Every marketer understands the importance of collecting and utilizing customer data to streamline your customer relationship management, your marketing efforts, and to increase conversions. But before you can put all of your customer data to work, you need to choose the right tools for the job. 

Because it can be challenging to make sense of all the customer data collected and activate it in meaningful ways. You likely have multiple channels and a myriad of data sources that need to be consolidated and organized into understandable unified customer profiles. And that’s just the beginning — leveraging your customer data to execute marketing campaigns that drive increased customer lifetime value is just as important.

That’s why a customer data platform (CDP) and marketing automation are such vital tools for your marketing tech stack. And to make your efforts shine across every stage of the customer journey, you need a solution that brings both of these tools together.

Let’s see what a CDP and marketing automation tool can do for your business, and dig into why it’s important to get a solution that combines the best of both worlds.

What Is a Customer Data Platform?

A customer data platform is a marketing technology that collects first-party customer data from various sources, such as online and offline interactions, and combines them into a single customer view. This view provides a unified customer profile, and gives you insights into customer behavior that were previously unattainable.

Consolidating all of your customer data is a CDP’s primary function. A CDP’s ability to manage customer data will ultimately give your marketing team key insights and data points needed to execute personalized marketing campaigns that drive revenue.

Once your CDP completes its data management responsibilities, it integrates all your customer information into a single unified database, it  builds a complete picture of your customers on an individual level.  A CDP makes all your data make sense, allowing you to harness a complete view of your customers to build effective and personalized marketing campaigns.

With a CDP, marketers can collect, segment, and activate their customer data, which allows for more accurate targeting, improved engagement, and increased revenue.

The Benefits of a Customer Data Platform

Some of the key benefits of incorporating  a CDP into your marketing strategy include:

Unified Data

A CDP creates a comprehensive view of the customer, which allows marketers to know what customers are doing across all marketing channels. This means that marketers can align their messaging with specific touchpoints in the customer journey, ensuring a more targeted approach for meaningful engagement.

Improved Customer Experience

A CDP helps marketers create relevant and personalized experiences at scale for their customers during  every stage of their buying journey. This includes personalized messaging, content, and recommendations that are tailored to the customer’s interests and preferences.

Improved ROI

A CDP can help increase ROI by providing marketers with a more accurate and in-depth understanding of their customers. With this valuable information, marketers can optimize their campaigns and focus on the channels and strategies that drive the most conversions.

What Is Marketing Automation?

Marketing automation systems allow marketers to replace manual marketing tasks with automation software that can both manage and monitor routine workflows. 

These workflows might span multiple channels, such as mobile, web, and email marketing, and may include tasks such as lead management, email nurturing, remarketing ads, personalizing content, and retargeting messages.

Put simply, marketing automation can put your most straightforward marketing efforts on autopilot, so you don’t get bogged down in mundane tasks. It’s a technology designed to help marketing teams create predefined customer journeys using real-time triggers, built-out scenarios, and predicted behaviors. 

With the right marketing automation platform, you can create targeted, personalized campaigns that are tailored to the customer’s needs and preferences — without the hassle of building them over and over.

Read This Next: Ecommerce Marketing Automation and Its Benefits

https://www.bloomreach.com/en/blog/2022/e-commerce-marketing-automation-and-its-benefits

The Benefits of Marketing Automation

Some of the key benefits of incorporating  marketing automation into your ecommerce strategy include:

Increased Productivity

Marketing automation enables teams to automate repetitive tasks, such as email campaigns, social media campaigns, and lead nurturing. This frees up time for marketers to focus on tasks that need a more human touch, like creating more engaging and personalized content for their customers.

Improved Lead Quality

Marketing automation helps marketers capture, nurture, and score leads more accurately. This means that marketers can target  the leads that are most likely to convert, which can lead to increased conversions and revenue.

Better Data Insights

Marketing automation platforms provide marketers with detailed analytics and reporting, which can be used to optimize campaigns and improve ROI. With a deeper understanding of each customer based on their habits and preferences, you can make data-driven decisions about nearly every aspect of your communications and get more from your campaigns.

