Ιmproving On-site Search for greek e-Shops: Key Findings and Solutions
In our recent survey of 100 Greek e-shops, we uncovered some critical issues with the performance of on-site search. The average effectiveness of search functionality reached only 59%, based on our “Website Search Excellence” evaluation model, which uses 12 essential criteria to assess performance. This reveals a significant opportunity for improvement, particularly in an area as crucial as the search bar, which is often the first point of interaction for customers.
Key Findings from Our Research:
➡️ Inaccurate Search Results: Many e-shops struggle to provide accurate search results, especially when faced with common issues such as spelling errors or the use of Greeklish (Greek written in Latin characters). According to our data, approximately 12% of consumers fail to find relevant results due to these issues, leading to frustration and lost sales.
➡️ Slow Response Times: Today’s online shoppers expect speed and precision. Our research showed that 35% of users abandon their purchase journey when the search experience is slow or fails to meet their expectations. This significantly impacts the conversion rate and overall customer satisfaction, pushing potential buyers to competitor sites with better search functionality.
The Role of AI in Enhancing Search Performance
As e-Commerce continues to grow, AI-powered features have become a game-changer in improving the on-site search experience. Solutions like Findbar’s Semantic Search, AI Image Search, and AI Visual Recommendations are reshaping the way customers interact with e-shops.
Here’s how these technologies can help:
- Semantic Search: By understanding the context and meaning behind a user’s search query, semantic search can deliver more relevant results, even when the keywords are vague or incomplete. This approach minimizes errors and helps customers find exactly what they’re looking for more efficiently【source: Forrester】.
- AI Image Search: Visual search powered by AI allows users to upload images to find similar products. This tool is especially useful for industries like fashion and home décor, where customers often search based on visual preferences【source: Gartner】.
- AI Visual Recommendations: Based on user behavior and preferences, AI can suggest visually similar products to enhance the shopping experience. This keeps customers engaged longer and encourages additional purchases by showcasing products that match their style【source: McKinsey】.
Positive Impact on e-Shop Performance
E-shops that have integrated Findbar’s AI-powered features have seen substantial improvements. These stores are not only delivering better search results but also using data-driven insights to continuously optimize the customer experience. The results are promising:
- Bounce rates have decreased by up to 30%, indicating higher user engagement and satisfaction.
- Conversion rates are on the rise, thanks to the faster, more accurate, and more intuitive search experience provided by AI.
The Next Step: Omni-Retail Solutions
We believe that enhancing the search experience is not only important for e-shops but also for omni-retail environments, where physical stores and online channels must work seamlessly together. In-store search tools that help employees find products quickly and accurately are just as critical as the online experience.
