WTF Is a Digital Twin of a Customer?

By Tim Geenen, Co-Founder and CEO, Rayn

The concept of digital twins has existed since as far back as the 1960s to model the Apollo mission, and was applied when NASA first used simulators to analyse Apollo 13’s oxygen tank failure in 1970. Since then, digital twins – which are virtual representations of real-world objects or systems designed to behave in the exact same way – have been applied in numerous situations both within space exploration and outside of it.

While NASA’s mission control was able to use twinning to adapt to the issues being faced by the Apollo 13 and figure out strategies to bring them back down to earth safely, this concept has now been expanded to mirror everything from cities to people. And it’s in the latter area that digital twins can make a significant impact within advertising.

Finding a virtual self

Marketers were once able to rely on third-party cookies and other identifiers but, as these fade away and privacy regulation grows, they need to consider ways to continue delivering relevant advertising while ensuring they keep customer data safe.

The newest application of digital twins is digital twinning of customers (DToC) – a process which involves creating a virtual representation of consumers based on their online and offline interactions to help  predict audience behaviour.

DToC enable marketers to use synthetic audiences to establish and apply best practices to physical customers. They are built on first-party customer data, which is used to create cohorts of digital twins. Unlike static simulations, DToCs are dynamic living data sets. They can be supplied real-time data and continually be kept up-to-date to reflect their real-world twins.

Importantly, first-party data is only used as seed data, so personal data isn’t present in any form once a digital twin has been created. This can be achieved by leveraging generative AI models to output entirely synthetic data. Using synthetic data in DToC can in fact output more accurate results while being far more privacy-compliant.

That being said, some of the most exciting examples of DToC include:

Single customer digital twin
This is a dynamic model of an individual that heavily relies on being fed personal data and tracking information, but relates to someone who generally appeals to advertising.

Customer group digital twin
Created using the aggregated behaviours and interests of specific groups, customer groups digital twins can represent any size of group, depending on requirements.

Customer journey digital twin
A digital twin that is only specific to the data points relating to the customer journey.

Product usage digital twin
This digital twin would take into account how likely a consumer is to use a certain product, based on interactions with various customer service touchpoints, feedback from customers, the questions they are asking, and the reasons they choose to interact with customer service.

Customer behaviour digital twin
Digital twins in this category would be built with a focus on behavioural data points, such as sentiment analysis and engagement.

Solving problems before they start

DToC enables marketers to get an accurate sense of how consumers will react to a campaign, without having to first run the campaign, potentially saving both time and money. Digital twins mean that marketers can predict consumer behaviours in advance and can make changes before a campaign has launched, rather than having to make optimisations in-flight. In being able to anticipate customer behaviour, brands can also be more proactive in adopting measures to improve customer satisfaction, thanks to the ability of DToC to map out the customer journey.

In the current landscape, where consumers are demanding more personalisation, while privacy regulations are making it harder to do that, DToC helps brands to both deliver the best possible experience consumers actually want without having to test it all out in the real-world first.

Thriving without cookies

While third-party cookies may be disappearing, the amount of data available continues to grow. Advertisers need to keep investing in alternatives and as the industry moves away from cookie-dependent solutions, synthetic cohorts and DToC will be key tools for advertisers in understanding audiences and creating effective campaigns, while remaining privacy-compliant.

With recent growth of AI, synthetic data will have an important role to play in the coming years. As such, marketers should begin exploring how DToC may be able to help their business.

To start, it’s worth figuring out a specific use case where DToC may be effective, then experimenting with the concept there. This will create familiarity with the idea of digital twins in marketing and, as time passes, more and more data points can be added to the mix to make the DToC more sophisticated.

As marketers navigate their way through the obstacles currently facing the industry, they should be looking at the opportunity DToC offers to solve some of the challenges cookie deprecation brings. It will unlock better ways for marketers to serve relevant advertising to customers while, most importantly, respecting customers’ growing desire for privacy.

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