Big Data for Retail
Big data for retail is a technology that nearly everyone in the industry needs to embrace as quickly as possible. As a decision maker in the home furnishing industry, you certainly know the importance of creating an exceptional in-store experience coupled with an easy to use and interactive online journey for your customers. You also know that you must have the right products available when, where and how customers are ready to buy. Leveraging the relatively new concept of ‘big data for retail’, both traditional and online retailers are finding it easier to both anticipate and meet customer demand across all buying channels.
Big Data for retail is changing the retail landscape at an incredible pace and every retailer who wants to survive in this brave new world needs to take advantage of every technology they can afford. In the April 18, 2018 issue of Retailer Now Magazine, Manoj Nigam, chief executive of MicroD, “encourages smaller retailers to work with providers who collect analytics on consumer behavior and can offer consolidated information that is normalized and shared by multiple retailers to provide insights on subjects like buying trends by region and pattern.”
The article points out several ways that smaller retailers and even Mom and Pop retailers can use “normalized and shared information”:
- Analytics and data mining of every transaction looking for shopping and buying patterns
- Data capture and analysis of every page visited by a customer along with the point of sale information
- Visual capture of store visits to track traffic increases and decreases matched against sales opportunities
- Development and tracking of “Key Performance Indicators” (KPI’s) and other metrics to properly set and manage expectations
- Simplified and more timely reporting to allow managers to make better decisions
- “Simulation, optimization and prediction” based on industry and individual company trends
- Acquisition, activation, and retention of data for better analysis
What is Big Data?
Every organization in the world is inundated with large volumes of structured and unstructured data. SAS, the grandfather of analytics processing says “it’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.”
With the introduction of cloud storage and server farms, the enormity of available data continues to grow exponentially and the companies who learn how to analyze the big data for retail can more accurately predict buying trends resulting in smarter purchasing decisions.
Big Data can help also retailers to make faster, more intelligent decisions. Data is collected from multiple sources including emails, mobile devices, applications, databases, cloud servers and elsewhere. Once the data is captured and manipulated it can help retailers to increase revenue, attract and retain customers and improve internal operations.
Retailers can “mine” publicly available data and match it to their own internal databases to understand where they may be missing opportunities.
Fast Data vs. Big Data
As users of big data for retail evolve they begin to understand there is another dynamic called “velocity” which can potentially alter how they acquire and use the data available to them. As VoltDb states, “fast data is fundamentally different from Big Data in many ways.”
They explain that while big data as most people understand it is “data at rest.” Fast data, on the other hand, is what they call “data in motion.” Fast data, as you would expect, has different characteristics which require a different approach. Because both in-store and online data is available literally in microseconds, tools must be developed that can capture, analyze and deliver actionable intelligence to decision makers in real time.
As this article in Furniture World points out, “Big Data . . . is no longer sufficient.” The patterns that present themselves from analyzing big data can quickly become outdated.” Fast Data, however, lacks the insights that more long-term data provides so combing big data with fast data provides an optimum solution for retailers wanting to avail themselves of the latest technologies in what Furniture World calls “the future of retail decision making.”
How to Use Big Data for Retail Sales and Operations
MicroD retail furniture and home furnishing customers are using another evolving technology called “Business Intelligence” which refers to “the analytical software that parses through vast amounts of data and delivers actionable insights.”
Creating actionable intelligence and delivering it in a user-friendly format, such as “executive dashboards” allows executives and managers to view website traffic, see exactly where and how users navigate through your site, view trends by product and understand how prospective customers find the website in the first place. Using this information, your purchasing people can know instantly what frames and fabrics are attracting the most attention and use this information to make real-time decisions on buying, stocking and other merchandising decisions.
When used properly, business intelligence allows retailers to focus on value-added, revenue-generating activities instead of wading through essentially useless reports about past buying activities. For example, they can view a dashboard of real-time activity generated directly from the company website and then tailor social media posts to include this information – “what’s hot today.”
Electronic Data Interchange
Although Electronic Data Interchange (EDI) has been used in the manufacturing world for decades, retailers have been slow to adopt the technology. MicroD predicts that 2018 may be the year to change all that and they point to the following trends to support that position:
- AR in your home – using “augmented reality” (AR) and 3D visualization, furniture, and furnishing customers can visualize how a piece of furniture will look in their room before they buy
- Website Performance – savvy online retailers know that a few milliseconds can mean the difference between gaining and losing a customer so they are ramping up performance
- Social Commerce – this evolving technology allows customers to buy directly from a post on Instagram, Facebook, and other social media platforms
- Machine learning – using artificial intelligence your systems can create a personalized buying experience for every individual customer
- Voice – Amazon Alexa and Google Home are great examples of how voice-driven technology can be used to interact with customers allowing them to research and purchase products online
How Furniture Retailers are Using Big Data for Retail
This Datameeer report examines how big data for retailers and other technologies are changing the retail landscape:
- Customer Behavior Analytics deliver better customer insights to improve conversion rates, personalize campaigns and increase revenue.
- Personalizing the In-Store Experience – In the past, merchandising was more an “art form” than any specific process. As online sales have increased, shoppers now perform their own research and savvy retailers capture the information real time. Online “people-tracking technology” allows retailers to analyze shopping behavior and measure the impact of merchandising efforts. Reporting platforms help optimize merchandising tactics while increasing sales.
- Increasing conversion rates through predictive analytics and targeted promotions- Data engineering allows retailers to directly correlate customers purchasing history with profile information captured from social media sites. The merging of these two different sources provides immediate, actionable intelligence.
- Customer Journey Analytics – because today’s tech-savvy customer is more connected than ever, they rely heavily on the opinions of others. They gather information from social media sites and rely heavily on the experience of others through the ever preset star rating systems. Customers expect retailers to maintain good relations with them and then vote with their money.
- Operational Analytics and Supply Chain Analysis – retailers have always understood the necessity to get the right products to the right places at the right time. Now they must learn how to use evolving technologies to optimize their assets for competitive advantage. Collecting and analyzing seemingly fragmented data from multiple sources ultimately leads to better decision making.
Big data for retail is something every retailer needs to understand and leverage. Traditional brick and mortar retailers are especially concerned about the erosion of their revenues and profits due to competitive threats from online retailers. They need to find ways to streamline business processes and maximize their time, money and resources to sell more both in-store and online.
To compete in the new world order created by Amazon, Wayfair, and others, retailers need to leverage information, automate order flow and improve data flow through the entire organization. They also must support dealers and distributors with cutting edge, cost-effective tools while keeping up with the changing expectations of today’s tech-savvy customers. At MicroD, our EDI for retailers is a big step in the big data world.
At the end of the day, they have must provide both an exceptional in-store experience for people who visit traditional locations and a streamlined and easy to use internet experience for those customers who want to shop online.