Data analytics is the new-age technology used for determining the health of the organization and taking the necessary steps to enhance business opportunities. The information’s are useful in organizing and drafting the future patterns. As the retail market expands globally, data analytics techniques have become a crucial component of every business house. From Retail to financial services, every sector recognizes the power of data. Today we look at the retail segment and understand how does data analytics proves to be the ‘game changer’ in this industry. Also as a ‘takeaway’, you get the top 4 benefits of analytics for retail brands.
Data Analytics and Retail segment: Identify the correlationRetailers face an uphill task capturing the correct customer experience. They are eager to figure out the realistic trends. Capturing the data of multiple touch points used by the customer is critical information. As retail data continues to multiply in volumes and velocity each year, retailers are ready to exploit these conditions to maximize the customer traffic.
As technology continues to dominate the retail industry, organizations prefer to use professional analytical services for improvising their services and strategies.
Importance of Analytics in RetailSystematic analysis empowers the retailers to associate and adapt to the dynamic trends of buying and competitive activity among the customers.
Modern gadgets and applications allow the retailers to get the ‘real-time’ analysis which gives a better insight and perspective. In today’s condition, even a month old data is of no use as the behavior of retail sector changes at a rapid pace.
4 benefits of analytics for retail brands
1.Excellent knowledge of your customersUnderstanding your customers is one of the essential benefits of retail analytics. The raw customer data is calculated on the basis of-
- Customer contact
- Buying Preference
- Choice of multiple touch points
- The shopping experience
Tracking the customer’s shopping pattern and a personalized shopping environment makes it easy for the retailer to manage his activities.
2. Discounts and OfferingsThe strategy is the key: The increased online traffic allows the retailers to strategize the flow of their business. Offering discounts, coupons, attractive deals are keys ways to pedal up the sales and gain customer loyalty. However, the question is- how effective this strategy works in the practical environment. Giving discounts without a plan is not the apt way to survive for longer periods. Here data analysis comes into the picture again and retailers need to customize the offerings as per the buying trends of the consumer. They have to determine the long-term objectives. Some of the key advantages of these offerings are below:
- Competitive marketing
- Loyal consumers
- Lure new customers
- Removing excess inventory
Data can help the retailers to identify these buying behaviors and design such schemes targeting these customers. Frequent deals help to create a loyal customer base and a good way of meeting the revenues. Often, retailers can add new customers in their database by launching exclusive deals for the ‘new customers’.
3. Reduces customer churn rateCreating a customer base is always a priority for the retailers. The cost of acquiring a new customer is many times high as compared to the existing loyal customers. Data analysis gives the insight into which section of the customer base is about to leave and what can be the possible ways to retain them. The data available helps to segregate the customers and with a decreased churn rate, retail brands can measure the lifetime value and scale faster. Some of the points for increasing retentions:
- Personalized approach
- Tracking and working on the feedback received from consumers
- Attractive deals for loyal customers as per their choice
- Monitor customer activity
- Analyze the brand’s strong and weak points and market accordingly
Technology has transformed as a guide for the retail brands in improving client interactions and maximizing customer satisfaction levels.
4. Predictive Analysis can do wonders in retailFor newbie’s, predictive analytics is a study of current and past data to forecast future results and trends. Combination of analytical queries, techniques and defined algorithms assist in building predictive models. These models are highly accurate and business houses rely on these inputs while drafting their future expansions and roadmaps. Although predictive analysis stands on facts and figures, the data is not precise and not always be 100% accurate.
It’s just a predictive calculation to judge the probability of future outcomes and prepare you accordingly. The motive is to minimize expenditures, save precious time and reduce waste of resources and products. Predictive analytics has flourished for 2 prime factors.
- High-end technology makes it accurate
- Intensifying competitions
- Future performance
- price optimization
- Maintaining the customer base
- Forecasting trends