Make people SEE and REMEMBER the brand
Get people to UNDERSTAND and WANT the brand
Get people to UNDERSTAND and
WANT the brand
Change people's BEHAVIOR and get them to CONVERT
Change people's BEHAVIOR and
get them to CONVERT
Take care of people to CONVERT OFTEN and ADVOCATE the brand
Take care of people to CONVERT OFTEN and
ADVOCATE the brand
U News
This article is quite favorable and quite basic for SMEs to have a concept of using Data in "Marketing 4.0" - I don't know what to call now because it has gone too fast and too big, from Digital Marketing, cannot include all.
The funny fact is that a lot of people today - from freelance to leadership - everyone talks about data, but when asked more closely, most people think user data is only encapsulated in a few words such as: name, email, phone number; or a little higher there are more positions & companies working, that's all; nothing more and nothing less. And more than 80% of SMEs do not know how to use their data in marketing, is it just very rudimentary data, and some very intense marketing methods such as SMS about promotions, birthday events. However, the process is inconsistent - causing ineffective results and often, apart from misunderstanding the nature of user data, will be divided into the following 4 groups:
- Group 1: There is no customer data yet, and it is not aware of the need to build a customer data collection system (traditional enterprises, small/micro-scale)
- Group 2: There is a bit of basic data, not sure what to do to create value (Small and medium enterprises, products that follow the trend of digital transformation, have participated in Digital Marketing)
- Group 3: Data mining 1 time -2 times, sell 1 time 2 times, cross sell, up-sales, no far circle to pursue more than 6 months - 1 year.
- Group 4: Has a lot of data, is actively exploiting other (Technology enterprises, a lot of revenue).
4 main steps in data-based business
Include 4 steps: Data Gathering - Data Management -> Data Analyze - Action
Data Gathering
Up to now, whenever you want to know a reason or need of a customer, we often perform survey - expensive cost, not guaranteed the answer of the customer is accurate, not counting episodes. If the sample customer does not represent the entire customer base of the enterprise, the survey is meaningless. In the data age, this disadvantage is overcome by customer behavior data collection systems, so the system must ensure a full range of customer data, from demographics to behavior data and service usage log ...etc...
- Customer Demographics: Demographic data of 1 customer such as name, age, date of birth, gender, address, occupation, parents, children in elementary school ...etc...
- Product Sale & Usage: this is a data group about your customers' buying and using behaviors: usage behavior, frequency of purchase, type of product, unit price, satisfaction level, time of purchase, similar products, supporting products, products sold together ...etc...
- Media & devices: this data is collected from the communication channels that customers can access to your products including interactive channels, models (Smartphone customers and feature phones with different shopping behavior), advertising sensitivity, types of social media accounts, ...etc...
- Third Party Data: data returned when you use 3rd party services in your business.
- Social Media: is the data source from social networks Facebook, Youtube, LinkedIn ...etc... small businesses mainly only have this type of data generated after advertising campaigns on Facebook, Youtube ...etc...
Data management
The data management according to world standards: CRM data, Channels, social media ... will be used to build Customer 360 (C360) system - is a data warehouse with full features revolving around 1 customers, all kinds of categorical, numberic, time series data ... it can be represented exactly like the name of 360 degrees view of customers. Depending on the industry, this data can be up to nearly 2000 fields.
Similarly, Product & Usage data will build on Product360 (P360).
Data Analyze
All 5 above data groups will be combined and used in different problems. Throughout the customer service life cycle, from new customers - upsell/cross-sell - and then leave the service (churn) can be analyzed.
Action
For new customers, we have Profile Customers (C360) combined with P360 to target for advertising campaigns, upsell, cross sell products. Generate sales revenue and growth.
From analyzing service use behavior, reflecting, complaining on social networks ...etc... will build Churn modeling - retain customers using the service. Small - medium businesses are often not interested in retaining customers, while the cost to get 1 new customer is 5 times greater than the cost to retain 1 old customer.
Briefly, user data is important, extremely important but almost rarely cared for by parties and leaders.
QH
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