This article was based on the interview with April Mullen of Braze by Greg Kihlström for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
One of the top trends in customer engagement for 2023, as outlined in Braze’s 2023 Customer Engagement Review, is the challenge of data management for brands. This is a challenge that many companies can relate to, and it has significant implications for customer experiences.
There are two main challenges when it comes to data management. The first is that there is often too much data. According to the report, 80% of companies say they are collecting way too much data, resulting in an overwhelming amount of information that they can’t effectively use. This excess of data can lead to inefficiencies and difficulties in extracting meaningful insights.
The second challenge is around capability gaps. Marketers often struggle to work with internal data scientists and BI teams who may not fully understand marketing priorities. Additionally, there is often a lack of data skills among marketing talent, making it difficult to effectively manage and utilize the data that is collected.
These data management challenges have a direct impact on customers. When companies struggle to effectively manage their data, it can result in a poor customer experience. Customers may interact with a brand online, only to have a completely different experience when they visit a physical store. This lack of recognition and personalization can be frustrating for customers, especially when they have been loyal to a brand for a long time.
Unfortunately, these challenges are more common than the positive experiences that consumers expect. Consumers have high expectations when it comes to personalized experiences, and many brands are struggling to meet these expectations due to data management challenges.
To address these challenges, there are several steps that brands can take. First, they need to be more intentional about the data they collect and align their collection strategy with concrete use cases, metrics, and goals. Hoarding excessive amounts of data is not the solution, as it can lead to inefficiencies and a lack of understanding of how to use the data effectively. Instead, brands should focus on collecting data that is relevant to their specific goals and objectives.
Another important step is for marketing, product, and data teams to align and avoid data silos. This alignment is crucial for avoiding errors and enabling real-time messaging. It also helps to streamline workflows and improve efficiency, ultimately leading to better customer experiences.
Building closer relationships with data counterparts is also key. By collaborating and consulting with data scientists and other relevant stakeholders, marketers can better test, experiment, and evolve customer experiences. This collaboration ensures that everyone is on the same page and working towards a common goal.
Data management challenges pose significant obstacles for brands when it comes to delivering personalized and seamless customer experiences. By being intentional about data collection, aligning teams, and building closer relationships with data counterparts, brands can overcome these challenges and create more meaningful and valuable experiences for their customers. Prioritizing data management is crucial for brands that want to thrive in a highly competitive and customer-centric landscape.
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