How can you balance search performance and accuracy? Caching solutions might be the key
One might ask: why is caching so important for optimizing search performance and accuracy in retail and e-commerce?
Essentially, the effectiveness of your caching solutions determines how quickly and accurately information is displayed to your customers. If the process is too slow, it negatively impacts the customer experience on your website. Additionally, if the information is inaccurate, it not only diminishes the customer experience due to lack of precision but may also lead to the abandonment of the shopping process, which is highly detrimental.
It’s important to clarify a few things and provide examples of inaccuracies. Practically speaking, let’s say a shopper searches for a product and finds it listed in the initial results with prices starting at $8. Everything seems fine up to this point. The issue arises when the shopper clicks on the product and discovers that the actual price is $16 or higher, which is double the initial listing. This discrepancy breaks the customer’s expectations and leads to frustration.
This situation presents a challenge: when dealing with caching, we need to find a balance. How much information can we keep readily available so we don’t need to query our suppliers every time? And how long can we retain that information before it becomes outdated and inaccurate? There is no silver bullet and this can be tremendously tricky, but by fine-tuning our approach, it’s possible to find effective solutions.
At e-Core, we have a specific use case in which we fine-tuned a solution for a client at minimal cost by maintaining a fresh cache. By doing this, we not only ensured up-to-date information but also significantly enhanced performance and efficiency, reducing the number of calls to suppliers. Let’s explore how we accomplished this.
Improving caching solutions with data collection points
In this case, we began by doing what we always do at e-Core: analyzing the unique aspects of the business, and then ensuring that we could adjust and refine the caching solution to deliver maximum performance and efficiency. For example, if you’re selling Christmas trees, your business needs will be vastly different from those of a car dealership. It’s not just about technical expertise; it also involves a deep connection and ongoing conversation with the business teams. Understanding these nuances allows you to fine-tune the caching solution effectively, optimizing performance.
The curious point is that we aimed to speed up the process, but during this effort, we started questioning how we could further evolve it. One idea that came up was to introduce data collection points. This would allow us to feed the decisions being made into a data lake, which could then be used for machine learning and intelligence generation to improve decision-making.
This way, we helped our client make the information reusable and optimizable for performance. The next step would likely be implementing real-time, dynamic changes based on this data. This is where analytics plays a crucial role in understanding the entire supply chain, omni-channel strategies, and more.
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