AI is taking over – and that’s not a bad thing when it comes to marketing.
Below, I’ve put together a list of ten types of AI marketing technology that will help you gain a competitive edge in 2019 and beyond.
1. Tear Down the (Software) Silos with AI Marketing
While that “tear down the silos” cliche is well worn at this point, the message is worth repeating.
Data is your most valuable asset, and these days, the data conversation is all about how you can use that unprecedented access to behaviors, preferences, and demographics to deliver a better and more personalized experience to your users.
However, when your company is working across multiple platforms and storing data in several different places, there’s a missed opportunity to use that valuable asset to its full potential.
Think about this: your customer service team is collecting information about product issues and returns. Your social media team understands what drives engagement, but doesn’t know much about the overall perception of the brand.
Accounting, sales and everyone else has their own set of data that says something about your customers.
I think that we’re starting to see a greater emphasis on evaluating the full picture of marketing and how it relates to every piece of the customer journey.
Where AI marketing helps with this is in the form of integrations and analytics.
You’ll want to evaluate each tool in your marketing stack, making sure that everything from your marketing automation platform to your CRM and social analytics talk to each other.
2. AI Marketing Offers Personalization at Scale
Most email marketers maintain a subscriber list a mile long. And while there’s a real push toward personalization and authenticity, there’s also this need to do so at scale.
But if you can do it, you can hit a marketing home run.
That said, it’s challenging to pull off and relies on brands being able to collect data from customers and pick up on the signals that they provide.
That’s where AI marketing comes in.
By using AI to analyze activities such as how visitors move through your website, what they buy, and what they share on social media, you can start to respond by sending relevant, well-timed messages based on individual triggers.
This process requires careful planning, as teams need to come up with a series of trigger messages that correspond with individual habits.
Triggers may include abandoning a shopping cart, buying a specific purchase, or a calendar date–i.e., you might start promoting summer clothes after Memorial Day.
These triggers will then be mapped to images, copy, and headlines most likely to speak to that person’s specific need. The challenge with personalizing lies in the power of using analytics to inform your decisions.
The cool thing about AI marketing is that by collecting information on the actions users are taking, you can then begin to predict sequences they’re likely to follow.
AI marketing can help trigger an email drip campaign. Image courtesy of Pardot (see full infographic)
In many cases, such as content or product recommendations, suggestions and sequences follow the rules of common sense. A buy-next algorithm might prompt a visitor to add a jacket or shoes to their cart after buying a dress, to complete the outfit.
3. Smarter Chatbots
We’ve chatted a bit about bots in the past from Facebook Messenger-based helpers to full-blown native sales assistants like the ones you can get with a service like Drift.
AI marketing can help you learn from user interactions with chatbots
The thing is, chatbots just keep getting better.
AI-based marketing and technology takes support to the next level, allowing you to chat with customers 24/7.
And, on top of their obvious use as a support tool, chatbots are the backbone of a concept known as conversational marketing.
Today, nearly 1.4 billion people interact with chatbots, and based on an Oracle Study, 80% of the businesses they surveyed said they were already using chatbots or plan on incorporating the technology by 2020.
Not only that, but based on a forecast from Juniper research chatbots will help companies to save over $8 billion annually by 2022, especially in areas like healthcare or financial services where users have less and less patience for long hold times.
Customers like interacting with chatbots as they offer quick access to information and can pull up their entire buying history, adding more context to each interaction.
On your site, native chatbots can help you get more out of your lead gen forms. Lead forms are great for collecting contact information, but they don’t give much insight into why someone chooses to fill out a form or not.
By adding a chatbot to your site, AI can ask the right questions that uncover pain points, values, and goals. From there, bot-based insights can inform your entire marketing strategy from how you present ads to individual segments to what you say in your email marketing campaign.
4. Marketing Automation
Marketing automation tools are a type of software that, as you might guess, automate repetitive marketing tasks and allow brands to scale their efforts.
Still, many companies do tasks such as email marketing, customer segmentation, and more manually, based on their perception of the analytics they have at their disposal.
Sure, marketing automation has become something of a buzzword, but we’re starting to see more accessibility coming to the space.
Technology is allowing machines to segment and automates email sequences based on user behavior.
