Finding Your Most Profitable Customers: Retail’s data ambition
To understand some of the radical ways in which consumer expectations are changing, let’s start with a scenario from the not-so-distant future.
A commuter finds herself admiring the running shoes worn by the person standing next to her on the platform. Asking the wearer’s permission, she takes a photo of the shoes and orders her own pair – knowing they will arrive just in time for her lunchtime run. Next, using the app of the coffee shop next to her office, she orders an espresso that will be ready at the exact moment she walks in. Then she asks a grocery store’s app to recommend the recipe she will feel like cooking later – asking them to deliver the ingredients she needs in time for her return. Finally, moments before her train arrives, she asks her friends’ view on a dress for an upcoming wedding and books a fitting appointment via the store’s chatbots.
All of this takes place in just a few short minutes and, as a scenario, is already a near-reality for millions of people. Simply put, consumers do not buy things like they used to. They want a deep and trusting relationship with brands, they expect to shop across multiple touchpoints and – above all – they have a growing interest in expertly curated, ultra-personal experiences that are sensitive to their habits and preferences.
Indeed, the latest research report from Accenture and the Retail Industry Leaders Association’s (RILA’s) (R)Tech Center for Innovation shows a strong and irreversible consumer desire for personalization. Whether it’s personalized wardrobe suggestions or tailored interior design advice, demand for curated expertise has risen by a third in just two years. What’s more, it’s growing particularly strongly among younger consumers, with around seven in 10 Millennials responding positively to personalized brand experiences.
But what does this mean for retailers today? After all, for each of the practical challenges presented by the above scenario, there are just as many opportunities. Retailers can’t afford to get left behind.
In response, we believe retailers should focus on using AI and analytics to track individual consumer preferences and profitability – thereby becoming “customerkeepers” – while identifying and cultivating the high-lifetime-value customers who drive growth.
The industry of customerkeeping
Once, retailers were “shopkeepers”. Today, they are customerkeepers. In effect, this means embedding a virtuous cycle of engaged employees that sell relevant products and services to happy customers – encouraging them to spend more.
Becoming a customerkeeper is far from straightforward, however. Brands that get it right combine world-class technologies with a deep understanding of consumer behavior (right down to their unarticulated wants and needs), the ability to communicate with warmth and humanity, and data mastery – all in real time.
And yet, thanks to advances in analytics and artificial intelligence (AI), the insight to deliver is now achievable for every retailer. This is the future of retail growth. But the real journey has only just begun.
Some retailers may assume that their internal capabilities are sufficient – yet significant investment and a different approach is needed. To look at AI as the one-stop solution for successful analytics would be misguided, for example. Before organizations can extract and exploit insights, they need to ‘teach’ their system using high-quality data. Low-quality data means the AI system produces distorted, inaccurate results that risk harming the business – instead of helping it. So, retailers have everything to gain from putting their datasets through rigorous vetting and cleansing processes before they’re deployed.
Achieving the data “impossible”
A data-driven mindset and discipline is a significant change for most retailers. But it is simpler and faster than many expect, and there are proven steps for achieving it. Like breaking down and integrating functional silos, acquiring data science and analytical skills, fostering a culture that welcomes change, and measuring what matters: which specific customers buy which specific items, where and how.
To generate maximum value from data, retailers should apply analytics on an enterprise scale, across areas including revenue drivers, marketing costs, fulfillment costs and digital levers for customer behavior. If they don’t, the misalignment between what customers want and what’s available could have detrimental consequences on profit and customer retention. Conversely, the aligned digitally-enabled organization will gain a true picture of how each consumer is behaving and how each product is performing. Then they’ll be in position to learn the right lessons from their data – by focusing not on margin-eroding, mass-market promotions, but on those high-value customers that deliver most of the profit.
Ultimately this is about taking a retailer’s insights and creating new business models centered around specific user needs and shopping styles. In this way, customer insights can be weaved throughout the whole business – with product teams leveraging data-driven creativity to understand their audiences, and marketing promotions grounded in insights about the profitability of individual products and customers.
Conclusion: Enabling the ubiquitous consumer
Like all technology-enabled developments in retail, what we see today is only an inkling of what will rapidly play out over the next few years. Already, we see the rise of “ubiquitous shopping” – consumers that expect to be able to buy anything they want, anytime, anywhere and anyhow. With this in mind, the industry leaders of tomorrow will be those that can identify lingering gaps in the consumer experience and use digital platforms to provide a reliable, satisfactory solution.
In turn, retailers at the beginning of their data journey are coming under greater pressure to catch up. Implementing AI and analytics technologies needs to become a priority. Brands should also strive to provide accurate, near-real-time answers to tough questions – around inventory shortages, new-customer acquisition rates and loss-making customer segments – and develop a credible plan for acting wisely on this information. If they can do so, they will be well-placed to win the loyalty of tomorrow’s consumer.
