How Data Contributes to Healthy Customer Relationships

Effective communication with recurring customers presents several opportunities for evolving a business model – thanks to the current advancements in technology.  From Social Media platforms to Customer Relationship Management (CRM) systems, data accessibility has become incredibly easy for organizations reviewing past performance to improve interactions and reduce churn within current customer lists. 

As technology improves market accessibility, organizations continue to adapt their model to stay ahead of competitors while considering how they can further improve the lives of customers through product and/or service offerings. Customer data creates synergy between a brand and the target user when a company can interpret the data and develop algorithmic models for testing and improving relationships.

When a potential buyer contacts an organization by subscribing to a newsletter, filling out a contact form or through other various actions, the interest generated in the product or service has already been established. Understanding each activity as raw data will allow for the organization in question to create a meaningful experience for a new buyer. 

As processes are refined, stakeholders can present solutions based on similar actions, personas, and other information customers presented before making a purchasing decision. Collecting data from established customers allows for marketers and sales professionals to optimize their funnels as new users intercept a brand’s messaging. Segmenting the data from lost-closed deals and won-closed deals will ensure the most effective content, communication channels and strategies are continuously adapted and implemented.

Surveying new users against recurring customers

Further analyzing previous strategies creates a basic guideline for content refinement and development. As new users become engaged, more data is collected. Collect all customer data in order to identify new trends, areas of improvement or growth. If your organization has multiple revenue streams, it is important to assess what is most profitable and what is producing waste to eliminate or improve upon areas of the existing infrastructure. 

Go beyond the data that is automatically collected and create variables in the way you survey customers — understand what they want, need, and how to expand the relationship. Creating associative data and translating this into a conversation will ultimately improve customer engagement and streamline internal operations.

Building personalized experiences into your business model using data

Customization does not have to be a manual process. With advanced tagging, field customization, and other machine learning activities – it’s possible to have advanced computer-generated interactions with users while building the system for the buyer to communicate sales representatives – no matter how much technology is integrated into the process. 

  • Email open-rates, social shares, click through rates, demographics, purchasing behavior and many other metrics can contribute to building data-centered processes. Customer data creates synergy between a brand and the target user when a company can interpret the data and develop algorithmic models for testing and improving relationships.
  • Collect data from win-loss: Segmenting the data from lost-closed deals and won-closed deals will ensure the most effective content, communication channels and strategies are continuously adapted and implemented.
  • Survey new users against recurring customers: As new users become engaged, more data is collected. Collect all customer data in order to identify new trends, areas of improvement or growth. 

Use data to know when to walk away

Not all customers are a fit for a business. Utilize data trends to analyze when customers drop off. It’s important to understand the ROI (return on investment) behind every action during the buyer’s journey.  If a specific set of actions leads to a declined customer rate, adjust your processes, or audience. If the USP (unique selling proposition) cannot be conveyed to the user, it’s important to look back at the data you’ve gathered to get a clear picture of the situation.