the actual need and then assigning the right action for a user to take.
Is it all about Deep Learning?
Machine learning, big data, artificial intelligence–they really all start to sound the same after a while. Just add a futuristic adjective to a noun and you have a new buzzword. However, the changes we can expect in 2017 may have more to do with Deep Learning (or deep structured learning). This is part of the broader group of machine learning methods; however, it focuses on learning data representations rather than situation-specific algorithms. Buzzword or not, expect to hear more about deep learning as data continues to proliferate everything we do.
AI and the Omnichannel
If nothing else, AI will be able to help funnel all that data from one marketing level to the next. As it stands, data is often trapped in just one sector, making it difficult for marketers or businesses to communicate effectively with their audience at different stages. This will require a lot of willingness on the part of businesses to invest in the right tools to let AI work throughout their omnichannel, but the results will be the next-next-generation of marketing.
The extreme level of automation required to create a seamless shopping or sales experience will need data, AI, proximity information, and other aspects of the IoT to come together. This is why AI in 2017 is not the same story as it was in previous years.
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