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Retail Analytics

Challenges faced by Companies in Retail Sector

Because of the least inventory cost and broad difference of commodities for the consumers to choose from the e-commerce, it has an enormous impact on the brick and mortar stores. The customer is highly spending more time and money on certain commodities and moving far away from the sales is yet unknown for stores. Assigning the products such that involving the survey level, the complete store is a problem that might annoy the retail store owners for ages. The retail analytics company wants to draw attention to the customer to implement the various products' firsthand experience. The retail sector is having many problems in this current age, such as:

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To administer retail data, analytics is the solution for SMEs using Big Data. The consumer's 360-degree view will help the dealers efficiently with the customers to picturise. To identify and sell particular shelves to the manufacturers is the only solution for in-store retail analytics. Big data analytics will help us run the day-to-day operations in staff marketing, manage stocks, manage the supply chain, develop unique strategies based on marketing analytics, etc.

Case Study 1:How to view your customers in 360 Degrees
Business Problem Statement

Customers give away their behavioral data through various sources & forums. Tapping into this data & drawing meaningful insights is a nightmare for the best of the companies.

  1. How to identify the various sources (direct & indirect) of customer data?
  2. How to bring that data into a common format?
  3. How to use the data to take proactive actions?
  4. Most interestingly, how to get an overall view of the customers?

These are the challenges which companies are struggling to address.

Business Challenges

  • Processing instantaneous information about customers from big data (structured and unstructured) collected from various sources
  • Identifying potential buyers from all customers based on the history of buying pattern, items searched online, social media usage, etc.
  • Targeting customers with personalized offers for products based on shopping pattern, social status, social activity, demographics, etc.
  • Effectively addressing customer requirements and increasing customer satisfaction

Business Solutions

  • Using various big data solutions such as Hadoop / spark, data can be extracted and integrated from various sources and transformed into information about customerS
  • Segmenting potential buyers into different groups. Focus your attention on the most efficient and profitable segments rather than the insignificant, unproductive, and unprofitable segments.
  • Single source of data about customers help in personalizing offers and to provide right offers at the right time, in the right location and in the right context
  • Predictive model is built to study the patterns of customers and provide proactive service to retain them
  • Sentiment analysis performed on data from customers’ social media pages and web, helps in upgrading the services accordingly

Business Impact

  • Single view of all aspects of a customer
  • Proactive service to customers
  • Quick responses and solutions to customers
  • Improve in quality of service provided
  • Increase customer satisfaction
  • Customer retention

Case Study 2: How to identify procurement fraud (Inventory purchases for retail)
Business Problem Statement

Procurement management is one of the key departments of any organization. Procurement happens in the space of hardware, software, human resources, goods, etc., & there have been a lot of instances of fraud in the transactions of the same. If suppliers & procurement department join hands to commit a fraud then it is extremely difficult to identify it. It is even worse given that the fraud transactions happen under-the-table, off-the-records. This will leave a deep hole in the cash pockets of organizations leading to losses to the tune of millions of dollars. Companies are finding it very hard to identify such fraud events by applying traditional accounting practices.

Business Challenges

  • Many instances of fraudulent transactions as employees purchase the goods
  • Increase in vendor-employee collusion, thereby increasing conflict-of-interest norms of company
  • Decrease in profits because of illegal means of winning the procurement bid
  • Decrease in quality of the material procured because of collusion of stakeholders

Business Solutions

  • Built probability based prediction model to get the probability of material procured being fraudulent given that employee purchasing it or vendor dispensing it or PO line number procuring it
  • Network analysis using Gephi & NodeXL to determine the centrality measures in identifying the closeness between employees & vendors based on the material procured
  • Descriptive analysis of the various variables leading to interesting insights on what type of transactions could be fraudulent

Business Impact

  • Reduction in the number of fraudulent transactions
  • Reduction in the illegal bids leading to improved profits & quality
  • Reduction in inflated invoices
  • Increased confidence in the vendor evaluation process

Case Study 3: How to use customer segmentation for better targeting with personalized tailor made marketing ads
Business Problem Statement

Business Problem Statement: Majority of profits for a company lies in the repeat orders and repeat customers. Businesses which are customer-centered would tend to focus much on retaining customers. Many of the companies fail to lure/attract customers due to lack of strategies, action plans etc. It's much more hard to acquire a potential customers than to continue an active customer. Companies often ignore this fact and try concentrating on increasing new customer base leading to poor performance.

