Understand This Human Behavior To Boost Sales

human behavior

What’s up ? This is THE stephane ANDRE !!! I watched an Olivier Roland’s video  and I learned some good stuff.

There is human bias that needs to get around to get your company up to the next level. What’s interesting with marketing is that it exposes human behavior. Marketing allows us to understand good and bad human behavior

Lazy

This one of the most common human misbehavior. Take the example of a registration page for online training. There are 200 prospects interested in this training who gave you their emails to know the start date.

You divide the prospects into 2 groups, group A and B. For group A (100 prospects), you ask them to write their first names and emails and click on the OK button in the form to register. For group B (100 prospects), their first names and emails are already pre-filled in the form, just check the information and click on the OK button. In group B, there will be about 10% more registration compared to group A.

Which means that in group A, there are about 10% of prospects who don’t have enough energy or motivaton to write their first names and emails in the form.

Honest

honesty

This is one of the most common good human behaviors. Take the example of a guarantee of 30 days without conditions satisfied or refunded. Technically, there are plenty of people who could benefit from this guarantee by saying : « I’ll use this product for 29 days and I’ll ask for a refund ». Of course, there are people who do that, but it’s always surprising to see that it’s a small minority. It’s something nice to see.

Psychology

Unfortunately, there are limits in honesty and it’s necessary to understand some human bias to have a good company. Otherwise your company is in jeopardy.

In a detective tv show, there is a perone who is looking for the best detective for his problem. The hero of this tv show is a detective.

The person sees the hero and says : « I did some research and you’re the best in your field ».

The tell him : « You did some research, but what exactly did you do ? ».

The person answers : « It’s simple, I went to see all your competitors, I asked them who was the best detective and they all said it was them. Then I asked them who was the best second detective after them and they said it was you, that’s why I realized you were the best ».

Did you see the human bias in this example ? When you ask a pro who is the best, he’ll answer you : « Me ! ». The pro does this because he wants to sell, he has his personal pride and maybe he really believes he’s the number 1 compared to others.

Which shows that it’s difficult to have the most objective answer possible with this question. By understanding this human bias, you can use a question that gets around that. This question is : « Okay, it’s obvious you’re the best but who’s second best after you ? ». In the majority of cases, the answer is objective.

Price

price

Let’s take another example. An entrepreneur conducts a survey with his prospects to determine the selling price of a product. The question is : « What is the price you would pay to buy this product ? ». If you ask your prospects how they want to help them, they’ll be honest but when you talk about the selling price, it become complicated. When you ask the question about the selling price, they will always tell you a lower price compared to the price they could pay.

There are 2 reasons :

  1. When a person ansers this question, she thinks : « If I tell him I’m willing to pay 100 dollars, he’ll sell it to me at $100. So, I’ll tell him $50 like that it will be cheaper ». It’s a behavior that all human beings do (me and you included).

  2. There are people who don’t know how much they would be willing to pay because they can’t see the product. When they see the product and see what it can improve in their life, they’ll decide whether to buy it or not.

To solve the problem of the 1st reason, ask the question this way : « As you’re one of the people who helped me to create this product, you’ll have a special price, but what do you think the price is that the rest of the world should pay ? ». With this question, the prospect knows that he is going to have a special price so he can give a more objective answer.

To solve the problem of the 2nd reason, there is only one way. It’s showing the product to prospects.

When you do a survey to prospects for the sale price, it’s very important that prospects understand that they’re going to have a special price. Ask the questions : « What price would you pay to buy this product ? » and «  As you’re one of the people who helped me to create this product, you’ll have a special price. But what do you think the price is that the rest of the world should pay ». You will be surprised by the different answers you will have. Test it !

Obviously, it’s not only with this question that you will determine your selling price, it will be just a clue. It’s very useful to understand human psychology otherwise you risk choosing a selling price really too low that should be and earn really less money.

Subscribe to my newsletter and share this article if you think it can help someone you know. Thank you.

-Steph

P.S. If you’re in Miami and you like Caribbean food, go to my cousin’s bistro to eat Haitian food, click here.

