Customer data: can’t understand it, can’t afford NOT to understand it. That’s how I used to feel about data, and I thought throwing AI into the mix would make the confusion even worse. I’m happy to report just how wrong I was.
Artificial intelligence (AI) makes collecting, interpreting, and acting on customer data far easier than traditional data tools. There are also countless products on the market to help make this process as effective and fast as possible.
Customer data platforms have been a resource for companies of all sizes for a long time, and AI has added a level of operational ease that will assist even the most numbers-adverse individual (raises hand) in confidently making data-backed decisions. Let’s look at what unique opportunities AI brings to the customer data conversation, and which platforms are the most popular (and why).
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What Is an AI Customer Data Platform?
An AI customer data platform (CDP) is software that gathers, organizes, unifies, and interprets customer data using artificial intelligence. It offers an unparalleled understanding of your customers’ first-party data, aiding in decision-making in every department.
Data collection must be done ethically to remain lawful and have adequate privacy compliance, and the data infrastructure must be secure to avoid breaches and outages.
How Does an AI Customer Data Platform Work?
The first step in using an AI CDP is setting it up to collect data. Your chosen platform will automatically sync with your website, email, CRM, etc., to unify diverse data sources into a single source of truth.
Then, a variety of AI functions, such as natural language processing (NLP), machine learning, and predictive analytics, will process your data.
Once your data is processed, you’re provided with actionable recommendations that advance your sales, marketing, and advertising efforts.
Benefits of an AI Customer Data Platform
While you can choose a CDP that doesn’t have an AI focus, I think there are endless applications of artificial intelligence worth considering. Here are the specific benefits you can expect when using an AI CDP.
Future-Facing Data Process
The data landscape is changing — rapidly. Cookies are dead. Regulations are changing. AI is being thrown around like confetti (and not always responsibly).
Many data platforms are working AI into their infrastructure, but not every platform is monitoring the changes on a larger scale. This can lead to important details being missed, for example not adhering to new regulations like the .
What if you’re not keeping up with the times? Your platform could still be relying on cookies, which have gone stale.
Statistic: When Google announced its phase-out of website cookies, 41% of marketers said their biggest challenge would be their inability to track the right data.
Data platforms that aren’t aggressively surveying and responding to changing regulations won’t be keeping up with the times for long. Small business owners aren’t data scientists; they can’t be expected to run their businesses, monitor the data landscape, and react accordingly.
This is why I think it’s beneficial to use CDPs that are leaders in the AI space, who will monitor AI’s evolution and adapt.
Get predictive insights.
AI can provide deeper predictive analytics than traditional data software. This predictive modeling turns a pile of numbers into actionable insights that can offer more personalized customer experiences.
Example: AI CDP platform generates a rating for each customer based on their likelihood of converting, which updates automatically as more data is collected. This creates predictive segments, making highly targeted campaigns easy to develop and employ.
Improve customer experience.
Data isn’t only used by sales and marketing to help woo new customers — existing customers benefit greatly from it as well.
Customers’ information being gathered and processed by AI helps your customer service team deliver faster, more relevant support. Customer profiles contain more information than just purchase history and first-party data. AI platforms gather communication across channels and provide unique and actionable insights for service reps.
I know this can make some users nervous, but I welcome this because I’ve seen firsthand how AI is improving customer service for platforms that I use. And I’m not the only one.
AI in the wild: The next time you’re engaging with customer services, look critically at the conversation and see if you can notice past communications being accounted for.
Leverage machine learning.
Machine learning is a very powerful function of AI that enables software to read your data, learn from it, and make predictive insights. While similar results can come from data analysis tools, machine learning does this automatically without needing to be programmed. In marketing and sales, it enables data-driven decision making.
Pro tip: I suggest you start using machine learning with a focused scope to improve accuracy. The vast amounts of data will naturally lead to a lot of unnecessary data, and starting with a wide focus won’t get the same results.
Personalize customer experiences.
Recommender system algorithms changed the online experience radically — these algorithms took millions of social media posts and identified which ones you would like most. It offered a tailored experience to each user, which can now be taken to even further heights with AI-powered insights into customer interests. This can advance your sales, customer service, and marketing efforts.
Statistic: A study by Accenture discovered that 91% of consumers reported being more likely to shop with brands that remember, recognize, and provide relevant recommendations and offers.
For example, your data platform can leverage behavioral data to identify customers at a specific stage of the customer journey. Then, run targeted ads to that unique group. You can further the financial impact of personalization by only targeting high-value customers with a high customer lifetime value.
Pitfalls to Avoid
We don’t need to dwell too long on the downsides of using an AI CDP, but I think it’s worth touching on briefly. You’re not ready for an AI CDP if the following statements describe you:
- Lack of a plan. Gathering data without knowing how to use it is like setting sail without a destination.
- No team training. It’s a miscalculation to assume that your team understands AI and how it’s working to help them (not replace them).
- Lackadaisical approach to AI ethics. Ignoring AI ethics puts you on the fast track to losing customer trust and sinking below industry standards.
Pro tip: Understanding your KPIs is essential for leveraging customer data efficiently. Use our free to help.
With the benefits and pitfalls understood, let’s get up close and personal with some of the most-recommended platforms on the market.
