Does marketing AI feel too buzzwordy to you? You've probably read about it on blogs, seen its hashtags trending on Twitter, noticed it being bandied about at conferences. But despite all this apparent popularity, do you still wonder how necessary Artificial Intelligence really is for marketers?
Implementing an AI strategy is becoming a standard for brands, online retailers and agencies. According to eMarketer, 70% of business leaders expect marketing AI to be critical for the future success of their businesses. AI brings data-rich insights and time-saving assistance to marketers, and those who aren’t already using it need to embrace it now.
In fact, of marketing AI’s early adopters, 69% say they’ve seen moderate to significant value as a direct result of its implementation:
This is according to a McKinsey & Company study, which also states that businesses’ greatest struggle with implementing AI is a lack of strategy for figuring out how to use it.
This study shows that not only is using AI critical for marketers, but creating a solid strategy for selecting, implementing and maintaining the right AI solution is critical, too. Since AI is always changing and new features are being developed continuously, marketers also need to be aware of its updates after implementation, so they can fully leverage them.
Choosing the right capabilities for your team might seem confusing, so here are some ways to get started quickly and easily. Whether you’re a specialized and technically savvy marketer, a jack-of-all-trades at a small business, or someone who has been tasked with finding the perfect AI solution for your company, these 10 steps will help you think critically and make the best choice.
Understand What Marketing AI Really Is
First, a quick definition:
“Artificial intelligence marketing (AI Marketing) is a method of leveraging customer data and AI concepts like machine learning to anticipate your customer’s next move and improve the customer journey.”
Before businesses can start implementing marketing AI solutions, it’s best to understand AI’s parts and pieces, and how they make work faster, easier and smarter. Below are explanations of AI’s components, based off of definitions from The Brookings Institution:
- Artificial intelligence is a collection of machines that respond to stimulation in ways similar to how a human would. It can make decisions that normally require a human level of expertise.
- Machine learning is a technology that analyzes vast amounts of data in order to discover trends and glean insights. It provides AI systems with the ability to automatically learn and improve.
- Data science is the study of where information originates, what it means and how it can be interpreted.
Generally, all three of these technologies go hand-in-hand. They give marketers the ability to understand vast amounts of data to inform their creative and strategic decision making.
Dive Deeper:
- AI Trends in Marketing for 2019 [Infographic]
- The Future of SEO: How AI and Machine Learning Will Impact Content
- How Artificial Intelligence Is Revolutionizing the Digital Marketing Sphere
See What Your Competitors Are Doing
Do a quick search to see what your competitors are up to. You may be able to find out what solutions they’re already using, and how well those solutions are working for them. Take a look at their blogs and social channels to see if there are any mentions of AI solutions that could benefit you.
Some ways that brands are using AI marketing:
- Chatbots
- AI-enhanced PPC advertising – AI-powered systems can help advertisers test out more ad platforms and optimize targeting.
- Personalized website – By analyzing hundreds of data points about a single user, AI can display the best-fitting offers and content.
- AI-powered content creation – From fashion to health to insurance, intelligent chatbots are providing borderline magic customer support.
- Personalized content in email – Algorithms can map a subscriber’s website experience and email browsing data to understand all the individual’s interactions with your content and create one-on-one personalized emails.
- Churn prediction – Machine-learning algorithms can help identify disengaged customer segments that are about to churn or leave for a competitor.
- Automated image recognition – Amazon, Facebook and Pinterest use AI-powered image recognition to identify people and objects from images and videos.
By knowing how your competitors’ solutions are working out for them, you’ll have an edge on what to look out for and how to catch up.
Learn More: How to Perform Marketing Competitor Analysis (+ 6 Best Tools Comparison)
Define What You Expect from Your Marketing AI
Think beyond the buzzword and meditate on where your marketing is struggling the most. Identify what areas of your business will benefit highly from data analysis and AI’s insights, and visualize the performance you’d like to see. When you determine what you need AI to do, you will be able to narrow down the search field.
For example, if you want to improve creative performance for digital ads, research AI solutions that will help your team identify top-performing creatives, so you can maximize results.
- Smartly.io is one such tool that allows you to create ads in different formats.The cloud-based automation tool cuts down the manual effort in running and editing paid campaigns and guides marketers to test and improve campaigns.
Alternatively, if you’re looking to discover more about your customers, look for an AI solution that will analyze their data and provide behavioral insights to you.
- Xinoah is an AI-driven tool that provides product and media recommenders, pricing solutions and demand predictors. It predicts customer behavior to help businesses provide a better customer experience.
Learn more about AI solutions in this article: 20 AI Tools to Scale Your Marketing and Improve Productivity
Understand Your Solution’s Data
Any AI solution with clout will be able to detail how their software works and where its getting its information from. Once you have determined a few solutions that could benefit your company, do some digging into their websites.
Take a look at platform descriptions and blog posts. AI companies who have true, efficient artificial intelligence solutions will describe how it works so that you know it’s not just a bunch of people in an office pretending to be AI.
Learn the details of where their data is coming from, how much data is available, and how frequently their AI is able to analyze it. True AI should be able to do this daily, so it can give you the most relevant recommendations, based off of what the data is indicating at any given time.
Dive Deeper:
- The Future of Data Science & Predictive Modeling
- How Artificial Intelligence Is Transforming Influencer Marketing
- How to Use Big Data Analytics to Grow Your Marketing ROI
- How To Write Data-Driven Posts
Research Case Studies
This point goes hand-in-hand with the previous one. Read through the case studies made available on your AI solution’s website, often found under “resources“:
Pay special attention to the following:
- Are their vertices or customers similar to your company?
- Were the customers in their case studies trying AI with the hopes of achieving similar goals as you?