A Pratical Tip To Validate Your Approach

data science tableau check

I have just enrolled in a Data Science course on Udemy  and I learned good stuff.

How was the A/B test « Number Of Product » ? Easy or difficult ?

Here is the result I found.

data science tableau check bar chart

I think you noticed there was something bizarre. There is an anomaly. We imagine that the more the client has products, the more the client is satisfied with the bank so this type of clients should stay in the bank.

In the first 2 bars we can see that a client who has 1 product is more likely to leave the bank than a client who has 2 products. But when a client has 3 or 4 products, we see a huge rate of clients leaving the bank.

Look, there is a little bizarre detail. In the 2nd bar, we can’t see the « Exited » label. This is because there is no place in the orange part to put the text. To make it simpler, we’ll remove the label « Exited ». Drag and drop on the « Exited » text label to the outside.

data science tableau check bar chart

data science tableau check bar chart

Perfect, we can read the percentages. On the 1st bar, we can see that among the client that have 1 products, 28% left the bank. On the 2nd bar, we can see that among clients who have 2 products, 8% left the bank. This show us that clients who have 1 products are more likely to leave the bank than clients with 2 products.

And for the next bars, we observe an anomaly. On the 3rd bar, we can see that among the clients who have 3 products, 83% left the bank. On the 4th bar, we can see that among clients who have 4 products, 100% left the bank. We clearly see that there is a problem and we need to do a deeper analysis to understand what is going on .

As a Data Scientist, we need to explain what happens in bars 3 and 4. Usually when a client has 3 or 4 banking products, that means he/she is satisfied and is loyal to the bank. But in our case, it’s the opposite because there is a high rate of client who left the bank. This is the time to do deeper analysis.

The first thing to analyze is the quality of the data. There is a very big anomaly and it may be because there is something insignificant in our data that disturbs the statistics. For example, it’s possible that when the bank selected these clients in this sample, there were very few clients with 4 products and all those clients with 4 products left the bank. Sometimes chance can create anomalies and you have to play attention to these effects of chance because they don’t seem important but they can create false interpretations.

To start, we will check the number of clients with 4 products.

In « Measure », move « Number Of Records » (which gives the number of observations) on « Label ».

data science tableau check bar chart

data science tableau check bar chart

We observe on the first 2 bars than many clients with 1 or 2 products selected for our sample. For clients with 3 or 4 products, we can see that there were fewer clients selected for our sample.

There are 220 clients with 3 products and 60 clients with 4 products. These small number of clients probably explain why we observe these anomalies.

In this sample of randomly selected clients, there are very few clients with 4 products and they all left the bank. In this situation, we can confirm that it’s a chance. When thing like that happen, you have to be very careful not to make conclusion too fast and make misinterpretations.

The conclusion is that a lot of clients have been selected for category 1 and 2. For category 3 and 4, there have been few clients selected so we can’t do accurate statistics. We need to do deeper analyze for these categories of clients with 3 and 4 products.

Now, let’s put the percentage back on the bar chart. Click on the « Back » button.

.

data science tableau check bar chart

Or do a click and drag of « SUM(Number of Record) » to outside.

data science tableau check bar chart

data science tableau check bar chart

We saw that there is an anomaly and what is interesting to do is to have a comment to remember to do a more in-depth analysis of columns 3 and 4.

Right-click between the bar chart’s title and the bars. Select « Annotate » then « Areas… ».

data science tableau check bar chart

A window appears. In this window, you write « Low observation in last 2 categories » and click on the « OK » button.

data science tableau check bar chart

data science tableau check bar chart

Click on the comment and move it on bars 3 and 4.

data science tableau check bar chart

data science tableau check bar chart

The next time you work on this bar chart, you will see this comment that will remind you to seriously analyze client who have 3 and 4 products.

Validate our approach

It’s time to show you how to validate an approach and how to validate the data. For this we will create a new A/B test.