Why You Need a CDP + Marketing Automation 

Now that we know how important a CDP and marketing automation software are for your business, it’s time to consider how these tools work within your marketing tech stack — because close collaboration is absolutely vital for all your platforms.

Building out your marketing technology toolkit is all about making sure your platforms are working in sync. If you have a system of separate solutions, they need to seamlessly collaborate with each other to make your marketing efforts run smoothly. 

Standalone customer data platforms can’t execute campaigns, and marketing automation tools can’t ingest and build out customer profiles from all the data you have available, so integration between these two platforms  needs to be absolutely perfect. 

That’s why a CDP with native marketing automation is such a valuable tool for marketers. With a platform that incorporates both solutions, you are guaranteed to have your customer data and marketing automation working hand in hand.

What You Get With a Standalone CDP 

With a standalone CDP, you get exactly what you expect: a customer data platform without extra capabilities. It ingests all of a company’s first-party data and builds complete pictures of all of your customers. That’s it.

This data is accessible for use by other systems, like email marketing platforms, campaign management tools, and various online channels, but a standalone CDP cannot execute campaigns. It needs dedicated tools that can make use of the comprehensive data it collects, and a lackadaisical add-on won’t always do the trick.

What You Get With a CDP With Marketing Automation

A customer data platform coupled with marketing automation is the next evolution of a CDP. It combines all the benefits of a standalone CDP with marketing campaign tools, creating a single, powerful, and customer-centric marketing platform.

This gives marketers the complete toolset they need for creating incredible customer experiences by bringing together AI-driven marketing capabilities, real-time analytics, and UX optimization — all natively powered by a CDP.

A CDP combined with marketing automation simplifies workflows and increases productivity since it merges  frequently used tools into one integrated interface. Now you don’t have to connect your platforms and pray that your data is syncing in real time with your automation efforts.  Instead, you can rest assured that it’s all working seamlessly in one platform, with a main hub for you to orchestrate truly unique and highly effective campaigns.

Ecommerce Personalization Powered By a CDP

A CDP plus marketing automation tool can also put your company ahead of the game when it comes to powering ecommerce personalization efforts.

With a CDP, you can confidently map out your customer’s journey, understanding their likes, dislikes, and shopping habits. After you have collected customer data to gain this understanding of your customers, you can begin to personalize content and shopping journeys for them to ensure they can go from browsing to purchase with your brand.

Want to make more sales? You’ll need to gather lots and lots of customer data. 

Customer data is the secret sauce behind marketing campaigns that convert and sow the seeds of customer loyalty. 86% of medium- and large-sized companies consider first-party customer data the most important aspect of their communications strategy. 

Customer data platforms (CDPs) are customer databases that house unified records of your customers, their preferences, and other relevant data. Because they organize all of the customer data you need to hit your business goals, CDPs are indispensable for organizations looking to deliver personalized experiences that drive revenue. 

When it comes to CDP installation, you have two options: building or buying your customer data platform. Before you decide whether to build or buy a customer data platform, let’s take a look at some important factors for your consideration.

Key takeaways:

• Building a CDP from scratch can be pricey. Prebuilt solutions will save you time and money on development and ongoing maintenance.

• Bringing your own CDP to market can take years, while an off-the-shelf CDP can go live in as little as six weeks. 

• Trying to scale a DIY solution can lead to resourcing challenges and compatibility issues with other tools, while out-of-the-box CDPs can seamlessly handle big increases in data volume. 

• Using a single vendor for your CDP means less complexity and more streamlined operations. You’ll also get standardized training and 24/7 support instead of doing it all in house. 

Key Considerations for Your Customer Data Platform

Cost-Efficiency

If you’re looking for an effective customer data platform that doesn’t break the bank, weighing cost-efficiency is crucial when deciding whether to build or buy your CDP.

