ANLY482 AY2016-17 T2 Group3: PROJECT FINDINGS

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ANALYSIS

Users, Customers & Professionals

Figure 6 - Users breakdown by type	As we can see from Figure 6, there are much more non-professionals (customers) than professionals who currently have an account on the Vanitee application. This shows that there is indeed a demand for beauty services on this platform as more customers are interested in signing up for an account. However, it is important to note that having an account alone is not indicative of how successful the application is doing in encouraging the customer to book through this platform. We will continue to explore further when we look at the bookings made in the later part of this analysis.
Figure 7 - Customers breakdown by age
Figure 8 - Customers breakdown by gender	Looking at Figures 7 & 8, we can observe that most customers that use this platform are mainly females aged between 20 to 35.
Figure 9 - Professionals breakdown by age
Figure 10 - Professionals breakdown by gender	Similarly from Figures 9 & 10, we can observe that most beauty professionals that use this platform are mainly females aged between 20 to 40.

Bookings

Figure 11 - Bookings breakdown by type	From Figure 11, we can see that there are slightly more online bookings than manual bookings, probably due to greater convenience in using the online platform.
Figure 12 - Bookings breakdown by status	Bookings made through the application can have 4 different statuses namely, Pending, Checkout, No show and Cancel. From Figure 12, we can see how 40% out of the initial 54% of online bookings were successfully checked out. This seems to be a healthy percentage as it can be said that Vanitee only earns revenue from online bookings that are successfully checked out. Hence, the graphs from this point onward would mainly be based on these online bookings that have the status of check out.
Figure 13 - Bookings breakdown by frequency	The next graph shows the bookings frequency throughout the past 2 years. Surprisingly, there are many users who have only booked once and this number of users actually significantly drops as the bookings frequency increases. There are probably many reasons why a user has only booked once and we hope to be able to identify these reasons in our future analysis as this would greatly help Vanitee improve on their customer retention strategies.
Figure 14 - Bookings breakdown by year	As seen from Figure 14, the number of bookings made in 2015 & 2016 are roughly the same, showing how Vanitee has managed to somehow sustain this over the past 2 years.
Figure 15 - Bookings breakdown by month	Moving to Figure 15, it can be deduced that these bookings tend to occur in the last quarter of the year.
Figure 16 - Bookings breakdown by month & year	From Figure 16, we get to see a clearer picture of how the bookings vary across the past 2 years. In general, it can be said that Vanitee did much better in the last quarter of 2015 (right after its official launch) as compared to that of 2016. In the earlier part of 2016, it suffered a decline in the number of online bookings that were successfully checked out. However, this number gradually picked up some pace towards the last quarter of 2016. One reason for this could be the change in Vanitee’s business model which happened around that period as well. The main difference in the business models is the introduction of customer cashback, in the form of credits, to incentivise customers to make more bookings.
Figure 17 - Bookings breakdown by day	In Figure 17, it can be observed that the frequency of bookings tend to increase nearer to the weekends (Friday, Saturday) where people naturally have more free time to themselves.
Figure 18 - Bookings breakdown by recency (initial)	The next thing we tried to find out from the Bookings data was whether existing customers have made any recent bookings. This was an important analysis to do as it provides us with a general idea as to how active the customers are in using this platform. As seen from Figure 18, we decided to calculate the duration from the last time that each customer has made a booking to 31 December 2016 which is the latest possible date from the data range we have selected. Initially, we came up with categories in terms of weeks with “>1 month” being the last category. However, upon generating the graph, we realized how skewed the analysis was as approximately 94% of customers fell under the “>1 month” category. Hence, to make this analysis more insightful, we decided to refine the categories to include durations in terms of months.
Figure 19 - Bookings breakdown by recency (final)	Figure 19 shows a much clearer picture of the recency analysis where we could conclude that 50% of existing customers have booked within the last year while the remaining half had not.
Figure 20 - Bookings breakdown by monetary value	The next figure above shows that 61% of online bookings made have a monetary value of less than $50. This possibly shows how customers are generally willing to pay for beauty services that cost around $50. Exceeding this mark shows a huge decrease in the number of bookings made.
Figure 21 - Bookings breakdown by duration from signup to 1st booking (initial)
Figure 22 - Bookings breakdown by duration from signup to 1st booking (final)	Figure 21 & 22 shows the bookings breakdown by the duration from when customers signup to their very first successful online booking. While generating this analysis, we faced a similar issue of having an overly skewed results, in this case 75% of customers make their first booking within 1 week of their signup. As this percentage was pretty large, we decided to take the same action and break it down to smaller durations in terms of days as seen in Figure 22. The final result ended up to be very positive showing that 62% of customers make their first bookings within a day of their signup.
Figure 23 - Bookings breakdown by service count	Figure 23 shows us the bookings breakdown by service count. In this case, 74% of bookings only involve 1 beauty service. This shows that most customers are specific in targeting the main beauty service that they want to engage in, be it nails or brows or other types of services.
Figure 24 - Bookings breakdown by category	This figure simply shows that most bookings involve nail, makeup and brow services.
Figure 25 - Bookings breakdown by campaign usage	As seen from Figure 25, about two thirds of the bookings made involve some form of campaign which allows customers to enjoy booking discounts.
Figure 26 - Bookings breakdown by credit usage	However, when we tried looking at the percentage of bookings that utilized credits, we found out that this percentage only amounts to approximately to 1%. One possible reason for this extremely low number is that most customers have only made 1 booking, which means that they have not even utilized the credits earned from their 1st booking. Another reason is that the current business model that involves customer cashback in the form of credits was only introduced in the last quarter of 2016.
Figure 27 - Profit per booking formula comparison	The last thing that we wanted to find out was the total profit that Vanitee had made over the last 2 years. Utilizing the 1st formula in Figure 27, we calculated the profit to stand at a surprising value of -$98k. One of the main reasons for this is that their current business model doesn’t allow for much profits to be made, especially when there are Vanitee discounts involved in bookings. As compared to bookings that have no discounts or have professional discounts, we noted that Vanitee discounts are naturally absorbed by Vanitee itself and may be part of their marketing budget to try to incentivise more people to use the platform. Also, in this specific scenario where Vanitee discount is present, other fees such as payout, transaction fee & customer cashback are still calculated based on the initial price before the discount. As we felt that such calculations may put Vanitee at a disadvantage, we came up with a revised formula as seen in Figure 27 that calculates the profit based on the scenario where the above mentioned fees are calculated based on the final price after the discount. As expected, the final profit turned out to be a less negative amount of -$85k. A simple change in formula actually resulted in $13k being saved. However, we do understand that there may be a possibility that the calculated losses may very well fall within Vanitee’s budget.