Duplicate this worksheet with a right-click on the « NumberOfProducts » tab and select « Duplicate ».

data science tableau check bar chart

And rename the tab « Validation ».

data science tableau check bar chart

For this tab, we will erase the comment. Select the comment and press the « Delete » button on your keyboard.

data science tableau check bar chart

data science tableau check bar chart

Everything is ready, the idea is to find a variable that doesn’t affect our results. That is a variable that has no impact on a client’s decision to leave or stay in the bank.

Take for example, the variable « Customer Id ». Client’s identification number has no influence on the client’s decision to stay or leave the bank.

We’ll do an A/B test with the last digit of the « Customer Id » and we’ill check that there is the same clients proportion who leave the bank in the 10 categories of the last digit of the « Customer Id ». The 10 categories are the numbers 0,1,2,3,4,5,6,7,8,9.

Let’s g.To start, we will create the variable that contains the last digit of the « Customer Id ». To have this variable, we will create a « Calculated Field ».

Right-click on « Customer Id », select « Create » and click on « Calculated Field ».

data science tableau check bar chart

data science tableau check bar chart

Name the calculated field « LastDigitOfCustID ». In the text field, we use the « RIGHT » function with « Customer Id » in parenthesis to select the last character of the « Customer Id ». In our case, the last character of the « Customer Id » is the last digit.

Here is the code to write in the text field : Right ({Customer Id},1)

data science tableau check bar chart

data science tableau check bar chart

Oooops, you see there is a small mistake => The calculation contains errors.

There is an error in the formula because « Customer Id » is a number variable and the « RIGHT » function applies to a variable of type « STRING ».

To use the « RIGHT » function, we will convert « Customer Id » into a string. We will use the « STR » function with « Customer Id » in parenthesis.

Here is the code to write in the text field

And click on the « OK » button : Right (STR({Customer Id}),1).

data science tableau check bar chart

Now, you can see that our calculated field « LastDigitOfCustID » is in « Dimensions ».

Click on « LastDigitOfCustID » and move it on top of « NumOfProducts » in « Columns ».

data science tableau check bar chart

data science tableau check bar chart

Now we have a new bar chart and we see that for every last digit of the « Customer Id » there is about the same proportion of clients leaving the bank. All these proportions don’t correspond exactly to the average of 20% but these slight variations aren’t important.

Seeing this uniform distribution allows us to validate our data because these data are homogenous.

Conculsion

Here’s how you can check the homogeneity of your data. You take a variable that has no impact on the fact that a client leaves or stays in the bank. The example we did with the last digit of the « Customer Id » is excellent. We were able to verify that in each of the categories taken by this variable, if there was the same proportion of clients leaving the bank. As is the case, we can validate our data.

Imagine another result. When we do the test with the last digit of the « Customer Id », we observe that for one of the numbers, the rate of clients who left is really higher than the average. This shows us that there is a problem in our data because it indicates an anomaly.

You can find other ways to verify your data by using other « insignificant variables » to see if the distribution is homogeneous. But be careful when you select an « insignificant variable » because there may be traps.

Here is an example. If you create a variable that takes the first letter of the first name, the distribution will not be homogeneous. The reason is simple, there are many more people who have a name that starts with the letter « M » than with the letter « Y ».

Share this article if you think it can help someone you know. Thank you.

-Steph

Online Guarantee

online guarantee

I watched an Olivier Roland’s video  and there is good stuff.

In Europe (yes, I’m living in Europe), the law says that a consumer has 15 days to return a product he bought by mail. Products bought on internet are part of these purchases by mail as digital products, training or softwares.

The law also says that a consumer may waive the guarantee by checking or unchecking a checkbox to receive a product faster. Some companies have a procesure to wait until the guarantee’s period is completed before sending a product to allow time for the consumer to think about if he/she changes his/her mind.

The most interesting guarantee to make is a 30-day guarantee for online training. If you do a 1-year training, you can make a guarantee on results with conditions. If after 1 year, a person doesn’t have expected results despite that person has seriously followed and applied the training’s content by showing evidence, that person may claim the refund.

For the 30-day guarantee, there aren’t conditions. Whatever reasons, a person is systematically refund. It’s true that is interesting to know why a person wants to be refunded but it’s not obligatory.

