Patterns are one of the key elements in category design and development. It reflects customer demographics and preference towards fashionability. Data insights from the Trend Performance module helps you to identify the best-selling pattern for a category/sub-category.
Step 1: Set the filters
Select your preferred market to kickstart the analysis. Brand or retailer filters are not necessary when conducting a trend analysis to gain a wider perspective. If applicable, you could narrow down your analysis by including the gender filter.
Step 2: Analyse the best-selling pattern for the market
Before deep-diving into a specific pattern, get an overview of the different patterns’ performance in the market.
Trend scores are captured and updated continuously for each pattern. The trend scores reflect either a green or red trend line depending on the performance of the patterns within the selected date range. Learn how our trend scores feature functions here.
In the example below, the graphic pattern registered a significant uplift in trend score by +7.3 in comparison to all other patterns in the UK.
Click into a specific pattern for a deeper analysis of the Trend Scorecard, where the pattern’s performance over time and popularity score can be assessed. In this example, the gap between the graphic pattern (solid line) and all patterns (dotted line) indicates a strong performance as Graphic constantly trended higher than all patterns in the selected timeline. This signals an opportunity to invest in graphic for your next collection.
You may further identify the top five categories, colours and materials for the graphic pattern surfaced along with the trend score graph to gain more insights into Graphic products currently available in the market.
For example, here we conclude that graphic is adopted most widely across tops made of cotton, in core colours like black and white.
Toggle over to the ‘Pattern & Colour Contribution’ tab to further identify the core patterns adopted by each category. This can be done by selecting the ‘Split by: Category’ filter. For example, observe that stripes, checked and graphic are the key patterns for tops.
Step 4: Validate best-selling pattern performance for a category/sub-category
It is crucial to validate patterns’ performance before buying.
With the insights gained in previous steps, toggle over to the ‘Pattern Analysis’ tab. Select the category you’d like to analyse from the main filter bar as shown below. It is required to select the retailers or brands you would like to benchmark against to understand patterns’ performance.
Select the ‘Sell Out Contribution %’ filter to gauge pattern demand among consumers. Compare the product contribution against sell-out contribution to determine if there is a strong demand for a pattern.
In the graphic pattern column, observe that the overall sell-out contribution (29.38%) for graphic tops is higher than the product contribution (26.05%) across all retailers, by +3.33%. This positive relationship between sell-out contribution and product contribution reflects a promising customer adoption rate for graphic tops.
Understanding the relationship between patterns and categories facilitate commercial assortment planning. The adoption of relevant patterns in respective categories drives stronger customer interest and excitement, which eventually leads to an increase in product sell-out and sales conversion.
Hope you found this article helpful! If you have any questions or would like to explore the Omnilytics dashboard further, feel free to reach out to your respective Client Success Manager.