Following is Part 1 of the Retail TouchPoints Analytics Optimization feature. This article will highlight research regarding retailers’ overall ability to collect, analyze and leverage customer data to create more relevant marketing campaigns and merchandising strategies. Part 2 of the feature will appear in the October 15 newsletter.
The browsing and buying behaviors of omnichannel consumers are evolving at a rapid pace. As consumers turn more to digital channels to browse and buy, some retailers are struggling to track shopping behaviors, preferences and insights across channels.
Data integration and analysis also are growing challenges, especially as retailers strive to create a comprehensive, 360-degree view of all consumers.
“Retailers are experiencing a ‘be careful what you wish for’ moment,” said John Lucker, Global Advanced Analytics & Modeling Market Leader at Deloitte, in an interview with Retail TouchPoints. “The availability of all this Big Data is presenting several new challenges and opportunities.”
The top challenge, Lucker explained, is that retailers are dealing with so much “digital exhaust,” that they’re focusing too much time and energy on managing data, rather than leveraging it effectively to improve customer experiences.
Businesses need to “learn how to effectively target customers without undermining the brand,” Lucker said. “Sometimes we that the messages being delivered to consumers are not highly relevant, nor did they display a keen understanding of individual customer preferences, needs and past purchases. This is a significant opportunity for improvement by retailers.”
Retailers across verticals are implementing business intelligence (BI) and analytics solutions to better understand and integrate these data points. According to the Aberdeen report, titled: Business Analytics and Unstructured Data: Are You Asking the Right Questions?, 45% of businesses are investing in more powerful BI and analytics solutions, especially to help better analyze unstructured data such as social media feedback.
More than half (52%) of all data an organization stores is unstructured, according to Aberdeen analyst Nathaniel Rowe. "Companies that had incorporated unstructured data — like text documents or social media analysis — into their BI architecture were able to get additional perspective on customer behavior and product reception."
Lucker explained that when used effectively, structured and unstructured data “can actually strengthen customer loyalty by demonstrating that the retailer deeply understands the unique needs of individual consumers.” As a result, businesses will be empowered to plan and execute more relevant marketing and merchandising initiatives.
Frank & Oak Tackles The Big Data Dilemma
As a growing brand, the mission of menswear eTailer Frank & Oak is to help young men dress and live well. Because the company sells exclusively through the e-Commerce site and mobile apps for iPhones, iPads and Android devices, the Frank & Oak marketing team has assess to an abundance of data.
Using solutions from RJMetrics, an SaaS BI and analytics company, Frank & Oak team members conduct custom analysis in order to understand key metrics and data that drive the business, said Ethan Song, Co-Founder and CEO, in an interview with Retail TouchPoints. “A Frank & Oak member can learn about a new product launch via a push notification on their phone, an email, a tweet, a Facebook or Tumblr post, an Instagram picture, and even via our new printed, quarterly magazine, The Edit. And typically, a member will interact with at least a couple of these touch points before they’re ready to come to the site to shop.”
As consumers hop across commerce touch points, Frank & Oak can collect and analyze this data, and then personalize site content, Song explained. “Purchase history, on-site browsing behaviors, and interactions with our different channels tell us what our members are interested in, and we’re able to craft relevant content as a result.”
Frank & Oak also recently unveiled StyleScape, a personalization platform that “only shows members the styles we know they’re going to like best,” Song said. “We get a few inputs for our data: members answer a brief questionnaire about their style preferences, previous styles the member has purchased, on-site behavior, in addition to what styles are trending in each shopper’s local area. This allows us to generate a custom, personalized shop for each of our members.”
Although Frank & Oak, like many retailers, still grapples with “data overload,” RJMetrics empowers team members to “make sense of it,” according to Song. “The combination of personalized shopping with custom, relevant marketing messages across channels is just the tip of the Big Data iceberg, but we feel we’re already ahead of the game.”
Embracing ‘Just-In-Time’ Marketing
Recent research from a variety of sources has confirmed the business-wide benefits of leveraging structured and unstructured data to personalize marketing and engagement strategies. As many as 61% of U.S. consumers said they feel more positive about a brand when marketing messages are personalized, according to research from Responsys.
The survey of 1,000 U.S. consumers also indicated that 53% of consumers are more likely to purchase from a brand that tailors digital communications ― perhaps since most consumers (64%) believe retailers that personalize offers and recommendations value their customers.
Overall, many retailers still are facing “a real-time challenge,” noted Rolf Anweiler, Regional Leader Marketing International at Teradata Applications. “Customers’ expectations of retailers are very high, and they expect the right offer through the right channel at all times. These high expectations are difficult to fulfill because there are a bunch of channels to manage and retailers can’t figure out how to do it effectively.”
However, other, progressive organizations are embracing “just-in-time” marketing, or sending relevant messages to consumers based on their most recent behaviors. Nearly two thirds (61%) of best-in-class businesses, as defined by Aberdeen Group, are delivering outbound offers customized to market segments. However, 48% of these companies are delivering outbound offers that are customized to individuals.
Tap customer behavior to segment and target marketing audiences (47% vs. 38%);
Optimize marketing offers and web experiences based on a buyer's social profile (42% vs. 22%);
Generate customer behavioral profiles based on real-time click-stream analysis (37% vs. 19%); and
Update customer profiles in real time or near-real time based on customer activity (32% vs. 23%).
“The combination of structured and unstructured data is where things get interesting,” noted Andrew Boyd, Managing Director of Content and Data Solutions at Harte-Hanks. “It allows us to combine classic value analysis, such as recency, frequency, monetary value, or customer lifetime value analysis, with sentiment to understand if high-value or high-potential customers are having issues. Moving forward, we see firms building an analytical infrastructure that allows them to respond quickly to unstructured buying signals.”
Runtastic Engages Users With Personalized, Real-Time Marketing
As a provider of fitness apps and activity tracking products, Runtasticrelies on customer data to make strategic decisions. More than 18 million registered users leverage Runtastic products to track distance, speed, pace, time, heart rate, calorie consumption and routes when running, biking and other physical activities. To keep users engaged and active on the apps, Runtastic is implementing data-driven marketing activities.
“It is really important that we get all the information we can from users so we can generate the most relevant campaigns for them,” explained Philipp Durstberger, Marketing Manager at Runtastic. “We’re getting a lot of data from them, which allows us to get a complete view of our users and their activity preferences.”
With the Digital Messaging Center from Teradata Applications, Runtastic can now send emails across different time zones, and tailor messages based on past behaviors and fitness goals.
“We’ll send users special emails and notifications based on their past behaviors,” Durstberger said. “We try to add value to our marketing messages and truly benefit our users, while also increasing revenue. For example, we’ll send cross- and up-sell suggestions based on their preferences and past achievements.
An activity-based segmentation model also empowers Runtastic to generate mobile-specific segmentations on customer data, so all emails and digital newsletters are optimized for multiple devices. Since partnering with Teradata Applications, email click-through rates have increased by more than 100%, and open rates have improved by 20%.
“Runtastic isn’t a traditional retailer, but this case study points to the importance of sending personalized offers in real time,” Anweiler of Teradata Applications said. “This is a good example that proves all organizations are moving in this direction. If customers have a specific need, you want to respond to that as quickly as possible.”
Look for Part 2 of Analytics Optimization in the October 15 newsletter.