Know Your Customers Better: How GenAI Can Drive Europe's SaaS Marketing Do you ever feel that your SaaS product speaks a different language than your customers? Here are two strategies that can improve your chances of increasing conversions.

Over the past 15 years, the number of European vertical SaaS businesses created annually has grown from 10 to 20 companies between 2011 and 2015, to 40 to 70 companies between 2016 and 2021. This ever-increasing number illustrates the heightened level of competition throughout the continent.

By stepping into your customers' shoes and understanding their needs, frustrations, and aspirations, you can develop a targeted message that resonates and drives conversions. This is how Empathy Maps (EMs) and Value Proposition Canvases (VPCs) are described. However, crafting these tools can be a time-consuming, resource-intensive process. So, how can this help European SaaS businesses to keep ahead of an increasingly competitive curve?

Empathy Maps and Value Propositions Canvas

On the one hand, an EM is a user-centric framework that helps you visualise your customers' thoughts, emotions, and behaviours in relation to a problem your product aims to solve. Understanding these aspects allows you to generate key insights to create more tailored experiences. On the other hand, a VPC is a tool that helps you articulate how your product or service addresses customer pain points, thus providing clear value.

Given the variations in SaaS businesses can experience in marketing across diverse European nations, the utility of EMs and VPCs can be an asset in catering to the varied needs of your consumers.

Although these tools work hand-in-hand, they serve different purposes. The EM gives you a detailed picture of your customer's world, while the VPC turns those insights into a concise message that connects your offering to the customer's needs.

What is an Empathy Map?

Imagine a visual tapestry woven from user insights. That's the essence of an EM. It's a structured framework that captures your target users' thoughts, feelings, actions, and words. By consolidating research findings into this four-quadrant format, you gain a holistic understanding of how users navigate the world, including the products and services they interact with. This user-centric approach ensures that the design process is focused on creating the best possible experience, one that caters directly to your audience's needs and desires.

So, how do we translate raw user research findings into a user-centric map? The journey begins with the process of gathering data through various UX research methods, including user interviews, usability tests, and focus groups. Once this treasure trove of information is collected, it's time to organise it within the four quadrants of the MP:

• Says: This quadrant captures the user's verbal communication. What are users explicitly expressing? Direct quotes from your research findings become the heart of this section.
• Thinks: Here, we delve deeper and explore the user's internal monologue. This includes their unspoken thoughts, beliefs, and assumptions—the unsaid desires and concerns that drive their behaviours.
• Does: Actions speak louder than words, and the "Does" quadrant reflects this. When interacting with products or services, we map out user behaviours, habits, and specific actions. Clicks, taps, and navigation patterns all tell different stories.
• Feels: Emotions are a crucial part of the user experience. This quadrant focuses on users' emotional states during their interactions. By understanding their frustrations, anxieties, and positive emotions, we can design solutions that resonate more deeply.

Designers, strategists, and anyone involved in product creation in Europe and beyond can quickly identify pain points and areas where users struggle. This process allows for focused problem-solving and ensures user-driven design decisions, ultimately leading to more satisfying user experiences.

What is the Value Proposition Canvas?

The VPC is a strategic tool designed to ensure that a product or service aligns perfectly with its target customers' needs, desires, and pain points. It's a visual framework that helps businesses understand and meet customer expectations, ultimately driving customer satisfaction and success.

The key components of the VPC are as follows:

Customer profile:

• Gains: What customers desire or expect from a product or service.
• Pains: The negative experiences, emotions, or risks encountered by customers.
• Jobs to be done: The functional, social, or emotional tasks customers are trying to accomplish.

Value map:

• Gain creators: How your product or service addresses customer gains and provides added value
• Pain relievers: How your offering alleviates customer pain points
• Products and services: The specific offerings that create value for your customers

How to use the VPC:

1. Define your customer segments: Identify the different groups of customers you're targeting.
2. Create customer profiles: Map out each segment's gains, pains, and jobs to be done.
3. Develop your value proposition: Identify how your product or service addresses the identified needs and challenges of your target customers.
4. Align your value map: Ensure that your product or service aligns with the customer profiles you've created.
5. Iterate and refine: Continuously evaluate and adjust your value proposition based on customer feedback and market trends.