Building a CDP from the ground up can be expensive. You not only have to invest significant capital upfront, but you’ll also need to update and maintain your CDP over time to keep it running effectively. 

A prebuilt solution allows you to avoid hefty development costs and ongoing maintenance expenses. While you’ll still need to pay for the initial setup and deployment of the customer data platform, prebuilt systems aren’t as expensive in the long run. 

Time-to-Market

You know what they say: time is money. This is especially true when you want to deploy a customer data platform. 

Designing your own platform is an attractive part of DIY CDPs. However, when you have so many decisions to make, you can easily spend years developing and deploying your CDP. When it takes too long to bring your CDP to market, it’s easy to go over your budget and cut costs elsewhere to fund the project.

Buying an off-the-shelf customer data platform saves you an incredible amount of time. For example, Bloomreach Engagement can have you up and running in just six weeks, so your team can spend less time building your CDP and more time actually using it. 

Scalability

Scaling up is a goal for most brands. Expanding your business indicates that your brand is successful and attractive to both customers and investors. When your business scales, you’ll need to make sure that your tools can scale with it. 

A do-it-yourself CDP can be hard to scale, especially when you mix and match several different tools to create one master CDP. This is because some vendors may not accommodate scalability to the extent of others, and if your platforms can’t play nice together, your business suffers.

An out-of-the-box CDP like Bloomreach Engagement is designed to seamlessly expand with your business, ensuring uninterrupted operations even during high-traffic events like Black Friday. In fact, during Cyber Week 2022, Bloomreach handled approximately 1.2 billion user events per day, while consistently maintaining 100% uptime. When you use a CDP like Bloomreach, you can provide exceptional customer experiences year-round.

Customization

Every business is different, so it only makes sense to pursue a CDP that can be customized to fit your needs.

In fact, customization is what drives many teams to build their own CDP. Creating a CDP from scratch is an appealing idea to those who believe they can only get what they need from a CDP when they build it themselves. 

However, that’s not the case. Expert CDP providers also prioritize data flexibility and customization. With Bloomreach Engagement, you can configure capabilities, like custom analytics, reporting, segmentation, and AI prediction models, so that they align with your unique needs.

Single Vendor Advantage

Managing multiple suppliers can be a logistical nightmare. Dealing with several different vendors and systems can lead to problems like inefficiency and disorganized data management.

Unfortunately, that’s what many business owners face when building their own customer data platform. Because building a CDP necessitates that you work with countless vendors to build your own tech stack, you don’t get the luxury of having a solid relationship with one vendor. 

When you buy an out-of-the-box CDP, you don’t need to deal with multiple service providers. With only one company handling your CDP and its upkeep, you can simplify contract management, reduce complexity, and streamline your operations, ultimately leading to cost savings.

System Integrations

System integrations should be top of mind when considering building or buying a CDP. Why? Because if you can’t plug in all of your tools, you can’t use your CDP. 

When building a CDP, dealing with system integrations can become complicated and expensive, causing delays in your implementation. You’ll need to collaborate with each vendor to ensure you understand how to connect their product to others. This process can drag on, especially if your CDP tech stack includes numerous solutions.

Working with one supplier who has already done the legwork in securing integrations saves you from having to do this yourself. For example, Bloomreach offers an impressive 139 integrations with some of the most common tools on the market, so you can streamline your integration process and reduce costs.

Standardized Training

Customer data can take your brand’s success to new heights. Once your CDP is implemented, you’ll need to make sure that everyone on your team can use it properly so you can put that data to good use. 

This can be a challenge for a DIY customer data platform, which will include several different parts and protocols. When you build your CDP, your tech stack isn’t unified and will therefore lack standardized certifications and training materials. This makes it harder to teach your team how to use your new CDP effectively. 

When you buy your CDP, you’re purchasing a single solution that is powered by a single vendor and has its own training system. This empowers you to train your team in one standardized way, which reduces confusion and speeds up adoption. 

24/7 Expert Support

As an ecommerce pro, you understand that Murphy’s law can strike at any time. When that happens, you’ll need round-the-clock support to help you get back to work. 

