Placeholder Image

Subtitles section Play video

  • Hi everyone!

  • This is a quick crash course video where well talk about customers analytics, data science,

  • and how the two work together!

  • The topic we will be discussing here is price elasticity.

  • Leading companies are always on the lookout for savvy data scientists to join their fast-growing

  • Customers Analytics teams.

  • In that sense, considering a career as a data scientist in customer analytics is a super

  • smart choice.

  • But here’s why exactly: First, companies need people who know how

  • to use data to understand their customers' needs.

  • Once they understand their needs, they can provide the products customers want to buy.

  • Secondand that’s a bit more technicalcompanies need people who have the skills

  • to build the analytics capabilities that will help them provide these innovative customer

  • experiences.

  • In these videos, well be focusing on the customer part of customers analytics.

  • Why?

  • Because even if you know how to do the technical analyses well, unless you understand the customer,

  • you won’t be able to meaningfully help your company.

  • So let’s build those foundations, shall we?

  • Just one more thing before we get started!

  • We’d like to mention something else weve put together – a very comprehensive data

  • science training.

  • The 365 Data Science program contains the full set of data science courses you need

  • to develop the entire skillset for the job.

  • It’s completely beginner-friendly.

  • For example, if you don’t have any maths or statistics knowledge, well teach you

  • that first.

  • And if you’d like to build a more specialized skillset, you can do that with courses on

  • Time Series Analysis, Credit Risk Modeling and more.

  • If you’d like to explore this further or enroll using a 20% discount, there’s a link

  • in the description you can check out.

  • Perfect!

  • Now, let’s get into customers analytics and more specifically price elasticity.

  • In the broadest terms possible, price elasticity measures how purchasing behavior changes when

  • the price changes.

  • For instance, let’s assume a bottle of Coca-Cola costs $1.

  • If the price increases to $2, many people would stop buying Cola, as it would be too

  • expensive.

  • On the other hand, if the price decreases to 10 cents, many more people are going to

  • start purchasing Coca-Cola.

  • The measure we use to quantify this phenomenon is called: ‘price elasticity of Coca-Cola

  • demandorprice elasticityin short.

  • Now, as you can imagine, if we assume that a Pepsi also costs $1 and Coca-Cola cuts its

  • prices to 10 cents, then most of the people that used to buy Pepsi, would immediately

  • transfer to coke.

  • If prices of coke increase to $2, instead, people will likely stop buying coke and turn

  • to Pepsi.

  • That is to say that there seems to be another important phenomenon - ‘price elasticity

  • of Coca-Cola demand with respect to the price of Pepsi’, or the so-calledcross-price

  • elasticity’.

  • Now, in the first case, where we measure the elasticity of Cola with respect to itself

  • only, we call that own-price elasticity, price elasticity of Coca-Cola demand, or simply

  • price elasticity of Coca-Cola.

  • However, in the second case, where weve got 2 products, we must say the whole name:

  • price elasticity of Coca-Cola demand with respect to the price of Pepsi’, in order

  • to be sure that there will be no confusion.

  • Alright.

  • Now that we have an idea about what price elasticity is, let’s discuss it in economics

  • terms.

  • Price elasticity stems from the basic economic law of supply and demand.

  • The cheaper the productthe higher the demand.

  • The more expensive the product, the lower the demand.

  • Simple as that.

  • It is extremely important for businesses though, because there is this sweet spot which maximizes

  • revenue.

  • Since revenue is equal to thepricetimesunits sold’, we can use this price

  • elasticity concept to find the point at whichpricetimesunits soldis optimal.

  • Okay, but how does this look in mathematical terms?

  • Well, price elasticity is the percentage change of an economic outcome of interest in response

  • to a 1% change in the respective price.

  • Usually that economic outcome of interest is the number of units sold.

