Many students said: I clearly did BI, but why can't I reflect my performance? There are not many people who even read reports. It makes the leaders question every day: What is the role of our BI?!
What's up? !
In fact, the smell of wine is also afraid of deep alleys. All kinds of problems have something to do with many students who can only bury their heads in typing on the keyboard instead of raising their heads to tell stories. Today we have the most easy-to-understand sharing, everyone sit down and stay steady.
1. Why data products are useless
Ask a simple question: a salesperson who does not perform well this month, what will he do?
- He will scan the customer phone
- He would run off his leg to find potential customers
- He will look around for the latest promotions
- He will be pious for advice
Huh? What about the data?
It's Di, the only thing he doesn't do is look at the data. As long as he can read the data, he won't work on the front line. Even if he sits in the office and looks at the data, he will be kicked by the leader: "Don't work every day! Where does the performance come from!" For the front-line grassroots such as sales, clerk, and teller, the data is useless. What they care about is what they can do.
Will their leaders care? Will care, but they only care about the result:
- How much did you do this month?
- How far is it to meet the standard?
- Which little brat did the worst?
After that, he probably kicked his ass angrily.
Facing the subordinates who are waiting to be fed, they need skills, lists, methods, and policies. Only there is no data.
This is the true portrayal of most physical companies: To make money, chase performance, just increase the amount of action, regardless of the logic behind it. However, their senior management often hopes to promote digital transformation, information construction and so on. So the tragedy began: the buddy in charge of the data finished talking with the boss, thinking that he was holding the sword of Shangfang and entering the scene, he began to engage in BI system, data modeling, and data warehouse construction. As a result, the people below did not dare to attack the boss, but he dared to attack you, the worker, so he made various complaints: "Your big data is useless! It's not easy to use! Can you sell me a dime?" Lun Tucao came down, and ended sadly.
What to do? ╮(╯﹏╰)╭
2. What is the nature of the problem
The essence of the problem is: data is not an ancestral life-saving elixir, it cannot be eaten. As far as sales performance is concerned, promotion is the elixir of life, and sales will surely occur once the price is reduced. But we know that the so-called life-saving elixir is actually mercury, nitrate, and sulfur, which are highly toxic things. People will die if they eat too much. Therefore, the data is more like a health product. Although it is not a life-saving product, it will not be delayed to the point where it is necessary to eat elixir. How to visualize this slow health effect is the real problem with data products.
"Then why don't we learn to sell health products!" Don't laugh, Teacher Chen not only said so, but also did it. And I really work as a driver, and I go with a bunch of old ladies to participate in the old farmhouse organized by organizations that are not MLM but similar to MLM. And very seriously summarized their promotion routines. To put it simply, it is: divide and conquer, coercion and temptation.
First of all , people who sell health care products will never say that they are protein powders. Protein powders are common. They usually mention: XX amino acids, XX nucleic acids, and XX molecules. In short, the name is very tall. Secondly, selling health products will never say that they are just a complementary food. People open their mouths: prolong life and live longer. So the first wave of curious old ladies who are not bad at money will try.
With a breakthrough from 0 to 1, everything behind is fine!
In the second wave , I started to attract small favors: "You see such a good thing, you try a little bit and you don’t suffer. Someone is already buying it. You see how well they eat it. Now you buy it and you get eggs, milk, rice, oil, I can still go to the farmhouse on the weekends"-just like this, another wave of old ladies.
In the third wave , the herd effect started: "You see everyone is selling, so you can try it, so many people can't be wrong to buy it"-just like this, another wave of old ladies.
In the fourth wave , he began to threaten and intimidate: "Hey, look at that aunt, everyone is not using her. It's a pity, maybe her child doesn't give her money/maybe her financial strength is not enough, it's a pity, too pity "——Yes, you are very pitiful if you don't buy it. You are inferior to others, so you even spit out the last wave of old ladies.
PS: This is why these people like to hold conferences in closed spaces, such as suburban hotels and farmhouses. If the environment is closed and there is food and drink, this is very easy to handle. People in small circles are easy to be surrounded by people. Drive emotions.
perfect!
