Skip to main content

Big data and commerce/eCommerce merchandising

As Craig Mundie, Senior Advisor to the CEO at Microsoft mentioned that "data are becoming new raw material about the business", the Omni-channel merchandising are making their decision based on the data and analytics helps them to predict the future demand flow.

The Big data analytics are helping the merchandising decisions retailers are making every day. A few examples where data driven decision are being taken in the etail/retail space regularly. Although, business decisions are very complex and based on a lot more factors, below are the few examples where key matrices are created and helps management to take decisions.
  • Assortment:  Keep product A, drop product B, add product C – these kind of decisions were taken based on the data and sensitivity analysis using big data frame work.
  • Online Marketing and campaign management: Big data can analyze the sentiments of the customers based on the reviews and analyzing the social media and helps marketing team to take informed decisions about the products. Some products need to be de-commissioned or some products need more campaigning.
  • Pricing: Big data can help to analyze and change prices based on pre-defined parameters and thus helps to drive the business. Few of the parameters are competitor's price, stock quantities, future demands etc.
  • Promotions: The big data helps to strategies the promotion for the products. Based on the analysis, merchandisers can decide the time period, when to give, promotion based on local market or global requirements. These helps merchandisers to personalize the promotions.
  • Local Market: Big data analytics helps to curve the adaptation strategy for the merchandiser. It helps analyze if there is a new trends in the local market which not available in the global space by analyzing the marketplace sellers.
  • Product Content: With the power of analysis of large data from different sources, etailers/retailers can decide the product content in the platform. The analytics helps to analyze and predict the future products to be/should be present on the shelves in each of the target segments. In fact, the power of analysis may help to predict if the merchandiser need to look beyond the cliché segmentations and look for niche segmentation.
  • Seller information analysis: Using big data analytics can analyze the performance of the marketplace sellers based on pre-defined parameters. Big data analytics framework can gather and analyze data from difference sources. It'll create dash board for the management about the performance of different sellers. So, management can take informed decisions to on-board a new seller or off-board an existing seller for their platform.
Investment in Big data analytics will not give you a competitive edge, it is a requirement to stay in the market. With the power of social media (word of mouse), it has become a rudimentary requirements for a business to have good market share and stay afloat.​

Comments

Post a Comment

Popular posts from this blog

Hybris Beanshell and Groovy script example

While doing support, we need to check some of the scenario and their result in the production server. The beanshell and groovy script comes very handy on this. Below are the few example of how I used/using it in my various project. This is very handy to test your data as well 1.        Check the log: Sometimes getting server access is very painful in the enterprise landscape. However, person joined in the project is required to work as soon as they inducted in the project. In this scenario, below groovy script is very useful.   Please note, run these in the rollback mode unless and until the otherwise is required. a.        The application is running from the container. For the POC, it was running in the tomcat server (tomcat/bin). To know the exact directory, run the below script in groovy console println "pwd".execute().text Below will be printed in the output tab /usr/sap/hybris/bin/platform/tomcat/bin ...
1 comment
Read more

SonarCube and Hybris integration

There are some issues reported for SonarCube 6.7 integration with Hybris. The recommended version is Sonar 6.4 or less. For Sonar 6.4, there is no need to build the database. Please follow the below steps to use sonarcube with Hybris. For the POC, we have used Hybris 6.4.0.2 and sonar 6.4. Sonar Cube configuration 1.        Download sonar 6.4 and install/unzip. 2.        For the POC, we have used Embedded Database (default). But multiple database is supported. Access management can also be implemented. However, for the simplicity purpose, it is not used for the POC 3.        The java properties can be set at the sonar.properties file (not used in our case). Example of the property is sonar.web.javaOpts=-Xmx512m -Xms128m -XX:+HeapDumpOnOutOfMemoryError which can be enabled in the sonar.properties file under conf folder of the installed folder. 4.      ...
2 comments
Read more

SAP Commerce License

There are two types of license for SAP commerce application. Temporary license (valid for 90 days). Permanent license Will discuss how to install both the type of license one by one. Before that, let’s discuss few details about the SAP Commerce License. ·        Unlike other SAP products, SAP commerce license is not used for any specific H/W. So, the field HARDWARE-KEY in the license file is filled with some preset values. ·        Usually customer will choose three letter system ID (SID – SAPSYSTEM) while creating the SAP license. This SID must be configured in the local.properties # System ID license.sap.sapsystem=XYZ If this is omitted, system will think that CPS as the default value. Installing the temporary license ·        Run license.bat from the platform folder license.bat -temp CPS_SQL In the above, license type is temporary (-temp) for the dev environm...
1 comment
Read more