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Examples of Some AI CDPs I Recommend
I’ve reviewed five of the most popular AI CDPs out there. Here’s a summary of their key features, stand-out qualities, and a summary of what have to say.
1.
Twilio Segment (previously just Segment) has a heavy emphasis on using data and improving customer satisfaction and experience. I like the focus on activating customer data using pre-built tools in your dashboard. Key features include a unified view of customer data, predictive insights, and 400+ advanced integrations.
A powerful element is the , which tackles data cleansing. You can also explore features that are specific to individual departments, like data, marketing, and products. When you set up your account, you can select which department you work in. Then, you get a specific guided onboarding process. I thought this was a great touch that helped reduce overwhelm.
Price: followed by company-specific pricing.
Reviews: Online reviewers like the robust integration library and real-time data processing but complain about the price.
What I like: Twilio Segment has some catchy copywriting on its homepage: “Know each individual like they are your only customer.” This is an easy thing to say, but they followed through. I saw firsthand the personalized customer experience. On my first visit, the AI chatbot provided this message:
Then, on my second visit, it customized the chatbot based on my time already spent on their website:
This type of data usage felt natural and personal; more than anything, it got my attention.
2.
The Adobe Experience Platform is a powerful AI-fueled CDP that funnels many data points into one unified profile that updates in real time, without relying on third-party cookies. It integrates seamlessly with other Adobe products as well as major platforms you may use, like Salesforce, Paypal, Amazon, etc.
Data is pulled from both internal and external data sources, creating a holistic view of your customers at a glance. Not only is your customer data gathered for your review, but you can also have a conversation about it with Adobe’s AI system, called Adobe Sensei. For example, you can ask, “What’s my top audience this quarter?” and get immediate answers pulled from your sea of company data. I think this feature is amazing!
Price: Tailored pricing for each client.
Reviews: like the platform for both data activation and governance but cite steep learning curves as a drawback.
What I like: The ease of creating a customer or audience segment. Customer segmentation allows you to speak directly to specific groups within your customer base. Sometimes, these groups are easy to identify, such as customers who purchased a certain product within a set timeframe. Other times, AI can help you find much more nuanced groups, such as customers who are disengaged with your content and most likely not renew their subscription.
3.
Salesforce Customer 360 is technically a customer relationship manager (CRM), but it’s a large, umbrella software that also fulfills the role of an AI CDP. Salesforce summarizes their platform capabilities this way: AI + Data + CRM + Trust. The Salesforce name is synonymous with trust. The company is a longtime pillar of the data world, and they’re now leading the way with how AI and data are integrated.
Price: followed by company-specific pricing.
Reviews: like the flexibility and scalability of the product, but the learning curve is cited as a common complaint.
What I like: I used Salesforce at my first salaried job out of college, and I remember how overwhelming I found it. In hindsight, I think that there’s no way for a software this enormous to feel approachable at first use. Salesforce invites you to set up a free with their team so they can discuss their software’s application in your business, which will help offer you a map through this massive platform.
4.
ActionIQ is a more contemporary AI-fueled data platform with advanced data architecture options. It’s a much younger platform than Adobe and Salesforce — Adobe is old enough to be ActionIQ’s parent. The advantage is that it feels more modern. As a user, I also feel like there’s a focus on adoption. Instead of reading endless info on product features, you can look at specifics for your different departments: marketing, information technology teams, data teams, and advertising.
Price: Tailored pricing for each client.
Reviews: ActionIQ has fewer reviews than other platforms, but customers shared that they liked the customer support and expertise of the team. Some reviewers also mention that there are kinks still being worked out.
What I like: Combine the comfortable user experience with its customer support, and this platform is very approachable for small businesses. I felt seen (and slightly called out) when they described their platform as having a “marketer-friendly interface.” This wasn’t just a line of sales copy — looking at the user interface, I feel like it rings true.
5.
Blueshift describes itself as a three-piece combo: a CDP, an AI-based decision aid, and a cross-channel marketing platform. It focuses on data unification across channels, then leveraging AI decision-making to save time and improve efficiency. Customer reviews cite the ease of use and customer support as the biggest pros. Blueshift gets credit for being the only AI CDP on this list with a free plan.
Price: Free and $750+ per month.
Reviews: Online reviewers cited the automation and onboarding process as pros, while others mentioned some complexity when implementing.
What I like: The volume of data available is incomprehensible to me, so I like Blueshift’s emphasis on data activation. It feels to me like this platform was designed with the entire team in mind, which helps with software adoption and avoiding data silos. The focus on the customer journey, paired with the built-in generative AI features, paints a really exciting picture of what data can mean for your marketing efforts.
Detangling Your Data
It shouldn’t take a data science team to use an AI CDP. Thankfully, there are enough products on the market for each business to find what suits them best. I hope these statistics, tips, and product recommendations helped demystify the process of inviting AI into your data management process.
The presence of AI everywhere makes it feel like you’re living in the future, doesn’t it? To quote Spock, “Data is the key to everything.” Boldly take your customer data where no one has gone before.
An Introduction to Data Analytics
Unlock the power of data and transform your business with 黑料吃瓜网's comprehensive guide to data analytics.
- Fundamentals of data analytics
- Different types of data analytics
- Data visualization
- And more!
Download Free
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