Customer Data – A marketer’s guide for flawless customer data orchestration

Customer Data – A marketer’s guide for flawless customer data orchestration

One of the few pillars of the marketing campaign is customer data, customer journey automation and mapping. These pillars were earlier considered as a privilege and now are being used as a powerful tool. They help in cross-channel marketing coordination and also impact email marketing programs. An ideal customer journey optimizes customer journey optimization. This is taken to the next level by Appice through adapting ideal customer actions and triggers. 

Customer journey gets tedious if it requires to be monitored. This monitoring includes tracking fluctuation and updates of the brand marketing assets in email behavior trends. For doing all this, customer journey orchestration is needed. The process is made efficient and profitable with tools, but before we go ahead, let’s clear some basics. 

What Is Customer Journey Orchestration?

Every marketing platform requires customer interactions and automation, and this process is called customer journey orchestration. In this process, the developmental function is necessary for formulating and adapting every customer’s behavior patterns. Let’s take an example:

Analyze: We need to analyze every customer’s website and retail outlet visit 

Insight: Check if an email offers redeemable coupons and then consider how many customers have opened the emails.

Action: The redeemable coupons can be sent to customers. 

Now the next step is to track how many coupons are being used by the customers, and then based on that, and reports can be made. Customer data platform comes into play here. Through orchestration and real-time interaction, we can track people while they are shopping. 

Customer journey orchestration allows marketers to provide every customer a unique customized experience. It does not matter the customer’s relationship with the brand, intention, source of access, or location. The personalized content will be delivered to every customer:

  1. Following your brand on social media
  2. That receives your email 
  3. Visits your website

This practice is accelerated by 18% with the use of customer journey orchestration. Now, one thing is obvious that by using this relevant and personalized content, you will get more conversions. 

Customers’ perseverance of brands, triggers, touch-points, and brand channels can be dealt with separately with the help of orchestration. If you have not adapted the customer journey orchestration fully, below is how to do it. 

Step-by-Step Customer Data Orchestration 

Customer data orchestration can be built up using four steps which are mentioned below:

Identify: Marketing goals should be defined, and orchestrating journey should be identified. By identifying your goals, you will be able to derive the required data for instigating the viewer’s reaction and performing the action. This would eventually convert website customer’s behavior into a lead nurturing task.

Collect data: Now connect your CDP with customer data streams. Data should not be copied or migrated but need real-time live data for data orchestration to work. Data is continuously refreshed, due to which you have to deal with duplicated or outdated data. CDP should have more data that will help in completing customer profiles. So, you should collect as much data as possible, 

Filter and consolidate data: CDP is quite similar to CRM and DMP. When this step comes into play, all these three technologies can be differentiated. CDP brings together cross-device data and cross channel which also includes identifiable information machine learning and Artificial intelligence algorithms are used by the CDP continuously which follow the following processes:

Ingest and store data: It is not about accumulating data personally from the customers. If you have a good CDP, it will automatically collect data like IoT data, CRM data, website visits, and customer reviews. Accurate customer profiles can be easily created through this process.

Identifying similar data across various channels: A good CDP will also gather matching data about the customers from different channels. This would include similar names and addresses of the customers through multiple channels. 

Data cleansing: Old leads are removed, outdated data is cleansed, corrupt or duplicate records are also cleared. A good CDP will have real-time interaction that helps in creating accurate customer profiles. 

Define: Goals are defined for setting an appropriate condition so that prospects can be converted into leads. The data received will set up triggers. 

Rules and goals are created compulsorily in the user’s mind. Known as milestones, these goals are needed for triggering a rule. Once CDP unifies the entire data of one particular customer, which also includes third-party data, a single and holistic customer view is created. 


By making use of a good customer data program, automated data is collected. This data is enriched profoundly and would be more valuable than your first-party customer data available with the company. Let’s take for an example; you might come to know that 80 % of the customers that visited your company’s online store have a similar hobby. Based on that, your company can go ahead with ads or other copies to be used in a particular segment. 




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