One of the most competitive industries now-a-days is E-commerce. Present day consumers are expecting personalized experiences, easy to access product information and extraordinary services. In order to meet high expectations from consumers, online retailers need to utilize data being collected to the optimum level and proactively integrate analytics to enhance their decision making process. This holds good for every retailer. They should take advantage of analytics for better understanding of customer preferences, and further give them the right product offerings. Also, online retailers should benefit from their data for generating value instead storing it for information gathering and monitoring.
After defining and implementing basic analytics processes for measuring key performance indicators, retailers should look to utilize data more for performance related analysis such as customer experience, customer retention, targeted promotions, customized recommendations, and to increase share of wallet.
Analytics in E-commerce can also be used for specific purposes like:
- When does product stock out happen
- Which customer is likely to open and respond to the email marketing campaign
- How to efficiently manage the inventory to meet market demand
- What are the key insights that will generate higher customer satisfaction
- How to organize website for a smooth and trouble free customer experience
Above are just a few examples. A lot more can be attained when analytics is merged with business decision making. Further, we will discuss how analytics can be applied to various business sectors of an online retailer, just to highlight the benefits of choosing a data driven decision making process.
1. Optimize the Marketing Mix
One of the important factors for the success of an online retailer is to attract the right customers, and engage them with the right product offerings which would ultimately lead to a purchase. This won’t be a one- time process and investing in an appropriate marketing promotion mix is the key for success. For an online retailer, the marketing process will be different from a traditional business, since equal importance should be given to digital media as well as offline media.
Using predictive analytics, we can find out prominent factors which drive more sales or consumer acquisitions. Based on the model outcomes, one can effectively use the marketing budgets assigned across various marketing promotion mixes to maximize the returns. This process will be an ongoing activity and depending on the business budget cycle, predictive models need to be updated periodically and make relevant changes to the budgets as per the changing consumer media preferences.
2. Use Right Analytical Techniques
Another useful feature for E-commerce that benefits, is providing customized product recommendations and promotions. By using analytical platforms it makes it easier to understand past purchase history, to know consumer’s purchase behaviors and performance of various products on the site. With the help of such information, online retailers employ machine learning algorithms to recommend customized products which would possibly raise product sales. This kind of capability enhances overall consumer experience and converts more visitors to customers increasing the number of purchases.
When we talk about consumer behaviors, each one of us tend to behave, respond and react differently. There is no one solution for all kinds of consumers. With help of advanced consumer segmentation methods, we identify various characteristics of the consumer base to target each of those segments with specific discounts, promotions and product offerings. By adopting this strategy, Amazon has succeeded tremendously and managed to become and sustain as a leader in the e-commerce space.
3. Make Sure Supply Meets Demand
This dimension is one of most essential and sometimes would become a key differentiator from your competitor for being successful in the e-commerce industry. It is crucial for any online retailer to develop a fair understanding about customer demand. Using analytics, we effectively and efficiently manage the supply chain which includes planning, forecasting, purchasing, storing, assorting and delivering. Retail leaders like Walmart completely depend on analytics for their decision making in day-to-day supply chain management. Using these insights produced, we can plan our inventory and avoid out-of-stock situations.