Ground-Breaking Tips for Data Management of E-Commerce Biz

Big data is introducing a lease of life into various businesses. The crew of data analysts and marketing experts go beyond their boundaries to dig out the most generic & productive ideas. But they are not alone causing business revolution. Internet of things (IoT), digital devices, robust security and machine learning are providing their unprecedented support.

Has our primitive generation ever thought of online shopping? Perhaps, it might be a dream for them. But the predictive analysis did unimaginable makeover. By churning the real-time data of clients or customers, it helps in pre-empting their behaviour, interest and potential to buy.

Around 79% US citizens loved online shopping while India registered 80 million online buyers in 2016. Of course, they are convenience and exclusive services that scaled this trend up. Want to know how big-data is doing this miracle? To know it, we have to catch on the data management tips that almost every successful eCommerce organization follow:        

1.       Define: Every e-Commerce organization has set goals. Its hierarchy of management is fed with the message to bite bullets for achieving them. Had not Andy Murray premeditated his win in the Wimbledon 2016, he would not be the winner. It’ obvious that deciding what to achieve should be pre-empted.   

The e-Commerce bigwigs draft a business plan that includes:

·         Developing and optimizing their website

·         Drafting online campaigns to target audience, like Google Adwords Ads, FB ads.

·         Choosing medium to air the ad campaigns.

·         How to process data for predictive and sensitivity analysis, like using Weka software.

·         Which tools should be shortlisted for scaling up productability.

·         Strategizing execution of feasible ideas on the basis of real-time data analysis.

·         Arranging budget.

·         Tying shipping, logistics, retailers and wholesalers.  

·         Segregation of budget for every plan.     

·         Identifying challenges and sources to overcome.  

·         Setting up timeline for individual task.

2.       Identify Data: Every industry has its own source and resources to pile up information. If we talk specifically about startup e-Commerce companies, they gain customers’ data through ad campaigns on social media network mostly. Even, search engine marketing also makes them a buzzing name since billions of netizens are present online today.

Email marketing, newsetters and CRMs are unmatched when the existing e-commerce giants want to scale up. Since their websites have explosive traffic, they hire outsource data management companies for filtering out the demography of productive customers’ details. Thereafter, the expert data analyst brainstorms how to spike the sale. The extracted customers’ data has their ethnography and the sense of their likes captured in it. And their in-house backend team communicates their offers for off selling and cross selling.      

All in all, the traditional as well as modern sources of data are determined to mix and merge for deriving meaningful predictive analysis.  

3.       Prepare & Explore: For sure, data comes from multiple sources to online sellers. Suppose an ecommerce organization collects data of the existing as well as new buyers. It can use Google Analytics for analyzing the activities of the online traffic on its site. But not all visitors are potential buyers. To dig out the details of actual buyers, it can shortlist the names that have spent many minutes to hours on the site. The current buyers can be re-targeted through offers tailored for building up loyalty.

4.       Predict: Would you predict plans on the basis of buyer’s history? Ok, just answer, would the one who booked a bike online can ever be targeted with the same offer within a month? In such cases, the targeting campaign and money would go all waste.

Hence, evaluate your marketing plan first. You can include complementary products or services in your future marketing plans. Wisely choose your models. 

5.       Visualize: What looks good that sells good. Let’s say you sell wedding gowns but the site lacks images. In this case, the selling will drop down.

The image has the expansive power of amplifying your words to sell.  It communicates directly and influentially. If I want to buy a backpack, I would definitely have curiosity to visualize its size, style, straps, zips and other detailing. This is why e-Commerce companies put the image parallel to the description of all products.

6.       Deploy: Efficient data processing concludes accurate analysis. Once the buying patterns of every online visitor on the e-commerce site are known, the predicted feasible plans can be executed accordingly like a piece of pie.

Suppose a loyalty program site tracks data to know the age group of maximum number of visitors. By thoroughly examining, most of the visitors are identified as the corporate companies. In order to get them converted, it can deploy some exclusive offers as per further communication with them.     

7.       Take Action: Last but not the least, action accomplishes the goal. You would have data that hides who, with what, when, how and where to target. Execute the marketing plans only after detecting feasibility in them.