The Truth Behind Using AI in Your Marketing
By Kelsey Jones
Using AI for better results isn’t new to marketers, but it’s big business worldwide and has a strong presence in Canada in particular. According to the Ontario Investment Office, a website managed by the province of Ontario, there are over 300 artificial intelligence startups in Ontario alone. What’s more, Forbes reports that Google, Microsoft, and Geoffrey Hinton (known as “the godfather of AI”) are all located in Canada.
AI has become big business in the last decade because it brings a wealth of benefits to both consumers and businesses. From automating customer service for faster help (no more hold music!) to creating a customized shopping experience based on a person’s preferences, artificial intelligence in marketing holds a lot of potential not just for Canada, but for the world.
Below are some of the most common ways artificial intelligence is already being used in marketing.
Personalization in Email Marketing
Vala Afshar explains how marketers are using AI to personalize the consumer experience:
- Real-time, personalized pricing
- Personalized content
- Optimized purchase candidates
- Visual search
- Anticipated service needs
- Voice recognition
People like getting one-on-one service from brands, so it makes sense for marketers to use AI to create a more customized experience in email campaigns. Marvin Chow, the VP of Marketing at Google, writes, “A big part of the opportunity for marketers is how AI will help us fully realize personalization — and relevance — at scale.”
Your email marketing platform must be able to run personalized campaigns. Personalizing emails to include someone's name or characteristics about them, such as their location, has been shown to increase open rates and overall order value. A popular field that many marketers test and personalize is the subject line, where they include someone's first name in order to get their attention. Research has shown that this can increase open rates.
The body and content of the email also needs to be personalized, and AI can help accomplish this at scale. Many marketers run abandonment drip campaigns that remind recipients of their abandoned shopping carts, or alerts them when something they've added to a wish list or viewed in the past is on sale. This type of personalized experience encourages users to transition through the sales funnel, and artificial intelligence helps marketers run these catered campaigns for users.
The abandoned shopping cart campaign is one of several different types of personalized drip campaigns that are available to marketers. Marketers use drip campaigns by setting up a series of emails, texts, chats, or other marketing messages to their current and potential customers based on their interactions with the company.
For example, when someone completes a purchase, they then enter a specific current customer funnel. In this particular funnel, a marketer set the drip campaign to automatically remind the customer of recurring sale items they might be interested in based on their purchase history and recommendations from AI. If the user doesn’t make another purchase, they could go into a new funnel, where the drip campaign will remind them of the item they purchased, send a discount for future purchases, or ask why they haven’t made another purchase.
These are examples of different tactics, and their success rate depends on what works best for the audience. Thanks to artificial intelligence, the suggestions made in email campaigns can be individualized even when a marketing email is sent to thousands of subscribers.
Algorithms Help Find Preferences
Before users receive a single drip email campaign message, artificial intelligence can be used to recommend products, actions, and services. One of the most well-known examples of this in action is Amazon and its recommended products section. Once a user adds something to a wish list or their shopping cart, Amazon shows them related products based on that item and their overall shopping history.
Fortune covered Amazon’s recommendation algorithm back in 2012. It shares that Amazon’s implementation of the recommendation feature on their website and in emails coincided with a 29 per cent sales increase: “A lot of that growth arguably has to do with the way Amazon has integrated recommendations into nearly every part of the purchasing process, from product discovery to checkout.”
Using AI and email marketing software, Amazon’s email marketing team relies on a system of qualifying metrics (order frequency, open rate, and more) to automatically determine which types of emails to send a user over any given period. To avoid overwhelming users with too many messages, Amazon only sends emails that have the highest revenue-per-email average across its customer base. This is determined by machine learning.
A personalized experience can lead to more than just higher revenue. Spotify’s Discover Weekly playlists, which are automatically generated for listeners based on their song history, have led to more time spent on the service, which increases advertiser air time on free accounts or greater user satisfaction for paid accounts.
No matter what counts as a goal metric or a conversion in your marketing, most companies generally want users to be on their websites or to use their products and services for as long as possible. Personalized marketing, services, and product offerings based on customers’ preferences do just that, not only increasing time on site, but also the possibility a user will actually make a purchase or otherwise convert.
The way we communicate continues to change. Millennials and teens generally prefer using text-based communication instead of calling a company or person on the phone. Because of this, brands need to interact with customers and respond to customer service requests using a text-based method.
Chatbots are a great way to implement a text-based communication channel with current and potential customers. Many brands are launching chatbots on Skype, Slack, WhatsApp, or Facebook Messenger to interact with customers, including using chatbots to answer common questions before transferring the conversation to an available customer service representative. These conversations can be about making a purchase, tracking a shipment, or another common customer request. Chatbots free up human resources by taking care of routine inquiries, and also allow brands to have a written record of what their audience is asking and saying, which is valuable for content creation.
The instant attention a chatbot gives a customer increases their success rate. In this age of on-demand content (for example, Netflix and Spotify), customers are used to getting what they want fast. In fact, the 2018 State of Chatbots Report reveals that almost two-thirds of consumers say that 24-hour service is one of the biggest benefits of using a chatbot to connect with a company.
The ways chatbots can be applied to a company’s marketing efforts are wide-ranging. Sephora uses one to book customer consultations, whereas Nordstrom has one to recommend outfits, specific pieces of clothing, and item size options. Chatbots can also be used for other goals, such as providing a call to action to read an article, sign up for a newsletter, or enter a giveaway. Consider what customer communication can be automated for your marketing and see if a chatbot is up to the task.
Answering Specific Search Queries
One thing chatbots aren’t ideal at (yet) is providing relevant answers to highly specific search queries. For instance, a chatbot could easily bring up results for a search like, “women’s loose sweater,” but something more complex like, “main differences between cashmere and merino wool” might not be something a retailer’s chatbot could really answer.
Luckily, artificial intelligence is already prevalent in search engines, and they bring users the most useful and relevant search engine result pages (SERPs) possible. Google rolled out RankBrain in 2015 as a part of its core algorithm that determines and displays relevant search results. RankBrain puts connections between past and current queries to provide better SERPs for users. For instance, if someone searches “Detroit” and then does a separate, new search for “tigers,” Google is likely going to show results for the Detroit Tigers baseball team instead of the animal.
RankBrain is Google’s attempt to make search results better for the user, thus optimizing their experience. Besides using AI in ranking algorithms, the Marketing Artificial Intelligence Institute reports that search engines are also using AI for quality control and query analysis to understand more about what users are looking for online. This makes search engine marketing (SEM) and search engine optimization (SEO), two technical arms of online marketing, more important than ever.