Services

Figure 28 - Services breakdown by price	Next, we shifted our focus to the services table, which includes the services that professionals have created through the application. For the following few analysis, we have only looked at services that are published, meaning only those active services that are currently visible to customers for their selection. To start off, Figure 28 shows how majority of services are priced at $50 or less. This shows that professionals have a rough idea that services that are priced at $50 or less may be more attractive to customers. The previous graph showing how majority of bookings having a monetary value of $50 or less reinforces this point.
Figure 29 - Services breakdown by professional
Figure 30 - Services breakdown by category	Next, Figures 29 & 30 show the number of services that most professionals have as well as the category the most services belong to respectively. We can see that most professionals only have 1 service that customers can select from. A possible explanation for this could be the fact that some of these services could be over generalized such that the customer gets to only customize his or her service on the actual day of the booking itself. Also, as expected, majority of services offered involve nails, which corresponds the the graph earlier where most bookings are categorized under nails as well.

Campaigns

Figure 31 - Campaigns breakdown by duration	The final data table that we have explored and analyzed is the Campaigns table. Figure 31 shows that most campaigns last for either 1 week or 2 months. This duration is calculated by taking into account the start and end date of the campaign. However, this graph alone does not tell us why the above stated durations are more prevalent.
Figure 32 - Campaigns breakdown by type
Figure 33 - Campaigns breakdown by discount type	Figures 32 & 33 show the breakdown of campaigns by type and discount type respectively. We can see that majority of the campaigns involves partnering banks such as DBS etc. Also, these campaigns often offer a fixed amount of discount.
Figure 34 - Campaigns breakdown by discount amount	This discount normally amounts to less than $20 per booking which we feel is already a substantial amount for customers to utilize.
Figure 35 - Campaigns breakdown by usage	Next, we have also analyzed the campaigns by their usage. The way we calculated the usage basically whether a particular campaign has any booking that utilized the campaign codes belonging to that campaign. However, based on our previous meeting with Vanitee, we understand that such a graph may not be as accurate as it seems due to the presence of test data that we currently have no way of filtering out.
Figure 36 - Campaigns breakdown by duration from start to 1st booking (initial)
Figure 37 - Campaigns breakdown by duration from start to 1st booking (final)	Due to the uncertainty of the previous graph on whether campaigns created are actually being used, we decided to zoom into those current active campaigns that have at least one booking tied to it. From there, we came up with the above 2 graphs that tells us the breakdown of campaigns by duration from the start of the campaign to the very 1st booking made. Initially, 67% of the campaigns received their very first booking within 1 week of launch. After looking into further, we learnt that a positive percentage of 34% of campaigns actually had their 1st booking within 1 day. This shows how customers are quick to react to any new campaigns created.