How to Predict Customer Lifetime Value from Email Buyers Using AI
iAge Technologies uses AI to help marketing teams boost email performance.
The company uses machine learning to help customers predict customer lifetime value, optimize buyer journeys, and optimize send times across email marketing campaigns.
We spoke with Faruk Aydin, Head of Growth at iAge, to learn more about this marketing AI solution.
In a single sentence or statement, describe your company.
iAge Technologies is an AI development and email marketing company. We help dynamic marketing teams boost subscriber engagement and extend lifetime value of their customers through email.
How does your company use artificial intelligence in its products?
Marketers have never had so much data about their customers, and as they interact more with them along the way, the big chunks of data they acquire through various sources and devices only grow more.
At iAge Technologies, we use machine learning technology to tame this data and provide actionable insights for marketers. While it is impossible for humans to process millions of data points, machine learning allows us to make better and faster decisions. Particularly in email marketing, machine learning algorithms can optimize the entire email communication with subscribers, and help us send relevant and personalized messages.
What are the primary marketing use cases for your AI-powered solutions?
Data management and organization: Using machine learning capabilities, marketers can discover and group similar customers, using demographic, behavioral and transactional data. Each of these customer groups can be defined in clusters and labeled based on similar characteristics.
Customer lifetime value (CLV) prediction: By leveraging customer behavioral data, statistical models and machine learning algorithms, we can predict CLV. It allows marketers to see which acquisition channels deliver the customers with the highest value. This way, marketers can prioritize those channels and spend their marketing budget wisely.
Customer journey optimization: Machine learning helps marketers create a single customer profile, and each profile becomes a new segment. An individual communication sequence and schedule can be selected with personalized content according to each customer's wants, needs and preferences.
Personalization at scale: Using AI capabilities, email marketers can create highly personalized message content at scale. We use predictive recommendations and content optimization to build a stronger relationship with each subscriber, provide them a unique experience, and ultimately convert them into loyal, long-term customers.
Send time and frequency optimization: Based on past activity, timezone, and habits, machine learning algorithms watch how each person on an email list interacts with emails, and then find the best time to send an email with the highest likelihood to get opened. This way, email messages will not be buried in subscribers’ inbox.
What makes your AI-powered solution smarter than traditional approaches and products?
As humans, we have certain needs and limitations—most of us can't even wake up without a cup of coffee every morning. We’re very prone to making mistakes. However, machines can perform effectively day and night. Moreover, our decisions can be biased. We often make decisions to prove something or avoid something. On the other hand, machines are programmed to make the most logical decisions, and they can help us become fully data-driven.
Particularly in email marketing, AI-powered solutions do the heavy lifting with the data while email teams can focus on working on creativity, strategy and more revenue-generating ideas. Basically, email marketers can save time for things that actually matter.
Especially with the pandemic, brands went all-in digital and it is really hard to stand out in the crowded customer inboxes. Our AI-powered email marketing solution is profile-centric: Each subscriber has an individual communication sequence and schedule. It allows marketers to ditch the traditional bulk segmentation forever. Using AI, each profile becomes a new segment, and marketers can deliver a valuable inbox experience for their customers.
Most of the traditional email systems offer volume-based pricing and such an approach is no longer desired by both consumers and brands. Leveraging AI, we focus on smart marketing and engage subscribers based on their interest levels and activities. It translates to better engagement and we offer our clients performance-based pricing, which encourages better practices in the email marketing community.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
We promote email marketing best practices. As rule of thumb, we'd like to work with email marketers with first-party opt-in data.
Who are your ideal customers in terms of company size and industries?
Most of our clients are from various industries including financial services, media and publishing, call centers, affiliate marketing, and entertainment. We're open to work with SMBs, as well as enterprise companies.
What do you see as the limitations of AI as it exists today?
Although AI is commonly used nowadays, there are still plenty of marketers who do not understand the concepts around AI and the benefits it can offer to them. It is not very easy for everyone to get a grasp of what exactly AI or machine learning is, especially for those who do not have any technical background. Luckily, today there are so many resources, like Marketing AI Institute, available for marketers to learn more about these concepts and find ways to implement them in their business.
Another limitation is the misunderstanding around the cost, time, and complications around AI implementation. In the early days of AI's use in marketing, large enterprise-level CRM systems and email marketing service providers introduced certain features leveraging AI. Those were the times when the first adopters had to cover quite high price tags. For this reason, there is a perception in the market that AI is an expensive solution to implement.
However, AI is more and more accessible to marketers from all shapes and sizes. It is no longer a market which is dominated by a few enterprise-level players. As computing power is increasing and widely used, there are so many companies offering products and services using AI capabilities. AI is often perceived as futuristic and sophisticated which leads marketing teams to stay away from it as they think there would be a lot of work to do.
Nowadays, many companies offering AI solutions provide guidance and consultation that may help reduce potential issues at the early stages of implementation. Depending on the size of the company, the number of data sources, the necessary integrations and several other factors, the implementation time can range from a few days to several months. Most AI companies offer very convenient solutions to integrate your data sources to their systems.
What do you see as the future potential of AI in marketing?
AI goes hand-in-hand with automation and marketers have already realized that the only way that they can become relevant and "talk" to their customers via advanced personalization is through AI.
We'll see more and more marketing solutions add AI-powered features and they will champion the adoption of AI among marketers. We're witnessing AI developments that help accessibility for the visually impaired people or those who suffer with hearing loss. Computer vision and natural language processing fields will allow marketers to become inclusive. 2020 was a rough year, but we had a big leap in natural language generation especially with GPT-3. AI-powered tools that learn the way brands communicate with customers, and empower marketing copywriting will definitely disrupt marketing communication.
Any other thoughts on AI in marketing, or advice for marketers who are just getting started with AI?
We recommend marketing teams identify the problem they want to solve and define the results they want to get before jumping on the wagon with AI implementation in their marketing workflow.
As they prioritize their initial problems to solve, they can start small and scale up along the way with their AI adoption. Achieving successful results with initial use cases will help them feel more confident, have more support from their upper management and marketing team, and, ultimately, allocate more resources in the future.
They will definitely need to integrate their existing marketing tools and workflows with an AI system. AI can only work if marketers feed it with audience data from all available sources.
AI also requires human guidance, creativity, empathy, intuition, social, and emotional intelligence. In your marketing team, you may want to outline the cooperation between team members and AI to make the most out of this implementation.
Finally, marketers need to give AI time since AI transformation is a process. You may not see overwhelming results overnight.
About Paul Roetzer
Paul Roetzer (@paulroetzer) is founder and CEO of PR 20/20, author of The Marketing Performance Blueprint and The Marketing Agency Blueprint, and creator of The Marketing Artificial Intelligence Institute and Marketing Score. Full bio.