Artificial intelligence (AI) has rapidly advanced throughout 2023, leaving many marketers scrambling to figure out how to best take advantage of the technology. Earlier in the year, many companies were not prepared with many not even having a usage policy. But now a lot of organizations are adopting AI, and some marketers are worried about getting left behind. Salesforce is continuing to unveil a variety of generative AI suites as well as great improvements to Einstein with their announcement of the Einstein 1 Platform.
As we discussed in our recent article, “Getting Your Marketing Strategy Ready for AI,” it can be incredibly tempting to adopt the technology quickly to ensure you aren’t left behind, but you could be setting yourself up for inefficiencies down the road if it’s implemented without a plan. AI is only as effective as the data it is trained upon. You must have quality data, or your AI models could make inaccurate assumptions, leading to it confabulating facts and recommendations. Before integrating generative AI into your MarTech suite, it’s critical to ensure your data foundation is ready for the tech.
In this article, we’ll discuss how you can build a solid data foundation for your AI models, so you can use the technology to improve your brand experience.
The Importance of Clean Data
One of the largest challenges marketers have always faced is getting access to up-to-date, accurate customer insights. A solution we’ve seen explored is establishing a customer data platform (CDP) to integrate all your important customer data into a singular platform. These platforms, when implemented correctly, can help you create comprehensive customer profiles and bundle certain data attributes in a way where they can be used to personalize email communications and build specialized customer segments. For more information on how to properly implement a CDP, consider reading the following articles:
- How B2B Customer Experiences Are Becoming Technology-Led
- Determining the Next Steps of Your Digital Transformation Journey
- What Does a Marketer’s Digital Transformation Look Like?
- How to Overcome Your MarTech's Limitations
Since CDPs do empower you to integrate your customer data together in one platform, it can be tempting to dump all your data into it, use AI models to analyze it, and see what they spit out, but can you truly trust those insights blindly? To ensure your AI models are as accurate as possible, you must understand the data you have on hand as well as your data gaps.
Christy Glesing, Sr. Marketing Consultant at Lev, said in our most recent Level Up podcast episode that “In order to know what data you need, you really need to lay out your whole customer life cycle. What are you doing throughout that life cycle? How are you communicating? What is each customer's experience? By examining the customer lifecycle, you’ll see what data you need, which can help you start to understand how to fill those gaps. And then with a tool like a CDP, you can bring it all together and see the data for yourself. So, it's iterative, but I would always start with the customer experience, I guess, the whole lifecycle.”
Combing through your data and slowly adding it to your CDP helps you narrow your focus to specific use cases, avoid data paralysis, and customize the customer experience in a timelier fashion.
Best Practices for Building Out Your Data Collection Strategy
It’s easy to get your mind wrapped up in all the amazing benefits AI could provide marketers, such as enhancing MarTech optimization with AI-driven insights and generating assets from scratch but remember to analyze how any new advancement to your MarTech stack could affect your customers. They should be at the forefront of any decision you make.
This easily applies to your data foundation as well because, as marketers, we are always building the plane as we’re flying it. We’re still responsible for ensuring we are meeting our customers’ needs through our campaigns and content. In the same way, before you implement AI into your tech stack, you don’t need all your data consolidated at the beginning. Don’t feel like you need to boil the ocean. Focus on getting the minimum amount of data you need that will empower you to make the largest impact on the customer experience.
Data Integration Best Practices
- Before attempting to integrate your data into one source, consider your overall marketing strategy and objectives. Having a solid understanding of the customer experience you’re looking to design will inform you of the data you’ll need to offer that degree of personalization.
- Collaborate with all relevant stakeholders. Realistically, multiple teams are likely working out of the same CRM. How different platforms use data and collect data is going to look different. You must consider what data is necessary for each team and how the pass off between each team affects the customer experience.
- Don’t just dump your data into one place without auditing. It’s easier to clean data up before it’s integrated together than after.
- Adopt a use-case mindset. Before integrating data points together, consider how the data will be utilized within the backend. Scope creep is one of the biggest challenges and roadblocks that can arise when designing new personalization use cases, and it's easy to bite off more than you can chew. Start small and work your way up to designing the backend needed to provide that omnichannel customer experience.
The Light at the End of the Tunnel: How AI Can Improve Your Marketing Operations
Now that you have your data in place, you can finally take advantage of the many capabilities AI provides. So, once you have your data infrastructure and AI models in place, what type of operational improvements can you expect?
Benefits of AI Integrated within your MarTech Stack
- More efficient content creation: As we’ve discussed in our previous article, AI: How It’s Augmenting Marketing as We Know it, generative AI is empowering marketers to generate new images and copywriting. While generative AI in its current state may not be replacing copywriters, it can be incredibly helpful with brainstorming or creating a more effective starting point for writing.
- Enhance MarTech Optimization Through Natural Language Processing. MarTech suites are releasing tools that empower marketers with NLP-powered chatbots that answer any questions one may have about process optimizations and campaign performance. And with Salesforce’s upcoming Prompt Studio, for example, marketers will be easily able to customize specific prompts to continually refine the results Einstein Copilot provides.
- Greater Decision Making with AI-Driven Insights. AI-calculated insights have the potential to change how marketers’ segment and engage with customers. As part of Salesforce’s Marketing GPT offering, their Segment Creation tool promises to give marketers the ability to create segments with AI-driven recommendations.
Unsure Where to Start? Consider Bringing in a Trusted Partner
When it comes to designing a clean data architecture and strategy, sometimes it pays to bring in data experts. Clean data is key for delivering deeply personal, orchestrated omnichannel experiences. And when your team is just treading water when it comes to day-to-day strategy execution, it sometimes can seem impossible to improve your data infrastructure or implement new tools and processes.
We have had numerous conversations with marketers who are overwhelmed with performing a deep data cleanse and infrastructure overhaul, but with a trusted data partner, the ask becomes much more manageable. For example, at Lev, our dedicated team of strategic and technical subject matter experts can help you realize your future, idealistic customer experience. We begin every data engagement by:
- Understanding your strategy and goals
- Identifying the minimum yet most robust sets of data required to maximize effectiveness, reduce time to value, and improve business visibility
- Structuring your data architecture in a way that ensures data is accurate and leverageable
- Activating your data throughout your MarTech stack and ensure it works to provide the specific use cases you need to achieve your goals and improve the customer experience
- Training your team on how to accelerate value creation across tools
This way, you can focus on ensuring your day-to-day marketing operations are excellently executed while remaining confident that you are improving your capabilities for the future.
Enhance Your Marketing Operations with Trusted AI Experts
You don’t have to embrace this AI frontier alone. Reach out to us today to discover how we can help you bring your strategy, data, and technology together in a way that breaks down informational silos that are preventing you from crafting dynamic, personalized experiences. Also, consider visiting our AI marketing hub for further insight on how AI can help you revolutionize your brand experience.