A complete Customer 360 view is more than just a great idea. It’s a basic step brands need to take to succeed. Having a clear sense of who each customer is so you can give them the best experience no matter where they connect with you means better customer satisfaction and better business.
So companies buy Customer 360 capabilities from a vendor, or they try to build it themselves, which is a great start. The problem is, getting a true 360 customer view is really hard, which is why people have been trying for years.
There are some critical technical challenges to contend with, and coming up short on any one of them can completely derail achieving that elusive Customer 360.
Customer data comes in multiple forms from a wide array of sources, and getting it all organized can be a huge headache. This is the original problem that a Customer 360 set out to solve: getting all the data into one place. Marketers and data analyst teams have been hacking away at this problem for years now, but just because it’s a familiar challenge doesn’t mean that it’s easy to solve.
The laundry list might be familiar: data comes from email, from Facebook, in-store interactions, call center calls, Instagram, wi-fi logins, Tik-Tok (for the young at heart). Data exists as purchase records, clickthroughs, form entries, help tickets. The systems where all this data lives often don’t talk to each other. If you don’t have the right tech in place, you’re stuck organizing the data the old way of extracting from one database and reformatting it to go where you want it, record by record, which sounds like tons of fun if you like migraines.
Your 360 needs to be flexible and source-agnostic, so it can smoothly accept data from anywhere.
Resolving Identities is Tricky
Once you have all the data together, you have to clean it up. There may be ten records for a single customer, one from each channel where they interacted with your brand. If you want to recognize them on any platform and give them the best service regardless of where they interact with you, those ten records need to be resolved into one.
The problem is that it may not be obvious when multiple records refer to the same person. People change snail mail addresses, change email addresses, even change names, but each one of these disparate records still needs to point to the same customer. On top of the normal changes that take place over the course of life, people often typo on their names or contact info when entering forms, further confusing the records.
Without the right algorithms and advanced intelligent matching to put together a single solid identity, the view of the customer isn’t accurate, which means you can’t give them the best service across channels.
Data is Big & Getting Bigger
More people connect with brands across more channels than ever before. With digital natives like Millennials, Gen Z, and whatever cohort comes next swelling the ranks of consumers, the amount and variety of data is only going to keep increasing.
But many data management tools have a hard time handling so much data. Fumbling at scale leads to a whole raft of problems: slow ingestion, clunky processing, inaccurate unification, and less-than-helpful analysis.
Without speed, accuracy, and scale in handling data, a 360 isn’t much use.
So you got your data together, resolved all the identities, and you have a system that’s fast and powerful — 360 problem solved, right? Well, maybe for today. But your data can and will keep changing, and if your Customer 360 is too rigid then it won’t be helpful for very long.
New use cases come up. Other elements of your tech stack are replaced. New customers come, existing customers leave, and old customers come back (hopefully).
Historically, customer data management platforms aiming for a 360 customer view have been designed statically, without paying attention to the reality of ever-shifting data. The way of dealing with this has been to write a continually expanding tree of rules to deal with any new variation. “If customer name changes, refer to record A.” “If new segment is created, pull from record B.” “If action C occurs on an old record, initiate action D.” It quickly becomes unwieldy, disorganized, and ineffective. So they build a new version of Customer 360. It’s not uncommon to find brands that have 360 v2, 360 v5, or even 360 v10.
If your Customer 360 is trapped in a scaffolding of rigid rules and can’t adapt to changing inputs on the fly, then it’s not giving the best results for your customers or your business.
(Bonus points if in addition to being able to handle change your 360 provides a secure environment to experiment with changing inputs)
Checklist for a Real Customer 360
With so many claims out there around Customer 360 technology, it’s important to focus on the core capabilities that make it valuable. Any 360 you buy or build needs to:
Get data in the same place
Resolve multiple IDs into one record
Handle large amounts of data
Easily adapt to changes
If any of these are missing, you need to go back to the drawing board. If all these boxes are checked, you could be on your way to a happy ecosystem of great data in, great customer experience out.
Read more about what questions to ask when looking at a Customer 360.