Benefits of the VPC:

• Clearer product focus: Helps you understand what customers truly value and need.
• Improved product-market fit: Ensures that your product or service actually meets market demand.
• Enhanced customer satisfaction: Delivers products and services that address customer pain points and provide value and benefits.
• More effective marketing: Enables you to tailor your messaging to resonate with your target audience.

EMs help you understand your customer's mindset, emotions, and needs, while VPCs communicate the specific value your product offers to meet those needs. They work together to align your product or service with your customer's expectations, ensuring that your offer resonates deeply with your target audience.

Why Empathy Mapping can be a struggle and how GenAI helps

Traditional methods of Empathy Mapping, such as surveys and focus groups, can be limiting. On the one hand, surveys often yield surface-level data, while focus groups can be susceptible to groupthink and lack diversity. Generative artificial intelligence (GenAI), on the other hand, unlocks a treasure trove of customer insights hidden within vast datasets.

European SaaS companies are set to benefit from the rapid evolution of generative AI tools like Empathy Mapping over the coming years. Projections suggest that Europe's GenAI market is set to reach a value of $68.79 billion by 2033, representing a CAGR of 32.92% over the years ahead.

Imagine analysing social media comments, customer support tickets, and online reviews - a goldmine of unfiltered customer sentiments. GenAI can sift through this data and identify recurring themes and patterns. This process allows you to uncover hidden frustrations and aspirations that your customers might not be able to articulate in traditional settings.

Let's translate this growth into use cases. Say you offer a project management tool. GenAI might analyse customer reviews and discover a consistent theme of being overwhelmed by task management complexities. Delving deeper could reveal a hidden persona - the "Micromanaging Martha" who thrives on organisation but struggles with information overload. With this newfound understanding, you can design a bespoke value proposition that speaks directly to Martha's anxieties, highlighting features that streamline task delegation and prioritise workflows.

Managing AI with control: The importance of human oversight

One key challenge in using GenAI to create EMs and VPCs is ensuring that the process remains under human control. GenAI can sift through vast data, generate insights, and even simulate user personas. However, controlling how and where AI is applied in the marketing process is important.

For example, although GenAI can help you generate ideas, content, or customer insights, humans must supervise these outputs to ensure that they align with your business strategy. AI is a powerful tool, but it cannot completely replace human intuition or expertise. Thus, you must monitor AI's role throughout the content creation process, gradually reducing control only when you build enough trust in AI's ability to handle more complex tasks.

Practicality and continuous adaptation: Empathy Maps and Value Proposition Canvases are not static

One common mistake European businesses can make is to treat these tools as static. They create an EM or a VPC once and forget to update it. However, successful marketing requires continuous adaptation based on real-world feedback. This is where validation comes into play. The assumptions you make about customer pain points and desires must be validated with real data from interviews and interactions with customers.

When you develop these tools with GenAI, you must eventually replace early assumptions with real customer feedback over time. Furthermore, while GenAI can help you analyse large volumes of data, you must always validate and refine your insights through direct customer interactions. For instance, you can start with AI-simulated interviews and then conduct real interviews with users to verify and refine your results.

Example of a GenAI-simulated interview:

John Marvel, an experienced designer

• Persona: A seasoned designer with over 20 years of experience, John is seeking a new design tool that seamlessly integrates with his existing workflow.
• Interview simulation: Ask John about his frustrations with current tools, his priorities in a new tool, and his willingness to pay a premium for a solution that meets his needs.
• Validation: Compare the AI-generated responses with feedback from actual experienced designers.

It is tempting to view GenAI as a magic bullet that can solve all marketing problems, but it is crucial to manage expectations. While GenAI can process vast amounts of data and generate insights in ways that would be difficult for humans to achieve, it does not replace the need for a well-rounded marketing strategy or human expertise.

Although GenAI helps you process information, discover patterns, and identify opportunities, it won't single-handedly craft your unique value proposition or understand your business on a deep level. Therefore, as you incorporate AI into your processes, it's vital to maintain a realistic perspective: AI can assist in structuring, optimising, and validating your work, but it won't replace your creative or strategic decision-making.

