If you want to offer a better Customer Experience in 2016, you’d better hurry up

Customer Intelligence is built on data and analytics

Customer Intelligence enables offering of a better, personal and data driven customer experience. Read more on "A value of big data - improved relevance with targeting" on my earlier blogpost.

Data and analytics are needed to be able to offer a personal, best-in-class customer experience for the customer. You need to start with data collection. The first step of collecting the data is to define and standardize your company’s data capture processes:

1.       The company defines the identifier framework and tags, against which the customer core information and his behavior will be collected (for example, fixed, identified, enterprise-level cookie, mobile identification). In this phase it will be ensured that all collected information of the customer is stored utilizing manageable and standardized customer tags.

2.       Only the data that the client has given permission to use, is allowed to be used. The company must harmonize the privacy policy and marketing consent procedures, and the ways how permission from customers is requested to gather and combine information and to use it for marketing purposes. At this point, it is important to understand the prevailing EU data protection rules.

3.       The technologies to support data collection are selected. The technologies must be set up and taken in use in different channels (web and mobile).

Technical options for data collection

There are different options for data collection:

On Premise Versus  Cloud

Saas capabilities are strengthening all the time. Data collection into cloud-based environment and platform is very popular and quick to implement (e.g. Adobe, Google Analytics).

The challenges of the Saas services are the limited possibility to combine collected customer understanding to the other architecture / customer channels (contact center, e-mail etc.) of the company, as well as, for example, data ownership, storage location and the constraints of the real-time utilization.

If selecting IaaS (e.g. Amazon)  instead of ready SaaS, you can quite easily implement a data capture and management capability utilizing Amazon cloud infrastructure. Below a battle tested example architecture picture on such solution.

Tagging versus server log information

-          The data collection of Saas services is usually based on website tagging. The amount of work can be very significant if the target in data collection / customer intelligence is to go to a level where the ad display time, page scrolling or mouse movement on the screen is measured.

-          The primary alternative of tagging is to collect information from the server logs. The challenge is the lack of real-time information.

-          An interesting third way to collect information is so called data collection solution without tags. In this model (e.g. Celebrus) almost all interaction between the user and the pages is automatically collected and the selected, relevant information is transmitted for analysis.

Mobile data collection is still developing as the mobile browsers have limited support for cookies and the data collection mechanisms must be generated and integrated to the mobile applications of each mobile platform (iOS, Android, WP).

Data collection implementation

The workload described above in the three-step implementation of data collection is significant. However, implementation of all three steps is mandatory. The work requires enterprise-level will and know-how to make the right conceptual and technical choices. The right technical choice always depends on the company's existing data infrastructure, the company's cloud strategy and the target state as well as the desire to combine data from online and offline channels to each other.

Information can be collected for analysis, to be combined and for marketing purposes only after the authorization from the customer is requested and permission obtained. The customer ID mapping and privacy policy harmonization must be done prior to starting the data collection. Only after this the data collection as well as improving the customer experience using the collected data can be started.