Descriptive Data Collection (Customer Analytics)

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来自 University of Pennsylvania 的课程

商业分析毕业项目

299 个评分

University of Pennsylvania

商业分析毕业项目

299 个评分

课程 5（共 5 门，Specialization 商业分析）

The Business Analytics Capstone Project gives you the opportunity to apply what you've learned about how to make data-driven decisions to a real business challenge faced by global technology companies like Yahoo, Google, and Facebook. At the end of this Capstone, you'll be able to ask the right questions of the data, and know how to use data effectively to address business challenges of your own. You’ll understand how cutting-edge businesses use data to optimize marketing, maximize revenue, make operations efficient, and make hiring and management decisions so that you can apply these strategies to your own company or business. Designed with Yahoo to give you invaluable experience in evaluating and creating data-driven decisions, the Business Analytics Capstone Project provides the chance for you to devise a plan of action for optimizing data itself to provide key insights and analysis, and to describe the interaction between key financial and non-financial indicators. Once you complete your analysis, you'll be better prepared to make better data-driven business decisions of your own.

从本节课中

Module 2: Defining the Problem

In Module 2, you'll define the problem adblockers poses for GYF. GYF is intended to be a composite of leading internet platform and content providers who derive substantial revenues from mobile advertising like Google, Yahoo, and Facebook, so you should frame your research around the real-world problems these companies have faced and are facing. Defining the problem thoroughly will have a direct impact on how successful your strategy will be received by your peers. The more deeply you consider the effects of adblockers on the companies that buy advertising space from GYF, the more appropriate your overall strategy is likely to be. Please use the resources below to find out more about the problem, and then create your Problem Statement and submit it for peer review below. You can and should draw from all of the Business Analytics Specialization courses, but your Problem Statement should focus on how adblockers might adversely affect GYF’s relationship with the companies that pay GYF to place advertisements on GYF’s mobile applications and content. You should consider the issue of causality in your Problem Statement - we've included some lectures from the underlying courses to refresh you on that topci. And you are strongly encouraged to complete and include a response to Application Exercise 1 (see link below) as part of your Problem Statement.

What is Descriptive Analytics? (Customer Analytics)6:25

Descriptive Data Collection (Customer Analytics)6:38

Passive Data Collection (Customer Analytics)4:58

Beyond Period 2 (Customer Analytics)10:11

Causality 1 (People Analytics)5:11

Causality 2 (People Analytics)6:47

Reverse Causality (People Analytics)4:30

Causal Data Collection and Summary (Customer Analytics)8:18

与讲师见面

Wharton Teaching Staff
Educators
The Wharton School

So in this part, we start talking about descriptive data collection.

So descriptive data collection, as you recall, basically talks about trying to

understand, for instance, who are our customers?

What is the share of wallet?

And all those kinds of questions where you have to have hard numbers.

So how can you do this?

This can possibly be done in two ways.

One is active data collection and one is unobtrusive data collection.

In the active data collection, you can start thinking about again two ways

broadly of thinking about data collection.

One is surveys, which is a mainstay of market research for many, many companies.

The other one are self-reports coming from your costumers,

we’ll talk about both of them.

So, let's start with surveys.

Surveys, pretty much used by every Fortune 500 company.

Regularly used for gathering customer attitudes, you can think about sentiments,

you can think about purchase habits,

many different things actively gathered by surveys.

And data of course can be helped to segment customers, start

thinking about who our customers are, start thinking about who do they buy from,

all of those questions that you need to understand to set your marketing strategy.

Now there are many, many companies out there that can hep you do these surveys.

I'll give you some examples.

Qualtrics is a very famous company that helps you conduct free surveys sometimes.

Another example is surveymonkey.

Now both of these companies not only help you do sometimes free surveys, but

they can also be full service companies.

So for instance, if you look at the pricing plan of one of these companies,

they allow you and they price you differently

based upon whether you would like them to find your customers.

You would like them to set up the survey, analyze the data and give you that data.

