Over the decades, technological innovation becomes more divergent in every industry and sector, it induces a massive amount of information that possesses valuable information and insights. That's where data analytics step in through predicting trends & behaviours, enhancing productivity, and making evidence-based intelligent decisions.
Why retail business needs data analytics?
The retail industry is witnessing a significant change & eCommerce portals as the most preferred shop for the customers. As more businesses shift towards digital, widening many more data capture opportunities. Consequently, retailers are facing challenges in capturing & process the true data and taking suitable action. So here comes, Data analytics solutions are applied at all stages of the retail process and allow retailers to track the customer buying behaviour, sales & demand forecasts, targeted advertising, and pricing decisions.
According to Mordor Intelligence, "Big data analytics in the retail market was estimated at $4.18 billion in 2020 & expected to reach $13.26 billion by 2026 at a CAGR of 21.20%"
Data engineering consulting firms harness the power of contemporary technologies to deliver advanced retail analytics solutions that enable retailers to derive meaningful insights & help to hold a strong position in this competitive environment.
Let's look into ways data analytics make your retail business perform better:
- Understand Customer Behavior
- Improve Customer Retention
- Targeted Advertising
- Price Optimisation
- Optimize Supply chain management
Understand Customer Behavior
The retail business manages an enormous amount of customer information, and every customer interaction has a big impact on business performance. Nowadays, marketers place a strong reliance on big data analytics to foresee customer behaviour trends & to ably reach new and existing customers.
With the help of predictive analytics, retailers can able to forecast purchasing trends, identify suitable marketing channels, and offer the suited products on the right platforms.
Improve Customer Retention
The majority of the eCommerce enterprises hunted on their efforts to onboarding new customers to expand our business. But with the support of big data analytics, the business can able to make an optimal customer retention strategy in this fierce competitive edge.
Using Big data, retailers can analyse what customers really love & narrow it all down deep & offer the customer what they truly want!
Many digital transformation consulting services believe that Big data analytics can steer the next wave of innovation in customer experience.
Targeted Advertising
In the retail business, digital advertising is an important part of customer personalisation. If you see the data, "Over 50 per cent of prospective customers turn out to be a mismatch for businesses".
Targeted & customized advertising will be more persuasive, hold fewer costs, and be better accepted by society as well. Blending AI/ML techniques with big data helps retailers to make more personalised advertisements, optimize the potential advertising space, and eventually drive maximum marketing ROI for the business.
Price Optimisation
Pricing is one of the vital factors in determining the growth and profit of the business. A study done by Mckinsey states that "Approx 30% of business fails to deliver the best price that makes a huge loss of potential revenue"
By leveraging data analytics solutions, a retail enterprise can track the real-time inventory levels & demands, respond automatically to tackle market challenges and make data-driven decisions for the business growth.
In Big data analytics, there is a technique called "Markdown Optimization" particularly using stock clearance sales- It understands the customer buying patterns and suggests the optimal discounts that could elevate the product demand while ensuring maximum profits.
Optimize Supply chain management
Retail enterprises can utilize data analytics solutions to optimize better logistics and supply chain management. Thanks to inventory & sales data from multiple resources can eliminate the risks of product stock-out or be overstocked. Furthermore, predictive analytics can be used to distribute the inventory to a highly effective point of demand and allot surplus to alternate locations.
Hence, retail enterprises can reap multiple benefits including collaboration in product development, supply and demand synchronization, and enabling an excellent way to enhance speed to market.
Bottom Line,
Retailers aspire to comprehend which products, services, and offers are engaging for the customers to drive business growth & profit!
Taking that into consideration, it is highly suggested that retail enterprises should tap into leveraging big data analytics solutions to hold better business performance in the demanding times.
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