*I frequently get asked questions about Data Science, so in the interest of helping as many people as possible, I’ve started this blog to answer those questions as simply as possible. This is a robust topic, and if you want a more in-depth discussion, please revisit my blog, where we will be going into greater depth at another time.
AI marketing uses AI to gather data and insights to help enhance your marketing efforts. From automated content creation to increased personalization, there are several ways AI can improve your startup’s marketing efforts. These tips will tell you everything you need to know and help you get started.
AI marketing uses artificial intelligence to collect data and consumer insights. It can help your marketing team enhance its efforts by creating efficient, targeted strategies backed by data.
Artificial intelligence is a significant asset in businesses and startups, specifically those with a solid digital presence. There are countless benefits to implementing AI tools into your operations. Learn how AI can be used to improve marketing efforts in this article.
Table of Contents
What is Artificial Intelligence?
5 Ways Artificial Intelligence Can Improve Marketing
#1. Tracking Marketing Analytics
#2. Improved Customer Experience
#3. Faster, More Effective Decision Making
Getting Started with AI Marketing
#1. Evaluate Your Use Cases and Pick One
#3. Narrow Down All Possible Solutions
#5. Develop an AI Marketing Strategy
What is Artificial Intelligence?
To fully understand AI marketing, it’s vital to understand what artificial intelligence (AI) is.
“AI simulates human intelligence through high-tech machine processes and computer systems.”
These AI machines or systems can perform tasks that mimic human intelligence and behavior. They also continuously improve themselves as they collect more data and information.
Artificial intelligence is constantly evolving and can take many different forms. Some forms include chatbots, AI assistants like Siri and Alexa, and recommendation engines that monitor your viewing habits on platforms like Netflix. Artificial intelligence is a vast concept made up of several distinct moving parts or subsets that are all often used in combination. Two of the primary AI subsets are as follows:
- Machine Learning
- Deep Learning
#1. Machine Learning
Machine learning is the concept that computer programs can learn and adapt to new data without human intervention. Machine learning is a complex algorithm or source code built into a computer. It allows it to identify data and form predictions based on said data.
Machine learning is helpful in the effort to process big data. It’s also valuable across various industries, from marketing and e-commerce to trading systems and banks.
#2. Deep Learning
Deep learning is a subset of AI, but more specifically, it’s a subset of machine learning. Deep learning networks are designed to mimic human brain behavior. It’s like a neural network, supporting the collection and analysis of large data sets, much like the human brain learns.
Deep learning is mainly focused on teaching computers to learn by example, another natural human process. Deep learning models are often recognized for their potential to achieve high accuracy. It is the key to significant tech advancements like self-driving cars and speech recognition software.
Machine learning and deep learning are two essential components of AI marketing. Let’s explore the concept more closely in the next section.
What is AI Marketing?
AI marketing produces customer insights to optimize marketing efforts, streamline spending, and improve the customer’s journey. One of the primary focal points of AI marketing is to understand customer behaviors. Many companies use it to predict their next moves, and better serve target audiences.
“AI marketing is ideal for startups looking to build relationships with the consumer base and grow their business.”
People like to feel that the brands they interact with care about and understand them. AI marketing tools can help you achieve that by personalizing content and improving engagement.
AI marketing pulls customer data from both on and offline sources. It uses machine learning to make predictions about customer engagement. This allows you to make better data-driven decisions when spending marketing dollars. Stop wasting money on projects that aren’t guaranteed to succeed.
5 Ways Artificial Intelligence Can Improve Marketing
You don’t have time for errors and unnecessary expenses when you’re a startup. Meanwhile, existing businesses seek to reduce waste and cut operational costs. Using AI marketing can help save time and money while minimizing human error.
There is a long list of benefits, but check out these five first:
#1. Tracking Marketing Analytics
Because AI is data-centric, gathering insights and tracking analytics can be advantageous. It can be hard to know what your customers want or what they respond to most if you’re just starting out. Historically, marketers would rely on surveys or assessments after purchases to gain insights into trends. However, AI marketing can make these evaluations in real-time.
This means you can understand your customers’ behavior before purchasing to target them more effectively. Getting to know your customers by gathering insights allows you to create more imaginative advertising and marketing campaigns bound to have higher success rates. AI marketing also yields more precise measurements for future projects.
“AI marketing also allows you to tap into predictive analytics to estimate revenues and predict customer behavior.”
Being able to predict customer behavior will enable you to target them better. For example, you may find that your customers only open email content on Mondays. Thus, you launch a marketing campaign that emails your customers every Monday morning.
#2. Improved Customer Experience
No matter what kind of business or startup you’re running, your customers are likely the most crucial piece of the puzzle. From the targeted content you send out to the level of customer service you offer, it’s essential to deliver in the customer experience department.
AI marketing allows for custom, specific targeting, which makes your customers feel important and can increase satisfaction rates dramatically. When customers are satisfied, they’re more likely to revisit you and recommend your services or products to their friends and family. This organically increases your retention, loyalty, and reach.
Chatbots are one of the most common forms of AI implemented on the consumer engagement front. These computer programs can simulate and process a human conversation. Chatbots allow you to offer 24/7 service to your customers with real-time responses. They’re even used at big companies like Spotify and Starbucks. AI lets customers use their fingerprints or face recognition to place orders, search the site using voice search features, or receive guidance from a virtual assistant.
#3. Faster, More Effective Decision Making
Implementing AI technology into your startup can be a significant time saver. It works alongside your human employees to assist and supplement their work. AI marketing strategies can also handle tedious tasks that bog down the day-to-day workflow.
“With AI marketing, you can save time when it comes to developing consumer-focused initiatives.”