When you create your own CDP, you are in charge of fixing issues and offering support during platform downtime. While you can seek assistance from individual vendors who can help with specific parts of your CDP, you won’t have a single reliable source for resolving conflicts. This could lead to a costly and time-consuming process to ensure your CDP operates smoothly.

When you buy a prebuilt CDP, you can rely on 24/7 expert support. Trusted vendors provide personalized assistance through global teams, available whenever you need help. This means you can get back to work quicker without the hassle and cost of troubleshooting your platform during downtime.

The marketing industry constantly changes, and new techniques and technologies are being developed daily. One promising development is the growth of generative AI in marketing. Traditionally, marketing relies on machine analysis and human prediction. However, generative AI allows for greater creativity and effectiveness by leveraging the speed of a machine with how about saying ‘super-human’ instead of ‘human-like’ predictive abilities. This rapidly growing technology can automate content generation, design, and strategy with algorithms and machine learning, providing a window into the evolving future of marketing.

With technologies like generative AI and generative attribution reshaping marketing aspects ranging from personalized content production to predictive analytics, staying on top of the latest advances is critical to keep your brand competitive. This blog will help to do that by exploring the impact of generative AI on the marketing industry and the future of marketing.

What is Generative AI?

Generative AI focuses on producing unique and fresh content. It consists of a generator and a discriminator that work together to create realistic and distinctive outputs. The discriminator evaluates the generated samples and distinguishes them from accurate data, while the generator produces new pieces like images, sounds, or texts. This process is repeated until the generator can produce outputs indistinguishable from real data. Generative AI has various applications, including text creation, virtual characters, images, and videos. It can revolutionize entertainment, design, and marketing by offering original and innovative ideas.

How Does Generative AI Work?

Generative AI has been in existence since the 1960s. While many people associate AI with GPT-based models, it goes beyond that and focuses on using computers to create new and unique pieces of data autonomously. It can include sentences, images, consumer touchpoint journeys, and more. The discussion around generative AI today tends to focus on GPT-based applications, but it is important to recognize this technology’s broader scope and potential.

What are the Uses Cases of Generative AI?

Generative AI has a wide range of applications across various industries. Some of the most prominent applications of generative AI include:

Efficient Data Analysis and Predictive Modeling

Generative AI algorithms can process and analyze these extensive datasets much faster and more accurately than traditional methods, enabling marketers to uncover patterns, trends, and correlations that would be otherwise difficult, if not impossible, to identify. Moreover, it can help in predictive modeling, using huge datasets, including historical data, to anticipate future trends and outcomes, enabling organizations to address potential challenges and seize opportunities proactively.

Recovered Consumer Journeys 

Generative AI has revolutionized data analysis, enabling the recovery of consumer journeys that were previously unavailable due to missing data. These customer journeys provide valuable insights into consumer behavior and preferences. It uncovers hidden patterns and trends in consumer journeys that were previously inaccessible.

Personalized Content Creation

With generative AI, marketers can effortlessly create content tailored to individual preferences, interests, and needs. Whether it is personalized product recommendations, customized emails, or targeted advertisements, it helps them deliver content that resonates with their audience on a personal level. It not only enhances user engagement but also increases conversions and brand loyalty.

Improved Customer Experience Through Chatbots

Generative AI-powered chatbots enhance customer experience by providing instant and personalized assistance. These bots understand natural language and context, engaging in human-like conversations and offering accurate responses. Marketers can use it to provide 24/7 customer support, efficiently resolve queries, and ensure seamless interactions.

Targeted Advertising and Recommendation Systems

Generative AI algorithms enable advertisers to analyze vast amounts of data quickly. This analysis helps them understand consumer preferences, interests, and behavior patterns. As a result, they can create tailored advertisements that resonate with their target audience. It leads to higher conversion rates and better marketing ROI. Generative AI also powers recommendation systems that analyze user data and provide personalized suggestions based on preferences and past behavior. It enhances the user experience, increases engagement, and drives sales.

