Fibe QR Journey

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Context

Can a customer while seating in the waiting area at merchant site explore a zero cost loan ( BNPL) and get limit which he\she can use to pay to merchant as a zero cost ( provide affordability).

Fibe is a lending NBFC which provides loan to individual for a small ticket size i.e. 5K to 5 lakh.

• Currently most of the journey is agent assisted in BNPL sector but thats manpower heavy and reach is limited
• Agent does the basic step for customer to do their eligibility check for loan, once approved, customer does the journey
• New QR Journey , customer discover the Fibe on its own and explore the journey themselves without any assistance and get the loan disbursed to the merchant at the same time

Core value of the product

Provide affordability to the customer , get best quality product without any pressure on the pocket to the customer, lifestyle upgrade product

Provide higher conversion rate for the merchant and an opportunity for them ( a tool in his belt) to upsell or cross sell to the customer , increase ticket size or attach product i.e. increase PPC ( product per customer) to more than 1

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Different Pitch of the product:

• Get best quality service at zero cost EMI
• Dont compromise on health due to money constraint
• Upgrade your style with Fibe at no cost
• Convert your worries into zero cost EMI
• Convert your medical bill into zero cost EMI
• Opt for expert care now and pay in easy instalments
• Care now pay later
• treat now pay later

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ICP

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JTBD

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Teardown

teardown of the project as attached

Fibe QR onboarding- Alok Jain ( Gx19).pdf​

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Teardown Feedback:

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• A lot of Good things:
• • Placement of banner at place where customer can discover
  • First set the context in terms of explaining the product and step to get onboarded on the product
  • Gratifications at the right time
  • 1 step at a time so easy for customer to click and move
  • Animations in between to keep the customer engaged when system is in process

Overall able to deliver the product it was hired for

• Few things that can be improved
• • Duplication of work, showing limit again
  • Showing tracker at 2 places
  • Few CTA\screens are not required
  • Small sub module should be done at same screen and not part of main journey screen

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Hypothesis:

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Sign up : customer came to jouney, fill basic detail or KYC

Onboard : took the first loan

Activation : repeat transaction on app

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1: Customer activation : 4 transaction in 180 days

Reasoning: A new customer who is just signed up and moved from sign up to onboarded to take the first loan , I will not call that customer as an active customer since they just took the first loan and might never come back. For activation , customer atleast has to come to the app regularly which includes the smaller milestone of repayment on app where customer is able to Transaction on the app. Hence atleast 4 transaction on the app - first being the loan taken and 3 more i.e repayment of EMI or taking another loan.

does this metric demostrate user commitment - yes

does the user realise value from product - may be

does this metric affect conversion - yes

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2: Complete journey : 1 loan disbursal in 12 min

Reasoning: If the customer is able to disburse the full loan journey in less than 12 min, customer will feel very comfortable with the app and most likely will repeat the app

does this metric demostrate user commitment - yes

does the user realise value from product- yes

does this metric affect conversion - Yes

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3: Referral : 3 referral in 1 month

Reasoning: A customer who is referring fibe to atleast 3 people within a month time has a higher probability of activation as compared to a customer who just took the loan

does this metric demostrate user commitment - yes

does the user realise value from product - yes

does this metric affect conversion - yes

4: Session on app : 4-5 session in a month

Reasoning : If a customer is visiting the loan app 4-5 time in a month , high stickiness , than the customer will be retained by the Fibe

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does this metric demostrate user commitment - yes

does the user realise value from product - no

does this metric affect conversion - yes

5: Prepayment: 3 prepayment out of 6 EMI

Reasoning: A customer who is pre paying the EMI amount understand the system and flexibility available in the system and normally repeats the loans

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does this metric demostrate user commitment - yes

does the user realise value from product - yes

does this metric affect conversion - yes

6: Used 3 digital asset in 1 journey:

Reasoning: If the customer is all digital journey in the flow i.e. digilocker, Account aggregator, UPI NACH , customer experiences a non stop journey which just finishes in a jiffy and that generates an Aha moment for the customer that without any physical document they got loan

does this metric demostrate user commitment - Yes

does the user realise value from product - Yes

does this metric affect conversion - Yes

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Other metric to be tracked

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1. Churn Rate : less than 30% in an year

Reasoning: It should be opposite of the activation rate where how many customers are dropping off even after getting activated. If my Churn rate is increasing it means customer are liking my product any more and I need to change something to keep them engaged. Ideally churn rate should be what percent of customer are dropping off and not coming back to the app after being activated. Churn will be higher in BNPL Lending , but more than 30% could be an alarm which means I need to fix something

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2. Time to onboarding : 50% onboarded in 20 min , 80% customer onboarded in 1 hour

Reasoning: it is very important metric to monitor how much time a customer is taking in onboarding themselves, time spent on the app excluding the break. If the time to onboarding is high , journey is not customer friendly and customer not come back or recommend it to others

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3. Onboarding Completion rate : minimum 40% from sign up to disbursal in 1 day

Reasoning: How many customer are actually buying the product from the top of the funnel, A customer who signed up on the journey and Fibe has also approved the same customer , how many of them are actually end up taking the loan from fibe and not from other.

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4. DAU to MAU : atleast 10% on a monthly basis

Reasoning: the ideal number should be around 10% DAU to MAU ratio since this is a lending app and customer generally come for loan taken and repayment so it will be low but if increase this by engaging customer \ nudging customer and ratio is moving upwards , which shows higher stickiness , will result in higher repeat loan and higher LTV

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5. Feature adoption rate : 5% higher onboarding in 15 days

Reasoning: whenever we launch a new feature in the app, how many customer are actually migrating to that feature , for eg : UPI NACH setup , new bank validation method. If the population who is getting oboarded using this new feature has 5% higher signup to onboarding rate , than new feature is a success and helped in increase the activation rate

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6. D30, D90 and D180 retention

monitoring a customer retention over a period of time since this is a lending app, retention cycle is a longer since a customer who has taken a loan in last 3-5 days have nothnig to do on app, only when they plan to repay or buy something new they will repeat\come to the app again

7. Sign up / retention

Monitoring the complete funnel including repeat i.e. out of 100 customer who signed up , how many got onboarded, how many are activated and finally how many are retained \ repeat loans with Fibe

8. Different stages of the App - funnel

From basic sign up to first Aha moment - customer approved ( limit given) - KYC approved - Bank details- Disbursal

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9 Repeat rate \ LTV

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Number of product a customer is taking from us is a key metric to make money - normally we dont make money in 1st loan due to CAC and other cost , it is only the 2nd or 3rd ( depending on IRR and other factor) we start making money hence my repeat rate , PPC ( product per customer) is very important which actually helps in calculating LTV of the customer

10. Cohorts

​ Behaviour of the customer in different cohorts is a key metric to follow,

For example :

• • customer female customer base has a lower NPA rate as compared to male customer
  • Customer with an cash loan has a higher probablity of repeat as compared to customer only BNPL loan
  • Customer with Thick credit history ( long credit history) has lower bounce rate ( EMI doesnt bounce\default) so less collection effort are required for these customers

Understanding the customer ICP and JTBD ( problem the customer is trying to solve), and tearing down the journey of the product , we can say what all needs to be fixed and the same can be tracked using above mentioned metrics if the fixed that we are doing are actually improving the customer experience or no

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