Following is Part 2 of the Retail TouchPoints Analytics Optimization feature. This article will highlight case studies and best practices for leveraging merchandising, social and marketing data to predict future purchase behaviors. Click here to access a PDF version of the complete report.
Without a single view of customers across all channels, retailers are facing challenges when it comes to implementing successful omnichannel marketing, engagement and inventory strategies.
However, the RSR report, titled: Omni-Channel 2013: The Long Road To Adoption, noted that retailers believe consolidating customer data (43%) and gaining better insight into cross-channel behaviors (35%) will help them overcome this challenge.
Collecting data, though, is only the beginning.
“What really matters is how you use that data,” noted Mark Simpson, Founder and President of Maxymiser, an online testing and personalization company. “It’s standard practice to use reliable platforms that can effectively analyze all of the data for you and work out what is most predictive now.”
To ensure digital marketing is relevant and compelling, brands and retailers “need to make sure that analyze and apply these insights right then and there, so personalized experiences can be served in real time,” Simpson added. “The brands that harness this immediate influence and power are going to see the biggest surges in ROI.”
Multichannel retailer OSP Group, for example, is harnessing conversions, clicks and other marketing performance metrics, to improve the online shopping experience. The company, which sells several retail brands, including fullbeauty, Jessica London, KingSize and Woman Within, has partnered with SiteSpect, a marketing optimization company, to implement multivariate testing and targeting.
“We started working with SiteSpect to conduct more in-depth testing on new campaigns, features and investments that we want to guarantee are up to par with customer expectations,” said Mathieu Clavie, Director of E-Commerce at OSP Group, in an interview with Retail TouchPoints. Using the solution, the retailer is testing multiple versions of banner ads, landing pages and offers, to ensure all marketing investments have a positive impact on the bottom line.
OSP Group also leverages SiteSpect to test new site functions and features. For example, the retailer recently experimented with the shopping cart experience, which Clavie calls the “checkout flow.” Using SiteSpect, Clavie and the e-Commerce team compared the results of the current five-page model, and a new single-page model.
After comparing the conversions of each layout, “we were able to validate that the single-page checkout experience was more effective,” Clavie said. “So we’re going to roll that out.”
More detailed customer segmentation also will be used to further personalize other marketing campaigns and initiatives. Although OSP Group hasn’t captured a 360-degree view of customers “we have an excellent database because a lot of our customers are repeat customers,” Clavie noted. The retailer also has captured customer data from its catalog business. “We have a lot of people coming from the catalog to the web site for quick ordering, so we’re able to identify those multichannel customers and give them specific attention.”
Clavie reported that overall, OSP Group is working towards “more granular segmentation efforts versus just working off of past purchase.”
Embracing Analytics To Improve Merchandising And Assortment Planning
Although marketing optimization is a key in winning and maintaining customer loyalty, it also is important that brick-and-mortar stores carry the products and brands that are relevant and desired in specific stores and regions.
Macy’s was one of the first retailers to tout product localization with its “My Macy’s” initiative. But as more retailers embrace analytics, they are reporting positive results.
For example, M.Video, an electronics retailer in Russia, has improved assortment control, forecasting and replenishment since partnering with Predictix, an SaaS merchandising solution provider.
As Russia’s largest consumer electronics retailer, bringing in approximately $5.2 billion in sales in 2012, M.Video sought to “take command of merchandising and supply chain processes,” according to Christopher Mangham, CIO of M.Video.
“We needed more accurate forecasting and planning decisions across all channels, in addition to building and improving our sales plan on a SKU and chain level,” Mangham said in an interview with Retail TouchPoints. “We also wanted to improve service levels and reduce both overstocks and stock-outs, allowing an even higher level of customer satisfaction.”
Initially, M.Video went live with the Predictix Demand Forecasting and Item Planning solution. The second phase consisted of implementing the Purchase Planning solution, which helped extend item planning “down to the distribution center and vendor level,” Mangham explained. “M.Video subsequently rolled out Predictix Assortment Planning, Store-Level Forecasting and Target Stock Optimization.”
