30 Nov Data Analytics in Retail: Your Guide
With the retail industry becoming more competitive than ever, it’s important for brands to have the edge over their competition.
One way of doing that is by utilising data to understand your ideal customer, track your performance over time and accurately predict future trends.
We’re sharing some of the ways that we use data analytics to help big retail brands improve their offering.
What is data analytics in retail?
Retail analytics refers to data analytics that are used to optimise pricing, supply chain, customer experience, marketing and sales efforts in the retail industry.
Retail data analytics includes:
- Descriptive analytics: recording data like sales, inventory and customer data that tell the story of how the brand is performing.
- Diagnostic analytics: using statistical analysis, algorithms and AI to discover patterns, reasons and anomalies.
- Predictive analytics: predicting what will happen next by detecting clusters, exceptions and statistical methods.
- Prescriptive analytics: assessing the best outcomes and how to get there. Using AI to prescribe the best course of action.
Why should brands consider using data analytics in retail?
Retail is a complex and fast-moving industry. To help businesses succeed, data analytics can assist with every area of the retail operations.
Supply Chain Analytics in retail
Data analytics can help retail businesses assess consumer buying needs and predict what will be in high demand.
Analytics can be used to:
- Manage inventory and warehouse logistics
- Predict future inventory needs
- Assess the best suppliers
- Find the best ROI for products and services
- Analyse and predict industry trends to choose the right products to market
Sales and Marketing analytics in retail
Staying on top of industry trends and predicting future possibilities is an essential part of any business.
In Sales and Marketing, data analytics can help with:
- Optimise pricing
- Manage pricing trends
- Predict industry trends
- Assess which offers perform best
- Measure the exact cost of acquiring a lead or customer
Customer behaviour analytics in retail
One of the most important factors of running a retail business is knowing how to best serve your customers.
Analytics can help with:
- Understanding current customers
- Predicting consumer behaviour
- Creating targeted marketing campaigns
- Analysis of top performing marketing campaigns
- Social listening – understanding what consumers say about you online
- Analysis of trending topics that your consumers care about
- Providing targeted communication to customers depending on their preferences
- How are your teams performing?
- Where are their weaknesses?
- Where could potential problems crop up?
- Who needs contract reviews or renewals?
- How are employee timetables and business hours being managed?
These kinds of questions can be answered and predicted using intelligent and responsible data analytics. Not only will you be able to gain a better overview of your current situations, you’ll also be able to close gaps and minimise under or over staffing.
Want to use data to your advantage?
At InfoCentric, we’re experts in data analysis and can provide deep insights into best practices for the use of data analytics in retail.Ready to get started? Book a consultation today.