3 Steps to Create a Data Management System that Works Every time for your CRM
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3 Steps to Create a Data Management System that Works Every time for your CRM

Author: Raj Singh | Categories: CRM, Personalization, Analytics, Business Intelligence, Big Data, Customer Experience

In the age of digitalization, data and insights form the cornerstone for all businesses. It is also the engine that drives your CRM. Without it, how can you determine where to invest your resources or who are the top performers in sales, marketing and service?

Business decisions rely heavily on data points and metrics. Therefore, it is critical to securely manage company data to facilitate informed decision-making.

A very rusty and unreliable data engine, will result in the following outcomes:

  • Old, unmanaged and poor quality of data
  • Duplicate customer/ contact/ lead
  • >50% data not being used by sale and marketing team
  • Inaccurate sale opportunities funnel report

Therefore, when we are migrating data from a legacy system, building reports to share with multiple teams, assigning sales quotas, or reaching out to customers to foster relationships – we have to ensure that the account, lead, contact and customer data is accurate, clean, and complete with the right set of information.

We have identified three indispensable steps to creating a solid foundation, for building and maintaining good data quality, and reporting without the fear of poor data quality:

Step 1: Identify the Current State of Data Quality


Data quality dashboard is a quick and easy method to get a visual representation of your CRM data quality. Not only do we get a report that lets you analyze your account, contact, and lead records, but we also gain details on data completeness and quality.

How it works: First, we need to create the problem statement and outcome from the below method:

Discovery

  • Review the process that takes care of current lead, account and contact creation
  • Next step on historical data – Identify contacts not used by sales and marketing team, in the past one year
  • Identify incomplete data set and the data creation source
  • Maintain a record of key profiles and roles of individuals entering this data
  • Develop validation rules on key object, to avoid data duplicity

Analysis

  • Study and develop recommendations based on data management best practices
  • Store marketing data in MAP, or tag them under campaigns
  • Discuss findings, recommendations, action items on best practices

Outcomes

  • Improved data quality and better CRM management
  • Segregate sales and marketing data, and use the marketing data for campaigns
  • Throw old, inactive data which has not being used for any campaign and sales activities, in the past one year
  • Inculcate best practices to improve data quality

Another great tool that allows us to identify duplicate records is the Salesforce dupe management. It also prevents future duplicate records from being created. With the help of our experts, we can help you remove duplicate records, along with implementing best practices on data.

Step 2: Build Useful Dashboards

To measure the right data quality, we need the right dashboards and insights derived from it. These dashboards help assess the health of your sales data, marketing data or customer base in a quick glance, and even while on the go. It helps companies to see the overall health of correct data in the sales funnel and correct customer behavior.

Data Quality Report

  • Number of contacts, leads, and accounts created per week/month
  • Contact created by source - Data available online or created manually
  • Campaign data quality
  • Missing account and contact data

Step 3: Create a 360-degree View of Customer Data

This is the age of Omnichannel customer experiences, as communication with customers in siloes and broken customer journeys are a passé. Building a 360-degree view of your customer, based on data is the key to drive investment and business decisions.

360-degree view of customer simply means bringing data from all channels of interaction, combining it with third-party data, and then cleaning and matching all data sets to form a single view.

Building a master data management strategy can be a daunting task. To ease this process - we have built multiple Accelerators to help you identify the best approach to building a single view of the customer.

These aforementioned steps will surely go a long way to carve rich, 1:1 personalized customer experiences. As a result, providing customers with the right content, at the right time, and on the right channel will be a new norm, for your brand.