Tech Casing - easy break down!
A quick primer for tech recruiting featuring timelines, types of cases, frameworks and application using a Doordash example
Tech interviewing for roles in US MBA programs range across product management, product marketing, strategy, business/ops/category management, sales and even HR roles. Having interviewed at companies such as Dell, Google, Amazon, Walmart, Lyft, Experian, EY-Parthenon (Deal Tech Consulting) I believe casing is extremely important and fun! Broadly to simplify, there are 2 types of casing interviews involving problem complexities such as -
Product casing
Product Marketing - Features for launch/market entry, positioning
Product Management - RCAs (Root cause analysis), Analytics, Technical problems involving data sets, product redesign
General Business/Strategy
Revenue/Growth - Estimation & Sizing of actual $ outcomes for new product idea, partnerships, strategic M&A
Business Ops (typically efficiency levers) - Cost reduction in business in areas such as sales, support, supply chain, retention, planning, operational planning etc
The most common frameworks for solving each of these casing challenges include
Circles - Used for solving most problems. Considered comprehensive, methodical and structured. Written by Lewis Lin (MSFT)
RICE - Used for prioritization problems. Great utilisation for numerical outcomes and presenting an analytical data driven view. Written by Sean Mcbride (Intercom)
Both frameworks can be applied while solving the case and bringing a structure around solving the problem. RICE (Reach, Impact, Confidence, Effort) particularly intrigues me because of the creativity I can apply around solving a problem.
Problem : Let’s assume you are the PM for the receipts at DoorDash, how would you go about redesigning the feature? (referenced from Rocketblocks)
I will use both frameworks here to solve the problem (~30 mins during an actual case)
C-Comprehend the situation
In 2023, Doordash had roughly 350k restaurants, AOV (avg order value) of $37, 37M users of which 18M users subscribe to DashPass (free delivery)
Email receipts are sent to every customer after a)placing an order b)order being delivered with the order receipt
It is important to note customers are also constantly receiving app and text based live delivery updates too.
Design should be a key part of re-design with a focus on simplifying omni-channel customer communication.
I-Identify the problem
Read receipts are being redesigned to meet a few potential challenges
Customers -
Order updates featuring data points such as time, dasher details, order reciept are sent across multiple notifications.
Customers are over-whelmed with frequent updates across SMS, Email, App, Voice(calls).
Customers do not get email receipts on time, sometimes they land in spam/junk
Customers find it super painful to track a live order (it takes three clicks to know status) and double dash from the app during a specific live order window
Doordash business teams -
Trigger points for order failure impacting dasher and support teams potentially don’t reach on time. For example, a customer could potentially trigger delayed support tickets due to email receipts being delayed
Customers don’t react due to multiple reminders - failed orders, cases of fraud which are missed by business teams leading to negative CX (customer experience)
Monetization -
Doordash is potentially missing out on a monetization opportunity of integrating ads with email receipts
Report customer needs - My primary goal here is to consider 2 primary customers - end customers (users) & businesses that may use DoorDash’ ad platform and consider for each
Users -
Users need order details such as order status, items, price, discount, card used to be communicated seamlessly.
Users also want the ability to double-dash through emails directly in a single click
Human-like Iron Man centric personalized emails delivered on time. Current emails are extremely robotic which annoy users
B2B - Businesses that are already spending $ on ads on Doordash can get fractionally better outcomes through ad based real estate on email receipts. I do believe, Doordash does have a tech based ad platform. Incremental needs could include
Ability to bid for ad space on emails for a specific time or window
Ability to track, visualize, measure performance on Doordash ad platform
Ability to design and ship omni-channel design consistent brand ads
Cut through prioritization - This is where I will use RICE to compare both my areas of focus and prioritize. What this also means is that as a PM I do aim to solve for both customer types but for now solve for 1 using the formula
(Reach x Impact x Confidence)/Effort = RICE Score
Users - Seamless email receipts and double dash will have impact and reach.
We can calculate reach since we know DoorDash has an AOV of $37 and annual revenue of $8B - this gives us an OPD (orders / day) of ~0.7M or a run rate of ~233M orders annual.
Similarly we can calculate impact $ by assuming a conservative base that 5% OPD will now double dash due to this redesign increasing AOV by 10% (base $37), leading us to annual impact of $47M
I do believe I am pretty confident of this solution redesign given the relatively low complexity (databases exist, UI redesign seems to be the main work) hence I’d award a 0.8 (scale of 1) here on confidence
Similarly, on effort, adding CTAs and personalization is low on effort since the work will be frontend based largely with very limited backend intervention of services. All microservices which pre-exist can be used to ingest data into our email reciept re-design stack
Businesses -
Doordash does an annual revenue of $720M on ads, I am assuming 10% of all brands will want real estate on emails due to the frequency of customer visits, duration of app-engagement as well as overall app stickiness
I will assume 5% gain on a $720M base wrt revenue impact viz ~$36M
On effort and confidence, I believe this will high on effort and relatively low on confidence since there will be core ad services that may get impacted to additional instrumentation needs (analytics)
My comparison stack yields the following
It is evident that redesign for users building a compelling story for Doubledash and seamless comms should be prioritized.
List solutions - Since my primary focus is to help streamline comms and help customers double dash, the solution could entail the following features
Redesigned personalized email receipts with all data points(order status, discounts, price etc) which can be triggered / paused by users - helps users stay underwhelmed and improve chances of comms
Personalized email based double dash recommendations with one-stop CTA to add item on cart - incentivizes users to double dash through alerts
Integrated alerts - one stop email tracking with same subject line for order confirmation, delivery and support with a single ticket ID - helps users manage order recall
Centralized comms service called Jarvis (ref Iron Man) - integrated support comms platform for customer communications across Email, SMS, Voice(calls) and app - helps solve for technical deficit for failures. If email is not built into this service, ensure it is.
Evaluate tradeoffs - Here, I’d like to highlight the user benefits and business objectives that are being met for each such feature described above
Some key metrics to thus track -
Business
AOV gains on OPD
Daily/Monthly brand revenue % growth on platform
Product
AHT for live order support tickets
TAT for live order support tickets
Click through rate for double dash CTAs
Email attachment downloads of actual receipts
Open & Response rates of emails (past vs future)
Summarize - Redesigning the email receipt feature in Doordash is a great lever for monetization, customer experience and driving product growth. By introducing features such as integrated alerts, one-click doubledash, Doordash can potentially gain an upside of $47M annual impacting minimum 5% of their daily OPD viz ~0.7M. As next steps, to implement my recommendations, I’d like to meet my Engineering counterparts on specifics such as sizing, scoping estimations and technical design.
The above problem was solved using both frameworks and one is free to choose either/or while solving a problem as long as there is depth, creativity, technical know-how and as well as clarity of user needs, business expectations. The entire case above can be solved verbally in ~30-40mins, there is some work involved in sizing asking for basic estimates such as revenue, orders per day, average order value but companies do expect one to read / know these stats since they are so core to the business of Doordash. In my opinion, this is the main difference between tech and consulting casing where Tech casing does expect you to be creative and size problems bottoms up without too much hue or cry.
I will be solving more cases in the future, stay tuned follow and let me know if you need any specifics!