Benefits of Retail Analytics: Optimizing Strategies using Consumer Data

 

What is Retail Analytics?

Retail Analytics is the process of collecting data through various means, like online footprints of visitors on an e-commerce website, feedback forms, point of contact during a purchase at a brick-and-mortar store, etc. and then analysing this data to get helpful insights that are either predictive in nature or is an actionable that can help improve an aspect of a business.

Since retail businesses are commonly medium scale to large scale and consist of a lot of brands, deals, products, customers and now, even channels under their umbrella, Retail Analytics Services can really help retail business owners to zoom into different areas of their business that would otherwise go unacknowledged.

 

Types of Retail Analytics

There are 4 types of Retail Analytics:

1. Descriptive: A general Overview of how the business is currently performing.
2. Diagnostic: Deeper insights and spotting patterns, trends and the relations between the two.
3. Predictive: Predicting trends that are possibly going to occur in the future, using historical data.
4. Prescriptive: Actionable insights fetched using real time data for immediate changes.

 

10 Benefits of Retail Analytics

 

1. Increased Sales and Revenue: Business tools aid organizations to achieve their goals and objectives, which often includes generating more revenue.  By leveraging data analysis techniques, retailers can identify consumer behaviours, track customer journey maps, and gain insights into top-selling products and popular deals that create the most engagement..
2. Improved Customer Service: Retail analytics can help improve customer service by providing retailers with valuable insights into customer behaviour and preferences. By analysing data on customer interactions, purchases, and feedback, retailers can gain a better understanding of their customers and tailor their services to meet their needs.
3. Cost Savings: Retail analytics can be an asset for any business looking to save costs. With its help, you can improve your inventory management and identify which products aren’t selling as well. This allows you to save money on excess stock and avoid the costs of running out of popular items. Plus, retail analytics can also help you optimize your pricing strategy to maximize your profits!
4. Inventory Management: As mentioned above, customer data and store data can provide insights into which products are selling faster, which are not being sold at all, etc. to make better decisions for ordering and stocking. This does not just help with saving costs, but also makes the store more welcoming for the customers.
5. Marketing Optimization: Retail Analytics can aid in marketing strategies by helping analyse where, when and how to allocate marketing budgets and activities. It can help retailer customise their marketing strategies for different types of customers. Targeting customers based on their behaviour and needs can help make a great difference.
6. Predict Trends: It is no surprise that historic data does not just give insights into the past, but can help analysts predict trends by observing patterns, customer behaviour and more. If the activity of predicting trends using data analysis is sustained in a retail business, the business can stay ahead of the curve and far ahead of other competitors in the market.
7. Price Optimization: Prize optimization is done by identifying price sensitivity or how customers respond to changes in price. By using data to set prices, retailers can make more informed decisions and improve profit margins.
8. Promotional Analysis: Promotional analysis is somewhat related to price optimization and involves analysing the effectiveness of promotional activities such as discounts, coupons, and other marketing campaigns. This is done by tracking the impact of the promotion on sales, margins, and customer behaviour.
9. Tracking Competitors: Using BI Tools like ClicFlyer does not just help with monitoring your own retail activities, but also of other key players in the market. This can help in predicting trends, offering better prices for greater customer satisfaction and revenue and help retails be highly competitive and lead the way.
10. Tracking the Customer Journey Map: This process can include tracking and analysing customer behaviour at various touchpoints, such as in-store interactions, website visits, social media engagement, and more. Some BI Tools can provide deep insights into customer behaviour by tracking the entire customer journey map which can ultimately help business owners to create better engagement points on the map and provide a better service for increased customer loyalty.

 

Consumer Data: The backbone of Retail Analytics

Data Analysis tools without voluminous consumer data (preferably real-time and historic) cannot do much. A good tool with a large repository can do wonders for a business.

Consumer Data helps gain insights into consumer behavior, preferences and, demographics. This is vital information for consistent growth of a business as it helps make data-driven decisions about pricing, promotions, marketing campaigns, etc.

Consumer data can be collected using various methods, including:

• Surveys
• Purchased Data
• Website Analytics
• Transactional Tracking
• Social Media Monitoring

One of the main purposes of consumer data in retail analytics is to segregate customers based on their demographics and target them for promotions accordingly.

Consumer data can also help identify the top-selling products, most effective campaigns and promotions, most popular times and days for sales, etc.

Go a step further, and you can personalize shopping experiences for your customers using retail promotions analytics.

This can prove to be one of the most rewarding elements of a business strategy as it maximizes customer satisfaction and helps build customer loyalty.

To sum it up, using consumer data for data analytics can help a brand in the following ways:

1. Tailor products, deals and campaigns according to the needs of each consumer.
2. Identify the most valuable customers and target and reach them.
3. Improve your brand’s customer service.
4. Increase sales, revenue and ROI.
5. Better promotions and product development.
6. Increased competitiveness (keep tabs on competitors’ offers, deals, products and campaigns)
7. Fraud Detection and prevention (Find loopholes in a business plan).
8. Identify new marketing opportunities.

ClicFlyer is an analytics firm specialises in Retail Analytics. We provide the best Analytics Dashboard in the market, along with relevant historical data. Our coverage includes supermarkets, departmental stores, brands etc.
For more information, reach out to us at sales@clicflyer.com