No longer centred around the four traditional seasons of spring, summer, autumn, and winter, huge consumer demand and the birth of fast fashion have resulted in there being an assumed 52 seasons annually. With so many rolling seasons, it can be difficult for retailers to keep on top of what their consumers want to see next.
Accurate predictions of what the upcoming season’s biggest trends are going to be can make or break a retailer’s success rate, and one of the best ways to do this is through data analytics. Retailtechs working across eCommerce and brick and mortar are capturing huge amounts of data on the shopping habits of consumers, but how many have considered that this data goldmine could help them predict the upcoming seasons with the help of embedded dashboards, reporting, and forecasting?
Consumer-centred data analysis
Many different retailers will have different levels of data available to them and will likely have varying data dependent on the platforms they are selling on. But one thing is for sure, not properly centralizing this data could lead to a huge loss in potential insight. At a bare minimum, retailers will have access to product sales data, showing which products their consumers respond to the most at different points in the year.
An extra layer of data is added for those retailers whose consumers have shopping accounts set up. Retailers with this function will have access to huge amounts of data, from the item's specific consumers and demographics shop for the most, down to data on store wishlists and favourites. Panintelligence’s embedded dashboards and forecasting tools utilize a historic regression algorithm to collate shopper data within your Retailtech to pinpoint potential future trends.
Retail predictive analytics
The modern principle of predictive analytics can help to put your Retailtech at the forefront of the industry, giving your customers the ability to turn their streams of data into valuable forecasting insight. Predictive analytics is a scalable solution that can be easily understood by everyone in the business thanks to our user-friendly analytics, meaning your Retailtech will remain easy to use for employees in all areas of your customers’ business.
Our predictive analytics can also easily be combined with a self-serve function and machine learning so that retailers can be fed visualization of data, showing what is likely to be popular within their upcoming seasons.
Rapid reporting
Integrating our embedded business intelligence (BI) reporting solution into your Retailtech will allow your customers to create automized reports containing actionable insights on the buying habits of their consumers. For example, a report could be pulled on what the top best-selling products from last spring were. Data access can be tailored to business needs with user-based role restrictions, meaning employees only see what is needed, enhancing your platform’s accessibility by only providing the user with information relevant to them. For example, seasonal trend forecasting data can be assigned directly to design and buying teams so that they can take relevant action in building the upcoming product collections.
Swift integration
Our embedded analytics dashboards are built by SaaS, for SaaS, so our team knows that rapid deployment is of high importance and long development roadmaps are avoided.
Panintelligence’s solution provides swift, seamless integration for your development teams, meaning you don’t have to use up valuable development resources for the implementation process. Your customers will be up and running with the ability to predict future season shopping trends in no time with Panintelligence’s embedded analytics solution.
If you’re looking to make your Retailtech stand out from the crowd next season, request a demo or speak to a member of our team to learn how we can help to elevate your platform.
