Retail Technology Insider recently talked with Alex Dean, CEO, Snowplow Analytics, about behavioral data. Behavioral data is a new approach to understanding retail customers that is quickly becoming a must-have for businesses as they look to understand their customers and build stronger relationships with them to grow the bottom line. Read on to learn more about how behavioral data is helping retailers adapt to the new economy.
What is behavioral data, and how can it be applied in a retail environment?
Behavioral data is data that explains how customers, end-users, or shoppers interact with an organization’s digital estate. In a retail context, this includes shoppers’ activity on a website, what they are looking at, adding to baskets, and each individual step to the point of purchase and beyond.
Behavioral data is quickly becoming a vital tool for retailers to increase sales, improve customer service, streamline operations and more. For example, organizations are increasingly using behavioral data to equip their customer service and help desk teams with timely and rich insights into customer interactions with their brand. This type of help desk enablement drives better customer outcomes and makes the help desk more efficient, as they can provide better answers quicker.
Why is behavioral data more important than ever before, and how can companies start using it?
With the explosion of digital services, apps and eCommerce, consumer behavior has rapidly moved online. This means deeply understanding how customers interact with one’s digital brand is increasingly vital. At the center of this are personalized experiences that seek to recreate “real-life” encounters and interactions.
To help foster and improve these experiences, companies are boosting investments in tools like machine learning and AI to better serve key audiences. But what many overlook is that feeding these technologies and capturing value requires the use of rich, structured and high-quality data.
Unfortunately, many waste time transferring data to new formats, gathering it from disparate sources or relying on prepackaged analytics tools that don’t provide a complete picture in real time. So, for those truly looking to take advantage of behavioral data, we recommend first establishing a fast, secure and unified approach to collecting and managing it.
How can behavioral data equip service teams to help customers faster?
Without behavioral data, it may not always be clear when a customer has hit a dead-end or is struggling with some aspect of your product or service. By using behavioral data, organizations can create predictive models to identify and resolve the roadblock. For example, these models can detect when customers have issues based on their unique, individual digital behavioral footprint.
Additionally, individual data on certain customers can equip helpdesk and support personnel with real-time insights to enable personalized interactions. These insights could come from a variety of aggregated data sources, including PC or mobile browsing, emails, smart devices, and more.
How can tech leaders help drive the use of behavioral data in their organizations?
We are currently in a time of transition, where demographic and transactional data are valued highly and well understood. However, behavioral data is still widely misunderstood and undervalued.
To change things, tech leaders should focus on a single, highly efficient app or use case for behavioral data that clearly illustrates the value to their wider organization. When showing such a solution, it’s also important that data teams are given ‘space and time’ to form their own opinions and evaluate how they can help build out and contribute to a successful behavioral data program.
Moving forward, tech leaders will inevitably play a vital role in articulating the value of rich, behavioral insights to the c-suite. And proving the value of this new tool could mean the difference between future-proofing for years to come or struggling to catch up after it’s too late.
Alex Dean is CEO and co-founder of Snowplow. Alex is a polymath: a keen technologist with a passion for functional programming, cloud-based architectures, and big data technologies.