It was during the economic recession in the 1990s that customers became increasingly selective of the brands they engaged with and those they purchased from. The successful brands were those which put their customers front and center of their business, offered excellent service and built customer relationships that they benefit from even today. It was also around the time when social media entered the landscape and revolutionized the way customers and brands interacted. It thus became an integral part of customer journey.
Data provides the foundation for brands to create a customer journey map that helps understand how customers move from the awareness stage to decision-making/buying stage. Where brands would theorize the journey of their customers in the funnel, data helps design a model founded on hard evidence.
A clear understanding of how prospects and customers relate to a brand helps improve the business while also benefiting the customers.
For example, on reviewing the customer journey, a company finds that many of its prospects spend a lot of time comparing several products in the inventory but ultimately decide to not make the purchase. A data-driven customer journey map helps identify and resolve the issues.
Popular Sources of Customer Data:
Browsing data: It is one of the widely-available and most significant sources of data. Data can be collected every time a user browses a business website and, in course of time, their activity on the site could be tracked to understand how they interact with a brand.
App data: Mobile applications are another source of data. Business apps help capture more information than a website as users create personal profiles and sign in while using apps. Another key aspect of mobile app users is they are usually further along in the customer journey and are perhaps loyal customers already.
E-commerce and in-store data: This type of data helps understand customer habits over time and gain insights into their purchasing decisions. For brands that have a brick-and-mortar store to go with an e-commerce website, the data could be combined for a more thorough understanding.
Social media data: Social media is an indispensable part of building and nurturing relationships with customers. Social data helps analyze how customers interact with a brand on the various platforms and provide the basis to improve strategies for social media and other marketing activities.
Customer service data: The customer service data helps gain valuable insights into how customers interact with a brand after completing the purchase. It helps understand what is right and what needs to be improved and is crucial to gaining and maintaining brand loyalty.
The importance of Data Quality:
According to one study, only 3 percent of data collected by organizations meets basic quality requirements. Bad data, or poor quality of data, afflicts companies’ customer strategy in more than one way:
- Increases costs and wastes time
- Compromises decision-making
- Annoys customers
- Hinders data strategy
The same study also mentions the fact that 47 percent of new data records, on overage, have at least one critical, “work-impacting”, error. In addition, more than 80 percent of CEOs express concern over the quality of data that dictates their business decisions. It is, therefore, vital that brands understand and address data quality issues.
Most companies work on different platforms and data systems. They may collect data from opt-in forms, point-of-sale (PoS) systems and other sources, which could potentially result in inconsistency in data collection and make it necessary to not only clean but also standardize data.
On the flipside, when brands ensure a high quality of data in a way that is useful, they reap the desired rewards. This, too, is backed by evidence.
According to researchers at the University of Texas, improving the usability of data by even 10 percent would result in a revenue boost of more than US$2 billion per year.
A high quality of data helps brands be competitive, agile to market changes and more.
Increased Customer Engagement:
Data that is usable and of a high quality helps drive customer satisfaction and retention. When brands know more about their customers and prospects, the more equipped they are to:
- Identify customer needs and buying signals
- Increase demand
- Create stronger, meaningful relationships
- Drive campaign personalization
A Comprehensive, 360° View of Customers:
Marketing, sales and customer success teams talk often about getting a 360-degree view of their customers.
Personalization and exceptional customer experiences are essential for a successful customer strategy—and the basis is high-quality, accurate data.
The 360-degree view of customers is also key to identifying the ideal customer and build accurate buyer personas.
Data quality helps ensure the right message is sent to the right audience at the right time.
High-quality data is also critical in identifying what motivates the ideal customer, the products they are keen to purchase, their preferred communication channels and more.
All these attributes help increase the effectiveness of campaigns and the return on investment (ROI).
High-quality data helps improve business process efficiency, reduce costs and deliver better customer experiences. For example, validating the email addresses in the database or at the time of collection will ensure email deliver ability and thus enhance overall effectiveness of a campaign. Higher email deliver ability also means potentially higher open and conversion rates, higher CRTs and helps protect reputation.
Bad data does not only affect an analyst’s productivity, it also afflicts sales and marketing teams, impacts brand reputation, creates negative customer experiences and the effects are almost endless. Data quality is an ongoing challenge which can be addressed with the help of regular data quality assessments, by following best practices to help keep data clean and by leveraging the right tools for effective data management. As it is evident, high-quality data helps generate a 360-degree view of customers, incorporate personalization, improve campaign effectiveness, and drive overall business efficiency.
Author Bio: Suhith Kumar is a digital marketer working with Indium Software. Suhith writes and is an active participant in conversations on technology. When he’s not writing, he’s exploring the latest developments in the tech world.