Attempting to manage all marketing channels and efforts manually is not only time-consuming but subject to human error. While AI is nowhere near perfect, it can eliminate certain risks and streamline processes from data collection and analyzation to segmentation and message deployment.
Additionally, by combining AI with marketing automation you can better ensure that the right message will be hitting the right audience. This, again, goes back to personalization.
By using the insights and predictive technology of AI, you can deliver an overall better and more relevant customer experience.
5. AI Marketing and Social Listening
Natural language processing is becoming an essential tool for companies that want to understand what their customers actually want.
These days, customer demands are higher than ever. Meaning, if a complaint slips through the cracks or you present the wrong offer, they’ll probably start shopping with another brand.
AI marketing gives brands the ability to listen in on social conversations, reviews, and survey results through a process known as sentiment analysis.
The benefit of this process is that AI systems can analyze feedback from several channels at once, which can reveal issues, complaints, and general sentiment before problems get out of hand.
Another major benefit of AI marketing in social listening is that it can uncover data and insights that may have previously gone unnoticed. AI can pick up on extensive historical data, past and current brand or topic mentions, etc. to help you evaluate trends over time and better plan your strategy.
6. Dynamic Product Pricing
Dynamic, or demand-based pricing, isn’t exactly new.
Simply put, demand pricing is a strategy where product pricing continuously shifts in response to real-time measures of supply and demand.
Think flight prices that change based on day of the week or hotel room rates rising and falling with the seasons.
But AI changes the game.
By bringing machine learning technology into the fold, brands can analyze customer purchasing patterns and make predictions about how much they are willing to pay on an individual basis.
AI marketing can also measure how receptive customers are to exclusive offers so that you only push out discount codes to customers likely to use them.
In the past, one of the primary arguments against dynamic pricing has been a worry over losing control of the brand and undermining its perceived value.
However, because AI is improving all the time, dynamic pricing gives brands more flexibility when it comes to staying profitable.
Brands can get super granular here, calculating the exact discount needed to push that customer toward making the purchase.
Dynamic pricing can also be used to look at competitor pricing to gauge whether pricing is too high, too low, or just right.
Companies like Amazon and Walmart have long been using this strategy to stay ahead of the competition, as well as offload the underperforming products.
You’ll see this quite often on product listings where some colors are much cheaper than the others.
According to eConsultancy, big brands (and increasingly, smaller ones, too) are using intelligent pricing software that allows them to scan thousands of products within minutes, adjusting prices based on real-time demand.
Beyond the more common examples of dynamic pricing, Airbnb uses a similar algorithm to help property owners get a sense of how much to list their properties for.
The system uses a range of factors that include amenities, location, booking dates, local events, reviews, market demand, and more to set a price in line with other regional listings.
Property holders aren’t beholden by the dynamic pricing recommendations; instead, they function much like Google’s PPC recommendations–designed to help you based on the algorithm’s historical data.
7. Speech Recognition and Google Actions
With Google slowing rolling out advertising opportunities through its Google Assistant and Amazon’s Voice Search, speech recognition is on the rise.
The reason for this is that digital assistants across the board are becoming more accurate and less frustrating for consumers.
In 2017, Google’s speech recognition accuracy hit an astounding 95%, and of course, smart speakers like Google Home and Alexa have become part of the family for many households.
This means we’ll begin to see more and more audio content from brands to increase awareness on a new platform.
To show up (or get a shoutout from a virtual assistant) you’ll need to focus on writing blog posts and web copy in a conversational tone. People don’t say “Okay, Google, food near me open now.” They’ll say, “hey, Google, where’s the nearest Thai restaurant?”
As it stands, the search algorithm that determines whether or not you’ll show up in a voice search isn’t fully known.
We recommend following a similar approach as you would when trying to lock down an appearance in the featured snippet. Provide FAQs, how-to guides, and in-depth content that really solves problems. In other words, emphasize EAT. Expertise, authority, and trustworthiness.
We wrote about it recently, but given that Google Local Services ads can now be read over Google Assistant, it’s only a matter of time before all kinds of companies can buy ad space.
While speech recognition is only one component of voice experience, it does play an important rule in making sure that voice interfaces and voice interactions function smoothly, and that users’ requests are interpreted correctly.