Using the cloud-based solution, M.Video can create more powerful and accurate forecasts based on real-time purchasing patterns and consumer trends. Additionally, the retailer can easily alter the solution based on “the demands of Big Data, omnichannel retailing, and strategic and in-season planning and forecasting,” Mangham said. “This flexible platform also adapts to our changing business needs, which is helping us maintain a leadership edge in the rapidly growing Russian retail market.”
The Predictix solutions also extend across all enterprise applications, which helps create “one unified source” of data, analytics and demand forecasting. Silos are broken down, so the retailer can make better decisions as a fully integrated, omnichannel business.
“There are an enormous number of factors that influence consumer demand in an omnichannel world, and retailers must consider vast amounts of data when trying to understand the key influencers of demand,” Mangham explained. Predictix enables us to really understand what drives demand, and quickly adjust our assortments, forecasts and plans in-season. This allows us to better serve our customers, improve our service levels, and reduce both overstocks and stock-outs.”
Integrating Social Into The Analytics Equation
Although many analytics solutions provide retailers with a view of purchasing patterns and browsing behaviors based on structured data, they don’t necessarily address unstructured data, such as social interactions.
In turn, more retailers are embracing text and social analytics solutions. These offerings are designed to capture unstructured customer feedback, and help retailers connect the dots between hard data, customer experiences and overall brand sentiment.
Analysis of unstructured social and other text data can help businesses “identify process failures that impact the customer experience,” noted Andrew Boyd, Managing Director of Content and Data Solutions at Harte-Hanks. “Customer sentiment doesn’t stay private for very long in the age of the empowered, social customer, so being able to identify sentiment issues is now an imperative.”
For example, DICK’s Sporting Goods recently implemented the platform from newBrandAnalytics (nBA), a social intelligence solution provider, to better track, evaluate, and respond to social media feedback. By integrating social insights into in-store and online CRM data, the sporting goods retailer can keep a constant pulse on customer sentiment and constantly monitor and improve the cross-channel shopping experience.
“Our CRM analytics team has a plethora of data, but there was a huge gap when it came to humanizing that data,” said Ryan Eckel, VP of Brand Marketing at DICK’s Sporting Goods, in an interview with Retail TouchPoints. “Numbers can tell you what’s going on to a certain extent, but there is extreme value in social media because it tells you why you are getting specific results.”
Eckel added: “At the end of the day, we’re dealing with humans, not collections of numbers. With nBA, I’m able to really keep pace with how people perceive the brand, then pull levers at the store level to improve customer experiences.”
Social listening and analysis also plays an important role at Frank & Oak. Because the menswear retailer was built on community and communication, the team “loves” to engage with members “and some platforms, like Twitter, facilitate this,” according to Ethan Song, Co-founder and CEO of Frank & Oak.
“But generally, we don’t think in terms of ‘mining’ and ‘harvesting’ data,” Song added. “Instead, we just make sure we’re a part of the conversation in an authentic way. If a member posts a picture on Twitter of his new shirt, we’re happy to ‘re-tweet’ and thank him for sharing. When we do this, we know that this specific shopper is more likely to spread the word about Frank & Oak in the future.”
Social media also is empowering Frank & Oak to address customer service issues, and even provides intelligence into future products.
“Because our members are from the most digitally-savvy generation, they aren’t shy about reaching out on Facebook or Twitter to let us know what they think, which we love,” Song said. “It not only gives us an opportunity to fix problems in real time, but it’s also an important feedback loop for our web and product teams. Our users give us great data on what they think about the clothes, the web site, our apps, and because we’re so agile, we incorporate a lot of what they say into the next release of our products.”
So what will the future of analytics hold? According to Boyd, the future of analytics optimization revolves around business’ overall ability to “combine classic value analysis with sentiment to determine if high-value and high-potential customers are having issues. Moving forward, we see firms building an analytical infrastructure that allows them to respond to unstructured buying signals within an optimal timeframe.”