No need to wait for the “Singularity”; artificial intelligence is already a part of our lives. As marketers, machine learning affects our keyword targeting strategies. As consumers, it influences our buying habits. AI is now a part of our smartphones, education systems, and even the new self-driving cars.
Here are five ways marketers can take advantage of AI in 2019.
1. CRO strategies
Machine learning and AI have a variety of applications for optimizing your customer conversion rates. Standard A/B testing of your website takes time and resources, but it’s critical to your bottom line. You have to identify obstacles to customers’ actions, whether it's downloading a PDF or visiting a landing page. Machine learning can comb through web analytics, heat maps, and datasets much faster and more accurately than humans.
Some A/B testing services can automate your multivariate testing using machine learning. These services can dynamically swap out elements of your website — like layout, copy, or design — until its AI zeros in on the highest converting combination. Automated A/B testing can help increase your CRO much faster than traditional means, saving you marketing dollars and time.
2. Chatbot implementation
A common customer complaint is not being able to get answers to simple questions on a website. Chatbots are an inexpensive and effective way to answer these types of customer questions. These AI-powered customer service robots excel at answering common questions that have straightforward answers. Plus, they work 24/7.
Chatbots of the past have shown mixed results. Their learning algorithms weren’t sophisticated enough to deliver the right information, nor were they "human" enough to alleviate customer aversions to speaking with a robot. But innovations in software have transformed chatbots into effective customer support tools.
Depending on the size of your business or client, you may want to look for a chatbot service that works with the existing live customer service. One common strategy is to offload customer traffic to AI chatbots when your human customer service reps are overwhelmed.
3. PPC campaigns
No one does machine learning algorithms like Google. Ads comes equipped with plenty of AI features for getting the best return on ad spend. AI-based bidding for PPC campaigns lets you analyze hundreds of audience parameters for better insights.
Google’s Smart Bidding is an automated bid strategy that predicts how different bid amounts will affect your conversion rates. And its in-market audience feature uses AI to analyze trillions of search queries to determine the purchase intent of your users. With all these data points, you can process ads in real time, optimize your bids, and place them in the most valuable auctions. As the system learns over time, your bid performance will get more efficient.
4. Content creation
The online world is awash with content. And finding topics and angles for high engagement is getting tougher. But machine learning can improve the creation and delivery of your content. Today, not only can AI marketing tools help you discover high-performing ideas, they can also track their effectiveness. Instead of pouring through keyword difficulties and search volumes yourself, use AI to automate competitive research on topics and predict their ROI.
You can also use machine learning to analyze your audience and deliver content in a personalized way. Some AI can highlight the parts of your blog that are meeting your engagement standards. Then, the system provides that content to individual users based on their social engagement behavior. For example, you can deliver a social video to individual users when they’re most likely to be using social media.
Recruiting top content producers that meet your standards is another challenge to improving your content. But machine learning can even help you optimize your job listings and find the best candidates. Services like Textio use AI to help you draft job listings that will attract the perfect content creator for your team.
5. Email marketing
Website owners can use machine learning to personalize their email campaigns. For example, some email services can use customer profiles and buying history to include recommended products within campaigns. And as the AI gets to know your customers, they can finetune your segmentation, separating “big spenders” from “coupon users.” Enhanced segmentation will increase conversions and profits.
Another way to use machine learning for email marketing is with cart abandonment services. Around 70% of online shoppers abandon a product in their carts. So, re-targeting these customers with reminder emails (always ensuring you stay GDPR-compliant) results in revenue increases. Abandonment services track your users’ actions, note when abandonment occurs, and sends out a reminder email several days later. You can customize the emails and set a delivery cadence yourself.
ROI with AI
One aspect of AI that's an objection for some marketers and their clients is the time investment. Machine learning, like human learning, takes time. As their algorithmic brains evolve, machines get fast at delivering results. Therefore, marketers should look at AI investment as a long-term game.
But that doesn’t mean you shouldn’t set goals and expectations for performance — just be realistic about your timelines. This is critical not only for analyzing your gains and losses but for evaluating an individual service or tool for its effectiveness — not all AI is created equal.