So in that sense, when you start thinking about doing surveys there are already

companies out there that can help you reach out to customers, collect that data,

and analyze that data.

And of course,

surveys are not the only way in which you can get information from customers.

You can actually ask customers directly to self report some of those surveys.

So if you look at, for example, mobile service, that's the next frontier.

And these are basically companies that are giving these surveys on mobile devices.

Again, some common examples, Qualtrics is one company that does both.

It does surveys on your desktop.

It also does surveys on mobile devices.

Another company, for example, is Mixpanel.

Again, what's the idea here?

The idea here is, you want to basically send surveys to customers in the moment of

purchase sometimes.

So what do mobile surveys allow you to do?

They allow you to capture customers' reactions in-situ

rather than being retrospective.

For example, you can actually send a survey to a mobile device of a customer

at the time that they're making a purchase decision, rather than one month later.

So clearly the kind of sentiment,

the feelings the customers might have at the time purchase might be better

captured, rather than making them think about their purchase one month later.

The questionnaire can be tailored based on location and context.

So, again looking at where the mobile device is.

In other words, it tells you where the customer is.

If the customer is in a mall,

you can ask questions about what they're doing in that mall.

If the customer is in a restaurant, you can ask questions tailored based on that.

So very tailored service can be done, but what's the caveat?

You don't want to overdo it.

Marketers should be very careful,

rather than using this leverage of making a tailored survey,

you don't want to keep sending surveys again and again to the same customer.

You quite often see a huge amount of survey fatigue setting in.

So it's important to again, use this power of mobile surveys, but up to a limit.

I also want to talk about one particular type of survey that has gained a lot

of recognition.

That's the net promoter score.

What is that?

It actually just boils down to one question.

How likely is it that you'd recommend a particular brand,

your company, to a friend or colleague?

Just one question.

It's done on a zero to ten scale.

The promoters are people who score a nine or ten on the scale.

Passives are people who score a seven or a eight.

Detractors are people who score zero to six.

And what's the net promoter score of your company?

That's the percentage of promoters less the percentage of detractors.

So what does this allow you to do?

This basically allows you to track the health of your brand.

Do your customers overall like you?

Or are there growing percentage of people who might become detractors?

Net promoter score has found a lot of leverage in terms of linking the score

to stock prices, linking the score to future sales and

as a leading indicator of how good your brand is.

So surveys are one clear way of reaching

out to your customers in terms of collecting data from them.

But there are other ways customers themselves

might be willing to give you some data.

So besides surveys where the company is reaching out to customers,

many times customers can reach out to companies by giving self reports of what

they are buying and when they are buying it.

So InfoScout is one example of a company that actually attracts of incentivizes

consumers to do the following.

Once they have to made their purchases, they take the receipt,

they have the mobile device, take a picture of the receipt and send it back.

What does InfoScout do with it?

They basically collect all this information across many,

many customers to get insight into when people are buying certain products.

Where are they buying it?

Is it in mom and pop stores?

Is it in convenience stores?

Is it in big box stores?

So that's one example in which customers are giving companies that information.

Another example would be word-of-mouth dynamics.

So as a company, we would like to know what people are purchasing.

But we also want to know what people are talking about.

How is our brand being mentioned?

So there are many companies out there that collect this type of data.

As an example, Keller Fay is a company that collects word of mouth dynamics.

How do they do that?

They have a panel of customers which basically are given the following task.

When you talk to somebody, note it down.

Who is it?

Is it a friend?

Is it a colleague?

What did you talk about?

Collecting this data in a diary format over time across months,

they're able to observe what people are talking about, who are they talking to,

how is a brand being mentioned and so on.

So word-of-mouth dynamics is a powerful way of understanding how

the brand sentiment might be changing over time, and or so on.

Now again, there are many,

many different ways in these people can collect this data.

Keller Fay is a company that does through panel data, through a diary form.

And there are other unobtrusive ways of collecting these data as well which you'll

talk about next.

So at this point, we talked about active ways of data collection.

Next we'll talk about unobtrusive, passive ways of data collection.

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