Single Customer View (SCV) Overview for 2022
By Samuel Kellett
Jan 29, 2022
11 min read
Single Customer View (SCV) Overview for 2022
Table of Contents
The term single customer view (SCV) has been bandied about in marketing circles for over a decade. However, it's hard to lock down a universal definition due to other variables (how the data is sourced, the speed of profile updates, etc.) that are often overlooked or omitted.
What Does Single Customer View Mean in 2022?
With customers purchasing from multiple different devices, and the move toward omnichannel communication, a method of cataloging all that data is required. At its simplest, a single customer view is a database with customer profiles (purchase history, site activity, product recommendations) for every individual person.
A true single customer view is that customer database, but scalable, flexible, and updated in real time. This last point is a crucial difference. SCV data is used to enable segmentation and marketing automation; if the system is out-of-date, your customers could be seeing the wrong messages. Despite this, many companies with a rigid framework and time-delayed updates still discuss their single customer view as though it's the same thing.
This article will explore the history of customer data management that led to the single customer view , the importance of having one, and actionable examples of a true single customer view in use.
Why Most Single Customer Views Don't Work
History of Database Management System
In the 1970s, companies began storing their customer data using Relational Database Management (RDBM) systems. These systems allowed companies to store data as individual pieces of information in different fields (first name, last name, customer ID), and then access that data through SQL queries. As the popularity of computers continued to climb, this method of managing customer information became the standard.
The internet continued to grow, and companies continued to invest in their RDBM systems. These systems could still handle the customer information being gathered, and most companies saw no need to change their methods. Until about 2008 – when Big Data started hitting hard. The amount of customer info that could be gathered increased exponentially, and the formerly superior RDBM systems could no longer efficiently handle all the details.
The idea of a single customer view was born then out of necessity. Customer data was far richer and more detailed than ever before. Customers were starting to make purchases from all different directions: in-store purchases, phone, tablet, PC. All that customer data was going to different places, often managed by different departments, and even using different software. There was no way to effectively track the customer throughout their lifecycle, and communicate with them in a relevant way.
Introduction of NoSQL Databases
NoSQL databases began to be seen as the solution. NoSQL is built to handle large amounts of unstructured data. It’s more flexible, scalable, and faster than SQL when dealing with something like Big Data. Unlike SQL, NoSQL systems can track any piece of data at any time, with no need to prepare the structure for it. New data sources can be tracked without the need to set anything up. In short, NoSQL was better for using the data these companies now had access to.
Unfortunately, decades had been spent building Relational Databases — countless personnel hours and piles of cash — and this widespread system was now showing its limitations. In addition to the previously mentioned issues of collecting more detailed data and customers that connect through multiple devices, all methods for the company to interact with customers were disconnected as well! Customer relationship management (CRM) systems were in one data silo, email management was in another, analytics in a third, and on and on.
The Legacy companies that had invested early on (Oracle, IBM, Emarsys) were now at a disadvantage. With all the time and money spent on their now out-of-date RDBM systems, they couldn’t just start over from scratch. Instead, they tried to convert their Relational Databases into Non-Relational Databases (NoSQL). This required pushing together a number of different data silos and pointing them all in the direction of the customer, hardcoding something that looks like a Single Customer View, but doesn’t function with the same flexibility or speed.
How Did Bloomreach Solve the Single Customer View?
Rather than altering existing tech to face a new problem, Bloomreach had the opportunity to look at the problem first, then create the tech around it: a customer is interacting with my company right now; I need to qualify them and take action. This approach allowed Bloomreach to create a truly customer-centric system; an all-in-one customer data platform built around NoSQL, rather than one adapted to work around the limitations.
CRM system, Email management, campaign building and automation, real-time predictions, analytics, etc. all available within one dashboard. With data updating so fast you can actually watch a customer profile update itself as the customer clicks around.
And it’s not just about speed. The flexibility of this customer-centric system, built around NoSQL and using In Memory Framework, creates new opportunities for communicating with customers. With a system parsing each individual action that every customer takes, in real-time, Bloomreach has been able to develop powerful customer recommendations that adapt and interact with the customer, even as they browse the site.
Picture it like this:
Legacy Database: You’re dropped in the ocean, and you manage to scrape together a raft from what’s floating around you. It keeps you from drowning for now, but it’s not ideal.
Bloomreach Engagement: You’re given a boat designed for the ocean. Not only does it keep you afloat, it’s the optimal method for navigating the seas.
Finally, another advantage of an all-in-one platform is how quickly the software can be implemented. Bloomreach’s basic software can be set-up and running within days. The most bare-bones version can be installed in minutes, as it only requires a single code integration. Compare that to the weeks or months required to integrate all the disparate parts of a Legacy company.
Key Takeaways for Single Customer View
- In the simplest sense, a single customer view is a database of customer profiles (one for every user), composed of purchase history, site activity, product recommendations, etc.
- NoSQL (Non-Relational) Databases are superior to Relational Databases when dealing with large sets of detailed data (ie Big Data).
- Not all single customer view are equal — most legacy companies run theirs on converted Relational Databases, creating a slower, less flexible single customer view than one built around a NoSQL database from the beginning.
- Bloomreach Engagement's Single Customer View is built around NoSQL. It's flexible, updates in real-time, and combines CRM, email management, campaign building and automation, real-time predictions, analytics, and more into one main dashboard.
- A true single customer view is a valuable resource, enabling (among other things):
- Optimal email send times
- Personalized customer journeys
- Simple A / B testing
- Detailed segmentation
- Real-time automated personalization
- Advanced predictive analytics
Could your company grow faster with a true single customer view? See for yourself.