If you’re a marketing executive, you may feel like the ground is constantly shifting under your feet. Everything that the industry thought was a best practice ten years ago is now obsolete, buried under an increasingly mountainous pile of data.
It all started simply enough with website traffic. Then social media. Then, just when you started to get your head around social media data, along comes mobile data. And then data on every single tap and swipe done by every customer using your mobile app. Oh, and wait: You actually now have 20 different mobile apps, plus two for wearables (Apple Watch and Android), and your product guys are working on an augmented reality app that will be totally amazing, and just wait until you get the engagement data from those users, all of it tagged with geodata and more!
Whew. It’s not surprising, then, that many marketers are starting to take the promise of artificial intelligence more seriously. How else are they going to deal with this ever-increasing flood of data?
In fact, AI offers an array of benefits that can help turn gigabytes of unmanageable data into workable insights and real-time decisions. Here are five.
1. 360-degree view of your customer
You’ve probably sunk tons of effort into combining your CRM data with other internal sources, but that data is by definition limited: It only includes information on your customer’s interactions with you. Yet there is much more data, by orders of magnitude greater, available on the public web. There are billions of web pages, tens of thousands of news stories a day, posts on social networks (Twitter, Facebook, LinkedIn, etc.), contact databases, and more. Sorting through and making sense of all this raw data is impossible without AI, which can automatically discern relevant bits and synthesize them together with your own data, painting a much more complete picture of each customer.
2. Action, not analysis
The current marketing data pipeline starts with collecting data, followed by running a report, analyzing the results, making a decision, and then taking action. It works, but it’s time-consuming. AI, by contrast, lets you compress all these stages into a single moment: analyzing data, identifying patterns, discovering correlations, and putting the insights into action immediately — while a customer is right there on your website.
3. Smarter budget allocation
At trade show booths, you’ll give the same T-shirt to a VP of marketing, an experienced marketing professional looking for a new job, and a student just exploring the field. Yet the first one is a million-dollar sales opportunity, the second is a potential hire, and the third is wasting your time. The same applies to current customers: If you’re like most companies, 80 percent of your revenue comes from 20 percent of your customers. If you use AI-driven models to predict future revenue, and you can do this at scale, you’re able to invest more in the most promising customers and prospects.
4. Intelligent lead routing and territory management
Today, sales teams are organized through archaic and fairly arbitrary rules: This person is responsible for pharmaceutical company leads, that person is responsible for company names from A through F. With AI-based assignments, you can allocate the preferences and background of your buyer with the most relevant person in your sales organization, in real time, based on the AI’s understanding of which matches are most likely to result in a closed sale. You might not realize that one of your sales execs previously worked at the same big pharma company that an inbound inquiry is coming from, but an AI lead management system will.
This is perhaps the most promising avenue for the use of AI in marketing. As I’ve written elsewhere, it enables your company to have incredibly personalized, one-to-one conversations with customers at scale. From dynamic ad copy to individually personalized emails to adaptive website content that’s tailored for every one of your 10 million visitors, this is all feasible through tools that ingest clickstream data, customer information, and publicly available web data, and interpret it through machine learning.
Ultimately, you can imagine an AI-based business concierge (think Amazon’s Alexa for B2B) that has deep knowledge of the buyer and can deliver an end-to-end curated buying experience. As you can see, there are many ways to use AI to take your marketing to the next level. The next question is how to make smart decisions about which AI to deploy.
This article was written by Aman Naimat and Demandbase from VentureBeat and was legally licensed through the NewsCred publisher network.