Democratized Data

A lack of technical expertise can significantly challenge marketing teams in handling and analyzing data quality. However, generative AI has eliminated this barrier. Marketing teams no longer need data scientists or IT professionals to access and interpret data. Generative AI tools empower marketers to quickly understand and use data for informed decision-making. This data democratization improves marketing campaign efficiency and effectiveness, allowing teams to target the right audience, optimize content, and personalize customer experiences.

What are the Benefits of Generative AI in Marketing?

In the field of marketing, generative AI offers several advantages that can greatly enhance advertising and promotional efforts. Some advantages of Generative AI in marketing include the following:

Increased Efficiency and Productivity

Marketers utilize generative AI to automate tedious tasks and procedures, enabling them to concentrate on strategic and creative aspects of their business while eliminating human error that impacts data quality. This technology simplifies and enhances the creation of tailored and targeted content on a large scale. With generative AI, companies can optimize their marketing efforts, improve campaigns, and successfully reach their intended audience efficiently. 

Enhanced Customer Engagement and Satisfaction

Generative AI can analyze data to understand customer behavior and preferences better. It allows marketers to tailor their strategies accordingly. The technology enables personalized recommendations, targeted advertising, and interactive experiences, which resonate with customers on a deeper level.

Cost-effective Marketing Strategies

By utilizing generative AI technologies, marketers can automate and optimize various aspects of their campaigns, reducing the need for manual labor and streamlining processes. This automation saves time and reduces costs associated with traditional marketing methods. It analyzes data, identifies patterns, and generates personalized marketing content for more targeted and effective marketing campaigns. Due to this cost-effectiveness, marketers can allocate resources efficiently and achieve better returns on marketing investments.

Ability to Learn Constantly

With access to more data over time, generative AI algorithms improve their understanding and ability to cater to a customer’s specific needs. As they learn from user interactions and feedback, these AI systems continuously enhance their capabilities, allowing them to provide more accurate and personalized solutions.

What are the Best Strategies for Implementing Generative AI for Marketing?

Implementing generative AI in marketing requires careful planning and consideration of the best strategies. Let’s look at the best strategies for implementing generative AI for marketing.

Clearly Define Marketing Goals

Defining your marketing goals includes identifying specific objectives, like increasing brand awareness, improving customer engagement, or driving sales. Having clear goals helps align generative AI strategies with your overall data-driven marketing strategy. This clarity guides implementation and ensures the effective use of AI technology to meet marketing objectives.

Identify Relevant Data Sources

Identifying relevant data sources involves determining the types of data that will be most useful. These data sources could include customer demographics, purchasing behavior, social media interactions, website analytics, and more. Marketers should utilize these relevant data sources to train the generative AI on accurate and valuable information, ensuring more effective marketing initiatives.

Train and Fine-tune Generative AI Model Using Collected Data

One effective strategy is to train and fine-tune it using collected data, which includes gathering relevant data from customer interactions, market trends, and historical marketing campaigns. Marketers can create more personalized and effective marketing materials by continuously refining the model through iterations. The trained model can generate content such as ads, social media posts, and email campaigns that resonate with the target audience.

Evaluate and Optimize Generated Marketing Content

Generative AI can benefit marketers by automating marketing content creation. This can be done by analyzing engagement, click-through rates, and conversion rates. Ongoing evaluation and optimization maximize the impact of generative AI in marketing campaigns.

Find the Ideal Generative AI Tool

New technologies are often adopted in the marketing industry without assessing if they genuinely address a particular problem. Marketers must exercise caution when embracing it to follow trends. Instead, they should evaluate whether this technology aligns with their goals and enhances their product or campaign. 

Prioritize Security Measures

Marketers must guarantee that the AI tool has the necessary security measures to protect sensitive data. For example, allowing anyone to upload data to platforms like ChatGPT or other open-source tools can potentially expose confidential information. Therefore, it is crucial to thoroughly evaluate the security protocols of the AI tool to ensure the secure handling of proprietary data.