- Determine what their success metrics are, and imagine your company having similar metrics. Would this look like success to you?
- Are there any customer quotes in their case studies? If so, what did they say and, specifically, what elements of the AI did they praise?
Ask if AI Solves Your Business Problems
Break away from the buzzword and think critically about what you really need. Just because everyone else is hopping onto the AI bandwagon doesn't necessarily mean that your company needs to right now.
After you’ve established clear goals and done your research on solutions and competitors, you should start to get an idea of whether or not AI is right for you. Sometimes, it’s not – or not yet – and that’s ok. Don't feel that you've wasted the effort doing the research that you have; it will come in handy when the perfect AI solution for your business is created.
Dive Deeper:
- 22 Digital Marketing Trends You Can’t Ignore Going Into 2020
- Content Marketing and Artificial Intelligence: A Perfect Marriage?
- How Machine Learning Is Transforming Content Marketing
Draft Your AI Ethics Statement
Ethics in AI is a hot topic these days, with publishers like The Wall Street Journal and Harvard Business Review discussing how to foster principled software development (one of the reasons is because of a tendency for racial and gender biases in AI hiring practices).
When you’re sure you’ve found the perfect marketing AI for your company, you’ll need to think about how to ensure that you use it ethically.
When getting started with implementation, write out how AI will make your company better, due to its transparency and ethical approach to data analysis. If you publish your ethics statement for customers to read, it will build trust in your business and credibility in using cutting-edge technologies. If you decide to keep your ethics statement private, use it to hold yourself and your team accountable so that your work remains fair and transparent.
Here are a couple examples of companies' AI ethics statements:
Understand the Risks…and Opportunities!
With every marketing AI solution comes a few risks to consider:
- Your chosen solution may be expensive and you don’t yet have an AI budget. Some AI solutions pay for themselves because they offer cost-saving insights. Keep this in mind when shopping around.
- There may be a learning curve for your employees when using AI. Power through it! AI is new, and everyone who chooses to implement it has to learn, too. Everyone will be able to adapt here.
- People may feel threatened by AI and try to hold out on using it. The fear that AI will steal jobs is pretty wide-spread. Contrary to this popular belief, experts such as Forbes say that AI will take away menial tasks, not jobs. In fact, according to McKinsey, 77% of companies expect no change in their workforce when AI is implemented, and 17% expect workforces to grow as a direct result of AI.
Along with these risks are loads of opportunities, such as:
- Understanding your customers better, and determining the best messages, mediums and creative opportunities for reaching them.
- Discovering the best ways to save money on marketing campaigns and advertisements by learning how to optimize ads and spend.
- Freeing up time on your calendar. Because many marketing AI solutions automate tasks, your team could save hours every week. This can give you more time to focus on creative and strategy work that would further benefit your business.
By thinking carefully through the risks of AI adoption and choosing the right solution for your brand, marketers will be able to find more opportunities than risks.
Find Partners Who Will Pilot with You
Before committing yourself to an AI solution that might work, see if you can pilot it first. As mentioned before, there is no singular AI solution that fits everyone, so you’ll want to try it before you buy it. Many solutions will let you test drive for free.
During your pilot period, monitor your metrics. Track how well the AI you’re piloting is helping you reach the goals you determined, and keep in mind that it might discover new insights for you, too. Its data analysis capabilities could lead you to unexpected results that are as beneficial as the original goals you set. As with any type of testing, keep an open mind.
If you complete a pilot without staggering results, that’s ok! There is likely another solution out there that will help you. Research will help you find it.
Dive Deeper:
- The Effects of Natural Language Processing (NLP) on Digital Marketing
- Making Data-Driven Decisions for Better Website UX
- How AI Can Help Both Recruiters and Job Candidates
- How to Use Predictive Analytics for Better Marketing Performance
Include AI in Your Strategy from Here On
Now that the machine learning revolution has begun, there's no going back. Like any new and useful software solution, AI will only get better as time goes on. Whether you decide to implement it into your work today or wait it out until the next quarter, it is critical to start accounting for it in your marketing strategy now.
After implementing your AI solution, do an in-depth analysis of its usage and success metrics every quarter. Think about the following:
- Revisit the goals you set when you introduced AI into your marketing. Determine if you met those goals, failed to meet them, or exceeded them. You may need to adjust your goals for the next quarter, based on performance.
- If your chosen AI solution didn’t help you meet your goals, think about why. Did you set your sights too high? Could your software be a bad fit? By analyzing its weak points, you’ll be able to adjust your strategy for the upcoming quarter or find a better software.
- Honestly look at how frequently you’re using your AI. If you’re disengaged, would using it actually help you meet your success metrics? What opportunities did you miss by failing to engage with AI?
- Did you use your AI solution differently than you expected? If so, think about what you learned from it, and if its actual use benefitted you.
- Review the new features your AI solution has released. Developers are constantly working to create the latest and greatest innovations for marketers. Be sure to read update emails from your software provider to see if they’ve created anything new that could benefit your business. If you find new and beneficial features, start using them and include them in your upcoming strategy.
Marketing AI Requires Strategy and Perseverance
43% of AI adopters say that their largest hurdle in implementation is a lack of clear strategy. Following the steps above will alleviate this hurdle in the long run.
Thinking strategically about your business’ problems, needs and goals will assist you in making the best choices when implementing AI for marketing. Research and experiment with different solutions up front, so you end up purchasing the marketing AI tool that delivers exactly what your team needs.
Once you find the solution that seems to be the perfect fit, regularly evaluate it. Ensure that your team is engaged and frequently monitor and adjust your success metrics so that you know you’re getting the most out of your software.
The post 10 Easy Ways to Get Started with Marketing AI (Artificial Intelligence) appeared first on Single Grain.
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