In the retail industry, opportunities for big data analytics are galore.
“The world is one big data problem,” according to Andrew McAfee, the co-founder cum co-director of the MIT Initiative on the Digital Economy, and the retail sector is no exception to this statement.
We all know the Walmart story, for example. Back in 1987, it was steamrolled by competition from Kmart. Then, in 1990, Walmart’s revenue exceeded Kmart's by $2.9 billion despite having fewer stores than Kmart.
Since then, there has been no looking back for the retail giant.
The Power of Data in Retail
The Walmart Story
At present, Walmart captures 2.5 petabytes of unstructured data from 1 million customers every hour. The company’s sustained investment and focused effort in becoming a data-driven organization have paid off.
But, what does Walmart do with this data?
- Firstly, they enhance their marketing strategy with rich customer data covering more than 145 million Americans. This plays a major role in drawing more and more customers into Walmart stores–both brick-and-mortar stores and via eCommerce.
- Secondly, they use behavioral insights to predict and influence customers’ shopping behavior within their stores. For example, by analyzing a customer's credit card purchase history, personalized shopping recommendations are provided.
- Finally, instead of playing catch-up with data, they do all of this in real-time. This means that their in-line inventory, sales activities, and promotional offers are all backed by up-to-the-minute insights for optimum results.
Thus, it is evident that Walmart has aced the data game in retail.
But, does it mean that the benefits and superpowers of retail analytics are reserved only for the large players in retail–i.e., the Walmarts of the world? Not necessarily.
This is where FORMCEPT comes in. We democratize AI-powered analytics for businesses of all sizes across a wide range of sectors, including firms in the fast-evolving retail industry. In this blog, we share with you how retail companies can survive the hypercompetitive environment with MECBot–our award-winning data excellence product.
The Retail Analytics Landscape
#1 Retailers are recognizing the importance of data
Most retail companies have warmed up to the idea that data-centricity is the key to success in this industry. For example, a survey conducted by Alteryx and RetailWire across ~350 retailers and brand manufacturers revealed that 81% of respondents gather shopper insights and 76% consider these insights critical to their performance. Another study by Forrester found that 74% of retail firms say they want to be data-driven.
#2 Deep personalization is on the rise
Interestingly, the personalization of offerings in retail is happening at a higher rate than ever before. Studies show that 86% of consumers feel that personalization plays an important role in their purchase decisions. In e-Retail, product recommendations are even more personalized using data such as the user’s search history, search histories of similar users, time of the search, socio-demographic profile of the user, and so on.
#3 In-store analytics and mobile marketing are gaining ground
Another study revealed that 76% of the buying decisions are made in the store. This means that in-store analytics like store layout and design, point-of-sale analytics, and prescriptive analytics for product arrangement and display are extremely relevant. Parallelly, omnichannel marketing analytics has gained prominence because 77% of shoppers use a mobile device to search for products.
#4 Innovation in retail is creating unprecedented opportunities
The advent of technology such as sensors, RFID tags, QR codes, NFC tags, and beacons has opened up a whole new vista. They can facilitate personalized experiences and in-store promotions in real-time while customers are picking products off the shelves. For instance, when a customer uses a store's mobile application and approaches a display, a message can be sent directly to their device.
#1 The ability to harness value from data remains a puzzle
Merely 16% of retail merchants consider themselves as “experts” in generating insights from data, whereas 24% and 60% of retail merchants describe themselves as "newbies" and "getting there," respectively. This means that the struggle is real when it comes to deriving value from data. Interestingly, merely 29% of retailers believe that they can connect analytics to action. Data also often turns stale by the time it is put to use. This makes timely decision-making with updated data hard to accomplish.
#2 Surge in the cost of customer acquisition
Retail marketers are currently paying more for each lead as the average cost for a retail lead has increased to $34. Ad spending in retail continues to rise. With the average customer conversion rate in retail hovering around 3%, retailers are spending more to acquire new customers but are failing to convert leads fruitfully.
#3 Difficulty in mapping the customer journey from start to finish
Retail is characterized by complex customer journeys that are spread across multiple channels, devices, and touchpoints. Creating a complete picture of the customer journey is at the heart of impactful personalization. Yet, according to a study, 30.9% of retailers are unable to “track consumers across devices”, while 38.2% can only track “some consumers some of the time”. Put simply, retail marketers lack a single source of customer truth.
#4 Lack of trusted data and auditable insights
Accelerated data volume, variety, and variability are causing an erosion of trust in retail data. With much of retail data being sourced externally, data quality is on a slippery slope. Bad data makes even the best models doomed to failure. Furthermore, once within the analytics environment, loss of data lineage occurs and insights become less and less auditable with time. This makes it harder for retailers to rely on their data as the trusted navigation system for decision-making.
A Leading Data Excellence Product Harnessing AI and Big Data Analytics
MECBot by FORMCEPT is a frontrunner in the unified data analytics space. It is fueled by high-end AI and data science technologies that are orchestrated to put the business first and not the data. It is an integrated product to enable insight-driven decision-making just in time without having to rely on the underlying databases or the structure of the data. Put simply, MECBot uses cutting-edge AI to automate data sourcing, pre-processing, discovery, analysis, and visualization in real time.
How It Works
#1 MECBot Automates Data Preparation: MECBot directly captures the data from pre-configured sources and maps it to the Business Domain-Entity Model specified by the user. It then cleans, pre-processes, and contextualizes all data to create a Smart Data Fabric or an Enterprise Knowledge Graph.
