When you go beyond identity and descriptive data, and get into more qualitative or attitudinal data, you can learn a lot about what’s important to your customers. Good customer data management lets you do just that.
As brands adapt to the ongoing shift towards digital commerce, they should strive for a seamless, unified customer experience (CX). However, data-related roadblocks can make that difficult. Data silos, customer authentication and consent management, and compliance are common issues.
Daunting as these challenges are, brands that want to compete in the experience economy need to solve them. Forrester predicts that one quarter of brands will achieve statistically significant CX improvements by the end of 2021. To reach their CX goals, many brands are turning to customer data cloud technology and implementing a customer data hub.
What is a customer data hub?
A customer data hub (CDH) collects, organizes and centralizes data from various systems across the customer journey. It provides a central repository and source of truth to facilitate the use of data by different teams, including marketing, customer service, and sales.
The hub integrates different types of data from internal and external sources, including structured data like personal and transactional data and unstructured forms like mail and conversations.
Know thy customer: Benefits of a customer data hub
A customer data hub benefits brands in a number of ways:
- Identify known customers and build profiles based on unique identities that extend across the enterprise and its channels
- Provide the data transparency that customers want and the compliance regulators require
- Allow for unified customer profile management and journey orchestration
- Deliver operational value for the business, increase security, reduce costs, and boost revenue.
But in order to get these benefits, an organization must take a careful, strategic approach to avoid common pitfalls.
Types of customer data serve distinct purposes. Identity data, descriptive data, attitudinal data, behavioral data defined with examples.
Customer data hub: Getting started
The most efficient way to begin a customer data hub implementation is with first-party data to establish each customer’s identity. For example, if the customer has shared their name and email address or other contact information, migrate that data into your new central data repository.
This approach ensures that your customers’ data was provided with consent. Centralizing it also can improve security.
The next step is tying unidentified customer data to first-party customer data correctly. For example, a customer navigates to your website, looks at a power tool, and adds it to their cart. That interaction generates customer behavior data that you need to link to the existing customer identity, including what kind of tool, what brand, and what price point. Most brands can’t do this if the customer isn’t logged in.
There’s also the issue of integrating older, siloed customer data from across the organization. Often, this data is fragmented or in a format that’s different from your CDH and from other customer datasets in your company.
A CDH contains logic to identify names, email addresses, or other information and generate a rating for the level of confidence that the imported record matches a customer’s first-party data. This helps if you’re unsure whether you’re looking at one customer with varying contact information or two customers with similar names.
Over time, the confidence rating may change as the datapoints increase. If subsequent customer behavior indicates that the old data belongs to a different person with a similar name or other information, it’s easy to adjust.
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Building a 360-degree view of the customer
As you gather and align this customer data, a customer data hub can help you apply it to your marketing, sales, and service. However, trying to work with too much data too quickly can bog down the process.
A more effective approach is to start working with the customer data from one perspective within the organization, and then bring data related to other perspectives into the platform until you build that 360-degree view.
For example, the marketing team could quickly leverage the data about the power tool in the customer’s cart to send a follow-up email to try to get a conversion. They’ll use a marketing tool, which creates more customer data as it generates the offer and tracks the response.
Those actions could create another silo of data, but with the unique customer identifier you’ve set up in your CDH, that new data can link to the customer’s first-party data profile to generate one view of the customer as they interact with the brand. Once the data for the marketing perspective is properly identified, you can apply a similar process with your sales or service team and then repeat until you’ve created your 360-degree view of the customer.
Customer data management is customer service you can't see with results you really can measure. CDPs deliver exceptional customer data management solutions.
Make smart choices about data retention
Because it’s so easy to collect data, it can be tempting to hold on to all of it. However, storing data for data’s sake is inefficient. It can increase costs, slow down queries, and makes it harder for marketing, sales, and service to find the information they need in a sea of data.
Going back to the example of the customer who added a power tool to their online cart. They spent 20 minutes on the website. The brand has access to the number of seconds that they spent on each page, total time spent on the website, total number of products they looked at, and more. How much of that data is relevant?
In most cases, you don’t need the full log, timestamps, or the number of seconds per page. Instead, you may only need data about total visit time, products viewed, brands, and price range.
CDH implementation: One step at a time
Efficient CDH development starts with first-party data that customers have consented to share and builds gradually to the 360-degree view of the customer based on internal perspectives and relevant data integration.
By following this process rather than trying to start with the 360-degree view, brands can efficiently build a customer data hub that helps marketing, sales, and service to deliver a better experience at every step in the customer journey.