For example, say you’re looking to create a new marketing program to target the younger side of your consumer base. Instead of spending hours brainstorming tactics in a meeting, you can rely on AI to pull insights from your customer data in a matter of seconds.
This customer data could tell you that the best place to reach younger consumers is on Instagram in the evening. From there, you can launch targeted marketing campaigns backed by data. Data-driven decision-making is more error-free than human decision-making. Avoid spending unnecessary funds on corrections. Use real-time data analytics.
#4. Content Curation
Several AI marketing tools help you scale up or enhance your content creation. They are designed to identify fresh and exciting content ideas for different audiences bound to be engaging. The content is backed by your startup’s specific data.
AI marketing tools can generate automated email responses or social media messages and suggest blog topic ideas. AI-generated content can provide a significant competitive advantage and increased marketing ROI.
#5. Personalization
Consumers like personalization. Whether it’s the ability to customize the color of a product they’re buying or how often they receive emails from you, they like adding their preferences to get what they want. AI marketing allows you to tailor content that each person who views your website sees with relevant product recommendations based on browsing history.
Hyper-personalization shows that you understand your customers and their needs individually. It also demonstrates consideration of their preferences and concerns. This is a great way to target specific audiences by referencing each consumer’s behaviors and preferences before sharing marketing materials.
Getting Started with AI Marketing
“There are many ways to use AI marketing, from customer service to social media and sales leads.”
With all these different use cases also come various AI marketing tools. That said, it’s a vast field and can feel daunting to get into, but it can be worth the effort with help from a data scientist. Here are a few steps you can take in the meantime:
#1. Evaluate Your Use Cases and Pick One
First, identify all your problems or areas you want to level up and think about how AI can help. Think about the daily repetitive tasks your marketing team does that take up a lot of time and resources. Once you identify all your use cases, pick one to focus on.
When working with AI marketing, it’s best to start small and build up from there. You won’t be able to solve all your problems immediately. Break them into actionable, repeatable steps to make them seem more manageable.
#2. Do Initial Research
Once you know what you’re focusing on and have your steps outlined, you can start researching AI marketing applications. You can do broad searches like “AI for social media” or “AI marketing software” just to see what’s out there.
During the research stage, you can also take your AI marketing questions to professionals like AI engineers and data scientists. Both are skilled enough in technology and data usage to help steer you in the right direction when laying the groundwork for your new AI marketing operation.
#3. Narrow Down All Possible Solutions
You’ll likely have a list of solutions and resources following your research. Now, it’s time to narrow down all the possible solutions. Check out articles and reviews of each one to see which option may be the best fit for your startup’s needs.
#4. Test Technology
At this point, you could narrow it down to three different AI marketing tools. Now it’s time to demo or test each one to see which is best. AI tools have specific applications, and you need to ensure you have the data required for it to work while providing the tool works how you expected it to.
Taking these AI marketing tools on a test run can help you determine which tool is best for your specific startup needs. By testing the software out there, you can also avoid wasting money on programs that don’t fit your needs.
#5. Develop an AI Marketing Strategy
After you’ve vetted some tools and found something you like, you can start looking into securing funds to roll out these new programs. Still, it’s crucial to develop an AI strategy.
Your AI strategy should be formally documented and vetted by your key stakeholders and outline how you will implement the new tools. This will also help streamline the implementation and help you understand how to lead your team.
“Experts can help you avoid common mishaps that could cause you to lose time and money.“
When building your AI marketing strategy, you can also refer to data scientists, artificial intelligence professionals, and other resources to answer any questions. Identify how to use AI in your startup effectively.
Conclusion
AI marketing uses artificial intelligence to collect data and consumer insights that can help your marketing team enhance its marketing efforts by creating efficient, targeted strategies backed by data.
One of the main focal points of AI marketing is to understand customer behaviors and predict their next moves. This helps streamline and improve your marketing efforts, which can be helpful if you’re a startup looking to build relationships with your consumer base and scale. There are several methods to use AI to improve your marketing efforts but talk to a data scientist to develop a tailored approach.
About the Author
Tiffany Perkins-Munn orchestrates aggressive strategies to identify objectives, expose patterns, and implement game-changing solutions with agility that transcends traditional marketing. As the Head of Data and Analytics for the innovative CDAO organization at J.P. Morgan Chase, her knack involves unraveling complex business problems through operational enhancements, augmented financials, and intuitive recruiting. After over two decades in the industry, she consistently forges robust relationships across the corporate spectrum, becoming one of the Top 10 Finalists in the Merrill Lynch Global Markets Innovation Program.
Dr. Perkins-Munn earned her Ph.D. in Social-Personality Psychology with an interdisciplinary focus on Advanced Quantitative Methods. Her insights are the subject of countless lectures on psychology, statistics, and real-world applications. As a published author, coursework developer, and Dissertation Committee Chair, Tiffany still finds time for family and hobbies. Her non-linear career path has given her an exclusive skill set that is virtually impossible to reproduce in another individual.
One Response
Hi Tiffany,
ML and AI have also been helped remove some human bottlenecks for my team and I. 3 or 4 years ago, the analysis we could do was somewhat limited by the amount of ideas we were able to generate based on our limited understanding, and by the speed at which we could construct and test various hypothesis and visualizations. In the past couple of years, the ML techniques have helped ideate much faster than what we had been able to although this automation of ideation needs some oversight and human expertise to add explainability and logic check.
An additional area I believe offers tremendous potential is being able to integrate and analyze end-to-end data across various career stages to optimize the products and benefits for the entirety of consumer’s life. In addition to using deep learning to match the customer needs and products at different career stages (early career involving accessing and building credit, mid career where we start to save and build wealth, late career needs such as tax optimization and growing wealth, and retirement stage involving estate planning and annuities etc.), optimizing for the full financial life cycle could create more customer benefits and brand experience benefits.