Using Digital Twin of Customers as Thought Partners for Marketing

You may have accumulated a lot of market data. But understanding your customers is a different ballgame altogether. Most companies already have industry research reports, buyer interviews, survey responses, and market insights scattered across documents, spreadsheets, and dashboards.

The real challenge lies in turning all that fragmented information into something teams can actually use when making marketing and product-related decisions.

For WIN, a rapidly growing internet service provider in Peru, this meant finding a way to turn their audience research into structured personas and interactive “thought partners” for marketing experimentation.

Read along to see how the company used Research Persona and Digital Twin of Customer by Delve AI to generate data-driven personas and test marketing, content, and pricing ideas before taking them to market.

About the Company

WIN is a telecommunications provider based in Peru that offers fiber-optic home internet connections, along with fixed telephone services and digital television for residential customers.

Operating in a competitive telecom market, the brand heavily relies on digital marketing to acquire and engage customers. So, knowing how different consumer segments evaluate internet providers, based on factors like pricing, speed, and brand perception, is critical to building effective campaigns.

WIN’s marketing team regularly conducts research and gathers insights about its audience. But like many organizations, they needed a better way to organize and turn those insights into actionable entities (personas) and strategies.

The Problem

The marketing team had the research data, but using it in day-to-day decision-making wasn’t always straightforward.

Customer insights were difficult to translate into practical actions. Also, segment differences in preferences, motivations, and concerns were not always easy to visualize or communicate across teams.

More importantly, traditional customer profiles had a limitation: they were static.

Once created, they served mainly as reference documents. Teams could read them, but they couldn’t interact with them or test ideas against them in real time. For a marketing team constantly experimenting with messaging and content, this made rapid testing difficult.

The Solution

WIN’s marketing team needed a solution that could help them better understand behavioral differences across customer segments and test marketing ideas before launch.

One of the tools they chose was Delve AI, which helps brands and agencies convert their research materials into structured personas and interactive digital twins.

Implementation

To get started, the team purchased Delve AI’s Research Essential Bundle, which includes the ability to create segment-wise personas from descriptions of audiences and research data (survey data, interview transcripts, presentations, etc.), the generation of synthetic users for research studies, and several thousand chat credits for chat/interactions with the generated personas (digital twins of customers).

Turning research data into personas

The entire process began with the Research Persona tool. To those who don’t know, the platform allows brands to create user personas by uploading various research materials, like interview transcripts, survey responses, research reports, internal documents, and industry news.

Even if no research documents are available, the tool can still generate personas. Users simply need to add a brief description of their target audience, and the AI persona generator takes it from there.

Once the documents are uploaded, Delve AI analyzes the material and automatically generates persona segments based on patterns found in the data. For WIN, the system generated four research personas, representing key B2C segments.

Persona details provided a structured view of the segment’s characteristics, including:

• Persona summary and personal aspirations
• Factors influencing purchase decisions and buying triggers
• Goals, motivations, and needs
• Core challenges and day-to-day pain points
• Job roles, annual income, organizations
• Lifestyle, interests, values, and hobbies
• Preferences (e.g., games, entertainment, sports, news, and reading)
• Influential news sources, social networks, brands, and shopping websites
• Resonating hashtags, products, pages, and content types
• Products purchased or likely to be purchased
• Industry-specific insights derived from customers' likely online queries

These details helped the marketing team spot and analyze the subtle differences in how each customer group approached internet service providers.

Moreover, the persona segments also included a Distribution tab that showed how each segment was spread across different attributes, such as:

• Age groups and gender
• Languages and locations
• Social platforms and communication channels
• Activity levels across marketing channels
• Topics that strongly resonated with each audience segment

This visual breakdown made it easier for the team to find engagement patterns and behavioral differences between segments.

Each persona further came with a Customer Journey tab that mapped the stages customers go through when evaluating an internet provider. This allowed the brand to see how different personas discovered, compared, and eventually chose internet services.

Bringing personas to life with digital twins

While research personas provided structured insights, the Digital Twin of Customer software gave the marketing team a more interactive way to engage with those insights.

The images shown in this post are for illustrative purposes only and are not actual representations based on real data.

Persona segments generated through the platform can be turned into digital twins – synthetic representations of real customer segments that users can chat with. Instead of simply reviewing persona profiles and drawing conclusions, teams can ask questions directly to their digital twins, such as:

• How would you react to this social media message?
• What kind of marketing content would catch your attention?
• What concerns would you have before subscribing to an internet provider?
• Does our pricing plan feel reasonable?

These conversations are powered by the same research data used to generate the personas in the first place. This means the responses reflect the motivations, preferences, and concerns associated with each customer segment.

The marketing team at WIN used the chat credits included in their plan to interact with these digital twins in Spanish, their local language, and to gain valuable insights from these “customer co-pilots”, available 24/7 for deliberations and feedback.

Once the twins were ready, they quickly became valuable brainstorming partners for the team. According to Jorge Igei Kohatsu, Digital Marketing Manager at WIN, “I really like the digital twins function. I got really interesting insights from them. We are onto synthetic users now.”

The team primarily used digital twins to:

• Test marketing messages to see how segments respond to different value propositions, tones, and positioning.
• Get early pricing feedback on potential pricing plans and promotional offers.
• Find content topics and formats that are more likely to resonate with their audiences.

The Results

WIN gained a more dynamic way to work with research data by combining personas with digital twins. Instead of relying solely on static market reports, they now had:

• Clear visibility into distinct B2C customer segments
• Detailed behavioral and preference insights for each group
• Interactive digital twins for idea validation and concept testing

The digital twins effectively turned customer research into an always-available feedback loop, empowering the brand to explore ideas without running time-consuming surveys or expensive focus groups.

Final Thoughts

Customer research is valuable, but only when teams can actually use it while making decisions. With the Research Persona and Digital Twin of Customer software from Delve AI, WIN was able to transform static research data into interactive customer simulations.

The result was a more practical way to understand audiences, test ideas, and create campaigns that resonate with their actual customers.

If you want to turn your research data into interactive user personas like WIN, try Research Persona by Delve AI and see what insights your data reveals.