AI is also the force behind the newest addition to the app scene – Google Actions and Alexa Skills.
Actions and Skills work with smart speakers, allowing users to interact your brand in the same way they would an app on their mobile device, only this time, it’s controlled via voice.
These voice apps are what represent brands on digital assistants and via voice command, and I think they’ll play a powerful role in marketing going forward, as they offer a way to closely connect with users and offer them personalized experiences thanks to – you guessed it – AI.
8. Programmatic Advertising and AI Marketing
We ran a recent article discussing a whole host of reasons not to use programmatic advertising.
AI marketing: programmatic ad spend is on the rise
Right now, this strategy is complex. It’s an advanced PPC method best used as a last resort, not your go-to campaign strategy.
If you missed that one, here’s a quick refresher: programmatic advertising is an AI-based process that automates the ad buying process so that you can target more specific audiences. AI allows you to bid in real-time, so you can catch your target audience when they’re most likely to be online.
The idea is, programmatic is faster and more efficient than traditional PPC, which best case scenario, results in lower customer acquisition costs and higher conversion rates.
Programmatic isn’t exactly new, either, but it is getting better.
So much so that eMarketer predicts that 90% of digital display ads in the US will be programmatic by 2020.
And here’s the thing: though programmatic shouldn’t be approached lightly, if you have significant experience with paid media and have already experimented with the other major ad channels, it may be well worth a try.
9. Predictive Analytics
One of the most exciting ways where Artificial Intelligence meets Martech is predictive analytics. The term refers to using data mining, statistics, and modeling to make predictions about how customers might behave in the future.
Due to the rise of AI and big data, predictive analytics is essential for brands angling for the competitive edge.
Here are a few ways that marketers can use predictive analytics to produce higher performing campaigns and a boost to the bottom line.
Understand Your Customers Better
Predictive analytics are ideal for customer segmentation.
Here, AI algorithms can break down audience attributes and create super specific lists. From there, you might use these lists to run Google PPC ads or your next Facebook campaign. And, further down the line, those Facebook insights will allow you to collect more information about that audience.
Using demographic and behavioral data, marketers can also level up their lead nurturing process by presenting the right offer at the right time. They can also use that information to upsell or cross-sell related products and deliver better recommendations.
Qualify Leads
All it takes is a strong command of internal data to mend the longstanding rift between marketing and sales. As we’ll go over in the chatbot section, predictive analytics allow teams to uncover specific qualities that determine whether someone is likely to buy from your company.
This is especially useful for B2B brands with long sales cycles, allowing sales reps to focus on following up with the right people, and giving marketing the data needed to inform their paid advertising, SEO, and email marketing strategies.
10. AI Marketing Provides a Better User Experience (UX)
The tenth way that AI can improve your Martech strategy comes down to making customers happy. Your marketing efforts should be designed to pay off in the form of loyal, satisfied customers.
Customers want a seamless customer journey from the time they first see your brand to after the initial sale. By using AI, marketers can design marketing campaigns around each user, presenting the right offer at the right time, based on contextual clues.
AI and UX design are a natural fit, giving brands the ability to automate tasks like split testing and set up self-optimizing websites.
This means that marketers can step back and take a more strategic approach to UX, focusing on the human side of the strategy, rather than getting bogged down with experiments that reveal the best color for CTA buttons.
When customers have a positive experience, the more likely they are to tell their friends and family about it, return to your site for more purchases, and leave positive reviews in public (online) spaces. As such, marketing teams must be able to run sentiment analysis, review navigational behavior, and track purchasing patterns, working to make improvements based on the data.
Wrapping Up How to Use AI Marketing to Improve Your Martech
In the world of marketing, sitting out one trend or another means you’ll get left behind. Those who embrace AI and all of the possibilities stand to reap the biggest and best benefits long-term.
As you may have noticed, just about all of these entries are centered on using data to inform your entire marketing campaign, and I certainly don’t think big data is a trend we’ll forget about anytime soon.
That’s not to say every piece of AI-powered martech is right for every company. The key is to look at these emerging–or to be honest, improving–technologies to identify where AI can help you deliver the best possible results.
