Overcoming the Challenge of Customer Data Silos

by   |   December 9, 2016 5:30 am   |   1 Comments

Johann Wrede, Global VP of Audience, Brand, and Content Marketing, SAP Hybris

Johann Wrede, Global VP of Audience, Brand, and Content Marketing, SAP Hybris

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.

A True Customer Profile

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.

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. Bringing the data together is an excellent first step, but customer experience is not just the work of marketing or customer service: It is a combined effort across departments and systems. But once this full view of the customer is built and richer, more actionable insights are extracted, they need to be applied at every stage of the customer’s journey.

Landscape Complexity

An enterprise’s ability to apply these insights throughout the customer journey will depend greatly on the complexity of its system landscape. Creating an integrated customer profile solves the problem of better understanding the customer, but a diverse set of customer engagement and commerce systems presents a daunting challenge to those who want to deliver consistent and personalized experiences across channels. Organizations first need to assess the ability of their systems to adapt the customer’s experience in real-time based on insights. They then need to weigh the cost of integration and ongoing maintenance against the weaknesses that these integrations will create. Agility will be lost as integration complexity increases, but without integration, how can the customer experience be consistent?

If organizations focus on turning customer data into “small data” rather than big data and take a platform approach to customer engagement and commerce, they will be able to create context for each interaction, whether personal or automated. Small data provides actionable insights by breaking down complex customer engagement problems, allowing organizations to be more informed about their audience and better at driving action. This context allows businesses to not only understand where the individual is on their customer journey, but also follow them across channels. By applying this context uniformly across a platform, brands can begin to deliver customer experiences that consistently set them apart from the rest. Given how commoditized most goods and services have become, it is the customer experience that ultimately differentiates a brand. Data can drive this, but only if it removed from silos and utilized to its full potential.


Johann Wrede is Global Vice President of Audience, Brand, and Content Marketing for SAP Hybris, the customer engagement and commerce division of SAP. He has written, implemented, sold, and marketed software for a variety of companies both large and small.  Johann is passionate about using storytelling to inspire business people to find ways to better engage their customers.  He spends his days working with a team of talented people to engage marketing, sales, service, and commerce professionals with informative, entertaining, and emotionally intelligent content.


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One Comment

  1. Posted August 3, 2017 at 8:33 am | Permalink

    Thanks for sharing this Johann!

    We’ve seen this as a huge challenge amongst companies we’ve worked with too – for all the reasons you’ve outlined (like having insights across the customer journey, advancing your CRM, and driving uniform engagement). It seems there are six common data integration methods that have emerged amongst companies – and one new method:

    1. One-click “native” integrations (e.g. Salesforce AppExchange)
    2. Manual export/import (often via a spreadsheet)
    3. If/then workflow tools (e.g. Zapier)
    4. “All-in-one” CRMs and platforms (e.g. Intercom, HubSpot, Salesforce)
    5. Custom code and scripts (via webhooks and APIs)
    6. Customer data warehouses (e.g. Amazon Redshift)
    7. Customer data platforms (e.g. Hull)

    You can read a complete deep dive into all these customer data integration methods in our guide here: https://www.hull.io/blog/customer-data-integration

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