In the B2B industry, how to conduct analysis when there is a lack of data?

In the B2B business field, data analysis is a key tool to drive performance growth, but many companies suffer from a lack of data. This article explores in depth how to cleverly use existing resources for effective analysis when data is insufficient.

Many students complain that their company has no data at all, so how can they analyze it? At this time, you must remember these eight words:

Therefore, the first step in doing B2B analysis is to stop complaining and carefully sort out the data we have. Even if the foundation is poor, we have to start from here.

Remember, you have at least three pieces of data: the contract + the salesperson's payroll + the salesperson's resume. These three things can reveal a lot of information.

• Contract: customer name, industry, contract amount, purchased products, usage behavior (some can be monitored afterwards)
• Sales staff salary list: Which region and which team's sales staff are good at closing deals? Is it stability or luck?
• Salesman resume: whether he has working experience, whether he has his own resources, age, working time

So, do you have some feeling? Let’s analyze the last scene.

Scene restoration:
A SaaS company's sales team resisted using CRM software, saying: This thing has poor functions. So a large amount of data was recorded manually in a small notebook, and the system records were seriously missing, and the existing records were filled in randomly. Now the performance has declined, and the data analyst is required to analyze the reasons and countermeasures. Ask how to analyze.
Question 1 (fill in the blank)
Q: In the above situations, you first get information about

(The question is complicated, think about it for a minute)

How many students were misled by the introduction at the beginning and plunged into the contract or payroll and couldn't get out (yes, this is Teacher Chen's "pie-in-the-sky" teaching). Please note that the beginning said at least some data. The most critical data is not this, but sales leads.

Sales leads are the starting point of all B2B sales analysis. Only by grasping the starting point can we understand the whole process. So here you need to fill in: sales leads. If you don’t get sales leads and just look at the final order data, you may end up with a lost business (as shown in the figure below).

There are two types of sales leads: those provided by the marketing department and those developed by sales themselves. If they are provided by the marketing department, they are likely to have rich relevant data (those developed by sales are very likely to be incomplete/untrue/not submitted to the company at all).

So when you encounter B2B diagnostic problems, first understand:

• Where do sales leads come from?
• What are the fields?
• Where is it documented?
• Is there an initial entry time?
• Is there an initial assignment/follow up time?

Question 2 (multiple choice)
After understanding, it is found that sales leads are divided into two categories: leads provided by the marketing department (with storage time and first allocation time), and leads developed by sales themselves (with storage time, but it is filled in casually and is not true). Then, the following analysis should be done:
A. Analysis of all sales leads
B. Marketing department clue analysis
C. Sales lead analysis

(The question is complicated, think about it for a minute)

Note that this is the core crux that many students cannot analyze. We say that the B2B sales process is long, and we can use the funnel analysis method. But if the management is chaotic and too much process data is missing, this funnel does not exist. If you only have the final signed contract data but don't know why you signed the contract, there is no solution. So here we have to restore the funnel as much as possible, even if many links are missing, it is still a rough funnel (as shown in the figure below).

So, here is option B. Because the numerical quality of sales leads is too poor, give up first. Start with the ones that can be calculated, and finally clear the ones that cannot be calculated. This distinction seems simple, but it is actually of great significance. In the B2B industry, when there is a problem, the market, sales, and products blame each other (if it is a problem with the renewal rate of existing users, the operation must also be dragged into the fight).

As a data analyst, it is very important not to be overwhelmed by all kinds of criticism and to reflect the problems objectively.

Question 3 (multiple choice)
After analysis, I found that the leads provided by the marketing department were very touching, without any customer labels, and could not be classified. I could only count the overall leads/orders. Now the statistics: the trend of the number of leads and the order rate is as shown in the figure below. Question: Is there any problem with the work of the marketing department? ? ?
A. Yes
B. No

(The question is complicated, think about it for a minute)

How many students said there was a problem just because the stock market had been falling in the last three months?

Note that the decline may be a seasonal trend. From the data provided, the order conversion rate in June, July and August was the same as last year, but the number of leads obtained increased significantly, which is at least a satisfactory performance. Because there are two indicators, quantity (number of leads) and quality (order conversion rate), we can use the matrix method (as shown below) when tracking indicator changes, which can help us better judge the quality of market work.

If there is a problem, point it out; if there is no problem, clear it up.

It should be noted that considering the long B2B sales process, the order conversion rate needs to be calculated based on the life cycle, not the calendar month.

