Create next-generation personalized shopping experiences
Despite being at the forefront of analytics for many years retailers still struggle to parse terabytes of transactional data for patterns leading to actionable pricing, campaigning and category management insights with significant sales and bottom-line impact.
While personalization is the hot buzzword in the retail community right now only 15% of retailers have successfully implemented processes to make personalization extremely relevant and possible at scale, confirms Periscope by McKinsey at World Retail Congress 2017.
Siloed processes and data hamper efforts make it challenging to manage customer data and develop personalized content for each individual consumer. Exacaster helps overcome these challenges cost-effectively with an open-source Big Data technology stack and our personalization solution for retailers.
Our 1-to-1 marketing solution combines oodles of retail-specific business know-how to deliver tangible business benefits on a large scale:
Better Loyalty Programs – harness loyalty card history to identify relevant products at an individual customer level, and communicate much more relevant offers to your loyalty program members. Experience shows that personalized offering delivers up to 100% better response rates than before and margin gains, too.
Offer selection – use Exacaster to detect dynamic relationships between categories and individual products, and predict optimal above the line offers for individual products that drive traffic AND margin increase at the same time.
Behavioral Segmentation – cluster and analyse customers using multiple behavioral aspects at once. Understand segments and track segment performance over time using our powerful behavior monitoring dashboards.
Promotion Impact Analysis – it is often very difficult to calculate the impact of multiple promotions and discounts on thousands of items done each week. Exacaster calculates campaign impact, halo and cannibalization down to the product level to answer the key question – was the marketing investment in this promotion worth it?
Predict Entire Basket – customers make 20 clicks on average in an e-commerce shopping session, but offline buy 100s of groceries. How can the online basket be increased to match the offline basket? We have a solution to this click fatigue – populate basket in one click using machine learning and historical shopping data.
Downgrade to “Price leader” or Upgrade to “Eco-oriented” SKUs – different customers have different needs. We can automatically replace items in online shopping cart into lowest price per category or to organically and sustainably grown SKUs as requested by the customer to deliver in-basket recommendations.
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