Introduction
It is no secret that oversimplified data storage systems, especially ones that rely largely on manual labour, need to evolve to cater to the evolving needs of the market and the industry. Systems that deploy intelligent automation are not only capable of processing large volumes of SKUs in less time, but are also useful because they adapt to changing business needs and work reliably on edge cases. It is for this reason that dataX.ai is a huge advocate for intelligent automation, but how does one achieve this?
The 4 Pillars for Intelligent Information
- Descriptive Intelligence: This is the most fundamental process of all. This involves normalizing product descriptions to a specified standard automatically so that each product has one uniform description, and a set of accurate specifications. For instance, the quantity of a medicine is standardized to 8mL from diverse sources that may store it as 8ml, or 8cc, etc. This is how we create a “single source of truth”.
- Contextual Intelligence: Extremely specific product specifications or descriptions might not be what customers put in search bars on ecommerce websites. What contextual intelligence does is to enrich the data such that it includes industry applications, use cases, and more such relevant information, so that search results do not show up empty when customers look products up.
- Relational Intelligence: This allows for needs of customers to be met with as efficiently as possible, and reduces the amount of time spent in solving customer queries. Relational intelligence, as the name suggests, maps out the connections between different products. For example, we equip the system with the knowledge of which part might be obsolete, which might be a good replacement, which components are required for complete assembly, and so on. Therefore, when customers look up products that might be outdated, the system can automatically suggest current relevant products, and any relevant components that might be required to assemble them.
- Personalization: With such a myriad of products available in the market, customers might not always be able to wade through said products to find what they are looking for. This is where personalization comes into play– it allows for the system to cater to a user’s needs. If it is an engineer, for example, looking at a particular product, they might want to look at particular specifications, meanwhile, a procurement manager might look for something else.
Conclusion
These layers to a system not only allow for efficient work, but customer satisfaction and retention, reduction in order errors and technical support calls, increase in search-to-purchase, and higher revenue streams from bundles.
Therefore, intelligent automation can be the key to your company’s success. Transform your data today!
