How would you like to be able to forecast which customers will buy your new product? Or forecast how your business results will change as more customers switch from shopping instore to shopping online?
A digital twin is an online replica of a business’s operations providing information both on current business performance and the likely impact of future stresses or hazards. Digital twins have become increasingly important in the world of manufacturing and construction – think of modelling the impact of vehicles crossing a bridge – and in managing complex real-world systems such as crowd control or transportation, even up to the scale of entire cities.
Today many retailers use Business Intelligence reporting to help them make strategic decisions, but this is generally restricted to seeing events through a rear-view mirror. You observe what has already happened but often struggle to relate those learnings to what might happen in the future. A digital twin changes the equation by focussing on potential future outcomes depending on what actions are taken today: How does the weather forecast for this weekend affect inventory requirements for different products? How will inflation affect customer purchasing patterns over the next few months? How will competitor activity affect store sales in different regions over the next year?
A Retail Strategy Director can then apply their judgement to decide:
A digital twin allows retailers to experiment with different scenarios including bold, risky strategies at negligible marginal cost, and provides answers in a matter of seconds. The ability to simulate thousands of potential scenarios allows a bricks-and-mortar retailer to develop a similar level of agility to an online retailer. Even if the actual execution of a new strategy may still take time, knowing in detail how customers will respond helps to shape how the plan is delivered and prioritise the right actions.
There are some similarities between the concept of a digital twin and the emerging Metaverse. Both involve digital representations of a physical world. The difference is that whereas in the Metaverse customers are generally represented by avatars that can be controlled in real time, in the case of a digital twin the customer is represented as a mathematical vector stored somewhere in the Cloud. And instead of shopping for products in real time, a simulation of a year’s worth of shopping for a single customer can be performed in milliseconds! The digital twin serves as a decision-making assistant for retailers, helping them predict what will happen next.
Today retail decisions affecting customers are often made in silos. The marketing team, channel team, and category teams all have objectives for growing sales, but their plans end up overlapping with little coordination. This leads to duplication of effort, increased costs, and a potentially confusing customer experience. A digital twin permits businesses to validate a complete set of plans in full transparency before investing time and money in their physical execution. When overlaid onto a digital twin of your retail environment, advanced Machine Learning algorithms optimise investment across different customers groups and channels thereby increasing profitability and customer satisfaction.
To paraphrase the late US business leader Jack Welch, ‘knowing more about your customers than the competition is the best source of competitive advantage’. With a digital twin, the more accurate that representation of the real world becomes, the better a retail business can adapt to keep their customers satisfied and keep them coming back. We foresee digital twins becoming a key instrument in the retailer’s toolbox for anticipating and delivering on rising customer expectations.
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