Jill Standish is senior managing director and head of Accenture’s Retail practice.
A commuter finds herself admiring the running shoes worn by the person standing next to her on the platform. Asking the wearer’s permission, she takes a photo of the shoes and orders her own pair – knowing they will arrive just in time for her lunchtime run. Next, using the app of the coffee shop next to her office, she orders an espresso that will be ready at the exact moment she walks in. Then she asks a grocery store’s app to recommend the recipe she will feel like cooking later – asking them to deliver the ingredients she needs in time for her return. Finally, moments before her train arrives, she asks her friends’ view on a dress for an upcoming wedding and books a fitting appointment via the store’s chatbots.
All of this takes place in just a few short minutes and, as a scenario, is already a near-reality for millions of people. Simply put, consumers do not buy things like they used to. They want a deep and trusting relationship with brands, they expect to shop across multiple touchpoints and – above all – they have a growing interest in expertly curated, ultra-personal experiences that are sensitive to their habits and preferences.
Indeed, the latest research report from Accenture and the Retail Industry Leaders Association’s (RILA’s) (R)Tech Center for Innovation shows a strong and irreversible consumer desire for personalization. Whether it’s personalized wardrobe suggestions or tailored interior design advice, demand for curated expertise has risen by a third in just two years. What’s more, it’s growing particularly strongly among younger consumers, with around seven in 10 Millennials responding positively to personalized brand experiences.
But what does this mean for retailers today? After all, for each of the practical challenges presented by the above scenario, there are just as many opportunities. Retailers can’t afford to get left behind.
In response, we believe retailers should focus on using AI and analytics to track individual consumer preferences and profitability – thereby becoming “customerkeepers” – while identifying and cultivating the high-lifetime-value customers who drive growth.
The industry of customerkeeping
Once, retailers were “shopkeepers”. Today, they are customerkeepers. In effect, this means embedding a virtuous cycle of engaged employees that sell relevant products and services to happy customers – encouraging them to spend more.
Becoming a customerkeeper is far from straightforward, however. Brands that get it right combine world-class technologies with a deep understanding of consumer behavior (right down to their unarticulated wants and needs), the ability to communicate with warmth and humanity, and data mastery – all in real time.
And yet, thanks to advances in analytics and artificial intelligence (AI), the insight to deliver is now achievable for every retailer. This is the future of retail growth. But the real journey has only just begun.
Some retailers may assume that their internal capabilities are sufficient – yet significant investment and a different approach is needed. To look at AI as the one-stop solution for successful analytics would be misguided, for example. Before organizations can extract and exploit insights, they need to ‘teach’ their system using high-quality data. Low-quality data means the AI system produces distorted, inaccurate results that risk harming the business – instead of helping it. So, retailers have everything to gain from putting their datasets through rigorous vetting and cleansing processes before they’re deployed.
Achieving the data “impossible”
A data-driven mindset and discipline is a significant change for most retailers. But it is simpler and faster than many expect, and there are proven steps for achieving it. Like breaking down and integrating functional silos, acquiring data science and analytical skills, fostering a culture that welcomes change, and measuring what matters: which specific customers buy which specific items, where and how.
To generate maximum value from data, retailers should apply analytics on an enterprise scale, across areas including revenue drivers, marketing costs, fulfillment costs and digital levers for customer behavior. If they don’t, the misalignment between what customers want and what’s available could have detrimental consequences on profit and customer retention. Conversely, the aligned digitally-enabled organization will gain a true picture of how each consumer is behaving and how each product is performing. Then they’ll be in position to learn the right lessons from their data – by focusing not on margin-eroding, mass-market promotions, but on those high-value customers that deliver most of the profit.
Ultimately this is about taking a retailer’s insights and creating new business models centered around specific user needs and shopping styles. In this way, customer insights can be weaved throughout the whole business – with product teams leveraging data-driven creativity to understand their audiences, and marketing promotions grounded in insights about the profitability of individual products and customers.
Conclusion: Enabling the ubiquitous consumer
Like all technology-enabled developments in retail, what we see today is only an inkling of what will rapidly play out over the next few years. Already, we see the rise of “ubiquitous shopping” – consumers that expect to be able to buy anything they want, anytime, anywhere and anyhow. With this in mind, the industry leaders of tomorrow will be those that can identify lingering gaps in the consumer experience and use digital platforms to provide a reliable, satisfactory solution.
In turn, retailers at the beginning of their data journey are coming under greater pressure to catch up. Implementing AI and analytics technologies needs to become a priority. Brands should also strive to provide accurate, near-real-time answers to tough questions – around inventory shortages, new-customer acquisition rates and loss-making customer segments – and develop a credible plan for acting wisely on this information. If they can do so, they will be well-placed to win the loyalty of tomorrow’s consumer.
Jill Standish is senior managing director and head of Accenture’s Retail practice.