Want more Insights from SAS? Subscribe to our Insights newsletter. Or check back often to get more insights on the topics you care about, including analytics, big data, data management, marketing, and risk & fraud.
Big Data = Big Opportunities for Canadian Retailers
By: Shawn Smith, Sr. Solution Specialist, SAS Canada Retail Practice
It’s been a troubling year for retail in Canada. A new Stats Canada report reveals that December 2014 retail sales were down 2% in the busy holiday season. Combined with the recent closures or financial distress of retail outlets like Sony, Mexx, Smart Set, Target, Jacob and Bikini Village, the trend is clear: All is not well with Canada’s retail sector. Yet luxury retailers the likes of Nordstrom, Saks and Jimmy Choo are expanding in Canada, vying for a piece of Canada’s $1.6-billion luxury apparel market. While they are very distinct in demographic focus and customer segmentation, one thing that each of these retailers have in common is data. Lots of data. Big Data.
Whatever their customer segment or demographic focus, retailers have the opportunity to improve customer-centric and operational decision-making by building deeper insight from a massive stream of internal and external data.
Today’s retailers have access to vast stores of data that allow them to create a personalized retail experience that customers have come to expect. Used in the right way, data analytics can be the key to bringing customers in the door, building a better online experience, or simply helping weather slow periods by allowing faster, more efficient and more nimble supply chain changes. Whatever their customer segment or demographic focus, retailers have the opportunity to improve customer-centric and operational decision-making by building deeper insight from a massive stream of internal and external data. Analytics technology can help struggling retailers compete and thrive in today’s tough marketplace. Here’s how.
Big Data and Hadoop
Big Data is important to every line of business and industry. But marketing is a key passenger on the Big Data bus. In many ways, marketing was doing Big Data before it was Big Data. Concepts like segmentation, offer management and propensity to turnover have always required data and analytics. Big Data doesn’t change the marketer’s role. It encourages it to evolve. It allows marketers to use all data, not a just sampling, to do what they have been doing for years. It also opens the door to using data in ways they’ve only dreamed about.
The explosion of Big Data has fostered the Hadoop ecosystem, which, in turn, has marketing professionals awash in a sea of acronyms and buzzwords. Hadoop is simply an environment for storing and processing data. Huge volumes of data, certainly, but it’s still a tool to be mastered, not to be ruled by. As the amount of data we collect increases, Hadoop will enable marketers to leverage that data to move a customer to conversion, by providing context about how to deliver the most relevant offer to the customer.
The Mobile Retailing Experience
Today’s consumer is more connected than ever before. It’s staggering when you think about it: A single device that we keep in our pockets can be used to review products, check prices, share purchases, request coupons – and sometimes even to purchase products from one retailer’s online channel while standing in a competitor’s store. In this always-on culture, consumers are more demanding in how companies interact with them. Today’s consumer wants the right message delivered to the right channel, to the device of their choice, at the time of their choosing. As mobile devices continue to proliferate, marketers will need to understand the needs of the mobile user and be ready to deliver real-time, relevant communications with each and every customer communication.
In many ways the mobile phone has turned into our own personal shopper .The rise of beacon technology is making this a reality. Beacons are hardware sensors designed to wirelessly communicate and transmit data to mobile devices within a specific proximity. Beacons can be used for a bevy of in-store purposes, including geolocation, targeted messaging and shopper analytics. But in order to get the most out of beacon strategies, retailers must combine the technology with analytics to enable a shopping experience that is truly personalized and of value to the shopper.
A Personalized Customer Experience
Offers, advertisements and marketing messages can be sent from every possible direction, but savvy marketers must be careful not to bombard consumers’ senses. In an ideal world, consumers receive messages that are tailored, relevant and timely, and offered to them based on their actions and behaviours in the past--or better yet, how they might act or behave in the future. These personalized offers must be consistent regardless of the channel through which it’s being delivered and seem unique to the individual receiving them.
This is the experience customers have come to be expect, and only analytics can drive the type of real-time insight that underpins personalized marketing.
Personalized marketing and promotions can also help improve customer loyalty. By tailoring messaging or promotional offers to customers based on their preferences and past behaviours, retailers can establish a more personal relationship with the customer. Not only does this give shoppers a positive and personalized experience, but it can also help increase sales. Research from SAS has found that nearly half of smartphone owners would be more likely to return to a store that sent personalized promotions to their phone while they were shopping. In short, customers who receive personalized deals buy more and come back more often. Yet, according to SAS’s 3rd Annual Analytics in Retail Study, only one in 10 Canadian retailers make customer profiles available to merchandising and marketing teams in real-time. Retailers have access to mountains of behavioral customer data, but if they’re not effectively listening to what the data is telling them, then it’s of no use. A data analytics solution is integral to optimizing marketing strategy for retailers and ensuring customers are being offered the right deals for them.
Rewards-Based Incentive Programs
As the saying goes: You scratch our back, and we’ll scratch yours. This premise is especially important when it comes to gathering personal data from your customers: It should be give-and-take. When you can show consumers the value they receive by sharing data, they’re more likely to opt in. Customers know that their data is valuable, and they need to feel secure in giving it and assured that they’ll see a return on their data sharing. This means they expect retailers to make their information count, in the form of a personalized discount or recommendation for a complimentary item to something they recently purchased. Research from SAS has found that nearly three quarters of Canadians expect that, when they give a company personal information, such as their age, email address, income or birth date, the company will use that information to tailor promotions to them personally. Loyalty programs are only as good as the loyal customers they generate. And this means they’re only as good as the personal touch they add for customers.
A major obstacle for retailers is finding the perfect balance between out-of-stock and overstocked. When it comes to inventory, there is a crucial difference between planning based on activity from the previous year and making informed decisions using much more accurate forecasting based on solid insights. This is the difference between hindsight and the kinds of insight and foresight made possible by analytics. Analytics can help anticipate customer demand by identifying factors that might affect consumer needs. For example, a retailer stocking sports equipment can be prepared for an increase in demand for soccer jerseys before the start of the season. At a deeper level, analytics can help a retailer plan for a baby boom. Based on buying habits, data insights from predictive analytics might indicate an increase in growing families in a younger community. Now the retailer can plan for increased diaper sales, or other sales of items new parents need. Effectively utilizing analytics can help retailers optimize inventory management across facilities, distribution networks and products.
Let Your Data Work For You
The data onslaught is both a challenge and an opportunity for retailers. For most, accessing customer data isn’t the issue. The issue is what to do with it once you have it. Analytics can provide a deeper understanding of who your customer is, and what they value when it comes to the products and services you provide. Namely, it opens the door for retailers to interact with customers more purposefully and to become more personalized in those interactions. With the use of data analytics, retailers can help guide their marketing strategy and inventory decisions to truly serve the modern and much empowered consumers’ needs.
Originally published in Direct Marketing Magazine
Senior Solutions Specialist, SAS Canada Retail Practice
Shawn Smith is a Senior Solutions Specialist in SAS Canada’s Retail Practice. In his current role, he is responsible for helping clients gain value from current and future investments in analytic retail technologies. Shawn has extensive knowledge and expertise in retail analytics, and in devising and executing strategies to better understand shopper behaviour and omni-channel evolution.