We already know that AI solves several needs for marketers in every industry, and we all have one way or another used marketing technology to help us in our businesses.
With the rapid advancements in technology, the rise in Software as a Service (SaaS) companies, and a growing need for rich data-driven marketing campaigns, it’s no surprise that we are increasingly witnessing the integration of artificial intelligence in our strategies and operations.
Today, we’re showing you 8 of the best ways to use AI in martech this 2021, so that you can make the most of your own marketing tech stack to grow and scale your business.
Table of Contents
8 Uses for AI in Martech
Predicting marketing campaign performance
Martech has paved the way for what’s called predictive analytics, which can show marketers what may happen in future campaigns. These predictions are always based on existing data from previous campaigns and strategies, and with machine learning, your data and predictions only get richer over time.
You can use these predictions to help you create stronger campaigns that resonate with customers and prospects better, as well as to identify leads who are warm enough to proceed to the next sales stage in your business.
Improving customer service efforts
Another helpful way to use AI in martech is integrating chatbots into your customer service efforts.
There are several AI chatbot software and services you can add to your website or Facebook page, letting customers access instant information based on a pre-loaded set of options or questions or even with advanced keywords.
Here are a few use cases to apply AI chatbots in their marketing efforts:
- Give users a chance to learn more about your latest promotions or offers
- Let visitors see answers to FAQs you get about your products or service
- Remind them about upcoming events and webinars
- Send them updates about their orders or account
- Send subscribers your latest blog posts and content through an RSS feed
Creating personalized, targeted content
Over 70% of consumers only interacted with highly personalized content and offers.
And with AI in martech, creating personalized content and offers becomes easier. We’ve seen AI-based clustering systems with popular entertainment apps like Netflix or Spotify, who are known for their strong understanding of their consumers’ preferences and making targeted content recommendations.
And beyond entertainment, we’ve seen companies like Airbnb use this machine learning to offer users extremely personalized experiences and offers after gathering data like transaction history, preferences, and search history.
Managing social media accounts
Social media management is perhaps one of the most useful ways a company can use AI in its marketing strategy. Marketers can now easily automate their content distribution and promotion efforts at scale, offloading tasks that were once manual by nature.
You can use popular social media management tools to create a content calendar, schedule posts, and manage comments and messages all from the app. Even if you have multiple accounts across different platforms, you’re able to manage all your content and data and review your analytics all in one dashboard.
Providing dynamic pricing
Adjusting your prices based on the changing demands of the market is necessary for every business.
A seasoned business owner may know when to adjust prices based on quarterly data, historical trends, and other factors in the market. But this traditional method of determining prices is time-consuming and prone to human error.
Using AI for dynamic pricing is definitely the smarter strategy. It uses algorithms to identify the best pricing for every possible situation based on data gleaned from customer behavior. Targeting customers with customized discounts and offers becomes easier with AI. Price predictions are done continually and in real-time, so you can save valuable resources and avoid pricey mistakes.
Several industries ranging from airlines to travel companies now make use of AI for dynamic pricing to offer the most ideal prices to every customer.
Streamlining content team processes with digital asset management
As a business grows, it collects more digital assets or valuable electronic files such as images, PDFs, videos, and other documents related to your products and services.
These digital assets can be stored in servers or drives in the company, but they can be difficult to manage due to their increased volume and the changing conventions of data storage.
Some important digital assets may even be lost due to inconsistent file names, migrating data, or even during a messy digital transformation project within the company.
Thankfully, integrating AI into digital asset management adds useful and well-organized metadata to the files. By using machine learning to tag assets, AI improves categorization, provides suggestions based on similarities, and offers advanced and refined keyword searches for users.
This is especially useful for e-commerce and the real estate industry which deal with a massive catalog of images.
Sending retargeting campaigns
Using AI for retargeting campaigns essentially lets you follow potential customers even when they leave your online store or website, prompting them with reminders about your offers.
Possible use cases are for eCommerce stores sending cart abandonment emails. An observation by email marketing platform Moosend found that among all the users who click through after receiving a cart abandonment email, 50% make a final purchase.
AI retargeting is also used for email campaigns when a customer views your website or landing page but takes no action. You’re able to then retarget them through banner ads on other websites or social media ads, so you’re constantly top of mind.
Identifying top customers and net promoters
Customer stays loyal to your business when they feel prioritized, and their experience and behavior can be measured using the net promoter score (NPS). The NPS identifies top customers through a simple question of how likely they would recommend the business to a friend over a scale of 1 to 10.
Customers have grouped accordingly:
- Promoters (9–10) are loyal and enthusiastic customers who will continue to buy from you and tell their friends about you.
- Passives (7–8) are satisfied but not as enthusiastic as the Promoters and they might consider buying from your competitors.
- Detractors (0–6) are the dissatisfied and unhappy customers who might damage your brand, reputation, and growth through bad reviews and recommendations.
Identifying a customer’s NPS becomes optimized through AI-powered surveys. They combine conversations with customers and actual metrics and automatically analyze textual data in order to improve the customer’s experience. Thus, you can better increase the number of Promoters, know which Passives to appease, and lessen the number of Detractors.
Use AI in Martech to Boost Your Marketing Efforts
Martech is a constantly evolving and exciting field due to the rapid developments in Artificial intelligence technology. Consumers are producing data at a massive scale every day, so using AI in martech is the logical way forward to grow your business.