A guarantee for success

guarantee for success

Yes, it help you to have success because guarantee is a trial period for the entrepreneur and the consumer.

Consumer

Many people are anxious to buy a product on internet, especially if the product is digital. The guarantee make it possible to reassure them.

People who have hesitated to take an online training will continue to hesitate for 30 days but more intelligently. Because the 30-days guarantee are free trial days so they can see how it works, how is the content’s quality, how the community interacts with coaches, how is the track’s quality of each participant, etc. If your product is good, you’ll have more sale than refund.

Entrepreneur

This allows you to filter out annoying consumers. If during the 30 days, you see a consumer who demands weird stuff or complains, criticizes all the time or isn’t polite, you can say it’s better to stop and pay him/her back.

It’s like for a job, the employer sees if the employee corresponds to the workstation and the employee sees if the job is suitable for him/her. This for both side and it’s a good method to avoid having unnecessary problems.

Attention

I don’t advise you to filter consumers when you start your company. You need to accept all consumers to reach your break-event point. Once you have reached a certain threshold of success, you can filter your consumers.

The guarantee is also a legal protection. When consmers aren’t happy, they leave, it’s simple.

Marketing

human behaviour

With marketing, we can see human behavior and there are some surprising things. Here an exemple with a form to receive an eBook. We can have 10 % more conversion when we fill in the first name and email of a person in the form. We can do it only if the person is subscribed to our newsletter but this is show how people are lazy by nature.

Yes, 10 % more only because people just have to press the button « OK » instead to type their first name and email, surprising !

Something else. It’s true that you’re going to have people who will just register to enjoy the 30 days free but reassure you, it’s a very small minority. Most people are honest and if you gave a product that gives value and quality, you’ll have more sale than refund.

It’s easier to use this kind of guarantee with digital product but it’s possible to do it with physical products.

How do you set up this type of guarantee for your product ?

-Steph

Being Credible And Simple

credibility

I watched an Olivier Roland’s video  and there is good stuff.

How to do to use the power of simplicity to have more success ? Several studies have shown that humain being like simplicity. We like simplicity in name of things, people, products and companies. It isn’t an incredible information but there have been several studies on this subject.

Adam L. Alter and Daniel M. Oppenheimer did a great study. To validate the hypothesis that we prefer more companies with a simple name, they took 89 companies randomly in the New York Stock Exchange and they analyzed stocks performance between 1990 and 2004. Companies with a simple name consistently beat companies with a complicated name. The first year, there was a difference of $333.-.

« Predicting short-term stock fluctuations by using processing fluency »

by A. L. Alter, and D. M. Oppenheimer (2006)

They did the same study again with 170 companies et they found similar results. It’s surprising to see we are influenced by a simple name. I have a question for you, do you know a lot of successful companies with a complicated name ? It’s hard, such name like Apple, Google, Facebook, Sony, Acer are easy to remember because it’s simple names.

Simplicity = credibility

steve jobs simpicity

This means you must find a simple name for your company et also simple names for your products. Some studies have shown that two products with same features, it’s the one with a simple and friendly name that make the difference.

We, entrepreuneurs, it’s important to be simple in our communication with ours prospects, ours customers, ours suppliers et ours teams. The problem in companies world is some experts want show theirs expertises. Here a bad exemple :

« In line with our corporate values, our innovative solutions are placed in guiding our future customers. Responsiveness, professionalism and proximity are our priorities at all times ».

But what does that mean ? Who understand it ? You see, this is the type of communication to avoid. Often experts talk a jargon thinking it strengthens their credibility but the truth it’s this kind of speech discredit experts because we think they don’t know how to express the complexity of theirs ideas.

More you express simply, more you say your ideas in a simple way and more people will think you know what you talk about, more people will find you friendly. Avoid jargon, stay simple.

Look Steve Jobs business presentation. It was business presentation and everybody fought to be in the showroom. The key ? He used a simple langage. For the first iPod, he didn’t say : « there is a hard disk of 5Go ». He said : « You have 1000 songs in your pocket » and that’s what interests people. It’s a simple and clear langage that speaks directly to what interests us.

Be simple in your communication

-Steph