A 360-Degree Customer View: Personalizing the Consumer Journey
In today’s retail industry, consumers have an abundance of options to fulfill their shopping needs.
Because of this, it is necessary for organizations operating in this space to provide a truly personalized customer experience to help differentiate themselves from competitors. In order to improve this experience, many retailers have sought out to achieve a 360-degree view of their customers. In doing so, retailers give themselves the ability to create a better overall shopping experience through customized interactions and offerings while at the same time, improving operational efficiency. Although achieving a 360-degree view of customers isn’t a new concept by any stretch, retail organizations are still struggling to achieve this critical feat from a data management perspective.
Benefits of a 360-Degree view
Over the past few years, consumers have increasingly shifted towards ease of browsing and buying. This sentiment was only further intensified during the COVID-19 pandemic. This trend has pushed retailers to realize that they aren’t just in the business of selling their product(s), they are now expected to provide highly personalized customer experiences. Big data can help these organizations accomplish this objective by helping in better understanding emerging technologies, products, trends and price parity as it pertains to the consumer journey and seamlessly applying this information across all channels.
Here are just a few benefits retail organizations can expect by achieving a 360-degree view of their customers:
- Integrate omnichannel (eCommerce, Point of Purchase, etc.)
- Build and deliver applications faster
- Unite marketing, orders, inventory, pricing, promotion and customer records data
- Streamline supply chain and reduce input costs
360-Degree Customer View Model
In order to achieve a 360-degree view, retailers need to collect and store the data associated with purchase preferences, shopping patterns, and categories that customers are interested in. Our experience helping retail organizations has allowed us to develop a proven methodology that can progress any 360-degree customer view initiative. Here are the key areas of interest.
By unifying the various data sources (web, social media, loyalty programs, etc.) with centralized data storage, siloed data can be eliminated and the organization can begin harnessing the power of a single source of truth.
Having a structured representation of your organization’s data ecosystem will ultimately allow for ease of use and actionable insights, while meeting the needs of the business users and supporting associated business processes.
This critical framework assigns data permissions and access privileges to users to avoid data fragmentation improving the data’s quality and integrity for accurate reporting and analysis. It also provides security guidelines and protections for confidential data.
By utilizing a cloud-based data platform, organizations have the flexibility to scale up or down based on their data needs. Technology can also help support data governance and security initiatives. It is vital that the technology selected support the business’s data goals.
Understandably, this is not an easy initiative to take on. It requires an enterprise-wide undertaking that involves heavy collaboration from both the IT group and the various business units within a retail organization. However, by implementing a modern data management system retailers can improve the customer experience throughout the retail value chain by properly collecting, aggregating, and analyzing multi-channel data.
At Data Ideology, we have experience working with various retail organizations improving their margins by helping them attain a 360-degree view of their customers. Visit our dedicated retail page to learn how you can begin measuring success in terms of satisfied customer experiences per square foot instead of sales per square foot.
Written by Mike Sargo
Co-Founder & Chief Data and Analytics Officer at Data Ideology
Mike Sargo is Chief Data and Analytics Officer and Co-Founder of Data Ideology with over 18 years of experience leading, architecting, implementing, and delivering enterprise analytics, business intelligence, and enterprise data management solutions.