SERVICE / SOLUTION SERVICE / SOLUTION Customer data analysis

Enables "target selection" and "efficient allocation of sales force" by understanding the best scenario

About customer data analysis

We visualize the best case scenario from your existing customer data using the metrics of industry and size of operation and the largest database in Japan. We extract potential targets that match to the scenario, launch promotional campaign suitable to the targets and lead into efficient customer acquisition.

Suggested usage of customer data analysis

It can be used to solve the following cases;

1.We would like to identify target companies and have our sales force focus on them.

You can understand your best case scenario and identify the potential targets by customer analysis. You will know who to aim at.

2.We would like to share the secrets of success with other sales offices.

You can compare sales offices with good performance and poor performance and analyze factors making the differences.
You can then apply effective sales strategies to the weak sales offices.

3.We need to map out business plans such as medium-term business plan.

Through analysis of existing customer structure, you will understand what you should be selling, who you should be selling to, and how you should be selling. You can utilize it to map out your business plan

Illustration of customer data analysis report

You can analyze penetration rate by using Landscape's database with comprehensive coverage.
Using Landscape's business data, you can immediately start approaching when you find companies you have not contacted.
It also enables you to identify high potential leads by analyzing the profile of your existing customers and building a business model.

Penetration rate table

Penetration rate charts

Decision tree model

It statistically determines segments which could potentially become your customers after making factor analysis of customer profile over your customer data.
(We make an analysis merging your existing customer data and non-customer data randomly selected.)

Estimated results by constructing the customer model

You can efficiently make achievements by utilizing constructed model and executing promotion toward high potential targets rather than executing promotion randomly.