Crafting diverse personas with GenAI

Customer personas in Europe can differ significantly from country to country, and this can severely impact your SaaS company's value proposition at scale.

Research conducted by Criteo shows that while 88% of consumers in Poland and Sweden are willing to consider new brands, this figure falls to just 64% in the Netherlands. Likewise, 66% of shoppers in Spain feel that a brand's values shape their purchasing decisions, while in the United Kingdom, the sentiment towards brand values falls to 41%.

Customer personas are the lifeblood of targeted marketing. However, no two customers are the same, and the variations between personas can be more pronounced between European nations.

GenAI empowers you to create detailed customer profiles based on behavioural patterns, thus overcoming the limitations of demographics.

GenAI can handle massive datasets and identify subtle behavioural patterns that human analysis cannot check in a short period of time. This allows you to develop diverse customer profiles that represent the multifaceted nature of your target audience.

Another vital aspect of using GenAI is understanding that personas and VPCs are not a one-time project. When developing a customer persona, assumptions and insights drawn from the initial data are used. However, these assumptions must be validated through real customer feedback. As previously emphasised, GenAI can help structure these personas by simulating interviews or analysing behavioural data, but it's essential to refine this information by conducting actual interviews.

As new data emerges over time, personas should evolve along with them. AI-generated personas can be a starting point, but real-world validation is key to making them actionable. This continuous and cyclical process ensures that your marketing message remains aligned with changing customer needs and behaviours.

While GenAI can be a powerful tool for generating customer personas, it's essential to approach the task with a structured methodology to ensure accurate and actionable insights. Here's a step-by-step guide:

Step 1: Gather data and define personas:

• Leverage existing data: Utilise customer data from your CRM, analytics tools, and surveys to identify distinct segments. If you're using a payment processor that allows you to analyse the data, you could find some very important insights.
• Define persona attributes: Create detailed personas based on factors such as demographics, psychographics, behaviours, and pain points.
• Focus on behavioural patterns: Prioritise behaviours, such as preferences, order histories, and interactions with your brand.

Step 2: Conduct GenAI-simulated interviews:

• Create interview scripts: Develop interview scripts that are tailored to each persona's challenges and needs.
• Utilise GenAI tools: Employ GenAI-powered language models, such as ChatGPT, to simulate conversations with the personas.
• Explore different scenarios: Present various scenarios and questions to gauge these personas' reactions and responses.

Step 3: Validate with real customers:

• Select representative samples: Identify individuals who closely match each persona's characteristics.
• Conduct validation interviews: Ask these individuals to review the AI-generated responses and provide feedback.
• Identify discrepancies: Compare the AI-generated insights with the perspectives of real customers.
• Optimise customer personas: Based on the feedback and identified discrepancies, adjust the personas to better reflect the actual needs, behaviours, and preferences of your target audience. Ensure that the personas evolve as new data become available, keeping them relevant and actionable for future marketing strategies.

Step 4: Create EMs and VPCs:

• Utilise AI-generated insights: Incorporate the validated GenAI responses into the EMs and VPCs.
• Tailor specific EMs and VPCs to each persona: Customise the maps and canvases to reflect the unique needs and challenges of each persona.
• Identify opportunities: Use the insights to identify potential areas for product improvement or marketing strategies.

Here are some key considerations:

• Choosing the right tools: Not all GenAI tools are created equal. Research options that integrate seamlessly with your existing marketing stack and offer features tailored to your specific needs.
• Defining clear objectives: Identify your goals upfront to guide your data analysis. For example, what do you hope to achieve with GenAI-powered Empathy Mapping?
• Managing GenAI biases: Remember, GenAI is a tool, not a replacement for human expertise. As such, be mindful of potential biases in the data and use your judgment to ensure that the generated insights are accurate and representative.
• The human touch matters: While GenAI provides invaluable data, it shouldn't replace the human element. Thus, you should combine its insights with your marketing expertise and customer feedback for a truly holistic approach.

GenAI empowers you to build EMs and VPCs that resonate with varied European target audiences on a deeper level, leading to increased conversions and long-term customer loyalty.

Embrace the power of GenAI, but remember, the human touch remains crucial. The future of SaaS marketing belongs to those who can bridge the gap between data and empathy, and GenAI offers the tools to do just that.