#2 MECBot Removes Enterprise Dark Data: Using the concept of Linked Data, MECBot can understand unstructured data across various domains (industries). It achieves this by combining MECBot’s built-in Universal Knowledge Base with Domain and Tribal Knowledge Bases to understand data from multiple facets.
#3 MECBot Fosters Smart Data Discovery: MECBot culls out the relevant information to match the context of the user’s query and then visualizes the data using intuitive representations. It reveals hidden data connections automatically without depending on the user's query. It is not limited by the underlying datasets, schema, or algorithms.
#4 MECBot Enables Natural Language Query: Business users without a technical background can query the enterprise data and insight grid in the natural English language without having to do any coding. MECBot generates actionable insights for the query and creates a comprehensive recommendation engine for the next best steps.
#5 MECBot Supports Custom ML Applications: MECBot.ml enables Data Scientists, Citizen Data Scientists, Data Analysts, and Domain Experts to run multiple ML models on their data and choose the best one that fits their data, without worrying about scalability, infrastructure, or the configuration of various tools.
Retail Analytics by MECBot
MECBot’s Retail Analytics Stack
#1 Customer 360°
MECBot’s Customer 360° feature seamlessly combines diverse customer data from various sources like CRM, product databases, customer service records, industry reports on customer behavior, and multi-channel interactions of customers online.
It unifies and aligns fast-moving customer data streams from three key avenues as outlined below:
- Demographic, Transactional, and Behavioral Data on customers,
- Product, Sales, and Marketing Data generated within the enterprise, and
- Data collected and extracted from customers’ Feedback, Reviews, and Inquiries.
Essentially, MECBot ties together all customer data to create a unified view and single source of truth for each customer and each market segment. This happens automatically in a self-orchestrated manner. The insights are served in a self-service environment that requires no coding by the user. Retailers can take a deep dive into the unique needs and traits of each segment or group of customers and get smart recommendations to improve product penetration in that segment.
#2 Marketing ROI
With a vast number of marketing and promotion channels to be tackled across both physical and digital platforms, retailers are often at a loss. Getting the most out of their Marketing Budget is an age-old problem that retail marketers have been grappling with. MECBot’s Marketing ROI module is specifically designed to solve this problem.
It collates the marketing data of the enterprise as well as that of the industry and analyzes it to indicate which channels and marketing avenues are likely to bring more success. If competition data is available, which is often the case in retail, it can make smart comparisons to glean insights into the specific marketing strategies of competitors that can improve a business’s bottom line.
#3 Operations Management
Retail operations, processes, and supply chains are highly complex and often require the simultaneous contribution of many human as well as machine elements. While boosting revenues by acquiring and retaining customers is critical, equally important is the aspect of cost and time management.
MECBot can help with operational decisions like optimizing store layouts, finding new store locations, optimizing purchases and logistics processes, reducing transportation costs, improving delivery time in eCommerce, and optimizing inventory management across stores and warehouses. MECBot can also help to boost the productivity of customer service staff and other frontline employees who often need the right insights at the right time to execute their jobs efficiently.
How Can Retailers Benefit from Using MECBot’s Just-in-time Approach to Decision-making?
#1 Intelligent Segmentation for Better Personalization
Using MECBot’s Customer 360° feature, retailers can always stay ahead of the curve. They can perform intelligent segmentation of the customers and serve each segment better with personalized offerings that resonate the most with them. They can use MECBot’s predictive and prescriptive analytics to drastically improve the customer experience just in time.
#2 Churn Rate Optimization for Improved Loyalty
Retailers face a unique challenge when it comes to customer stickiness. At the heart of this challenge is the fact that retail customers usually have a lot of choices available in the market. Hence, competition is stiff and brand loyalty needs to be earned. MECBot’s loyalty analytics module identifies what works and what doesn’t in retaining customers and helps to reduce the rate of customer churn significantly within a short window of time.
#3 Optimizing Marketing Budget and Sales Efforts
With thousands of stores, outlets, channels, devices, and locations, having MECBot as a partner can ease the process of optimizing marketing and sales efforts. MECBot is intuitively capable of analyzing the revenue potential of various marketing and sales opportunities and delivers suggestions for improvement by keeping the focus on improving Marketing ROI. It is like having an in-house marketing expert to advise you on various aspects in a data-driven manner and doing so using just-in-time decision-making.
#4 Reducing Inventory Costs & Boosting Productivity
Inventory and stock management in retail is one area where costs can quickly go overboard if one is not careful. MECBot becomes your eyes and ears in keeping inventory costs at bay while boosting in-store productivity through expert recommendations on lead-time management, avoiding stock-outs, predicting peak demand cycles, optimizing the allocation of shop-floor staff and resources, and so on.
#5 Unlock Cross-sell & Up-sell Opportunities
MECBot also plays a key role in helping you capture a larger pie of the customers’ wallets. This is made possible by MECBot’s exceptional capabilities in identifying growth opportunities through up-sell and cross-sell. MECBot understands customer behavior like a marketing manager and can correlate large volumes of data on customer needs, behaviors, and preferences. This way, it can generate automated, intelligent insights on what products need to be pushed into a customer segment on top of the existing products, or what kind of service add-ons can bring more value to the customer. Thus, it unlocks sales opportunities through both cross-sell and up-sell using Customer 360° and rich segmentation analysis in a multi-variate manner.
Wish to take a deep dive into what MECBot can do for your business? Request a demo here: https://formcept.com/contact-us