What Is Data Management?

Data management is the process of effectively collecting, storing, processing, and applying data using computer hardware and software technologies. The goal is to make the most of data. The key to effective data management is data organization.

Manual management stage

Before the mid 1950s, computers were mainly used for scientific computing. The main characteristics of data management at this stage were:

(1) Data cannot be stored for a long time . Before the mid-1950s, computers were generally owned by research institutions on information. At that time, storage devices (

Mentioned earlier

In telemarketing, the sales team, product, and marketing database constitute the three essential elements of "who sells", "what to sell", and "who to sell to". The convergence of marketing objects as marketing objects plays a vital role in telemarketing. How to manage and use these precious data resources scientifically and standardly should become the manager of every telemarketing job. Need careful consideration and practical implementation. Let's start with the theory and look at the links of "data management" needs in telephone marketing!
The first concern: the import of data. <br /> Before the data is imported, it needs to do some processing to ensure that it can be maintained, statistics, and profiled during the application process.
First, it is necessary to stop analyzing and defining the attributes of the original data. Generally, various types of data from different channels are called in telemarketing, and these data have their own characteristics. This makes us first need to identify similar geographical attributes (local and remote), gender attributes (male and female), age attributes (different age groups), income attributes (high, middle and low income groups), industry attributes (finance, IT industry), etc. . Then according to these different characteristics, the data attributes are stopped from being classified and coded, and the data is further processed through telemarketing. Furthermore, we can analyze and find the most suitable user group for product sales, in order to complete the priority acquisition and selection of data information, and maximize the application of data resources.
Secondly, there is a seemingly simple but very meaningful work, which is to dispose the data in advance before importing the data, delete some invalid data, such as the data of the short contact phone number, the data of the missing contact phone number, or Data that does not differ in the attributes of the target customer base. Because these tasks are arranged before the data is imported, they can be processed in batches of the original data in order to obtain the data that is more in line with the dialing specifications most efficiently, while ensuring that the data allocated to the first-line TSR is accurate and effective, saving them time And work efficiency.
Finally, before the data is officially put into use, it is also recommended to stop the numbering and backup of the original data. Once the data is allocated to TSR, it is bound to stop the maintenance and update of the data information from time to time as the sales work progresses. Information, the original database for this backup is needed. Because the original data was stopped numbering in the previous period, we only need to use the data number to do a simple correspondence query in the original database. With the above disposals completed, we can now import data resources and wait for the phone marketing to bring us huge profits!
The second concern: the use of data. <br /> The processed data appears uniform and orderly after import, which is a good start.
Let us understand the process of using data together. While the marketing data is being used by TSR, a series of maintenance will be stopped on the data, which mainly includes recording and changing the dialing status and sales status. Let s take a look at several call statuses and sales statuses, and what they mean for us.
Dialing status: The dialing status is the connection status of the contact information such as the phone number in the marketing data after contact. Usually we can label according to the state shown in the figure below.
The data marked with the dialing status has a further meaning-the vitality of the data. All the data that can never be connected will be "Cancel" from TSR, and don't call it out to occupy TSR time. The data demand of "busy tone / call" will give priority to "calling at the wrong time". The status indicates that this phone is still in use, and the possibility of continuing the connection will be the greatest! By the way, the data on the need to continue to contact should be dial at the wrong time. The so-called dialing at the wrong time is mainly staggering between working days and non-working days, or staggering daytime hours and evening hours. Only after the staggered dialing of "working day dialing", "non-working day dialing", "day time" and "night time" can the effective application of data resources be achieved.
Let's look at the "sales status" again. The sales status is only three statuses that stop identification when the call is connected and the contact's data is found:

• Victory: Telemarketing Victory

• To be followed up: The contact needs to think, or the sales are not completed, and the needs are further followed up

• Rejected: The contact does not accept the product or service being sold, and the telemarketing fails

The above three states are easily identified during the use of telemarketing. What needs to be noticed here is the attention to the two states of "to be followed up" and "rejected". Looking at the follow-up data, we hope that we can understand what are the main factors that cause users to think about it? Production quality? Product price? Or after sales service? As long as we control this information, we can become more familiar with the data attributes and design sales scripts in a targeted manner to meet the needs of such users who need to follow up.
Similarly, we also need to find out the main reasons for user rejection. After corresponding to the data attributes, take effective measures to improve the sales victory rate.
The third concern: the application of data <br /> Experience has informed us that data does not need to be evenly distributed to each TSR, because different TSRs use data differently. When distributing data, we should stop effective regulation in real time based on the use of data by each TSR.
At this time, there are two parameters that can help us complete the regulation of marketing data: "victory contact rate" and "to be followed up". These are introduced below.
Victory contact rate = total user data reached / total of connected data × 100%. The victory contact rate is an indicator of the validity of the data. To understand the dialed data after winning the contact rate, there are several data to find the contact person and the sales target. The victory contact rate is a changing state value. With the data's second call, three calls and even more frequent calls, the victory contact rate will improve. In order to improve the effective application of data at a certain level, a "minimum victory contact rate" can be set. When the "victory contact rate" of the allocated data is lower than the set target value, the allocation of new data is reduced, and the TSR pair is requested at the same time. The busy tone / call and unanswered in the data are not connected repeatedly and are dialed incorrectly to achieve the purpose of improving the victory contact rate and applying the data more effectively.
Follow-up rate = Sum of data to be followed / Sum of data of contacts contacted × 100%. It is not difficult to understand according to the formula, the "follow-up rate" is concerned with the data that can be found in the contacts, and there are several data that need to be followed up. In the process of stopping the control of data distribution, for this indicator, it is necessary to set the "highest follow-up rate".
Set the "maximum follow-up rate". In order for the data resources to be applied well, and to stop secondary sales with the contact who is thinking about it in time, and seize the best follow-up opportunities, we need TSR to regularly view the follow-up data and stop chasing. When the "highest follow-up rate" is exceeded, it indicates that there is too much data to be followed in the marketing data called by the TSR. At this time, it is necessary to reduce the allocation of new data so that it can focus on follow-up intentions But still hesitant to sell to.
After the control of the "victory contact rate" indicator in the marketing data, find more contacts, and after the control of the "follow-up rate" indicator, find more sales opportunities. Attention to these two indicators is an important part of the "data management" of telemarketing.

Title: Data Management

Aka: data management: insight into retail and e-commerce operations

Author: Huang Chengming

Category: e-commerce, data, management

Pages: 306

Pricing: 59.90 yuan

Publisher: Electronic Industry Press

Publication time: 2014-7

Binding: paperback

Folio: 16

ISBN: 9787121234064

"Data Management: Insights into Retail and E-commerce Operations" tells the story of two young people working in the sales, merchandise, e-commerce, data and other departments of large companies, explaining data consciousness and retail thinking through a number of cases. The author integrates various data analysis methods into specific business scenarios, and finally forms a data management model to help enterprises improve their operational management capabilities.

All cases of "Data Management: Insight into Retail and E-commerce Operations" are based on Excel, and everyone can quickly get started and land.