In the early 2000s, the internet began disrupting traditional sales channels, introducing what would become the new standard for most industries: e-commerce.

Ten years later, companies started collecting large amounts of customer data. Initially, this data collection helped better understand customer behaviors. More recently, with the rise of cloud computing and data warehousing, it has enabled businesses to tailor their marketing approaches to individual customers thanks to data activation.

The recent release of ChatGPT by OpenAI in 2022 marks the start of a third chapter in this era of profound digital transformation. After years of promising research, AI technologies are finally making their way into the business world, driven by advances in GPU capabilities.

In this article, we explore how to embrace these new technologies to boost business operations, especially marketing.

For many B2C companies, customer support represents one of the most substantial overhead costs, particularly in maintaining call centers. The introduction of AI chatbots is starting to revolutionize this area by providing efficient and effective customer support at a fraction of the cost.

AI chatbots can now handle a wide range of customer inquiries, from answering frequently asked questions to assisting with troubleshooting issues. They are available 24/7, providing immediate responses and reducing wait times for customers. This not only enhances the customer experience but also decreases the need for large teams of human support agents.

Tools such as Reverse ETL also help to obtain 100% of customer information in support tools, enabling better prioritisation of tickets.

Machine learning technologies enable the automation of processes that, while not strictly repetitive, previously required human intervention. This can lead to drastic reductions in overhead costs.

By automating tasks like sending emails, managing advertising campaigns, and analyzing data, marketing teams can focus on higher-value tasks. For example, most data activation solutions enable large-scale synchronization of highly targeted audiences, enhancing campaign effectiveness and reducing operational costs through the use of fresh data.

Many tasks performed by different teams (data, marketing, support, etc.) can be automated using artificial intelligence.

AI helps to optimise advertising spend in real time, maximizing its impact on return on investment.

AI-powered advertising platforms can adjust bids in real time based on ad performance. This maximizes the impact of ads while reducing costs. For example, Google Ads uses AI to adjust bids automatically, ensuring that the advertising budget is spent optimally.

Exploiting customer data throughout the whole customer journey is key to:

Data was often locked away in an IT domain, and marketers were unable to use it for their strategies.

At DinMo, we are convinced that data should not just be used by data teams, but should be shared throughout the company.

Yet, one of the significant challenges businesses face is the technical barrier to leveraging the vast amounts of data they collect. Fortunately, AI can help overcome these barriers by automating complex data analysis tasks and providing intuitive tools that can be used by marketers without a deep technical background. For instance, AI-powered platforms can automatically clean, organize, and analyze data, presenting insights in an easily understandable format. This democratization of data allows marketers to make data-driven decisions quickly and efficiently, without needing to rely on specialized data analysts.

At DinMo, we offer an AI co-pilot, DAN, so that anyone can ask him questions about their company, marketing results or recommended actions.

When it comes to optimize acquisition and retention, marketers are debating over two fundamental questions:

And yes, you guessed it: machine learning can now answer these two questions with an accuracy exceeding by far any human analysis.

Machine learning excels at analyzing vast amounts of data to uncover patterns and trends that would be nearly impossible for humans to discern.

For instance, by examining past purchase history and browsing behavior, advanced machine learning models can forecast which products a customer is likely to be interested in next, identify which customers are at risk of churning, and estimate the potential lifetime value of each customer. These insights allow businesses to anticipate customer needs and preferences more effectively.

This predictive capability enables businesses to refine their marketing strategies, ensuring they target the right customers with the most relevant products, offers, and discounts at precisely the right time. This approach, known as the “next best offer” (NBO), enhances the efficiency of marketing efforts and improves conversion rates.

Additionally, by predicting which customers are most likely to churn, businesses can proactively tailor their re-engagement strategies. For example, targeted retention campaigns or personalized incentives can be designed to address the specific reasons for potential churn. Moreover, understanding a customer’s predicted lifetime value allows businesses to set optimal acquisition costs, ensuring that the investment in acquiring new customers aligns with their long-term value.

👇 Check what we've done with Galeries Lafayette to see how customer segmentation and Artificial Intelligence help them improve their performances.

As we discussed, implementing AI technologies into your business can drive significant benefits in customer engagement, operational efficiency, and marketing effectiveness. However, developing these tools in-house can be extremely complex, time-consuming, and costly. For most businesses, opting for specialized external solutions is a more practical and effective approach.

The development and deployment of AI technologies involve several challenges, including:

Fortunately, to overcome these challenges, specialized external solutions exist: Customer Data Platforms (CDPs). CDPs are designed to integrate, analyze, and leverage customer data efficiently, offering a range of AI-powered capabilities without the need for in-house development.

Traditional CDPs have often been boycotted by businesses due to lengthy implementation times and a sometimes lengthy ROI.

Fortunately, developments in the data ecosystem have led to the emergence of what is commonly referred to as a Modern Data Stack, offering cutting-edge technologies for diverse objectives.

The Modern Data Stack represents a major evolution in the way companies manage and utilize their data. The trend is towards highly customizable data architectures, where each company can build its own "à la carte" solution based on its specific needs, while maintaining flexibility and adaptability.

In that context, more and more companies are building their own Customer Data Platform, embracing a ‘Composable’ approach.

DinMo is a pioneering Composable CDP that leverages a reverse ETL engine on top of a data warehouse and AI to predict future customer behavior. As a versatile data activation platform, DinMo transforms any cloud environment into a dynamic and actionable hub for every team within an organization.

Powered by our advanced AI and a suite of no-code features, data and marketing teams can effortlessly access and activate data from their data warehouse directly into 100+ business tools and applications. This seamless integration allows teams to access comprehensive customer data within the SaaS tools you already use, enabling you to deliver the personalized experiences that modern consumers demand.

In conclusion, the integration of AI into marketing practices offers numerous benefits, from predicting customer behaviors and personalizing customer relationships to removing technical barriers to data leverage. As AI technology continues to evolve, its impact on marketing will only grow, providing marketers with powerful tools to engage with customers in innovative and meaningful ways. The future of marketing lies in the seamless integration of AI, enabling businesses to stay ahead in an ever-changing digital landscape.

DinMo is trusted by leading companies like Ankorstore, Interflora, Manor and MYM to sync billions of customer data points and audiences each year, providing the insights needed to stay ahead in a competitive market. Discover how DinMo can transform your data strategy by contacting us! 🌟