The burden on fashion retailers has been never greater. Malls, retails stores, digital experiences and organizations are continuously being re-imagined. Shopper behavior and consumer sentiments add a layer of complexity, as they keep rapidly changing across countries and demographics. How can companies keep pace in this ever-shifting landscape?
Until recently, technology barriers were the main problem, yet those barriers are starting to fall. As they do, more and more companies have an opportunity to develop a coherent, comprehensive profile of their customers and effectively engage them across multiple touch points through the growing use of data-driven insights.
From instinct to analytics: the center of the omnichannel retailer’s universe
The heart of today’s heightened interest in analytics lies in the ability to understand, predict and shape consumer behavior. A revolution initiated by Walmart in supply chain management, and carried forward by Amazon proved that inside a company’s data lies undiscovered insights. Acting on them is essential to stand out in a crowded marketplace, battling the loyalty of well-informed, highly connected and newly empowered consumers.
This change in priority has inevitably shaped the future state of a fashion company - calling for customer insights to be an enterprise wide strategic capability, embedded deep within the organization’s structure and culture, and enabled by integrated business processes and information systems. According to McKinsey & Company, fashion retailers that are able to amass a larger volume of shopper data to inform the way they interact with customers can increase revenue from 10-20%.
Majority of retailers are trailing in analytics maturity
Retailers see the clear benefit of investing in analytics capabilities. But while the goal is clear, the path is not.
In fact, according to recent research by RSR, creating an analytics-driven organization is proving to be far from easy. While the pursuit of retail data continues and remains invaluable to support omnichannel goals, it’s taking time to navigate the challenges of implementing analytics at a broader, enterprise-wide level, which requires difficult cultural, technical and process changes.
As a result, the efforts are disorganized. Majority of retailers lack the best practices or strong analytics leadership to guide enterprise-wide investments. Instead, analytics projects are springing up department by department, without tying to an identifiable strategy. Although, it seems as though retailers are moving analytics up the maturity ladder, they are doing so in an unfocused way – which does not affect the bottom line the way they aspire to.
This has caused an undeniable gap between the promise of technology and the realities of retail as evident in an RSR survey, which depicts the slow analytics progression in the retail industry since the industry-wide discussion of data analytics began several years ago.
Despite retailers consistently ranking analytics as a strategic priority, when surveyed by RSR about the status of capabilities related to capturing and analyzing “Big Data”, less than ¼ of retailers claimed to be “satisfied” with what they had implemented.
Why do these initiatives get bogged down before they take off? Because capturing the potential of data analytics requires the building blocks of any strategic transformation: it begins with a plan, demands the creation of a team to really focus on data, and most importantly, addresses the cultural challenges needed to embrace the change. New tools alone are insufficient to help deal with challenges and impediments in scaling data-analytics efforts.
A company’s core processes can also be a barrier to capturing the potential of sophisticated analytics. For companies, like Amazon, processes have been built around a foundation of automated analytics. But in more established organizations, processes have not kept up with the advancements in data analytics and they are often faced with poor data quality, resulting from disparate processes and information silos. Getting the right analytics tools in places also loom as a huge challenge. These basic building blocks are critical to creating the bedrock on which analytics-driven organizations are built.
Filling in the gaps as the bar keeps getting raised
It is clear that retailers will not be constrained in their ability to improve their analytics maturity because of lack of tools, budget or data. Rather, it will be due to a siloed organizational structure, competing priorities, an unclear understanding of where to focus and lack of determination to embrace a data driven culture.
Yet for all the challenges it brings, the growth of retail sales is now inherently tied to how fashion companies leverage analytics. Lack of investment in this critical technology may result in a competitive disadvantage that negatively impacts the company for years. For example, early adopters like Ulta Beauty have seen sales growth by using customer data to create more personalized and targeted direct marketing, whereas retailers such as Bed, Bath & Beyond, who delayed investing on technology, have seen weak sales and margins as they struggle to resonate with tech-savvy millennials.
Similarly, companies such as Rockport and Brooks Brothers have already begun their omnichannel customer analytics journey by setting in place an enterprise-wide real-time data repository to generate insights across key areas such as real-time inventory, multi-channel sales and customer analytics.
We’ve broken down a few areas that fashion organizations need to focus on to improve their retail analytics maturity:
- Data Integration. Data integration is key to shedding light on the customer journey as multi-device and multi-channel journeys take twists and turns when consumers move from one channel to the next. The challenge lies in lack of processes and technology to access the right data, since data is often stored in multiple systems, and is often of poor quality – missing key data elements, incorrect and outdated, or existence of duplicate records on the same consumer. However, technologies such as SAP Customer Activity Repository are attempting to overcome these challenges by cleansing, auditing and consolidating data in one platform to provide retailers a holistic view of their customers, inventory and sales.
- A real-time data repository. Analytics depend on accessing the right insights at the right time. For retailers, it is key to have a robust foundation that collects and delivers a real-time view of not only customer-related, data but insights into inventory, pricing, promotions and more by accessing a wide variety of data types from multiple sources for an overview of business operations across all channels.
- Prioritizing the analytics needed to operate a successful business. Defining a long-term analytics strategy starts with the basics. Each retailer needs to answer the question, “What value are you trying to deliver?” in the context of their specific market. Part of designing a data strategy is defining the decisions that need to be made and mapping the right data to inform them.
Business analytics will only evolve further into a strategic capability that sits at the intersection of customer preferences, business strategy and business processes. For retailers, the time is now to begin embedding insights across their functional value chain and work on building a more customer-centric organization.