“If data is critical to a brand’s success, now is a good time for them to evaluate whether their data management technology is accelerating progress or holding them back,” says Jakki Geiger, CMO, Reltio, in an exclusive interview with TalkCMO.
TCMO Bureau: What are the current challenges enterprises faces while dealing with structuring the immense amount of data at their disposal?
Jakki Geiger: When dealing with any data challenge, the first few questions to ask are, what will this data be used for? Is the goal to analyze this data to get insights that will lead to better decision-making? Is this data needed for regulatory reporting? Will this data be used to enable real-time operations, online transactions, and mobile applications? What line of business or department will this data support and what unique needs do they have? The initial challenge is to identify what enterprises will use the data for before deciding how they are going to manage it.
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Next, there are three general challenges that most companies face:
- First, the data landscape is more complex than ever. Data is on-premises, and in the cloud, it’s streaming in from devices, and it’s coming from third-party data sources. The number of sources and types of data keeps growing.
- Second, the need for data has exploded and each function within a company wants the data to be ready and accessible to meet their specific functional requirements. For years, CMOs were pushing the data-driven agenda just for their function. But now, more and more CMOs recognize the need for a single source of truth of trusted data across the business to drive better decision-making and run the business’s 24/7 operations, including delivering connected customer experiences, which is a cross-functional requirement.
- Third, many companies are saddled with on-premises data management products that pre-date big data and adopt cloud solutions. Think of old school software that is downloaded and runs on servers that a company administers, maintains, and upgrades on its own. None of these operate on a big data platform architecture which is essential to providing the performance, scalability, and flexibility needed to manage and gain insight from massive data volumes. But before that can happen, data needs to be accessed across numerous internal and external silos. In fact, there has never been a greater need for a single source of truth for data that can be used for analytics and real-time operational use cases
To meet the needs for a single source of truth of data that is complex and also meets the complex data requirement needs of the enterprise and each business function, businesses must implement a trusted master data management SaaS solution designed for the digital economy.
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TCMO Bureau: How do you ensure that the data is structured well enough to meet the needs of accurate analysis?
Jakki Geiger: To be able to trust their decisions, enterprise leaders need to be able to trust the data. This means that the data profiles used for analytics need to be complete, current, and reliable. But these are just table stakes.
In the digital economy, there are new requirements for data, and in particular, customer data. The most innovative companies are augmenting their customer profiles regularly with insights from transactions, interactions, social media, and third-party data.
The right master data management solution enables businesses to unify master data, make it trustworthy, identify and unlock the value of relationships among entities, and deliver it to analytical platforms or in real-time to consuming applications. In B2C and B2B use cases, that also means providing trusted data at the point of interaction, including online and mobile transactions. Doing this at the speed of the cloud is critical—performance matters.
TCMO Bureau: How does a single source of identity data enable enterprises to provide a seamless omnichannel experience to their customers?
Jakki Geiger: Trusted data plays a crucial role in enabling connected omnichannel customer experiences. Data needs to be delivered real-time at scale across all channels, not just to digital touch points but also to human touch points to empower employees to make good decisions and inform their actions. Relationship managers, field reps, store associates, and call center reps all want access to trusted data so they can deliver the best experience possible. All teams within an organization must have the trusted data and customer experience processes to deliver personalized and connected omnichannel experiences.
One of the biggest challenges most companies have when delivering personalized and connected omnichannel experiences are to recognize people across touch points. Data issues often expose gaps in the customer journey. Recognizing customers across channels is an essential first step to moving a customer from anonymous to known, enabling seamless transactions and interactions, building loyalty, and increasing lifetime value. This is incredibly valuable in omnichannel and multi-brand environments.
TCMO Bureau: Lastly, what can enterprises do to continuously improve their data management platforms while the data is set to grow more complex and diverse?
Jakki Geiger: One way to gain a competitive advantage is to use new data sources and data types to maintain up-to-date and enriched customer profiles. A brand’s data management technology should be agile and make it easy to adapt to the business’s changing needs, including adding, changing, or removing customer profile attributes and data sources.
One of the biggest lessons over the last 12 months is speed and agility which are the keys to thrive in the digital economy. If data is critical to a brand’s success, now is a good time for them to evaluate whether their data management technology is accelerating progress or holding them back.
Jakki Geiger is responsible for leading marketing at Reltio, a company trusted by innovative Global 2000 companies who know that connected customer data is at the heart of customer experience. She has 20 years of combined experience working in the data management and advanced analytics markets.
