Overcoming the Challenge of Customer Data Silos

Overcoming the Challenge of Customer Data Silos

Overcoming the Challenge of Customer Data Silos

The rise of digital channels has given both consumers and brands unprecedented access to large volumes of information. Consumers, however, have had a far easier time than brands at using information to achieve the outcomes they want. This has given them significantly more leverage and empowered them to take charge of their own customer journeys while brands have struggled to keep up. Why have brands struggled? Data fragmentation across systems and departments has made it difficult to take action.

System and process complexity within the enterprise is the unintentional outcome of the desire for departments to respond quickly to the changing needs of their employees and customers. Adding new tools to handle new channels or implementing standalone cloud applications to speed up the rollout of new capabilities to customer-facing employees is often done for the right reasons, but it leads to serious data fragmentation over time. In fact, research shows that marketers alone are using an average of 15 siloed data sources for any one consumer, which not only makes their job more challenging but also results in inconsistent and disjointed experiences for the customer.

Read Also:
How to Improve Your E-Commerce Store With Big Data

To make data actionable, organizations should first focus on the creation of a true customer profile — even for potential customers. A single view brings together all of the structured and unstructured data — such as commerce site browsing behavior — held by the enterprise, as well as relevant data from external sources such as social media, credit reporting agencies, and so on. To be truly actionable, however, this profile must not only be comprehensive but also updated in real-time. Insights derived from current behavior and social media posts can be used to personalize a shopper’s experience in the moment, but personalization based on aged or incomplete data can result in an experience far worse than one with no personalization at all.

It is important, however, not to confuse this profile with a customer record in a traditional customer relationship management (CRM) system. While CRM plays a vital role for the front office as the system of record, helping to manage everything from the sales forecast to support call escalation, it only includes a small subset of the data available on a customer. To build a complete customer profile, businesses must go beyond CRM and draw data from the back office, from sources outside of the enterprise and, most importantly, from systems of engagement.

Read Also:
Machine learning models need love, too

It is here in these systems of engagement where most of the action happens, where data is not only collected, but where insight is also applied.

 



Data Science Congress 2017

5
Jun
2017
Data Science Congress 2017

20% off with code 7wdata_DSC2017

Read Also:
4 examples of data, reporting and analytics in education

AI Paris

6
Jun
2017
AI Paris

20% off with code AIP17-7WDATA-20

Read Also:
Microsoft taps into Apache Spark to drive its Big Data & analytics services

Chief Data Officer Summit San Francisco

7
Jun
2017
Chief Data Officer Summit San Francisco

$200 off with code DATA200

Read Also:
Predictive Analytics: The privacy pickle

Customer Analytics Innovation Summit Chicago

7
Jun
2017
Customer Analytics Innovation Summit Chicago

$200 off with code DATA200

Read Also:
How Big Data is Changing and Influencing Internet Marketing

HR & Workforce Analytics Innovation Summit 2017 London

12
Jun
2017
HR & Workforce Analytics Innovation Summit 2017 London

$200 off with code DATA200

Read Also:
Artificial Intelligence: 2017 Predictions from Forrester

Leave a Reply

Your email address will not be published. Required fields are marked *