Assume you have a loyalty rewards program, where every user who makes a purchase earns 200% of their order amount as reward points and when users return the item - the 200% points based on the current price of the product are deducted. We suspect some users have realized a gateway where they buy the product at full price but return when it is at discounted price so they keep the net difference in points (the refund always refunds full order amount). If user does this accidentally or if the impact is less than 5000 reward points then business wants to ignore but identify anyone who is abusing this - how will you identify such users based on last 6 months of order and refund data. How will you identify this in real time as new orders/refunds are processed.
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I am writing a trading bot in C++. I am making limit orders that allow for 1% leniency. As you can see there is a market price of 2.2532, and I made a limit buy at 2.2757. Logically, if the limit buy should be activated once the market price is at or below the limit price. However, as you can see from the pictures below, this is not the case. I posted pictures of both the order book and the trade history. What I am wondering is why. Does this have something to do with the order book? I also noticed when placing market values generally there is a fairly large discrepancy between the price of the market and the average price it is filled at.
Since getting the market price on Binance does not seem to actually tell you if the market order will be full-filled at that price, or if the limit order can go through at a price around there. Is there a way to actually programmatically/mathematically find out if a limit order will go through. Or, find out what the actual average price of a market order will be if bought in that moment?
UPDATE
So when I go to place a market order, I get this message:
Your order price will be 8% higher than the latest market price. Please proceed cautiously. When I want to buy at the market price. Partially I want to know why. But also, is there a way to get the exact number in which this price will be? Also, Is there a way to get this on the API exactly what the next market buy/sell will be?
After some more research on the question. According to investopedia
A trade will only occur when someone is willing to sell the security at the bid price, or buy it at the ask price.
Meaning, the price at which the asset will be sold at has less to do with the current market price, and a lot more to do with the order book. Looking at the pictures above, at that time according to limit orders the lowest someone was willing to sell the asset was, was 2.500 and the highest someone was willing to buy the asset for was 2.499. These are the ask price and bid price respectively. Since no one was willing to buy at the ask price or sell at the bid price, the transaction did not go through. Notice that the quantities are also important for knowing how much of the order will be filled, for your future reference.
For those that might be a little confused, you need to buy at the lowest someone is willing to sell. You need to sell at the highest someone is willing to buy. These come from the limit orders.
Back to the original question, the update on the 8% difference makes sense, the ask price probably dropped a little. However, if you notice 2.2532 * 1.08 is 2.433456 which is much closer to the 2.5 price above than the limit buy created at 2.2757 meaning the 8% notification makes sense.
I will now explain how you would calculate this using mathematics and coding. You need to pull from the order book ticker. This api request is /api/v3/ticker/bookTicker
I am going to use the example of wanting a market buy for GRTUSD. The dictionary you get back from the link https://api.binance.us/api/v3/ticker/bookTicker?symbol=GRTUSD is {"symbol":"GRTUSD","bidPrice":"0.1391","bidQty":"3613.45000000","askPrice":"0.1393","askQty":"5183.18000000"}
Some quick math shows that 5183.18000000 of GRT is the equivalent of a little over 722 USD at the ask price. This means if I placed a market buy for GRTUSD. As long as the amount of USD I was investing at that moment was equivalent to or less than 722 USD it would get filled at the ask price of 0.1393
I have little experience with payment gateways, and am trying to figure out how to synthesize the type of subscription billing that I am looking for: the monthly price gets rebalanced once a year, based on another attribute (a number that can get as high as seven or eight digits).
So, for example, the monthly subscription price as of January 1st will be a % of a user's credit card debt balance as of Dec 15th in the prior year. But the debt balance can get very high / does not have a cap.
I looked at the Stripe documentation to figure out of there's a way to do this. The only thing I could come up with is to use unit_amount in metered pricing and tying this to the credit balance. In other words, I would grab the debt balance number and use it as the unit_amount, and then apply a %. But then I need to also forward bill, so I trick the logic into shifting by a month, which seem impractical.
Alternatively, I am not sure I could do this with per seat pricing (e.g. $1 in debt = 1 seat). But I assume there's a max to the number of seats (i.e. someone cannot have, say 1m seats). I just couldn't determine this from the documentation...
That's what I was thinking, anyway. Perhaps there's a better way?
You've got a couple different options here:
At the start of the year you update the Subscription to a new price based on the calculations of the customer's credit card debt balance by specifying items[0].price_data. Setting items[0].price_data (see the api ref) allows you to create an "in-line price" that as part of the updating the Subscription, so you don't have to create one separately through a separate API request. If you haven't seen Stripe's docs on how to update the price of a Subscription you can see an example here, and you'll likely want to read about proration_behavior as well.
You have a single Price where 1 seat = $1 in debt, and you control how much you want to charge by changing the number of seats for the Subscription. I don't think Stripe has a limitation to the number of seats (as long as it's a valid integer), but they do have a limitation on the maximum amount you can charge which you can read about here. For USD the maximum charge amount is $999,999.99, so the maximum quantity would be you could specify for a $1 price is 999,999.