  • Let us denote the economic outcome of interest with Y, and price with P. Then, the price

  • elasticity of the Y must reflect the percentage change in Y in response to a 1 percent change

  • in the P. We can obtain that by taking the percentage

  • change of Y and dividing it by the percentage change in P. Well, the percentage change of

  • Y is the difference between its present and past value, divided by the past value.

  • Similarly, the percentage change ofPriceis the difference between the present and

  • the past price, divided by the past price.

  • Okay.

  • Now let’s tie price elasticity to the subject matter of our course.

  • Remember, were going to address three questions related to economic outcomes of interest:

  • (1) Will a customer buy a product from a particular product category when they enter the shop?

  • (2) Which brand is the customer going to choose?

  • (3) How many units is the customer going to purchase?

  • These three questions boil down to the estimation of the following economic outcomes of interest:

  • (1) Purchase probability, (2) Probability for brand choice, and

  • (3) Purchase quantity.

  • Naturally, we would be interested in price elasticities of each of these economic outcomes,

  • so well look at: (1) Price elasticity of purchase probability,

  • (2) Price elasticity of probability for brand choice, and

  • (3) Price elasticity of purchase quantity.

  • Okay.

  • It’s time to see why we need each of them.

  • What can we expect when we calculate the price elasticity of purchase probability?

  • Well, there may be a lot of different brands with differing prices from the same product

  • category on the market.

  • For instance, the price of different brands of beer.

  • Suppose we can calculate an aggregate price for the whole category.

  • The law of demand says that the greater the price, the lower the quantity that customers

  • want to buy.

  • So, if the aggregate price increase, the probability of purchasing a beer would decrease.

  • And calculating price elasticity will show us how much exactly.

  • What about price elasticity of probability for brand choice?

  • Well, that’s the most interesting one.

  • And it’s the most important for marketers, as well.

  • If youre working for Oreo, you’d be interested in the Oreo brand, not in the aggregate biscuits

  • sales across the board.

  • That’s why all marketer’s efforts are devoted to influencing customers to choose

  • namely their brand over competing brands.

  • Similar to purchase probability, we can assume that if the price of a product from a given

  • brand increases, the brand choice probability for that brand decreases.

  • Again, calculating price elasticity of brand choice for a brand with respect to the price

  • of that brand would show us exactly how much.

  • Accordingly, if another brand increases its unit price, the brand choice probability of

  • the brand of interest would increase.

  • This is precisely the Coca-ColaPepsi example we started with.

  • Such elasticity calculations will show us how much the brand choice probability of our

  • brand would increase with a one percent increase in the price of a competing brand.

  • Nice skill to have, isn’t it?

  • Well learn how to do that and even more.

  • Finally, well discuss at length price elasticity of purchase quantity.

  • As you might expect, following the law of demand, the greater the unit price of a product,

  • the lower the quantity that is going to be purchased.

  • For a car, the difference may be from 1 to 0.

  • If the price of a Tesla is acceptable to us, we will buy 1 unit.

  • If it isn’t, we won’t buy any.

  • Alternatively, if were considering, let’s say, avocados, depending on the avocado price,

  • we may decide to buy 0, 1, or even 10 avocados at once.

  • Calculating the price elasticities will show us exactly how the purchase quantities move

  • with the change in price.

  • I bet youre impatient to see how all this is done and learn to do it yourself.

  • Well, let’s get to it.

  • To do all this, we could use many statistical software packages, such as SPSS, SAS, and

  • R. Here, we chose to use a statistical computing environment, which is widely used, has growing

  • popularity, and indicates it has the potential to become the most popular amongst data scientists:

  • Python.

  • We hope you found this video helpful.

  • And if you enjoyed it, please take a second to subscribe to our channel, hit the like

  • button, and share the video with your friends!

  • Thanks for watching!

Hi everyone!

Subtitles and vocabulary

Operation of videos Adjust the video here to display the subtitles

B1 price cola probability brand coca cola coca

Price Elasticity- Learn Customer Analytics

  • 2 0
    林宜悉 posted on 2020/03/09
Video vocabulary