The Marketing Value of AI Is Rising: 6 Ways AI Boosts Results
The Marketing Value of AI Is Rising: 6 Ways AI Boosts Results
What’s the marketing value of AI? Does artificial intelligence (AI) really earn its keep in sales and smart retailing? And how can you use it to boost your marketing ROI?
Long a topic of science fiction and academic research, AI has finally become a mainstream technology. When used on behavioral data, such as a history of what we’ve bought or clicked on, it can serve up targeted ads and promotions. Many of us seem to appreciate the more personalized approach that this allows, or at least tolerate it better than we used to.
Growing up, I always muted commercials or flipped through the channels when I watched TV. I ignored billboards. I fast-forwarded through trailers on DVDs. But now, AI must be getting better since some of the ads I see get my attention because they’re for products and services I’m actually interested in. Contrast that with the early 2000s, when an oft-played commercial jokingly showed a lot of angry people complaining about the online ads they were shown. “You keep trying to sell me kitty litter, and I don’t even have a cat!,” one angry viewer grumbled.
AI can add value by cutting away Irrelevant noise to engage consumers
Today, by aggregating and analyzing my search history, purchasing habits, YouTube views, and other data, AI can do a better job to predict which items I’m likely to buy in the future, and make it easy for me to make them mine. From the consumer’s standpoint, the benefits of such AI—while they may at first seem a bit intrusive—are obvious. From the marketing side of things, AI is becoming even more valuable in a fiercely competitive, omnichannel world.
In addition, to this example above, here are six other ways that AI can benefit your marketing team:
AI can free up time for other tasks
By automating simple, repetitive tasks, AI tools can help marketers devote more of their attention to solving tough challenges and thinking more creatively. In a Forbes.com article, Andrew Stephen, head of the marketing faculty at the University of Oxford’s Saïd Business School and a big proponent of AI for marketing organizations, writes that “prescriptive AI” (i.e., AI tools that can ‘make’ decisions based on learning and sets of preconfigured rules in an automatic, or semi-automatic, manner) will be a boon for decision-making executives because time will be freed up.”
AI can optimize product searches
Searching for desired products on a brand’s website can be more accurate and smarter than ever before with the addition of AI. As Daniel Faggella points out in a piece for TechEmergence.com, searches didn’t always yield the desired results. “Ten years ago, typing ‘men’s flip flops’ at Nike.com may not have yielded the results I was looking for,” he writes. “Today, it very much does.” These improvements are thanks to AI technologies like Elasticsearch, Indix, and software that anticipates and corrects misspellings.
AI can customize content for different customer segments
Just like the product recommendations I mentioned earlier, marketers can use AI to review customer data—such as lifecycle and level of engagement—and send customized emails, texts, and in-app notifications containing more relevant and engaging content. If a customer is more interested in what you’re telling them, then they’re more likely to trust you and make a purchase.
AI can deliver quality leads more quickly
According to Brad Power, reporting for the Harvard Business Review, in late 2016 the telecommunications company CenturyLink invested in Angie, a virtual sales assistant. She sends approximately 30,000 emails every month, interprets responses to determine the hottest leads, and then hands off the most likely prospects to a human salesperson. By automating this part of the lead qualification process, salespeople also have more time to work with accounts that are further along in the pipeline.
AI can facilitate conversational commerce
Thanks to AI-powered speech and chat interfaces popping up in the form of Amazon Echo, Facebook Messenger, Baidu’s Duer, and others, consumers can buy things just by speaking into machines or tapping out a request to a chatbot. The more convenient it is to make a purchase, the more your customers will appreciate it.
AI can improve customer support
While a few purists out there may not consider customer service a marketing activity, we can all agree that a pleasant support experience can engender a high degree of customer loyalty. For consumers with fairly straightforward problems, AI programs can easily provide the answers they need, without getting tangled up in an overgrown phone tree. Your customers stay satisfied, while your customer service professionals can handle more serious issues.
Enterprise Customer Data Platforms Provide the Data that Powers AI
The trick to using AI profitably is to identify high-value customers at scale, make relevant recommendations, and deliver more delightful consumer experiences. To accomplish these steps, you need to collect as much customer data as possible, unify it across different systems, and analyze it using the latest AI and machine learning algorithms.
But that’s a pretty tall order for many retailers and other enterprises. That’s why lots of retail and B2B businesses are turning to enterprise customer data platforms (CDPs). CDPs collect data from many different sources and use AI software techniques to decide which data relates to each customer, building a full, unified view of each one. Using this data, you can gather insights from an individual’s history, preferences, and behaviors —both online and offline — and use AI to deliver more targeted offers, creating outcomes that increase sales.
Turbocharging AI with a CDP
Arm Treasure Data has a CDP enterprise solution that brings together a number of machine learning algorithms to make data actionable at scale. Use the Arm Treasure Data CDP to market to millions as if you’re engaging them one-to-one, enhancing customer and prospect relationships by:
- Identifying brand advocates
- Accurately predicting buying behaviors
- Detecting customers likely to churn and preventing them from doing so
- Delivering meaningful product and service recommendations
- Serving up more engaging content