Artificial intelligence (AI) is all the rage today in the marketing world. In fact, many marketers believe that they will be left behind if they don’t adopt AI quick enough. According to a recent Mailchimp survey, 50% of marketers believe inadequate AI adoption is holding them back from achieving their goals while 88% believe their organization must increase its use of automation and AI to meet customer expectations and stay competitive.
With AI opening up many new dynamic marketing use cases, such as enhancing MarTech optimization with AI-driven insights and generating assets from scratch, it can be incredibly tempting to adopt the technology as quick as possible, but you could be setting yourself up for inefficiencies down the road if you implement it without a plan. In this article, we’ll examine AI-adoption best practices that ensure you are implementing the tech in accordance with your marketing strategy and goals.
Start with your Goals- Understand the Customer Experience You Wish to Create
As we discussed in our previous article, How to Craft a Successful Experience-Focused Marketing Strategy, the key to understanding how AI could accelerate the accomplishment of your goals is to understand the customer experience your audience expects from your brand.
To deliver an experience that appeals to your customers’ preferences, you must understand:
How your customers prefer to interact with brands. Short-form video content and email continues to be popular marketing channels with consumers, but they expect these communications to be hyper-personalized and relevant to their interests.
How customers want to be communicated with. More than ever, customers want companies to be authentic and trustworthy. It’s critical to speak to your audiences’ core values.
And if you don’t have answers to these questions yet, sometimes it’s worth just asking your audience directly via a survey. Ask them questions, such as:
What type of content do you expect from our brand?
What types of offers/promotions would you like to see from us in the future?
What do you value in some of your favorite brands?
These insights will help you form your vision of the ideal customer experience and provide a blueprint of what tech you’ll need to deliver on that vision.
Build a Solid Data Foundation as AI is Only as Accurate as the Data Utilized to Train It
AI models are only as accurate as the data sets it’s analyzing and utilizing to devise its insights. That’s why, when implementing AI functionality throughout your MarTech stack, you must establish a consistent data architecture that is going to enable you to deliver your envisioned customer experience.
To get your data strategy ready for AI, consider:
Developing a Use-Case Mentality
our data doesn’t have to be perfect to begin utilizing AI. Start collecting and using data that is going to have the largest impact on your productivity and user experience. Perhaps you will discover the easiest and quickest way to increase customer loyalty is to create a personalized birthday journey. If so, analyze what data you’ll need to implement it, such as your customers’ birth dates, map out where that data is stored, and consolidate it in one place where it can be actionable throughout your MarTech platform.
Create a Single Source of Truth for Customer Data
Data that is siloed is simply unactionable from an AI-standpoint, so it’s critical to consolidate your customer data in one place through a data lake/customer data platform (CDP). These empower your organization to break down these silos by storing your most operational-critical data in one platform.
CDPs not only centralize your customer data; they also match known identifiers, such as email address, phone numbers, and company names, with anonymous data. This means that you can track how your contacts are interacting with your brand and build customer journeys from that data. And having this data empowers your AI model to start learning and find patterns within your data, so it can begin to provide dynamic recommendations on how to implement new process improvements.
Merge and Clean Datasets
Preferably before your team integrates all your data in one platform, you should map out a desirable data structure, so you can begin to merge datasets accurately based on their relationship with one another. When starting to integrate your desperate data sources, you’ll start to see where your data is either inaccurate or missing. Inaccurate or missing data can lead to your AI model making more error-prone recommendations, so the more accurate you can get your data, the better.
When crafting your underlying data architecture, consider consolidating and integrating fields based on specific use-cases. The more organized you can be, the better off you’ll be, but remember data prep is not a one-and-done process. When you begin to integrate data, you’ll likely be exposed to a variety of issues, such as missing values, incorrect values, outliers, redundant information, etc. For this reason, data preparation is incremental, and often the job is never 100% finished. Work with key decision makers to ensure your data is as accurate as possible, but don’t be paralyzed by your data. Start small and increment from there.
Continually Train Your AI Model with an Experience-Focused Mindset
Implementing AI tools is just one part of the journey; to gain the full benefits of AI, you must commit to continually training your model. MarTech platforms, such as Salesforce Marketing Cloud, is empowering organizations to customize their own internal AI models with new features, such as Prompt Builder. Prompt Builder empowers your organization to customize your AI workflow, so you can personalize and optimize your marketing operations beyond what general models provide.
With it, you can create your own prompt templates that use protected proprietary data to customize the outputs your MarTech users get. In an email prompt template demo, they show off that you can customize the output of certain prompts by configuring the style, sender, recipient, length, and even the AI model, giving you the choice of utilizing multiple 3rd party language models. This way, you can continually refine what outputs your AI model provides to help your organization accelerate the delivery of the customer experience you envision.
Before Releasing New AI Tools Throughout Your Organization, Consider These Best Practices
AI has so many amazing use cases, but that doesn’t mean you should rush into utilizing its capabilities organization-wide. Before rolling out new AI tools internally, consider these best practices:
Continue to Test, Iterate, and Refine
You don’t know the outputs your AI model is going to provide until you test it. Before generating new content or blindly trusting AI-powered recommendations, continue to prompt your model to understand its strengths and weaknesses. Continually iterate and refine not only your prompts, but also your data to ensure it provides the productivity increases you are hoping for.
Just Because You Could Automate Doesn’t Mean You Always Should
Sometimes it pays to have a more manual, human touch within some aspects of your marketing operations. Before implementing new automations for automation-sake, understand how the new functionality will impact your productivity, how much it will be utilized throughout your team, and most importantly, how your customers may potentially respond to the outcomes of those automations. If it’s not going to further enhance the customer experience you are delivering, it may not be worth implementing.
Don’t Adopt AI on Your Own; Lean on Data and AI-Experts to Implement It Right the First Time Around
AI is a long game, one that requires continual experimentation, testing, and refinement. But when successfully implemented, it can completely revolutionize your productivity and customer experience, empowering your organization to hyper-personalize every customer’s experience and focus on strategic initiatives that grow the business.
With Lev’s energetic, empathetic, and growth-driven teams, we can help you get the most out of your MarTech platform by:
Crafting a vision and AI roadmap that will increase your productivity and accelerate the achievement of your goals
Establishing a data foundation that will empower fully realized, hyper-personalized customer experiences
Continually supporting your marketing operations and campaigns as a true extension of your team
Looking for more AI best practice advice you can incorporate to enhance your marketing operations? Check out our other AI marketing related content.
Ready to enhance your personalization strategy with AI? Contact us to explore how we can help you take your customer experience to the next level!