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Kautilya Ecommerce Efficiency Measurer
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E-commerce Industry – A Perspective •eCommerce is the fastest growing method of shopping
•According to a new projection from Forrester Research, Sales in US will hit approximately $262 billion in 2013, up 13.4% from $231 billion last year, •This year, online spending will reach $370 billion, which represents a nearly 10% compound annual growth rate from 2012
•India is the 5th largest eCommerce market in the world •India has 44 million online retail visitors which is only 62% reach of e-commerce among online users. The worldwide average is around 73%. •Added 15 million eCommerce users between Dec 2011- Dec 2012. •Saw a 50% growth in the number of Internet users between Dec 2011- Dec 2012. •Most large eCommerce portals have started moving away from own inventory to the Marketplace model •As a priority they are focusing on growing the list of Vendors on their Marketplaces
Its truly phenomenal and exciting on the potential and what
we can do; and this is only India and the US
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Kautilya Components
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What If ER Ad Hoc Ex Visual Analytics Root Cause
Export Print Mobility
Drills
Kautilya Engine
Advanced/Predictive/AI/ML
Kautilya Administration
User Dashboard
(ER/Production)
Predictive
Analytics Storyboard
(Data Discovery)
NLP* Search & Pin board
(Self Service BI)
Tabs
Edits
Warehouses
Transactional
Systems Flat, Legacy
or Modern ODBC
NLP*: Natural Language Processing
List of KPIs, Reports and Analytics
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Customer Management • Customer Analysis • Customer Wise Sales • Cross Gender Analysis
Finance Management •Profit Contribution
•Profit Analysis •Revenue Status •EIBITA by Departments and gender •EOV by Department and Gender •Gross Revenue/Net Revenue/ Operating Revenue Margins by Department and Gender •Net Profits by Department and Gender
Sales Management •Supply Chain Funnel With Details Of Dropped Items
•Telemetry Product Wise Upward Trend
•Sales By Products
•Telemetry Product Wise Downward Trend
•Sales Probability for bundling products
•Channel wise Detail •Sales forecasting based on past trends
•Net Conversion ratio by department and gender
Vendors •Vendor Performance over current year
Miscellaneous •Quantity Wise Upward/Downward Trend
•Promo Value Wise Upward/Downward Trend
•Return Value Wise Upward/Downward Trend
•Day Wise Order Analysis At A Glance
•Sales Analysis •Source wise drops and success Analysis
•Facebook data Analysis
•User Analysis by Facebook, Shopping Site and internal data for Marketing
•Advanced or Predictive Analytics •Campaign Analysis •Courier Company Wise
Inventory And Warehouse Management •Inventory Valuation
•Inventory Aging
•Stock Breakup
•Forecasting based on past trends
Supply Chain •Dispatch Tracking
•Dispatch Tracking (Detail) •Delivery Tracking (Detail)
NLP Analytics •Get all the business related critical question answered on the fly •Temporal Related questions •Top Bottom •Mathematical functions related
Order Management •Turn Around Time
All the above can be viewed by:
• different time dimensions like Calendar Year, Fiscal Year, Quarter, Month, Days.
• Market Place and Own Inventory models
• Omnichannel
• Geographical dimensions
• Channel Hierarchy
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Kautilya Analytics LLP Accolades
•Kautilya was showcased at NASSCOM’s Emerge Out in Chennai •Kautilya was a finalist in the Best IT Implementation Award for the year in the Enterprise segment •An article on Kautilya appeared in PC Quest •Named in Quadrant by Frost & Sullivan for BI products in India
•Mentioned in Gartner’s Report for BI in Asia Pacific
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Search Feature Used For Getting Top/Bottom Records
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Search Feature Used For Complex Temporals
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Search Feature Used For Building tables or Pivots
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NLP – Pin Board
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More NLP query examples are …
• To get categories wise number of orders received in the month of <month name>June <year>2016
• To get categories wise number of orders received and Invoice is also raised in the month of <month
name>June <year>2016
• To get categories wise revenue generated based on the orders received in the month of <month
name>June <year>2016
• To get categories wise revenue generated based on the orders received on <day>1st of <month name>June
<month name>2016
• To compare sub categories wise order received during first quarter of <year>2014, <year>2015 and
<year>2016 respectively
• To know yearly performance in terms of order received
• To know monthly performance in terms of order received in <year>2015
• To know daily performance in terms of order received in <month name>May <year>2015
• To know weekend performance in terms of order received in <year>2015
• To compare <day name>Sunday and <day name>Monday performance in terms of order received in
<year>2015
• To know top / bottom <number>10 campaigns performance in terms of order received in <month
name>May <year>2015
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Continued.. • To know running campaign performance in terms of order received in <month name>May <year>2015
• To category wise order received in <month name>April <year>2016 and dispatched in less than <number>4
days after invoice has been generated
• To know category wise profit gained in <month name>April <year>2016 whose quantity sold are greater
than <number>300 Units
• To know how the shoe category is performing as compared to other categories in the month of <month
name>April <year>2016
• To know the merchants names and the number of orders for which it took more than <number>20 days to
be delivered.
• To know the merchants names and the number of orders for which it took more than <number>20 days to
be delivered for the orders that are received in <month name>January <year>2016
• To know how the particular brand is doing monthly, in terms of orders that are received in <year>2016
• To know how the particular brands are doing monthly, in terms of orders that are received in <year>2016
• To know customers city wise orders received where customer state is different than the merchant state
• To know gender wise sales for customers whose age is greater than <number>40
• To show me Merchant wise sale for those products which ordered in month of <month name>April
<year>2016 and invoiced within <number>10 days and working on those customers which not belongs to
his city.
• To show me those Campaigns which are giving more than <number>30% profit of discount offered in
campaign and product ordered and invoiced in the month of <month name>April <year>2016. etc. 13 www.open-soft.net
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Campaign Wise Sales & Returns Analysis
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Thank you !
Kautilya Analytics LLP
512, Phase – V, Udyog Vihar, Gurgaon. INDIA.
Telefax : +91-124-2345223, Phone :- +91-124-4012305/06
E-mail: [email protected]
URL: www.kautilyabi.com
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