A 360-degree view of the customer is the cornerstone of data-driven marketing.
As such, it should contain customer attributes that can and will be used for various analyses, when dealing with campaign targeting, etc.
In order to determine what these attributes are, we can follow a customer’s online behavior and life in general. Apart from demographic data, you can track, analyze, and add to the 360-degree view their time spent on your website before making a purchase, dates and times they open your emails, interaction with your social media profiles, etc.
In this article, we look into real businesses’ different approaches to the 360-degree customer view. Keep on reading.
What is a 360-degree customer view
In the core of 360-degree customer view is an idea that all customer touchpoints can be aggregated inside a single database.
This allows companies to get a clear picture of all customer interactions with the whole brand by giving them a broader context across multiple databases in a single view.
360-degree customer view enables to perform deep analyses across the entire customer experience or set up complex marketing automation scenarios. If used correctly, 360-degree customer view should lead to informed decisions spanning from improving customer experience to an increase in profitability.
What to include in a 360-degree customer view
Of course, you can collect some data, put it together, and call it a profile. But that’s not what you’re up to, is it?
In order to build a rich 360-degree view of your customer, their profile must contain attributes that cover the most important interactions between you and them in all their life-stages.
What it doesn’t have to contain are attributes you can easily calculate. For example, it’s not necessary to include gross profit when you know your margin and revenue (because gross profit = margin * revenue).
That said, it’s easy to determine what the profile should contain – attributes that you can’t calculate from others so easily, for example, total revenue (sum of all purchases). Purchases are usually tracked in a separate table, so it’s better to precompute the total revenue attribute and add it to the customer profile.
Ideally, your 360-degree customer view also provides a historical context. That lets you analyze data from the past and make more accurate predictions for the future.
Building the 360-degree customer view the traditional way
Businesses in banking, telco, and insurance industries use various systems that produce data (CRM, customer portal, online store, billing system, etc.).
The data they collect is copied to a data-warehouse, blended together, and stored (almost) forever.
A group of data-savvy people then goes on to create an analytical data-mart (ADM), which is a structure in SQL database with hundreds of attributes about a customer.
The ADM is usually updated daily, and there are numerous use cases that require close to real-time data. So, companies add an operation data-store (ODS) to the stack. The ODS is a system that contains updated data but no history.
Should you take this path, expect your 360-degree customer profile to be split into two systems: ODS and ADM.
Advantages of the traditional way
- Structure and stability. The data model is fixed.
- Sufficient data quality. If data flows are well tested and primary systems don’t change too often.
- Requires SQL skills only
Disadvantages of the traditional way
- It takes a long time to build.
- The complexity of maintaining two structures at a time (ODS; ADM).
- Low agility. Adding a new attribute usually takes weeks.
- High maintenance costs. A simple change in the primary system might affect everything.
- High dependency on IT.
Building the 360-degree customer view the modern way
With a growing popularity of Hadoop and NoSQL, a new way to build the 360-degree customer view has emerged. You can store all customer data in so-called data lakes.
A data lake doesn’t require any fixed structure of the incoming data, and it can store literally anything about a customer.
Once collected, data is aggregated to a customer level, and a rich customer profile is built. The data lake approach can work as a combination of ADM and ODS.
Advantages of the modern way
- Rich data profile
- Variable structure, very agile
Disadvantages of the modern way
- Requires more than SQL skills to build
- Gaps in data quality
- IT guys are needed to change a structure
The Exponea way to build the 360-degree customer view
The customer profile is a beating heart of Exponea. We see three types of data businesses can collect:
- Data about customers
- Data about customers’ activities
- Data not related to customers
Raw data flows in from various sources and is divided into the three segments. Users then create the customer profiles in the Exponea interface.
The Exponea way is actually a data lake of user interactions with very high performance.
Our in-memory database allows us to build customer profiles on the fly. There is no pre-aggregated data, no caching, no complicated workflows.
Our approach is unique in the technology we use and the level of fine-tuning we’ve done. Clients have seen it unlock new use cases, and they’ve also enjoyed instant productivity boosts of their whole marketing department.
Advantages of the Exponea way
- Rich profile
- Variable structure
- On the fly calculations of the entire data history
- Unlocks new real-time use cases in marketing
- No IT skills required
Disadvantages of the Exponea way
- Sensitive to incoming data quality
- Changes in primary systems don’t break anything and may be overseen
- A user interface has some limits on aggregations
What do you think about building rich, 360-degree customer views? Have you got a different experience? Or do you feel like adding something to what we’ve just covered?