Required Assignment 1.1:
Key Analytics Questions of Your Organisation
Shilpi Tiwari
Suggested time: 90 minutes
Assignment Instructions
In video 9, Professor Gangwar summarises the implementation of business analytics into a
framework of key analytics questions. Use the framework in the video to reflect upon the key
analytics questions in your organisation.
Business Decisions
1. What DECISIONS does my business make?
E.g. Which offer to send to which customer?
Working as a business development to increase the retail of the vehicle in TVS motor
company. We generate enquiries from multiple platforms by running various
campaigns either Digital or offline. There is a dedicated call centre which can be used
to call & nurture the customers who have created enquiries regarding TVS product.
Key Business Decisions: Which enquiry customer cohort to be nurtured through the
call centre agents to improve the conversion/retail of the vehicle.
2. On what BASIS do I make those decisions?
E.g. Past purchase behaviors of those/similar customers
Targeting HOT leads (customer interested to purchase the vehicle within a week)
I filter the data where customer has shown interested to purchase the vehicle within a
week, they are potential customer (Hot lead) & should be nurtured e2e to address
their queries & explain vehicle specifications & competitive advantages.
Applied Business Analytics
Page 1
3. How do I quantify SUCCESS of my decisions?
E.g. What fraction of offers get converted?
Funnel conversion from dialled customer to retail% (Higher the better)
If the Dialled to retailed conversion has increased by significant number after nurturing
the hot leads, it proves that the nurturing customer after they create vehicle enquiry
gives better conversion into retail of vehicles.
Data Analytics
4. What data do I collect to EVALUATE my decisions?
E.g. Did customers redeem the coupons – after how long, how often?
Comparison of leads which was nurtured by call centre vs not nurtured by call centre
I will compare the lead conversion % of leads which was nurtured by call centre
agents (Hot leads- those who were willing to purchase within a week) & lead
conversion % of leads which was warm (willing to purchase within a month) or
cold (willing to purchase within 2 months) & was nurtured by the call centre.
If the conversion rate of Hot lead is better than warm & cold lead, then investment to
be made to nurture only HOT leads & other alternative cost effective solution like IVR
can be implemented for warm & cold leads nurturing.
5. What data should I collect to IMPROVE my decisions?
E.g. Point of sales data, Social data, Reviews, etc.
I can also collect & analyse the different lead generation sources (website, dealership
walk in, aggregators lead like Bikedekho & Bikewala, Meta etc), Model variant,
Enquiry category(Digital/Walk-in/BTL activities) to improve my decision.
Model Variant Example:
Applied Business Analytics
Page 2
Retail conversion of premium segment model is better than commuter/non premium
model because Premium buying customers expect more service & better customer
experience as they are paying higher charges.
Lead Generation source: we can collect & analyze data by generation source to
improve the decision. E.g.- lead generated through website can lead to more retails as
they are OTP verified leads & customers are genuinely interested to purchase the
vehicle.
6. How do I improve my MODELS from the data I collect?
More data, more features, better modelling…
Experimenting by analysing different criteria which can give better conversion
rate/retail of vehicle.
E.g. Number of pre-owned TVS vehicle, Salaried/Non salaried, Age group, part of
racing community or not etc.
TVS pre-owned customer- If customer is having vehicle of TVS motor, there can be
high chance that he can come back & repurchase TVS vehicle again.
Age- We can collect age group data & analyze which group range customers are
purchasing which kind of vehicle. E.g. customers below 35 years of age may prefer
sporty vehicle whereas customer >40 years may prefer commuter vehicle.
Part of TVS Racing community- There is high chance that if customer is part of TVS
racing community, then he can be easily converted for racing variant model.
Applied Business Analytics
Page 3