Basket Analysis

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Basket Analysis – Increase Sales

We use big data and advanced analytics approach
to generate actionable business insight. Basket analysis to us simply means –
to find purchasing patterns among customers. At Sybest, we understand such
patterns have numerous applications within disciplines like category management and marketing and can be used to optimize store layout by putting items that are often bought together in near proximity to each other – and by allocating shelf space not only according to sales performance of the productitself, but also according to sales of other items the product drives

We will also help your business to increase cross-selling and up-selling by understanding and leveraging the roles of product categories (e.g. basket drivers, traffic drivers etc.)

We recommend the optimize use of promotions,
e.g. promote items that often drive sales of other products – and avoid putting two items often bought together on promotion at the same time.

A typical grocery store has thousands of items
(SKUs) in its assortment and completes thousands of transactions each week. As the basket analysis has to be conducted on transaction level the dataset could be huge. Finding interesting patterns in such a dataset manually in Excel is most likely not possible due to data size constraints. Even if the dataset is
small enough to be opened in Excel, identification of patterns is both likely
to be random, time consuming and maybe even spurious. Luckily, our machine
learning algorithms can easily be applied to find interesting – and significant
– patterns in such a dataset. Our Apriori algorithm is well suited to help
your learning from our in depth analysis to measures and identify interesting
patterns.