What are the Challenges and Potential Risks of Generative AI?

As AI systems become more advanced and capable of generating increasingly realistic content, challenges arise regarding the potential misuse of this technology for other purposes. Some of the challenges and risks associated with generative AI are as follows:

Representative Data is Used for Model Training

One of the challenges is the reliance on representative data for model training. Just like humans, AI models learn from their environment, and if they are trained on biased or limited data, they will reflect those biases and limitations in their output. If the training data does not accurately represent the real world, the AI model cannot build an accurate real-world model, which can lead to skewed or inaccurate results. An AI model possesses limited knowledge and understands only what it has been programmed to learn.

Organizational Readiness

Although some applications of Gen AI are relatively simple and require low levels of readiness, more complex problems demand careful consideration of various factors. Privacy, legal, regulatory, and ethical concerns all come into play when dealing with these advanced applications. 

Generative AI has gained significant attention for its ability to mimic human intelligence and generate seemingly independent responses. However, it is important to understand that despite its impressive capabilities, it functions more like a highly skilled parrot. It reads the context and responds accordingly, but it is not truly independently intelligent. Instead of replacing humans, it serves as a tool to amplify human abilities.

Privacy and Data Security Concerns

As generative AI models learn from large datasets, there is a concern in data privacy that these models may inadvertently incorporate sensitive or private information into the generated content. This could potentially lead to the exposure of personal data or the creation of misleading or harmful content.

Legal and Regulatory Challenges

Many companies operating in highly regulated industries are hesitant to fully embrace AI due to concerns about the lack of established legislation and regulations governing its use. These companies are adopting a cautious approach, waiting for clear guidelines to be established before fully implementing Generative AI technologies. 

Ethical Considerations

One of the main challenges is the potential for misuse or malicious intent. Since Generative AI can create realistic and convincing content, there is a risk of using it to spread misinformation, generate fake news, or even create fake videos that can be used to deceive or manipulate people. There are also concerns about copyright infringement when using it to create content that may be similar to existing works.

What is the Future of Marketing with Generative AI?

As AI marketing continues to advance, marketers can build and recover models more effectively. They can understand consumer journeys with greater accuracy and recover valuable insights from them. By utilizing generative AI, marketers can close the loop more efficiently, taking faster and more informed actions based on each consumer’s specific interests and actions. This goes beyond traditional targeting and retargeting methods, as it allows for creating custom content tailored to each client’s unique preferences and probabilities.

Moreover, it holds immense potential for marketers with access to large CRM datasets. Marketers can go beyond traditional segmentation and personalize promotions and pricing for each individual consumer. This level of customization allows marketers to target their audience more effectively and deliver personalized experiences that resonate with consumers.

Commonly Asked Questions about Generative AI

What is generative AI vs. AI?

Generative AI refers to artificial intelligence systems that can generate new and original recommendations based on complex analysis, like media plans and content, such as images, music, or text, based on patterns and data it has learned. On the other hand, AI generally refers to the broader field of computer systems that can perform tasks or make decisions that typically require human intelligence.

What is generative AI good for?

Generative AI is good for generating new and unique content, such as artwork, music, and writing. It can also be used for data augmentation and for creating realistic simulations for forecasting or scenario building.

How does generative AI affect digital marketing?

Generative AI significantly impacts digital marketing by automating and enhancing various tasks such as complex marketing analysis like media mix modeling, attribution, media scenario planning, content creation, personalized advertising, and customer segmentation. It enables marketers to access powerful, robust marketing insights for decision-making and deliver more targeted and relevant messages to their audience, improving engagement and conversion rates.

How does generative AI affect marketing analytics?

Generative AI greatly enhances marketing analytics by generating more reliable, representative unbiased insights and predictions based on large amounts of data. It automates the analysis process, improves data quality and representativeness, identifies patterns and trends, and provides valuable recommendations for marketing strategies.