Pricing Analytics: Optimizing Price
ฝัง
- เผยแพร่เมื่อ 16 ก.ย. 2024
- The “best” price for a product or service is one that maximizes profits, not necessarily the price that sells the most units. This presentation uses real-world examples to explore how Excel’s Solver functionality can be used to calculate the optimal price for any product or service.
Downloadable slides are available from SlideShare at goo.gl/yGmGfq
This is a really good example of a business solution that is quite counter intuitive. I will suggest this video for any economics or business school students.
You can also use the formula p*= (A+Bc)/(2B) where A is the intercept (15,000 in the example) and B is the trend (133.33). That is p*= (15,000 + 133.33*59)/(2*133.33) = 85.75
AWESOME! thank you for sharing the formula, this will save me from doing the solver all the time!
Thank you, I had only ever done optimization with IBM CPLEX software, and didn't realize you could use Excel.
thank you so much, this made it very clear to me
-need an equation linking to your quantity and cost for the objective
-having costs set as changing variable
you optimise Total Profit cos after transformations you get a QUADRATIC function which as a curve has a max point.
If you study economic course then definitely read *_Managerial Economics_* by Samuelson, Marks. There is a whole chapter about that kind of optimisation calcs using demand curve.
Thank you! I was able to do my homework after I saw this!
I sugest complementing this with a video of simple linear regression and efficient frontier. you will picture in your head what the solver function is doing
Efficient frontier? Are you implying a "short sell" on printers and "longing" the cartridges? That is a weird way to visualise this. I understand it as simply picking a point on the line that results in the biggest squared area in the chart from that point to (0,0).
I love the video, although I have a question... where are we getting p=75.75 and d=4900?
rice elasticity = 2 that means if the price increases 1%, the quantity decreases 2%. Price increases 1% = 75.75 and the quantity decreases 2% = 4900
@@williamtourot5601 Thank you so much William!
@@williamtourot5601 where can I get info about every specific things elastity?
where does the '$8/$9' change to '$8$7' come from?
How come the other point on the demand curve was 75.75 and quantity of 4900? why not 80 and 4800
price elasticity = 2 that means if the price increases 1%, the quantity decreases 2%. Price increases 1% = 75.75 and the quantity decreases 2% = 4900
thank you
Watch how simple regression works, that's what is called "the slope", there are very good videos on youtube about it.
Awesome!
What if you have 5% of people that are able to get the lower price, i.e. cannibalization? How do you represent this in Solver?
Can you tell me how you came up with the Demand formula?
current price P0 1.5
current qnty Q0 2000
new price P1 1
new qnty Q1 4000
Q1-Q0 2000
Q1+Q0 6000
(Q1-Q0)/(Q1+Q0) 0.333333333 A
P1-P0 -0.5
P1+P0 2.5
(P1-P0)/(P1+P0) -0.2 B
A/B -1.666666667
start from y = ax + b
Y = B - Ap ; p-price, a,b-coefficients
cos it's linear model and higher price causes a decrease in demand.
Use at least two points (price,quantity) but in real cases you may need more data to see some pattern.
For some reason, I get really wierd values for the second example and don't get 525,112.42 as the total profit
hi, this may be 1 year later, I think the reason is the formula at 6:30. if you enter 15000-133.3*B7, instead of 15000-133.33*B7 (note the decimal places), you would get 525, 112.42
Boh da queste parti.. 👟