Business Challenges

  • Not targeting customers with personalized offers is discouraging them to maintain relationship with retailers and to make more purchases
  • Ineffective means of addressing customer requirements is reducing customer satisfaction & increasing the churn rate
  • Data from too many sources to be captured based on the customers buying behavior, purchase capacity, store visits etc.
  • Unable to deliver more profitable marketing campaigns

Business Solutions

  • Segmented customers into New, Active and Churn customers
  • Devising more personalized and relevant marketing campaigns based on each segment to maximize the impact of each campaign
  • Predictive model is built based on Decision tree technique to study the patterns of customers and identify Active customers who are about to churn
  • Retention efforts are devised to engage about-to-churn customers
  • Fine-grained sub-segmentation with accurate details helped in personalizing offers for customers

Business Impact

  • Increased customer satisfaction by providing proactive service to customers
  • Improved resolution time to provide quick solutions to customers
  • Reduction in Customer churn rate
  • Improved profit margins due to high retention of existing customers
  • Reduced marketing costs in acquiring new customers

Case Study 4:How to place products effectively through Association Rules
Business Problem Statement

Ecommerce era is having a huge impact on the brick & mortar stores because of the low inventory cost & wide variety of products for customers to choose from. Luring customers into buying more by ensuring that convenience is given the prime importance by effective rack placement, is sending shivers down the spine of retail giants also. Knowing on why customer is spending more time against certain exhibit & moving away without making a purchase is yet another challenge. Spacing the products such that the interest level of exploring the complete store is a problem, which is haunting the retail store owners since ages. How to compete with online stores in this tough world where people prefer convenience to commute, is the question, which many management pundits are trying to address.

Business Challenges

  • Reduced footfalls because of lack of interest generation amongst shoppers to explore more
  • Unoptimized product shelves placement in physical retail stores leading to fewer sales
  • Dealers showing lack of interest in purchasing shelf space due to lack of effective store layout
  • Increased inventory cost due to fewer sales for specific products
  • Reduced profits as inventory is pushed with large discounts due to impending shelf life expiry

Business Solutions

  • Used association rules to analyze & find out about the products, which are sold together with greater probability & thereby re-positioning the products
  • Using video footage's understood which rack is generating least interest for shoppers
  • Stocking the inventory appropriately based on forecasting the sales of products which go together in baskets
  • Predicting the disease outbreak in the specific region based on association of products purchased together

Business Impact

  • Increased footfalls because of Improved shopping convenience
  • Improved sales for manufacturers due to improved display of prominent shelves
  • Increased in sales in spite of reduced discount offer, thereby increasing profits
  • Reduction in the inventory cost due to effective logistics management
  • Arresting the epidemic by predicting the disease outbreak

Case Study 5:Targeted marketing using coupons through location-based analytics
Business Problem Statement

In countries throughout the world, massive shopping centers have become the glory of the city. These malls have a direct impact on the revenue generated by the tourism industry. With the expansion of malls, comes the increase in the inconvenience caused to customers such as: unable to find the right store or the right offer or the right product on the right floor. BPMN enabled signages, time-motion study, navigation charts, etc., to some extent helps customers in navigating through the mall. However, the bigger problem of converting the footfalls into sales, by suggesting the right product to the right customer at the right time is the challenge, which even the most aesthetically built shopping malls are trying to solve.

Business Challenges

  • Customers are overwhelmed with the size of the shopping mall & lack of proper navigation aids, including going back to parking lot
  • Capturing customer demographics for targeted marketing
  • Real-time notification of offers to customers without spamming them
  • Identifying the fraudulent & Illegal activities like shoplifting, terror strikes, etc., to ensure a safe shopping experience
  • Reasons of customer churn unknown
  • Matching store price with that of e-commerce stores

Business Solutions

  • Mobile Application was made available through access to free Wi-Fi
  • Pinning the start point from parking lot & helping traverse the path back on real time basis using maps
  • Statistical model to predict the probability of customer purchasing if discount coupon is sent
  • Implemented image processing to classify the activities such as shopping, stealing, etc.
  • Video analytic used to identify on how much time was spent on an exhibit/product & identifying reasons for churn
  • Analyzing customers’ browsing history of products in mall without breaching the customers’ privacy

Business Impact

  • Effective targeted marketing increased sales
  • Increased customer retention rate
  • Reduction in number of fraudulent events
  • Conversion of customers to buyers by offering best between the web vs store prices
  • Determined the most trafficked locations to position the products in store
  • Improved layout within stores based on time series data

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