Big data trends are making headlines and are providing new spurs and opportunities to all the sectors today, and retail being no exception. E-commerce giants like Amazon use data analysis to give personalized recommendations. Hence, all the activities performed on the e-commerce website are analyzed to deliver customized marketing messages.
Even the brick and mortar stores use big data analysis to personalize marketing communication. Here are some uses of big data in retail which can be applied to earn ROI from technology initiatives.
• Price Optimization
Under conventional marketing strategies, the price was determined on the basis of buying a season of a product, market condition, competitor’s price, etc. With the help of big data analytics, one can analyze data from numerous sources like the website, in-store sensors, the frequency of purchases, etc. and generate data based on these findings. With this information, a price can be optimized on real-time analytics, consumer behavior, and other influencing factors. Many small-sized IT companies are offering data analytics services, and any retailer can benefit from big data analysis by adequately analyzing it.
• Forecast Demand
Trends and market buzz are big influencers of demand as buying seasons. Any industry like fashion, personal care, health care, groceries, etc. can experience a sudden rise in order due to market trends and buzz. Big data helps in analyzing these trends from various factors like social media platforms, buying history, etc. Through predictive analytics and big data retailers can gain knowledge regarding the upcoming trends, demands and changes in the market price and hence these insights can help in forecasting market challenges in advance.
• Targeted Marketing
Consumers have become smart enough to differentiate between generic promotional content and a personalized message. Therefore retailers must prepare a precise marketing message at the right time to make your marketing work. Big data can help retailers in the following ways:
1. Analyzing the impact of different marketing endeavors on a client’s behavior and revenue.
2. Using customer data like cookies, browsing history, previous purchases for personalized messages.
3. Monitoring customer activity on social media and review sites to ensure excellent customer experience by addressing bad reviews if any.
• 360-degree approach
The modern clients are a lot more connected than before. There is an increase in the level of expectations of the customers and businesses are expected to cater those. Enterprises are fighting over customer experience, and big data is one such essential tool which is available at their disposal. With the help of big data analytics, retailers can gather data from multiple sources. Hence, retailers need to adopt a 360-degree approach to customer acquisition and retention.
• Identifying Customers
Businesses have to focus on their ideal customers who have a maximum lifetime value at minimal acquisition cost. However, an enormous amount of data is available which has to be analyzed to come up with insights regarding the target market and consumers thereby choosing the right market based on maximum ROI.
