Digital Analytics for E-commerce and Online Business

1. Digital Analyticsfor E-commerce and Online Business

2. Index • Introduction • Some important forms of Digital Analytics • Web Analytics • Social Media Analytics • Business Intelligence • E-Commerce Analytics • Functional Relevance • Sales • Marketing  • Operations  • Finance  • Overall Edge to Business • Informed and intelligent decision-making • Warning signals and Loss Aversion • Profitability analysis • KPI tracking

3. 1. Introduction The data created by little things done on digital devices is extremely relevant to businesses. Analytics could reveal various important factors such as which product is viewed most. Better marketing strategies and operational plans can be formulated with business intelligence and advanced data analytics. Digital analytics makes business sense out of the digital data that is being generated. Digital marketing analytics is the entire process of collecting, analyzing and converting the digital data

4. 2. Some important forms of Digital Analytics • Web Analytics • Social Media Analytics • Business Intelligence • E-Commerce Analytics

5. 2a. Web Analytics Features:- Understandsthe flow of web traffic, user behavior on a website, and the associated technologies Comprehendsuser psychology and behavior when they are on a business website Reveals crucial areas for improvisations.

6. 2b. Social Media Analytics Features:- Studies and analyses data created by the users on various social media platforms Targets customers and audiences by pitching with the use of humongous volumes of data are created on social media platforms like Facebook, Twitter, Instagram, Snapchat, YouTube etc Helps businesses to build sharp strategies Helpscompaniescan also focus selectively

7. 2c. Business Intelligence Features:- Focuses on the present circumstances. Helps in finding out the weaknesses and opportunities in the current business practices or way of functioning based on real-time or past data. Focuseson what future trends could be and what can be done. For eg. Going digital and omnichannel could help retailers to get their business back to motion as economic activities resume

8. 2d. E-Commerce Analytics Features:- Specifically targets ecommerce platforms owing to their immense potential of providing meaningful data Focuses and analyses the sources of user traffic Provides insighton user activities and other such relevant information Creates Better understanding of user experience on an ecommerce platform Analyses ways to increase traffic and conversions.

9. Functional Relevance • Operations • Finance • Sales • Marketing

10. 3a. Sales Digital analytics can helps sales function in Goal Setting, Providing Insights, Identifying Unmet Needs, Periodical Sales Analysis Majorly Digital Analytics helps Sales function by:- Settingproper and pragmatic targets Generatingsustainable revenue Understanding to drive a sales opportunity. To identify un‐served and underserved areas Assessingthe performance of the sales department Knowingabout performances, contributions, areas for improvement

11. 3b. Marketing Objective of Digital analytics in marketing is to improve the efficiency and effectiveness of the marketing strategies and efforts of a business enterprise. Majorly it helps Sales function in:- Predicting seasonal trends Merchandising decisions Redefine target segment Pricing decisions Supply chain decisions Website and social media analytics Performance of SEO and SMM strategies

12. 3c. Operations Areas where data analytics help in operations management are :- Procurement Planning Merchandising Supply chain and inventory Budgeting

13. 3d. Finance Department Areas where financial data analytics can help your finance division are:- Financial planning and forecasting Cash Flow Analysis Investment decisions, return on investment, break-even analysis, etc. Profitability, liquidity, and leverage

14. 4. Overall Edge to Business • Informed and intelligent decision-making • Warning signals and Loss Aversion • Profitability analysis • KPI tracking

15. 4a. Informed and intelligent decision-making Significanceof Data Analytics in Decision Making Analyses tons of relevant business data Makes informed decisions but also intelligent decisions  Provides grounds for an even better decision

16. 4b. Warning signals and Loss Aversion Significance of Data Analytics in providing Warning Signals Data analytics can help businesses make predictive analyses Resources being poured into a less profitable or more risky option/project/decision could be diverted to better alternatives.

17. 4c. Profitability analysis Significance of Data Analytics in Profitability Analysis Calculates and assesses the profitability of individual products, or its SKUs, or compute category wise profit Help to figure out which segment is your cash cow and which is not

18. 4d. KPI tracking Significance of Data Analytics in KPI Tracking:- Data analytics can help companies refine, redefine, and keep track of the established KPIs. Directs project and its parts to ensure they are headed in the right direction

19. 5. Summary The data from various sources can help the various teams in various ways. The analysis of data behind a campaign can help to pinpoint the successfulness of it, why and how the audience interacted with it. Data can be used to help refine and improve How YRC Digital will help? YRC is the service brand of YRC dedicated to digital products & digital transformation consulting. YRC is a dedicated team of professionals who understand digital analytics and know how it can be leveraged to achieve digital transformation from inside out. For more information visit www.yourretailcoach.com

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