Speaking of this, does everyone understand the essence of BI (Business Intelligence)! I was curious before that BI was clearly a data product, but it had a name that didn't even have data. Where is the business? Where is it smart again? Now I understand-you mention data products, just like an old lady's protein powder, they don't care at all.
You can only start the first wave of flicker if you have a name (smart) that is related to the company's making money (business) at the first hearing, and that is very high and deeply understood by others. This is the longevity ointment we sell to companies. But it’s Gartner from Amway’s hometown. When they named BI, did they also discuss with Amway...
The break starts here.
Three, data products break the game
First of all, we must be clear: we have to buy data first, and then we can make good data. If the data is not a good buyer, there is no selling point, such as fields, models, formulas, and charts that attract buyers, the more you make, the more annoying others will listen. Thinking from the buyer’s perspective: "What can I do?" Can I help him strengthen the control of the frontline, or can I make the frontline work easier? Focus on customer needs first, and then talk about landing.
Secondly, it must be clear: data is difficult to generate value alone, and people who use data need to cooperate. So "people" is the key issue. Different people have different demands for data and have different levels of understanding of data. Therefore: Divide and conquer. First find those who have the most trust in the data, and use people as the first wave of seeds. After that, it is divided into five levels and gradually advances.
Once again, there must be a means of advancing. What I said before: the four tricks of magic concept, small favor, herd effect, and threats are very useful. In fact, they are often mixed in operation. If the customer likes mystery, you can talk to him: big data, artificial intelligence. If the customer likes to be down-to-earth, you can talk about: sales assistant, store manager assistant; if the customer wants to start at the grassroots level, you can talk to him: first-line empowerment, ability fission, and experience inheritance. If customers want to strengthen management from top to bottom, you can talk about data-driven and data-based management. In short, the concept must be packaged in place. In short, there are always concepts available.
Xiao En Xiaohui's play style is very useful in promoting to the first line. Back then, when there was no WeChat red envelope, Mr. Chen once made a red envelope page in the corporate CRM, popping one at 6 o’clock every evening: "Congratulations on getting the red envelope for today’s president/district/store manager." Sales people like it. , Click in to see how much I earned today.
Of course, this is just a gimmick. After entering, most people only have a few cents, and it's just a number. It is about the payment of salary at the end of the month, but in fact, no one remembers it often. But the person with the best performance in each district that day really had a red envelope of 88, and other people also saw it. At this time, everyone would be curious: how did he sell so well? Click further down, and the data products you really want to push are hidden here.
A little trick can directly increase the utilization rate of data products in the first line. Of course, you can't use this small method for leaders, but rely on the overall business results-you see that Renjiadian has a coup! Do you want to know? You see that when people push A product, they can push it! Want to know? After digitizing the behavior of excellent teams and talking directly with pictures, leaders soon accepted the use of data products.
When the utilization rate rises, the herd effect will start: Most branch companies use a unified data template to report, why don't you use it? ! When more people were using it, they began to threaten and intimidate: If you don't look at the "sales assistant" for poor performance, it's no wonder you can't do it! So successfully broke through the initial problem and popularized data products.
Of course these methods are somewhat outdated. On the one hand, with the increase of Internet customers, a lot of demand no longer comes from sales, but from the operation department. The operation naturally likes to look at data and does not need to use these scams. Secondly, starting from 2017, the whole society has not despised data, but has become superstition about data, so avoiding excessive expectations has become the main direction of the project. But this set of ideas still works in some areas, such as Meituan, Toutiao, 58 companies that wear the cloak of the Internet but have huge offline teams, such as many companies that are still struggling in the quagmire of informatization and digital transformation.
Of course, by sharing these early experiences with the students, I hope you can feel the thought process of those old men who made roads in the mountains and bridged the water. I have never been born in an industry where leaders are wise, colleagues are harmonious, teammates are awesome, and customers are stupid and rich. All problems arise from "people", and then solve them through the idea of "people", and encourage everyone.
So here comes the problem, two problems in the new era:
1. Operations always like to look at the data by themselves, and then diss data analysts do nothing
2. The business department always expects "big data, artificial intelligence, precision", but the data foundation is poor
Which question is more interesting to everyone? See you in the comment area, let's share the next one.
Author: Chen grounded gas, micro-channel public number: down to earth school. A data analyst with ten years of experience and CRM experience in multiple industries.