Question 4 (multiple choice)
After analysis, we found that the number of leads and the closing rate of the leads provided by the marketing department are as shown in the following figure. The marketing department and the sales department started to quarrel. The marketing department said: You don’t know how to sell! The sales department said: You don’t know how to promote! The question is, who do you listen to?
A. Market
B. Sales
C. Don't listen

(The question is complicated, think about it for a minute)

After learning the matrix method above, we know that there must be a problem here.

The question is whose fault is it?

This is another eternal problem in B2B sales: Is it the market that doesn’t know how to promote or the sales that doesn’t know how to sell? Especially in companies like this case, where management is chaotic and process data cannot be distinguished, often the argument ends up being whoever has the bigger fist gets the final say.

In fact, we have a very simple way to judge: collective failure is due to the market, and uneven performance is due to sales.

Please note that this is not a strict attempt to trace the cause, but rather to think from the perspective of solving the problem.

If all sales conversion rates are collectively low, it means that sales have no way to solve the problem by setting benchmarks, finding experience, and replicating widely, so the market must intervene. If they are uneven, it means that there are still capable people in sales, so why not learn from their experience instead of just asking for food?

So the answer to this question is C. Don’t listen to anyone and just look at the data.

As shown in the figure below, we can check the sales performance. If these two trends appear in the changes in the last three months, the attribution is completely different.

Question 5 (fill in the blank)
Assume that after analysis, the customer service lead data is as shown in question 4, and is a collective failure. It is now known that the sales lead + market lead order trend is as shown in the figure below. Please fill in the blanks.
The figure belongs to the industry market needs to increase
The picture belongs to industry sales and needs to be added with notes: If you look carefully, the three pictures in August this year are lower than those in August last year. This is also the starting point for the boss to get angry.

(The question is complicated, think about it for a minute)

First, after the diagnosis in question 4, we can draw a preliminary conclusion: the conversion rate continues to decline + the sales are collectively failing = the market needs to find a way to improve. However, we still cannot determine whether it is just that the market leads are not done well or the sales leads are not high (there is no data for the sales part). At this time, we can look back at the overall trend.

The sharp-eyed students noticed at a glance: in the three pictures, the orders of market leads are exactly the same. The difference is the orders of sales leads.

• Sales leads fizzle out faster than marketing leads!
• Sales leads surged, but market leads flopped

Combined with the conclusion of question 4, it is easy to make inferences here:

In situation A, if the sales team fails to handle both their own leads and the market leads, and all of them fail, then there is really no way to turn the situation around. At this time, the market needs more policy support.

In case B, the sales team clearly favors one over the other. They are clearly capable of doing the job, but they deliberately let the market leads go to waste. Is there a conflict of interest between departments, or a problem with the sales team being too powerful to be removed? Both are possible! So the answer to this question is A, B.

Note that many students put the data of Question 5 at the beginning. However, due to the lack of data, the analysis of the sales part cannot be deepened. As a result, the discussion fell into an endless war of words: "You can't promote! You can't sell!" In the current situation, we try to use the accurate data to draw some conclusions first, and then go back to deal with the inaccurate data, so that the discussion can be gradually deepened.

Although the data is still the same, different order of display can produce different effects. You can taste the taste carefully.

Of course, data can be enriched. It just requires everyone to work together.

The data enrichment process of B2B is the process of management from scrambling to intensive cultivation, from relying on sales gifts, kickbacks, and foot massage parlors to formal, compliant, and professional services. The beneficiaries will be all the company owners.

Some students may be curious: When others talk about user analysis, they always draw a picture with dense labels, and then split it into various dimensions. Why does Teacher Chen always emphasize that the data is not enough, the data is too fake, and they shirk responsibility.

A: Because they are good at dancing with long sleeves and good at making money. Everyone knows that more data is easier to analyze, but the reality is just chaos. Because data does not fall from the sky, but is collected by systems one by one, and filled in by salesmen and customer service staff one by one. Especially in the B2B industry, there are many processes, high amounts, and complex relationships, and there are a lot of gray or even black operations. Expecting everything to be complete at the beginning is deceiving yourself.

Some cases always mention BAT. But in fact, there are only a few companies whose capital strength, data resources, data talents, and platform monopoly performance can compare with BAT. Most companies are lucky to survive and grow, and they have to try their best and use all means. It is common to sacrifice infrastructure for growth, not to mention it is just a piece of data. The real working scene is to build a building in the mud, of course, it requires architects to think more carefully to achieve some results.

Of course, if the environment is improved, we can make better analysis. For example, in this case, if the marketing department can give a few more user tags and the product can count the demo functions, the subsequent analysis will be different.