You could look into using metered pricing, but given that you don't want to bill at the end of the billing cycle the other two options seem better.
I think the first option (updating the price year by year) is your best one, but definitely try all of them out in test mode and take a look at how the Invoices look to see which one you like best.
we run an eCommerce store and constantly create & test new Facebook Ads. Now I am looking for a good way to create a scoring for these ads. Basically it is a very simple problem, but I can't get my head around it.
For each Facebook Ad, I have this data:
Budget Spent
Impressions
Clicks
Product Page Visited
Purchases
The most important event obviously is the purchase. So in a perfect world with huge amount of data per ad I would simply calculate the cost per purchase (= Budget Spent / Purchases) and know, which is my best ad. But here comes the problem..
On each ad we don't have much data. So let's say we have:
AD 1
50€ Budget Spent
10.000 Impressions
200 Clicks
50 Product Page Visits
2 Purchases
= 25€ per purchase
AD 2
50€ Budget Spent
10.000 Impressions
400 Clicks
130 Product Page Visits
1 Purchases
= 50€ per purchase
Simply based on the cost per purchase, I would choose AD1. But when I am looking at the data of the previous steps (clicks and product-page-visits), AD2 looks more promising.
How can I create a score value, that tells me which ad will likely generate the better cost per purchase in the long run, considering also the values of the previous steps?
That score value should take into account the data of the previous steps. So if we have less purchase-data, it should strongly rely on the previous data and if we have much purchase-data, it should rely less on previous data (and more on the actual cost per purchase).
I think of something like:
Use the click-rate as the base score (because we have much data for this)
then modify that score with the values of the following steps but in a weighted-way. So the more data we have on the following steps, the more the score moves toward that values.
Thanks in advance for your help!
Best Regards
Patrick
I'm working with Stripe. Our users subscribe to our service and they are billed every 2 weeks. We need to implement a way to give them $5 credit every time they refer someone to use our service.
Solutions I have considered so far:
Stripe coupons: Stripe has great documentation. Unfortunately, for
coupons there are many ambiguities. I tried working with coupons but
so far it seems like a coupon can only be applied once for each
invoice, and you can't apply multiple coupons for one invoice. This will not work with us since a user can earn $5 multiple times during the billing period.
Issuing refund: the problem with this is that we have to pay the user actual money while what we actually want is to give them credit to use in our service.
Am I missing anything with coupons? Are there any other solutions/suggestions?
If I understand your use case correctly, I think the best way would be to create an invoice item with an amount of -500 for each referral. When you create an invoice item, by default it is set as "pending" and will automatically be included in the next invoice, i.e. at the end of the current billing period.
Be aware that if the invoice's total is negative (in the case of many referrals), then the total will be added to the customer's account_balance and reduce the amount of the next invoice as well. If this isn't what you want, you'd need to reset the customer's account_balance to zero, or make sure that you don't create invoice items that will make the invoice's total go below zero.
More information about invoice items can be found here: https://stripe.com/docs/subscriptions/guide#adding-invoice-items. The guide only mentions invoice items with positive values (i.e. additional charges), but you can use negative values as well.
Have you considered just checking for available credit in transactions before you charge?
That way you can just store how much credit people currently have in some database, and just apply the balance on transactions. AKA charge them for full_price - total_credits.
Here is another question I have about being able to calculate this scenario in Access, or even at all for that matter:
I have a query that find the TOP 5 items sold in a given timeframe, and it groups by site. I use this to create a comparative chart between the site for ppt presentations. I do a lot of these but I have a problem with the presentation that I foresee they will have a problem with and it makes for bad metrics:
Some stores are bigger than others, and get much more supply. So a straight aggregate total of just qty of toping selling items, and comparing the locations is stacking the deck a little.
So if Site A gets 80% of the supply, and sells 500, Site B gets 15% supply and sell 75, and site C get 5% supply and sells 50 items, then Site C actually has the best sales for their size. I have exactly what I need in terms in the first chart (from my queries and such) to show the aggregate total, but what do I need to represent the idea mentioned above.
The factors that I have that go into this are:
ItemID - group by
Item - group by
qty sold - sum/descending (which is the variable that determines the Top 5)
Store/Location - Group By
and then I run a seperate query to get the total deliveries (supply) to each site
I realize that this may just be a lack of mathmatical understanding on my part, but can anyone help with this?
thanks
The first issue that I see isn't about SQL savvy; it's how to serve your data customer. What does he or she want to see? Metrics is a term with a holy ring, and for good reason: it's supposed to be what is used for the big business decisions, and it's scary easy to measure the wrong thing.
So I'd make sure I know what my customer wants. If you can't model it on a spreadsheet, you won't be able to develop your reporting effectively.
Every deck of cards is loaded. You have to know how they want it loaded.