As we all know, consumers don’t approach shopping like they used to. The changes they’re undergoing are both profound and interconnected — ranging from a growing desire to connect with brands, to usage of a vast array of new retail touchpoints, through to a rising preference for expertly curated ultra-personal experiences.
The latest research report from Accenture and the Retail Industry Leaders Association’s (R)Tech Center for Innovation reveals a strong and growing consumer desire for personalization in areas ranging from design ideas to recipes, both in-store and online.
Take design ideas. Whether it’s personalized wardrobe suggestions or tailored interior design advice, the study shows demand for curated expert service has risen by a third in just two years. What’s more, it’s growing particularly strong among younger consumers: 69 percent of Millennials expressed interest in personalized brand experiences.
Retailers need to be in a position to track individual customer preferences and profitability, identify and cultivate the high-lifetime-value customers who drive growth, and liberate the retail experience by enabling “ubiquitous shopping” — consumers buying anything they want, anytime, anywhere, in any way they choose. What does this look like practice?
Here’s an everyday scenario…
A commuter — let’s call her Jenny — arrives at her local bus stop a few minutes early in the morning. As she waits, she sees an ad for the latest running shoes. She snaps a picture on her phone, finds the item for sale and makes a purchase there and then.
On the bus, she pre-orders a latte and picks it up at the coffee shop next to her office. Later, she remembers she has friends coming for dinner that evening. So she uses her grocery store’s voice-enabled app to browse recipe ideas and arrange a delivery for when she gets home.
On the bus back, she chats with friends on social media, asking for ideas for what to wear to an old schoolmate’s wedding. Having found the perfect outfit from a local store, she books a fitting right away via the store’s chatbot. As she does so, she notices the store is hosting a wine-tasting event that weekend. She instantly sends out an invite for her friends to join her there.
Breakthrough visibility — and ubiquity — leveraging analytics-driven insight…
For retailers, now is the time to undertake a fundamental and radical shift — from “shopkeeper” to “customerkeeper.” When a retailer centers its whole business around serving its customers, everything changes. It creates a virtuous cycle of engaged employees providing relevant products and services to happy customers — encouraging them to spend more.
Getting to the point where it’s possible to give customers exquisite, personalized, seemingly spontaneous experiences takes some real genius behind the scenes. For brands and retailers to do this, they’ll need to combine world-class technologies with a deep understanding of customers’ behavior (along with their unarticulated wants and needs), the ability to communicate with warmth and humanity, and data mastery — all in real time.
Thanks to advances in analytics and in artificial intelligence, 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. Many retailers think their current internal capabilities are sufficient — yet the reality is that significant investment and a different approach is needed. For example, to look at AI systems as the one-stop-shop solution for successful analytics would be misguided. 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.
…across the enterprise
There’s no sugarcoating the fact that embracing a data-driven mind-set and discipline is a significant change for most retailers. But it can be simpler and faster than many might 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 the maximum value from this data, retailers need to apply analytics on an enterprise scale, across areas including revenue drivers, marketing costs, fulfillment costs and digital levers for customer behavior. The misalignment between what customers want and what’s being made available could have detrimental consequences on profit and customer retention. According to the DynamicAction Retail Index: “2018 Analysis & Holiday Outlook,” available inventory that shoppers were actually viewing was down 3 percent year-to-date 2018, with an average decrease of 13 percent in the month of August 2018 versus August 2017. A strong indication that as retailers headed into a significant seasonal shopping time period — Labor Day — shoppers were not able to find the items they truly wanted to purchase.
The aligned digitally enabled organization will gain a true picture of how each individual customer is behaving and how each product is performing. Then they’ll be in a 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.
This is about taking all of a retailer’s customer 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, for example, product teams leveraging data-driven creativity to understand their audiences, and marketing promotions grounded in insights about the profitability of individual products and customers.
Key questions to ask
So, as a retailer, how can you be sure you’re maximizing the value of consumer data? Here are some key questions to ask yourself:
- What percentage of your upcoming revenue plan will come from existing customers?
- What’s your rate of acquisition of new customers?
- What’s your rate of repurchase from 1st to 2nd, 2nd to 3rd, 3rd to 4th, 4th to nth? And how do those rates trend over a 12-month period?
- What percentage of your customer base is loss-making?
- How much of the inventory that your customers want to buy do you have in stock?
If you can answer these questions with certainty, your data use is probably in pretty good shape. Anything less, and it’s time to think about radically upgrading your data and analytics capabilities — or the insight gap will impact your bottom line.